ipynb/shahzoor-fifaproject_(1).ipynb

{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "<h1><p style=\"text-align: center\">How Good are FIFA Ratings at Predicting Actual Results?</p></h1>"
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "### Introduction\nEvery year, EA Sport releases a new rendition of its FIFA series, and every year I and 24 million other people flock to buy it. In the game, every player is assigned a rating between 0 and 100 based on their performances in the previous season. How specifically the ratings are calculated is somewhat opaque, but it involves some combination of performance statistics and subjective scout reports that are then reviewed by a team of editors at EA. \n\nIn this notebook, I try and examine if these ratings are any good at predicting real match outcomes. To do this, I use match data from last year's premier league season (2017/18) and ratings from this year's game, FIFA 19. That gives me a base of 380 games to work with. For every game that was played last year, I use lineup information to compute the average rating for each team, and then find the difference. Then, since I know what the difference in rating was for each game and I know the result, I can effectively compute the probability distribution of outcomes for a game given the difference in average team rating. \n\nSo how good are these ratings at predicting actual results? Turns out, not very. I used the distribution I estimated to see how many games I could correctly predict this season (the testing data) and I was right about 47% of the time. I got the same result when I simulated last season (the trainning data) based on my distribution estimate.\n\nNow, while that is not great, it is at least better than randomly picking an outcome (win, draw, or loss). Theoretically, if you did that, you would be correct one-third of the time. My simulation results bore that out; random picking was 37% correct on the testing data and 32% correct on the training data.\n\nThe main contribution of this project are the datasets I compiled for this and last season. This was a lot more difficult than I had initially anticipated, but the code I wrote to extract real match data is quite robust and would be able to extract lineup and match information for every season going back to 1992 (and I intend to do this). I was unable to find a free dataset online that had this information, so I took this project as an oppertunity to learn how to web-scrape and do it myself.  \n\nThe rest of this notebook is broken into two parts. The first part details what's in the data, how I scraped it, and what trouble I ran into. The second part shows my analysis of FIFA scores and match outcomes in more detail and examines the limitations of this particular approach. \n"
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "### The Data "
        },
        {
            "cell_type": "code",
            "execution_count": 1,
            "metadata": {},
            "outputs": [],
            "source": [
                "# import libraries\n",
                "import numpy as np \n",
                "import matplotlib.pyplot as plt\n",
                "from bs4 import BeautifulSoup as soup\n",
                "from urllib.request import urlopen as uReq\n",
                "import pandas as pd\n",
                "import unidecode\n",
                "import seaborn as sns\n",
                "from scipy import stats\n",
                "import math\n",
                "import warnings\n",
                "\n",
                "# set sns color code\n",
                "sns.set(color_codes=True)\n",
                "\n",
                "# suprress warnings, I'm doing this so the notebook is more readable\n",
                "warnings.filterwarnings(\"ignore\")"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "Instead of computing a squad average FIFA rating for each team, I decided to compute an average rating for the players who <i>actually played</i> in a given game. This is reasonable because if say Arsenal (a pretty good team) played their reserves against Crystal Palace's first eleven (a worse team), that would affect Crystal Palace's odds of winning.\n\nI could not find a dataset that contained the score, lineups, and substitutes for a given game. The datasets I created have these fields. For a given match, I got this information directly from the Premier League website results page (https://premierleague.com/results/). Every game has a unique match ID associated with it. To access the details for that specific match, you just need to append the match ID to that URL. Then, since all the results pages are identically formatted, you can run the same script to extract data from them. \n\nTo find the match ID for all the games in a season, you really just need to find the match ID for the first game. That is also available on the results page. I just scrolled down to the bottom of the page until I hit the first game of the 2017/18 season and then right-clicked, hit inspect, and saw the associated match ID. Since there are 380 games in a season (each of the 20 teams plays every other twice in a round-robin format), the last match ID is just the first one plus 379. I download and scrape the pages in turn. \n\nThe four functions in the following hidden cell do the web-scraping."
        },
        {
            "cell_type": "code",
            "execution_count": 2,
            "metadata": {},
            "outputs": [],
            "source": [
                "# main functions used for scraping the premier league website\n",
                "\n",
                "def remove_special_characters(name):\n",
                "    \"\"\"This function removes numbers, apostrophes, and addition signs from a string and returns the cleaned string. \n",
                "    This was specifically written with the format of name strings from the premier league match summaries in mind. \n",
                "    Strings of the form \"john doe 90 + 4' \" are returned as \"john doe\".\n",
                "    \n",
                "    :param str name: The full string of text containing the player name.\n",
                "    :return: A string containing the name with the unnecessary characters stripped.\n",
                "    :rtype: str \n",
                "    \n",
                "    \"\"\"\n",
                "    for c in ['0','1','2','3','4','5','6','7','8','9','+',\"'\"]:\n",
                "        name = name.replace(c,'')\n",
                "    \n",
                "    # remove trailing spaces\n",
                "    name.strip()\n",
                "    \n",
                "    return name\n",
                "\n",
                "\n",
                "\n",
                "def remove_team_code(name):\n",
                "    \"\"\"This function removes team codes from a string containing names+codes.\n",
                "    The function is limited in that it only does this for teams that were involved in the premier league\n",
                "    in the 2017/18 and 2018/19 seasons. \n",
                "    \n",
                "    :param str name: A team name of the form name+code.\n",
                "    :return: A string containing the team name with the codes removed i.e BurnleyBUR returns Burnley.\n",
                "    :rtype: str\n",
                "    \n",
                "    \"\"\"\n",
                "    # team codes\n",
                "    team_codes = [\"BUR\",\"BOU\",\"CRY\",\"WBA\",\"HUD\",\"ARS\",\"LIV\",\"BHA\",\"MUN\",\"WAT\",\"NEW\",\"CHE\",\"SOU\",\\\n",
                "                  \"MCI\",\"SWA\",\"STK\",\"TOT\",\"LEI\",\"WHU\",\"EVE\",\"WOL\",\"CAR\",\"FUL\"]\n",
                "    \n",
                "    # look for codes in name, if found, remove\n",
                "    for c in team_codes:\n",
                "        name = name.replace(c,'')\n",
                "        \n",
                "    return name\n",
                "\n",
                "\n",
                "\n",
                "def extract_epl_lineups(team_container, home):\n",
                "    \"\"\"This function extract lineups information from the matchLineupTeamContainer class \n",
                "    as defined on the the premier league results website. \n",
                "    \n",
                "    :param Tag team_container: Contains the matchLineupTeamContainer from the premier league website.\n",
                "    :param bool home: A flag for whether team_conatiner contains the home team lineup or away team lineup\n",
                "    :return:  A dictionary with the keys = [ \"player1\", ...., \"player 14\"], and the values are [{\"name\":\"John Doe\"}....].\n",
                "             If a team plays with less than 14 players in a game, the remaining slots are left blank (= '').\n",
                "    :rtype: dict\n",
                "    \n",
                "    \"\"\"\n",
                "    \n",
                "    # generate keys for return dict, initialize player names\n",
                "    if home== True:\n",
                "        base_string = \"home_player\"\n",
                "    else: \n",
                "        base_string = \"away_player\"\n",
                "    keys = [base_string+str(i+1) for i in range(14)]\n",
                "    player_names = []\n",
                "\n",
                "    # extract info from the container\n",
                "    lineup_container = team_container.find_all(\"div\",{\"class\":\"info\"})\n",
                "    \n",
                "    # extract player names\n",
                "    for i in range(len(lineup_container)):\n",
                "        if i < 11:\n",
                "            player_names.append(unidecode.unidecode(remove_special_characters(lineup_container[i].div.text)))\n",
                "        else:\n",
                "            if lineup_container[i].div.div.text != '':\n",
                "                player_names.append(unidecode.unidecode(remove_special_characters(lineup_container[i].div.text)))\n",
                "    \n",
                "    # create dictionary \n",
                "    player_dict = dict(zip(keys,player_names))\n",
                "    \n",
                "    # if player12, player13, or player14 don't exits, create and and assign '' as value\n",
                "    for i in range(12,15):\n",
                "        if base_string+str(i) not in player_dict:\n",
                "            player_dict[base_string+str(i)]= \"\"\n",
                "            \n",
                "    return player_dict\n",
                "\n",
                "\n",
                "\n",
                "\n",
                "def extract_epl_match_details(match_ids):\n",
                "    \"\"\"This function extracts match information for games from the premier league results website\n",
                "    given their match ids. \n",
                "   \n",
                "    :param list match_ids: A list of match ids for the games you're interested in. Can be a list of one or empty. \n",
                "    :return: A dictionary containing the match information for every match id. Each unique match\n",
                "            match id is a key. The value is the corresponding match information which is a list \n",
                "            five dictionaries the team names, score, result (encoded as 1 for a home team win, \n",
                "            0 for a draw, -1 for an away team win), the home team lineup,\n",
                "            and the away team line up. The dictionaries are formatted as follows:\n",
                "            team_names = {\"home_team\":\"Arsenal\", \"away_team\":\"Liverpool\"}\n",
                "            score = {\"home_goals\":2, \"away_goals\":3}\n",
                "            result = {\"result\": 1}\n",
                "            home_team = {\"home_player1\":\"Petr Cech\", ....., \"home_player14\": \"Alex Iwobi\"}\n",
                "            away_team = {\"away_player1\":\"Loris Karius\", ...., \"away_player14\":\"\"}\n",
                "    :rtype: dict\n",
                "    \n",
                "    \"\"\"\n",
                "     \n",
                "    # where the match data is being scraped from\n",
                "    epl_url = \"https://www.premierleague.com/match/\"\n",
                "\n",
                "    # initialize a dictionary to store the results \n",
                "    data = dict()\n",
                "\n",
                "    # this loop extracts the data through each game in turn\n",
                "    for match_id in match_ids:\n",
                "\n",
                "        # url for each math\n",
                "        match_url = epl_url + str(match_id)\n",
                "\n",
                "        # download page, call and then close client\n",
                "        uClient = uReq(match_url)\n",
                "        results_page = uClient.read()\n",
                "        uClient.close()\n",
                "\n",
                "        # extract html\n",
                "        results_soup = soup(results_page, \"html.parser\")\n",
                "\n",
                "        # extract home team name container\n",
                "        home_team_container = results_soup.findAll(\"div\", {\"class\":\"team home\"})\n",
                "\n",
                "        # extract away team name container\n",
                "        away_team_container = results_soup.findAll(\"div\", {\"class\":\"team away\"})\n",
                "\n",
                "        # extract score container\n",
                "        score_container = results_soup.findAll(\"div\", {\"class\":\"matchScoreContainer\"})\n",
                "\n",
                "         # extract lineup containers \n",
                "        team_lineups_container = results_soup.findAll(\"div\", {\"class\":\"matchLineupTeamContainer\"})\n",
                "\n",
                "        # extract team names from their containers\n",
                "        team_names = {\"home_team\": remove_team_code(home_team_container[0].text),\\\n",
                "                      \"away_team\":remove_team_code(away_team_container[0].text)}\n",
                "\n",
                "        # extract score from score container\n",
                "        score = {\"home_goals\": int(((score_container[0].text).split(\"-\"))[0]),\\\n",
                "                 \"away_goals\":int(((score_container[0].text).split(\"-\"))[1]) }\n",
                "\n",
                "        # use score to determine match outcome, Win for home team = 1, Win for away team = -1, draw = 0\n",
                "        result = {\"result\":  1 if score[\"home_goals\"] > score[\"away_goals\"] else\\\n",
                "                  -1 if score[\"away_goals\"] > score[\"home_goals\"] else 0 }\n",
                "\n",
                "        # extract lineups for the home and away team from their containers, this includes substitutes who made appearances\n",
                "        home_team = extract_epl_lineups(team_lineups_container[0], home = True)\n",
                "        away_team = extract_epl_lineups(team_lineups_container[1], home = False)\n",
                "\n",
                "        # append to data dictionary\n",
                "        data[match_id] = [team_names, score, result, home_team, away_team]\n",
                "\n",
                "    return data\n",
                "\n"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "Finding a complete data set with consistent naming conventions turned out to be a lot more difficult than I expected. The data set I eventually settled I found on GitHub (\"https://raw.githubusercontent.com/kafagy/fifa-FUT-Data/master/FIFA19.csv) most closely matched with the names on the Premier League website. Although I was able to match over 90% of the names using a combination of queries, I still could not get everything I needed from this dataset because some players retired between the release of the game and the end of last season, changed their preferred names, or were simply missing from this dataset.\n\nThis is why I created an auxiliary dataset with all the missing player ratings (https://github.com/shahzoor/FIFA_PROJECT). I used code to generate a list of names, but since the number of missing names was small enough, I just entered in their ratings manually. I uploaded the CSV file to my GitHub and read it in directly in the next section.\n\nThe two functions in the following hidden cell query these two datasets to find player ratings."
        },
        {
            "cell_type": "code",
            "execution_count": 3,
            "metadata": {},
            "outputs": [],
            "source": [
                "# main functions used for finding fifa ratings \n",
                "\n",
                "def last_name(name):\n",
                "    \"\"\"Extract the last name for a player given their full name. \n",
                "    \n",
                "    :param str name: A string of the full name of the player.\n",
                "    :return: Returns just the last name of the player. If their full name\n",
                "            is just one name - \"Ronaldinho\" for example - return what is passed.\n",
                "    :rtype: str\n",
                "    \n",
                "    \"\"\"\n",
                "    name = unidecode.unidecode(name)\n",
                "    names = name.split()\n",
                "    last_name = names[len(names)-1]\n",
                "    \n",
                "    return last_name\n",
                "\n",
                "def extract_fifa_rating(data_main, data_auxillary, name, club):\n",
                "    \"\"\"This function extracts the fifa rating for a player.\n",
                "    \n",
                "    :param DataFrame data_main: A master data store; this is the data from kaggle.\n",
                "    :param DataFrame data_auxillary: A supplementary dataframe that conatains data missing in data_main.\n",
                "    :param str name: A string containing the name of the player missing. \n",
                "    :param str club: A string containing the the player's club.\n",
                "    :return: The base fifa rating (type int) if found, else returns np.NaN.\n",
                "    :rtype: int\n",
                "    \n",
                "    \"\"\"\n",
                "    rating = 0 \n",
                "    \n",
                "    # check the main dataset to see if the full name matches\n",
                "    if data_main[data_main[\"NAME\"]== name][\"RATING\"].empty == False:\n",
                "        rating = data_main[data_main[\"NAME\"]== name][\"RATING\"].min()\n",
                "    \n",
                "    # check if the last name and club are enough to match \n",
                "    elif data_main[data_main[\"LAST_NAME\"]== last_name(name)][fifa_data[\"CLUB\"]==club][\"RATING\"].empty == False:\n",
                "        rating = data_main[data_main[\"LAST_NAME\"]== last_name(name)][fifa_data[\"CLUB\"]==club][\"RATING\"].min()\n",
                "\n",
                "    elif data_auxillary[data_auxillary[\"NAME\"] == unidecode.unidecode(name)][\"RATING\"].empty == False:\n",
                "        rating = data_auxillary[data_auxillary[\"NAME\"] == unidecode.unidecode(name)][\"RATING\"].min()\n",
                "    else:\n",
                "        rating = np.NaN\n",
                "\n",
                "    return rating\n",
                "        \n"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "The function in the following hidden cell converted the data I scraped into data frames with the appropriate format. Every row corresponds to a game. There are 33 columns: home team, away team, home goals, away goals, the result, a column each for the eleven starters and three substitutes for the home team, and a column each for the eleven starters and three substitutes for the away team. The final datasets include a 34th column for the match ID on the Premier League website."
        },
        {
            "cell_type": "code",
            "execution_count": 4,
            "metadata": {},
            "outputs": [],
            "source": [
                "# functions to formet the data (list of dictionaries) appropriate as dataframe\n",
                "\n",
                "def convert_to_dataframe(data, match_ids):\n",
                "    \"\"\"This function converts a list called data (see documentation for \n",
                "    extract_epl_match_details for format) and match_ids to create dataframe of 33 columns. \n",
                "    The column names are enumerated in the second line of the function.\n",
                "    \n",
                "    :param dict data: The data for all the games fromatted as a dictionary.\n",
                "    :param list match_ids: A list of all the match ids. These are the keys used to access the data parameter.\n",
                "    :return: DataFrame containing 33 columns with every row corresponding to a single game. The indexes correspond\n",
                "            to match ids.\n",
                "    :rtype: DataFrame\n",
                "    \n",
                "    \"\"\"\n",
                "    \n",
                "    # index and columns used to initialize return dataframe \n",
                "    index = [0]\n",
                "    columns = [\"home_team\", \"away_team\", \"home_goals\", \"away_goals\",\"result\", \\\n",
                "              \"home_player1\",\"home_player2\",\"home_player3\",\"home_player4\",\"home_player5\",\"home_player6\",\"home_player7\",\\\n",
                "               \"home_player8\",\"home_player9\",\"home_player10\",\"home_player11\",\"home_player12\",\"home_player13\",\"home_player14\",\\\n",
                "              \"away_player1\",\"away_player2\",\"away_player3\",\"away_player4\",\"away_player5\",\"away_player6\",\"away_player7\",\\\n",
                "               \"away_player8\",\"away_player9\",\"away_player10\",\"away_player11\",\"away_player12\",\"away_player13\",\"away_player14\"]\n",
                "\n",
                "    # initialize dataframe with one empty row\n",
                "    data_df = pd.DataFrame(index=index,columns=columns)\n",
                "\n",
                "    # append match info for each match in turn to return dataframe \n",
                "    for match_id in match_ids:\n",
                "        temp_df = pd.DataFrame.from_dict(data[match_id][0],orient=\"index\")\n",
                "        for i in [1,2,3,4]:\n",
                "            temp_df= pd.concat([temp_df,pd.DataFrame.from_dict(data[match_id][i],orient=\"index\")])\n",
                "        temp_df = temp_df.T\n",
                "        data_df = data_df.append(temp_df)\n",
                "\n",
                "    # remove the empty first row\n",
                "    data_df = data_df.iloc[1:]\n",
                "\n",
                "    # make the indices equal to the match ids\n",
                "    data_df.index = match_ids\n",
                "    \n",
                "    return data_df\n"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "The previous cells contain just functions. The following script makes the function calls necessary to compile the results for this season and last season into two datasets and a master list of players who played any minutes at all in the premier league last season and their ratings. I exported the outputs from this script into three separate CSV files. Since this script took 15-20 minutes to run because it had to download 570 webpages, I ran it once in full and saved the data. I replaced the actual number of matches played in the two seasons with 1 so you can run the script if you want to. I included comments to make it easy to follow. In the next section, where I actually use all this data, I read it directly from a GitHub link I set up.  "
        },
        {
            "cell_type": "code",
            "execution_count": 5,
            "metadata": {},
            "outputs": [],
            "source": [
                "# This code takes between 15-20 minutes to run to run through all the pages.\n",
                "# I've modified num_matches_2018 and num_matches_2019 appropriately so that doesn't happen.\n",
                "# I ran it once with full number of matches, saved the results, and uploaded them to GitHub.\n",
                "# In the next section, I directly read these files from the GitHub links.\n",
                "\n",
                "##### Extract Match Info #####\n",
                "\n",
                "# there are 380 matches played in a season, there are 20 teams and each team plays every other team twice. \n",
                "num_matches_2018 = 1 #380\n",
                "num_matches_2019 = 1 #190\n",
                "\n",
                "# list of match IDs for the games played last season, I found these by reading through the html on the website\n",
                "match_ids_2018 = [22342+i for i in range(num_matches_2018)]\n",
                "match_ids_2019 = [38313+i for i in range(num_matches_2019)]\n",
                "\n",
                "# extract data for each season\n",
                "data_2018 = extract_epl_match_details(match_ids_2018)\n",
                "data_2019 = extract_epl_match_details(match_ids_2019)\n",
                "\n",
                "# combine data to create a master dictionary\n",
                "data = {**data_2018, **data_2019}\n",
                "\n",
                "# convert data from dictionary to dataframe\n",
                "df_2018 = convert_to_dataframe(data_2018,match_ids_2018)\n",
                "df_2019 = convert_to_dataframe(data_2019,match_ids_2019)\n",
                "\n",
                "\n",
                "##### Compile Player Names and Ratings #####\n",
                "\n",
                "# import master FIFA19 file, includes just fifa ratings \n",
                "fifa_data = pd.read_csv(\"https://raw.githubusercontent.com/kafagy/fifa-FUT-Data/master/FIFA19.csv\")\n",
                "\n",
                "# remove special characters from the name column (accented e's etc)\n",
                "fifa_data[\"NAME\"] = fifa_data[\"NAME\"].transform(unidecode.unidecode)\n",
                "\n",
                "# add last name column to dataframe to aid querying\n",
                "fifa_data[\"LAST_NAME\"] = fifa_data[\"NAME\"].transform(last_name)\n",
                "\n",
                "# import missing fifa data, this is the  missing data file I created\n",
                "missing_fifa_data = pd.read_csv(\"https://raw.githubusercontent.com/shahzoor/FIFA_PROJECT/master/missing_player_ratings_final.csv\")\n",
                "\n",
                "# initiaize dictionary to hold player data\n",
                "name_team_rating_dict = dict()\n",
                "\n",
                "# extract player name, club, and rating for every player who played any minutes at all in the epl in the last two seasons\n",
                "for id in (match_ids_2018+match_ids_2019):\n",
                "    for i in range(1,15):\n",
                "        if data[id][3][\"home_player\"+str(i)] != '':\n",
                "            name = (data[id][3][\"home_player\"+str(i)]).strip()\n",
                "            club = remove_team_code(data[id][0][\"home_team\"])\n",
                "            rating = extract_fifa_rating(fifa_data, missing_fifa_data, name, club)\n",
                "            name_team_rating_dict[name] = [club,rating]\n",
                "    for j in range(1,15):\n",
                "        if data[id][4][\"away_player\"+str(j)] != '':\n",
                "            name = (data[id][4][\"away_player\"+str(j)]).strip()\n",
                "            club = remove_team_code(data[id][0][\"away_team\"])\n",
                "            rating = extract_fifa_rating(fifa_data, missing_fifa_data, name, club)\n",
                "            name_team_rating_dict[name] = [club,rating]\n",
                "\n",
                "# convert player data dictionary to dataframe\n",
                "player_data = pd.DataFrame(name_team_rating_dict).T\n",
                "player_data.columns = [\"CLUB\", \"RATING\"]\n",
                "\n",
                "\n",
                "##### Export Data #####\n",
                "\n",
                "# export dataframes as csv files\n",
                "df_2018.to_csv(\"epl_results_2018\", sep = ',')\n",
                "df_2019.to_csv(\"epl_results_2019\", sep = ',')\n",
                "player_data.to_csv('epl_player_ratings', sep=',')"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 6,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/html": [
                            "<div>\n",
                            "<style scoped>\n",
                            "    .dataframe tbody tr th:only-of-type {\n",
                            "        vertical-align: middle;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe tbody tr th {\n",
                            "        vertical-align: top;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe thead th {\n",
                            "        text-align: right;\n",
                            "    }\n",
                            "</style>\n",
                            "<table border=\"1\" class=\"dataframe\">\n",
                            "  <thead>\n",
                            "    <tr style=\"text-align: right;\">\n",
                            "      <th></th>\n",
                            "      <th>home_team</th>\n",
                            "      <th>away_team</th>\n",
                            "      <th>home_goals</th>\n",
                            "      <th>away_goals</th>\n",
                            "      <th>result</th>\n",
                            "      <th>home_player1</th>\n",
                            "      <th>home_player2</th>\n",
                            "      <th>home_player3</th>\n",
                            "      <th>home_player4</th>\n",
                            "      <th>home_player5</th>\n",
                            "      <th>...</th>\n",
                            "      <th>away_player5</th>\n",
                            "      <th>away_player6</th>\n",
                            "      <th>away_player7</th>\n",
                            "      <th>away_player8</th>\n",
                            "      <th>away_player9</th>\n",
                            "      <th>away_player10</th>\n",
                            "      <th>away_player11</th>\n",
                            "      <th>away_player12</th>\n",
                            "      <th>away_player13</th>\n",
                            "      <th>away_player14</th>\n",
                            "    </tr>\n",
                            "  </thead>\n",
                            "  <tbody>\n",
                            "    <tr>\n",
                            "      <th>22342</th>\n",
                            "      <td>Arsenal</td>\n",
                            "      <td>Leicester City</td>\n",
                            "      <td>4</td>\n",
                            "      <td>3</td>\n",
                            "      <td>1</td>\n",
                            "      <td>Petr Cech</td>\n",
                            "      <td>Sead Kolasinac</td>\n",
                            "      <td>Rob Holding</td>\n",
                            "      <td>Nacho Monreal</td>\n",
                            "      <td>Mohamed Elneny</td>\n",
                            "      <td>...</td>\n",
                            "      <td>Danny Simpson</td>\n",
                            "      <td>Marc Albrighton</td>\n",
                            "      <td>Matty James</td>\n",
                            "      <td>Wilfred Ndidi</td>\n",
                            "      <td>Riyad Mahrez</td>\n",
                            "      <td>Shinji Okazaki</td>\n",
                            "      <td>Jamie Vardy</td>\n",
                            "      <td>Daniel Amartey</td>\n",
                            "      <td>Demarai Gray</td>\n",
                            "      <td>Kelechi Iheanacho</td>\n",
                            "    </tr>\n",
                            "  </tbody>\n",
                            "</table>\n",
                            "<p>1 rows × 33 columns</p>\n",
                            "</div>"
                        ],
                        "text/plain": [
                            "      home_team       away_team home_goals away_goals result home_player1  \\\n",
                            "22342   Arsenal  Leicester City          4          3      1   Petr Cech    \n",
                            "\n",
                            "           home_player2   home_player3     home_player4      home_player5  \\\n",
                            "22342   Sead Kolasinac    Rob Holding    Nacho Monreal    Mohamed Elneny    \n",
                            "\n",
                            "       ...     away_player5       away_player6   away_player7  \\\n",
                            "22342  ...   Danny Simpson    Marc Albrighton    Matty James    \n",
                            "\n",
                            "          away_player8    away_player9     away_player10  away_player11  \\\n",
                            "22342   Wilfred Ndidi    Riyad Mahrez    Shinji Okazaki    Jamie Vardy    \n",
                            "\n",
                            "          away_player12   away_player13        away_player14  \n",
                            "22342   Daniel Amartey    Demarai Gray    Kelechi Iheanacho   \n",
                            "\n",
                            "[1 rows x 33 columns]"
                        ]
                    },
                    "execution_count": 6,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "df_2018"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 7,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/html": [
                            "<div>\n",
                            "<style scoped>\n",
                            "    .dataframe tbody tr th:only-of-type {\n",
                            "        vertical-align: middle;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe tbody tr th {\n",
                            "        vertical-align: top;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe thead th {\n",
                            "        text-align: right;\n",
                            "    }\n",
                            "</style>\n",
                            "<table border=\"1\" class=\"dataframe\">\n",
                            "  <thead>\n",
                            "    <tr style=\"text-align: right;\">\n",
                            "      <th></th>\n",
                            "      <th>home_team</th>\n",
                            "      <th>away_team</th>\n",
                            "      <th>home_goals</th>\n",
                            "      <th>away_goals</th>\n",
                            "      <th>result</th>\n",
                            "      <th>home_player1</th>\n",
                            "      <th>home_player2</th>\n",
                            "      <th>home_player3</th>\n",
                            "      <th>home_player4</th>\n",
                            "      <th>home_player5</th>\n",
                            "      <th>...</th>\n",
                            "      <th>away_player5</th>\n",
                            "      <th>away_player6</th>\n",
                            "      <th>away_player7</th>\n",
                            "      <th>away_player8</th>\n",
                            "      <th>away_player9</th>\n",
                            "      <th>away_player10</th>\n",
                            "      <th>away_player11</th>\n",
                            "      <th>away_player12</th>\n",
                            "      <th>away_player13</th>\n",
                            "      <th>away_player14</th>\n",
                            "    </tr>\n",
                            "  </thead>\n",
                            "  <tbody>\n",
                            "    <tr>\n",
                            "      <th>38313</th>\n",
                            "      <td>Manchester United</td>\n",
                            "      <td>Leicester City</td>\n",
                            "      <td>2</td>\n",
                            "      <td>1</td>\n",
                            "      <td>1</td>\n",
                            "      <td>David de Gea</td>\n",
                            "      <td>Luke Shaw</td>\n",
                            "      <td>Matteo Darmian</td>\n",
                            "      <td>Victor Lindelof</td>\n",
                            "      <td>Eric Bailly</td>\n",
                            "      <td>...</td>\n",
                            "      <td>Wes Morgan</td>\n",
                            "      <td>Demarai Gray</td>\n",
                            "      <td>Ricardo Pereira</td>\n",
                            "      <td>James Maddison</td>\n",
                            "      <td>Adrien Silva</td>\n",
                            "      <td>Wilfred Ndidi</td>\n",
                            "      <td>Kelechi Iheanacho</td>\n",
                            "      <td>Rachid Ghezzal</td>\n",
                            "      <td>Vicente Iborra</td>\n",
                            "      <td>Jamie Vardy</td>\n",
                            "    </tr>\n",
                            "  </tbody>\n",
                            "</table>\n",
                            "<p>1 rows × 33 columns</p>\n",
                            "</div>"
                        ],
                        "text/plain": [
                            "               home_team       away_team home_goals away_goals result  \\\n",
                            "38313  Manchester United  Leicester City          2          1      1   \n",
                            "\n",
                            "         home_player1 home_player2      home_player3       home_player4  \\\n",
                            "38313   David de Gea    Luke Shaw    Matteo Darmian    Victor Lindelof    \n",
                            "\n",
                            "        home_player5  ...  away_player5    away_player6       away_player7  \\\n",
                            "38313   Eric Bailly   ...   Wes Morgan    Demarai Gray    Ricardo Pereira    \n",
                            "\n",
                            "           away_player8    away_player9    away_player10        away_player11  \\\n",
                            "38313   James Maddison    Adrien Silva    Wilfred Ndidi    Kelechi Iheanacho    \n",
                            "\n",
                            "          away_player12     away_player13  away_player14  \n",
                            "38313   Rachid Ghezzal    Vicente Iborra    Jamie Vardy   \n",
                            "\n",
                            "[1 rows x 33 columns]"
                        ]
                    },
                    "execution_count": 7,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "df_2019"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 8,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/html": [
                            "<div>\n",
                            "<style scoped>\n",
                            "    .dataframe tbody tr th:only-of-type {\n",
                            "        vertical-align: middle;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe tbody tr th {\n",
                            "        vertical-align: top;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe thead th {\n",
                            "        text-align: right;\n",
                            "    }\n",
                            "</style>\n",
                            "<table border=\"1\" class=\"dataframe\">\n",
                            "  <thead>\n",
                            "    <tr style=\"text-align: right;\">\n",
                            "      <th></th>\n",
                            "      <th>CLUB</th>\n",
                            "      <th>RATING</th>\n",
                            "    </tr>\n",
                            "  </thead>\n",
                            "  <tbody>\n",
                            "    <tr>\n",
                            "      <th>Petr Cech</th>\n",
                            "      <td>Arsenal</td>\n",
                            "      <td>82</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>Sead Kolasinac</th>\n",
                            "      <td>Arsenal</td>\n",
                            "      <td>80</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>Rob Holding</th>\n",
                            "      <td>Arsenal</td>\n",
                            "      <td>74</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>Nacho Monreal</th>\n",
                            "      <td>Arsenal</td>\n",
                            "      <td>80</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>Mohamed Elneny</th>\n",
                            "      <td>Arsenal</td>\n",
                            "      <td>78</td>\n",
                            "    </tr>\n",
                            "  </tbody>\n",
                            "</table>\n",
                            "</div>"
                        ],
                        "text/plain": [
                            "                   CLUB RATING\n",
                            "Petr Cech       Arsenal     82\n",
                            "Sead Kolasinac  Arsenal     80\n",
                            "Rob Holding     Arsenal     74\n",
                            "Nacho Monreal   Arsenal     80\n",
                            "Mohamed Elneny  Arsenal     78"
                        ]
                    },
                    "execution_count": 8,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "player_data.head()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "### My Analysis"
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "Before I detail my analysis, I will load the datasets I created in the previous section."
        },
        {
            "cell_type": "code",
            "execution_count": 9,
            "metadata": {},
            "outputs": [],
            "source": [
                "match_data_2018 = pd.read_csv(\"https://raw.githubusercontent.com/shahzoor/FIFA_PROJECT/master/epl_results_2018_full.csv\")\n",
                "match_data_2019 = pd.read_csv(\"https://raw.githubusercontent.com/shahzoor/FIFA_PROJECT/master/epl_results_2019_first_half.csv\")\n",
                "player_ratings = pd.read_csv(\"https://raw.githubusercontent.com/shahzoor/FIFA_PROJECT/master/epl_player_ratings.csv\")"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "Here is the match data for the 2017/2018 season. I show just the first five results. There were 380 matches played in total over 38 match days. The data from this season is identically formatted but with fewer rows. \n\nThe result column is encoded as follows: 1 for a home team win, 0 for a draw, and -1 for a home team loss.\n\nMissing values in a home or away player12, player13, and player14 indicate that a substitution was not made. For example, if home_player14 has a missing a value, that means the home team made just two substitutions in the game."
        },
        {
            "cell_type": "code",
            "execution_count": 10,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/html": [
                            "<div>\n",
                            "<style scoped>\n",
                            "    .dataframe tbody tr th:only-of-type {\n",
                            "        vertical-align: middle;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe tbody tr th {\n",
                            "        vertical-align: top;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe thead th {\n",
                            "        text-align: right;\n",
                            "    }\n",
                            "</style>\n",
                            "<table border=\"1\" class=\"dataframe\">\n",
                            "  <thead>\n",
                            "    <tr style=\"text-align: right;\">\n",
                            "      <th></th>\n",
                            "      <th>match_id</th>\n",
                            "      <th>home_team</th>\n",
                            "      <th>away_team</th>\n",
                            "      <th>home_goals</th>\n",
                            "      <th>away_goals</th>\n",
                            "      <th>result</th>\n",
                            "      <th>home_player1</th>\n",
                            "      <th>home_player2</th>\n",
                            "      <th>home_player3</th>\n",
                            "      <th>home_player4</th>\n",
                            "      <th>...</th>\n",
                            "      <th>away_player5</th>\n",
                            "      <th>away_player6</th>\n",
                            "      <th>away_player7</th>\n",
                            "      <th>away_player8</th>\n",
                            "      <th>away_player9</th>\n",
                            "      <th>away_player10</th>\n",
                            "      <th>away_player11</th>\n",
                            "      <th>away_player12</th>\n",
                            "      <th>away_player13</th>\n",
                            "      <th>away_player14</th>\n",
                            "    </tr>\n",
                            "  </thead>\n",
                            "  <tbody>\n",
                            "    <tr>\n",
                            "      <th>0</th>\n",
                            "      <td>22342</td>\n",
                            "      <td>Arsenal</td>\n",
                            "      <td>Leicester City</td>\n",
                            "      <td>4</td>\n",
                            "      <td>3</td>\n",
                            "      <td>1</td>\n",
                            "      <td>Petr Cech</td>\n",
                            "      <td>Sead Kolasinac</td>\n",
                            "      <td>Rob Holding</td>\n",
                            "      <td>Nacho Monreal</td>\n",
                            "      <td>...</td>\n",
                            "      <td>Danny Simpson</td>\n",
                            "      <td>Marc Albrighton</td>\n",
                            "      <td>Matty James</td>\n",
                            "      <td>Wilfred Ndidi</td>\n",
                            "      <td>Riyad Mahrez</td>\n",
                            "      <td>Shinji Okazaki</td>\n",
                            "      <td>Jamie Vardy</td>\n",
                            "      <td>Daniel Amartey</td>\n",
                            "      <td>Demarai Gray</td>\n",
                            "      <td>Kelechi Iheanacho</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>1</th>\n",
                            "      <td>22343</td>\n",
                            "      <td>Brighton and Hove Albion</td>\n",
                            "      <td>Manchester City</td>\n",
                            "      <td>0</td>\n",
                            "      <td>2</td>\n",
                            "      <td>-1</td>\n",
                            "      <td>Mat Ryan</td>\n",
                            "      <td>Lewis Dunk</td>\n",
                            "      <td>Markus Suttner</td>\n",
                            "      <td>Shane Duffy</td>\n",
                            "      <td>...</td>\n",
                            "      <td>Fernandinho</td>\n",
                            "      <td>Kyle Walker</td>\n",
                            "      <td>David Silva</td>\n",
                            "      <td>Kevin De Bruyne</td>\n",
                            "      <td>Danilo</td>\n",
                            "      <td>Sergio Aguero</td>\n",
                            "      <td>Gabriel Jesus</td>\n",
                            "      <td>Bernardo Silva</td>\n",
                            "      <td>Leroy Sane</td>\n",
                            "      <td>Raheem Sterling</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>2</th>\n",
                            "      <td>22344</td>\n",
                            "      <td>Chelsea</td>\n",
                            "      <td>Burnley</td>\n",
                            "      <td>2</td>\n",
                            "      <td>3</td>\n",
                            "      <td>-1</td>\n",
                            "      <td>Thibaut Courtois</td>\n",
                            "      <td>Antonio Rudiger</td>\n",
                            "      <td>David Luiz</td>\n",
                            "      <td>Gary Cahill</td>\n",
                            "      <td>...</td>\n",
                            "      <td>James Tarkowski</td>\n",
                            "      <td>Johann Gudmundsson</td>\n",
                            "      <td>Robbie Brady</td>\n",
                            "      <td>Steven Defour</td>\n",
                            "      <td>Jack Cork</td>\n",
                            "      <td>Sam Vokes</td>\n",
                            "      <td>Jeff Hendrick</td>\n",
                            "      <td>Scott Arfield</td>\n",
                            "      <td>Jonathan Walters</td>\n",
                            "      <td>NaN</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>3</th>\n",
                            "      <td>22345</td>\n",
                            "      <td>Crystal Palace</td>\n",
                            "      <td>Huddersfield Town</td>\n",
                            "      <td>0</td>\n",
                            "      <td>3</td>\n",
                            "      <td>-1</td>\n",
                            "      <td>Wayne Hennessey</td>\n",
                            "      <td>Timothy Fosu-Mensah</td>\n",
                            "      <td>Scott Dann</td>\n",
                            "      <td>Jairo Riedewald</td>\n",
                            "      <td>...</td>\n",
                            "      <td>Tommy Smith</td>\n",
                            "      <td>Tom Ince</td>\n",
                            "      <td>Elias Kachunga</td>\n",
                            "      <td>Kasey Palmer</td>\n",
                            "      <td>Philip Billing</td>\n",
                            "      <td>Aaron Mooy</td>\n",
                            "      <td>Steve Mounie</td>\n",
                            "      <td>Rajiv van La Parra</td>\n",
                            "      <td>Danny Williams</td>\n",
                            "      <td>Collin Quaner</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>4</th>\n",
                            "      <td>22346</td>\n",
                            "      <td>Everton</td>\n",
                            "      <td>Stoke City</td>\n",
                            "      <td>1</td>\n",
                            "      <td>0</td>\n",
                            "      <td>1</td>\n",
                            "      <td>Jordan Pickford</td>\n",
                            "      <td>Phil Jagielka</td>\n",
                            "      <td>Ashley Williams</td>\n",
                            "      <td>Michael Keane</td>\n",
                            "      <td>...</td>\n",
                            "      <td>Mame Biram Diouf</td>\n",
                            "      <td>Erik Pieters</td>\n",
                            "      <td>Darren Fletcher</td>\n",
                            "      <td>Joe Allen</td>\n",
                            "      <td>Bojan</td>\n",
                            "      <td>Xherdan Shaqiri</td>\n",
                            "      <td>Saido Berahino</td>\n",
                            "      <td>Eric Maxim Choupo-Moting</td>\n",
                            "      <td>Peter Crouch</td>\n",
                            "      <td>NaN</td>\n",
                            "    </tr>\n",
                            "  </tbody>\n",
                            "</table>\n",
                            "<p>5 rows × 34 columns</p>\n",
                            "</div>"
                        ],
                        "text/plain": [
                            "   match_id                 home_team          away_team  home_goals  \\\n",
                            "0     22342                   Arsenal     Leicester City           4   \n",
                            "1     22343  Brighton and Hove Albion    Manchester City           0   \n",
                            "2     22344                   Chelsea            Burnley           2   \n",
                            "3     22345            Crystal Palace  Huddersfield Town           0   \n",
                            "4     22346                   Everton         Stoke City           1   \n",
                            "\n",
                            "   away_goals  result        home_player1           home_player2  \\\n",
                            "0           3       1          Petr Cech         Sead Kolasinac    \n",
                            "1           2      -1           Mat Ryan             Lewis Dunk    \n",
                            "2           3      -1   Thibaut Courtois        Antonio Rudiger    \n",
                            "3           3      -1    Wayne Hennessey    Timothy Fosu-Mensah    \n",
                            "4           0       1    Jordan Pickford          Phil Jagielka    \n",
                            "\n",
                            "        home_player3       home_player4  ...        away_player5  \\\n",
                            "0       Rob Holding      Nacho Monreal   ...      Danny Simpson    \n",
                            "1    Markus Suttner        Shane Duffy   ...        Fernandinho    \n",
                            "2        David Luiz        Gary Cahill   ...    James Tarkowski    \n",
                            "3        Scott Dann    Jairo Riedewald   ...        Tommy Smith    \n",
                            "4   Ashley Williams      Michael Keane   ...   Mame Biram Diouf    \n",
                            "\n",
                            "           away_player6       away_player7       away_player8  \\\n",
                            "0      Marc Albrighton        Matty James      Wilfred Ndidi    \n",
                            "1          Kyle Walker        David Silva    Kevin De Bruyne    \n",
                            "2   Johann Gudmundsson       Robbie Brady      Steven Defour    \n",
                            "3             Tom Ince     Elias Kachunga       Kasey Palmer    \n",
                            "4         Erik Pieters    Darren Fletcher          Joe Allen    \n",
                            "\n",
                            "       away_player9      away_player10     away_player11  \\\n",
                            "0     Riyad Mahrez     Shinji Okazaki       Jamie Vardy    \n",
                            "1           Danilo      Sergio Aguero     Gabriel Jesus    \n",
                            "2        Jack Cork          Sam Vokes     Jeff Hendrick    \n",
                            "3   Philip Billing         Aaron Mooy      Steve Mounie    \n",
                            "4            Bojan    Xherdan Shaqiri    Saido Berahino    \n",
                            "\n",
                            "                away_player12       away_player13        away_player14  \n",
                            "0             Daniel Amartey        Demarai Gray    Kelechi Iheanacho   \n",
                            "1             Bernardo Silva          Leroy Sane      Raheem Sterling   \n",
                            "2              Scott Arfield    Jonathan Walters                   NaN  \n",
                            "3         Rajiv van La Parra      Danny Williams        Collin Quaner   \n",
                            "4   Eric Maxim Choupo-Moting        Peter Crouch                   NaN  \n",
                            "\n",
                            "[5 rows x 34 columns]"
                        ]
                    },
                    "execution_count": 10,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "match_data_2018.head(5)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "\n\nThe player ratings dataset is show below."
        },
        {
            "cell_type": "code",
            "execution_count": 11,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/html": [
                            "<div>\n",
                            "<style scoped>\n",
                            "    .dataframe tbody tr th:only-of-type {\n",
                            "        vertical-align: middle;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe tbody tr th {\n",
                            "        vertical-align: top;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe thead th {\n",
                            "        text-align: right;\n",
                            "    }\n",
                            "</style>\n",
                            "<table border=\"1\" class=\"dataframe\">\n",
                            "  <thead>\n",
                            "    <tr style=\"text-align: right;\">\n",
                            "      <th></th>\n",
                            "      <th>NAME</th>\n",
                            "      <th>CLUB</th>\n",
                            "      <th>RATING</th>\n",
                            "    </tr>\n",
                            "  </thead>\n",
                            "  <tbody>\n",
                            "    <tr>\n",
                            "      <th>640</th>\n",
                            "      <td>Ben Gibson</td>\n",
                            "      <td>Burnley</td>\n",
                            "      <td>74</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>641</th>\n",
                            "      <td>Sean Longstaff</td>\n",
                            "      <td>Newcastle United</td>\n",
                            "      <td>63</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>642</th>\n",
                            "      <td>Angel Gomes</td>\n",
                            "      <td>Manchester United</td>\n",
                            "      <td>66</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>643</th>\n",
                            "      <td>David Button</td>\n",
                            "      <td>Brighton and Hove Albion</td>\n",
                            "      <td>68</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>644</th>\n",
                            "      <td>Xande Silva</td>\n",
                            "      <td>West Ham United</td>\n",
                            "      <td>67</td>\n",
                            "    </tr>\n",
                            "  </tbody>\n",
                            "</table>\n",
                            "</div>"
                        ],
                        "text/plain": [
                            "               NAME                      CLUB  RATING\n",
                            "640      Ben Gibson                   Burnley      74\n",
                            "641  Sean Longstaff          Newcastle United      63\n",
                            "642     Angel Gomes         Manchester United      66\n",
                            "643    David Button  Brighton and Hove Albion      68\n",
                            "644     Xande Silva           West Ham United      67"
                        ]
                    },
                    "execution_count": 11,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "player_ratings.tail()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "As you can see below, there are no missing player ratings. "
        },
        {
            "cell_type": "code",
            "execution_count": 12,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "False"
                        ]
                    },
                    "execution_count": 12,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "player_ratings[\"RATING\"].isnull().any()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "Now, back to the analysis. \n\nLet's first briefly analyze these player ratings. The function below will produce a swarm plot with a super imposed boxplot for each club in the league. "
        },
        {
            "cell_type": "code",
            "execution_count": 13,
            "metadata": {},
            "outputs": [],
            "source": [
                "def make_swarmplot(df, xlabel, ylabel, ax, point_size =3, point_color='darkgrey', box_pal=\"Blues\"):\n",
                "    \"\"\"Make a swarmplot with a boxplot super imposed given a dataset and two variables to focus on. The ylabel\n",
                "    must be categorical. \n",
                "    \n",
                "    :param DataFrame df: Dataframe, must have categorical and numeric data.\n",
                "    :param str xlabel: Label of column with numeric data, must match df.\n",
                "    :param str ylabel: Label of column with categorical data, must match df.\n",
                "    :param axes ax: Axis object from mpl. \n",
                "    :param dict box_pal: A custome color palette for the box plots.\n",
                "    :return: The original axis object with the plot imposed on it.\n",
                "    :rtype: axes\n",
                "    \n",
                "    \"\"\"\n",
                "\n",
                "    # make box plot for each category/club\n",
                "    ax = sns.boxplot(y = ylabel, x = xlabel, data = df, whis=np.inf, ax= ax, palette=box_pal, width=0.3)\n",
                "    \n",
                "    # make swarm plot for each category/club\n",
                "    ax = sns.swarmplot(y = ylabel, x = xlabel, data = df, size = point_size, color = point_color, ax = ax, alpha = 0.85)\n",
                "    \n",
                "    # remove the top and right line in graph\n",
                "    sns.despine()\n",
                "    \n",
                "    # set size\n",
                "    ax.figure.set_size_inches(20,14)\n",
                "    \n",
                "    # set labels\n",
                "    ax.set_xlabel((xlabel.lower()).capitalize())\n",
                "    ax.set_ylabel((ylabel.lower()).capitalize())\n",
                "    ax.grid(False)\n",
                "    \n",
                "    return ax\n"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "Conventionally, the \"big six\" in the Premier League are Arsenal, Liverpool, Chelsea, Manchester City, Manchester United, and Tottenham Hotspur. These six teams consistently finish in the top six positions in the league in some order and have much higher wage budgets than the other teams. This is borne out in the figure below. The boxplots for these six clubs are the ones farthest right indicating higher-rated players. \n\nYou might also notice that this graph has 23 teams even though the Premier League has just 20 teams. This is because of the relegation/promotion system in most football leagues (notably excluding the MLS). Since I compiled a master list of players who made appearances in the Premier League both this and last season, it contains data for relegated and promoted players. Stoke City, Swansea City, and West Bromwich Albion were relegated to the second division last year and replaced by Cardiff City, Wolverhampton Wanderers, and Fulham. "
        },
        {
            "cell_type": "code",
            "execution_count": 14,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "Text(0.5, 1.0, 'Player Rating Boxplot by Club')"
                        ]
                    },
                    "execution_count": 14,
                    "metadata": {},
                    "output_type": "execute_result"
                },
                {
                    "data": {
                        "image/png": 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\n",
                        "text/plain": [
                            "<Figure size 1440x1008 with 1 Axes>"
                        ]
                    },
                    "metadata": {
                        "needs_background": "light"
                    },
                    "output_type": "display_data"
                }
            ],
            "source": [
                "big_six = [\"Arsenal\", \"Liverpool\", \"Chelsea\", \"Tottenham Hotspur\", \"Manchester United\", \"Manchester City\"]\n",
                "promoted = [\"Fulham\", \"Wolverhampton Wanderers\", \"Cardiff City\"]\n",
                "relegated = [\"Stoke City\", \"Swansea City\", \"West Bromwich Albion\"]\n",
                "\n",
                "my_pal = {club: \"dodgerblue\" if club in big_six else \"hotpink\" if club in relegated else \"aqua\" if club in promoted else \"paleturquoise\"  for club in player_ratings.CLUB.unique()}\n",
                "\n",
                "ax_players = plt.subplot()\n",
                "ax_players = make_swarmplot(player_ratings,\"RATING\",\"CLUB\",ax_players,box_pal=my_pal)\n",
                "ax_players.set_title(\"Player Rating Boxplot by Club\")"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "How will these ratings help?\n\nI am basically trying to estimate the probability of a match outcome conditional on the difference in average rating between two teams. In (my best attempt at) math:\n\n<p style=\"text-align: center;\">Let <b>Y</b> ~ the outcome of a game <br></p>\n<p style=\"text-align: center;\"><b>Y</b> can take values in the set {win, draw, loss}</p>\n\n<p style=\"text-align: center;\">Let <b>D</b> ~ the absolute difference in rating between two teams <br></p>\n<p style=\"text-align: center;\"><b>D</b> can take on any real value <b>d</b> in  [0,100]</p>\n\nI want to estimate $P(Y | D = d)$ <br>\n\nSo the next thing I do is compute the average rating for both the home and away team for every match played in the 2017/18 season and then take the difference. These differences are appended to the dataframe. The two functions that do this are in the cell below. The function call is in the cell that follows."
        },
        {
            "cell_type": "code",
            "execution_count": 15,
            "metadata": {},
            "outputs": [],
            "source": [
                "# these functions compute the rating averages for teams, the differences, and append them to the match data dataframes \n",
                "\n",
                "def compute_team_average(names ,ratings ):\n",
                "    \"\"\"This function computes the average rating for a list of players. It accounts for any empty\n",
                "    strings (i.e. '') in the list.\n",
                "    \n",
                "    :param: list names : A list of names of the players.\n",
                "    :param: DataFrame ratings : An appropriately formatted dataframe containing player ratings.\n",
                "    :return: The average rating of the players passed in.\n",
                "    :rtype: float\n",
                "    \n",
                "    \"\"\"\n",
                "    \n",
                "    #initialize return variable\n",
                "    average = 0  \n",
                "    count = 0 \n",
                "    \n",
                "    # only count players who actually appeared, ignore empty places and NaN values\n",
                "    for name in names:\n",
                "        if type(name) == str:\n",
                "            average = average + ratings[ratings[\"NAME\"]==name.strip()][\"RATING\"].min()\n",
                "            count = count + 1\n",
                "            \n",
                "    # average contains the sum of all player ratings, thus divide\n",
                "    average = average/count\n",
                "    \n",
                "    return average\n",
                "\n",
                "\n",
                "def add_averages_to_df(match_data,ratings):\n",
                "    \"\"\"This function appends the following three coloumns to the match data dataframe:\n",
                "    home_team_rating, away_team_rating, rating_diff. It returns this modified dataframe.\n",
                "    \n",
                "    :param: DataFrame match_data: This dataframe must contain the lineups for each game in the set.\n",
                "    :param: DataFrame ratings: This dataframe must contain player ratings.\n",
                "    :return: Appends three columns to the match_data dataframe: one for the average rating for the home team,\n",
                "            one for the average rating for the away team, and a column for the average difference.\n",
                "    :rtype: DataFrame        \n",
                "    \n",
                "    \"\"\"\n",
                "\n",
                "    # initialize lists to store the home team average rating, away team average rating, and average team difference\n",
                "    home_team_rating = []\n",
                "    away_team_rating = []\n",
                "    average_rating_diff =[]\n",
                "    \n",
                "    # populate the above list by match\n",
                "    for i in match_data.index:\n",
                "        home_team_rating.append(compute_team_average(list(match_data.iloc[i][6:20]), ratings))\n",
                "        away_team_rating.append(compute_team_average(list(match_data.iloc[i][20:34]), ratings))\n",
                "        average_rating_diff.append(home_team_rating[i] - away_team_rating[i])\n",
                "        \n",
                "    # turn the three lists into series\n",
                "    home_average_series = pd.Series(home_team_rating)\n",
                "    away_average_series = pd.Series(away_team_rating)\n",
                "    average_rating_diff = pd.Series(average_rating_diff)\n",
                "    \n",
                "    # append the series as columns into the dataframe\n",
                "    match_data[\"home_average_rating\"] = home_average_series\n",
                "    match_data[\"away_average_rating\"] = away_average_series\n",
                "    match_data[\"rating_diff\"] = average_rating_diff\n",
                "    \n",
                "    return match_data"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 16,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/html": [
                            "<div>\n",
                            "<style scoped>\n",
                            "    .dataframe tbody tr th:only-of-type {\n",
                            "        vertical-align: middle;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe tbody tr th {\n",
                            "        vertical-align: top;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe thead th {\n",
                            "        text-align: right;\n",
                            "    }\n",
                            "</style>\n",
                            "<table border=\"1\" class=\"dataframe\">\n",
                            "  <thead>\n",
                            "    <tr style=\"text-align: right;\">\n",
                            "      <th></th>\n",
                            "      <th>match_id</th>\n",
                            "      <th>home_team</th>\n",
                            "      <th>away_team</th>\n",
                            "      <th>home_goals</th>\n",
                            "      <th>away_goals</th>\n",
                            "      <th>result</th>\n",
                            "      <th>home_player1</th>\n",
                            "      <th>home_player2</th>\n",
                            "      <th>home_player3</th>\n",
                            "      <th>home_player4</th>\n",
                            "      <th>...</th>\n",
                            "      <th>away_player8</th>\n",
                            "      <th>away_player9</th>\n",
                            "      <th>away_player10</th>\n",
                            "      <th>away_player11</th>\n",
                            "      <th>away_player12</th>\n",
                            "      <th>away_player13</th>\n",
                            "      <th>away_player14</th>\n",
                            "      <th>home_average_rating</th>\n",
                            "      <th>away_average_rating</th>\n",
                            "      <th>rating_diff</th>\n",
                            "    </tr>\n",
                            "  </thead>\n",
                            "  <tbody>\n",
                            "    <tr>\n",
                            "      <th>0</th>\n",
                            "      <td>22342</td>\n",
                            "      <td>Arsenal</td>\n",
                            "      <td>Leicester City</td>\n",
                            "      <td>4</td>\n",
                            "      <td>3</td>\n",
                            "      <td>1</td>\n",
                            "      <td>Petr Cech</td>\n",
                            "      <td>Sead Kolasinac</td>\n",
                            "      <td>Rob Holding</td>\n",
                            "      <td>Nacho Monreal</td>\n",
                            "      <td>...</td>\n",
                            "      <td>Wilfred Ndidi</td>\n",
                            "      <td>Riyad Mahrez</td>\n",
                            "      <td>Shinji Okazaki</td>\n",
                            "      <td>Jamie Vardy</td>\n",
                            "      <td>Daniel Amartey</td>\n",
                            "      <td>Demarai Gray</td>\n",
                            "      <td>Kelechi Iheanacho</td>\n",
                            "      <td>80.357143</td>\n",
                            "      <td>77.714286</td>\n",
                            "      <td>2.642857</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>1</th>\n",
                            "      <td>22343</td>\n",
                            "      <td>Brighton and Hove Albion</td>\n",
                            "      <td>Manchester City</td>\n",
                            "      <td>0</td>\n",
                            "      <td>2</td>\n",
                            "      <td>-1</td>\n",
                            "      <td>Mat Ryan</td>\n",
                            "      <td>Lewis Dunk</td>\n",
                            "      <td>Markus Suttner</td>\n",
                            "      <td>Shane Duffy</td>\n",
                            "      <td>...</td>\n",
                            "      <td>Kevin De Bruyne</td>\n",
                            "      <td>Danilo</td>\n",
                            "      <td>Sergio Aguero</td>\n",
                            "      <td>Gabriel Jesus</td>\n",
                            "      <td>Bernardo Silva</td>\n",
                            "      <td>Leroy Sane</td>\n",
                            "      <td>Raheem Sterling</td>\n",
                            "      <td>74.928571</td>\n",
                            "      <td>82.357143</td>\n",
                            "      <td>-7.428571</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>2</th>\n",
                            "      <td>22344</td>\n",
                            "      <td>Chelsea</td>\n",
                            "      <td>Burnley</td>\n",
                            "      <td>2</td>\n",
                            "      <td>3</td>\n",
                            "      <td>-1</td>\n",
                            "      <td>Thibaut Courtois</td>\n",
                            "      <td>Antonio Rudiger</td>\n",
                            "      <td>David Luiz</td>\n",
                            "      <td>Gary Cahill</td>\n",
                            "      <td>...</td>\n",
                            "      <td>Steven Defour</td>\n",
                            "      <td>Jack Cork</td>\n",
                            "      <td>Sam Vokes</td>\n",
                            "      <td>Jeff Hendrick</td>\n",
                            "      <td>Scott Arfield</td>\n",
                            "      <td>Jonathan Walters</td>\n",
                            "      <td>NaN</td>\n",
                            "      <td>82.285714</td>\n",
                            "      <td>77.307692</td>\n",
                            "      <td>4.978022</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>3</th>\n",
                            "      <td>22345</td>\n",
                            "      <td>Crystal Palace</td>\n",
                            "      <td>Huddersfield Town</td>\n",
                            "      <td>0</td>\n",
                            "      <td>3</td>\n",
                            "      <td>-1</td>\n",
                            "      <td>Wayne Hennessey</td>\n",
                            "      <td>Timothy Fosu-Mensah</td>\n",
                            "      <td>Scott Dann</td>\n",
                            "      <td>Jairo Riedewald</td>\n",
                            "      <td>...</td>\n",
                            "      <td>Kasey Palmer</td>\n",
                            "      <td>Philip Billing</td>\n",
                            "      <td>Aaron Mooy</td>\n",
                            "      <td>Steve Mounie</td>\n",
                            "      <td>Rajiv van La Parra</td>\n",
                            "      <td>Danny Williams</td>\n",
                            "      <td>Collin Quaner</td>\n",
                            "      <td>76.384615</td>\n",
                            "      <td>73.000000</td>\n",
                            "      <td>3.384615</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>4</th>\n",
                            "      <td>22346</td>\n",
                            "      <td>Everton</td>\n",
                            "      <td>Stoke City</td>\n",
                            "      <td>1</td>\n",
                            "      <td>0</td>\n",
                            "      <td>1</td>\n",
                            "      <td>Jordan Pickford</td>\n",
                            "      <td>Phil Jagielka</td>\n",
                            "      <td>Ashley Williams</td>\n",
                            "      <td>Michael Keane</td>\n",
                            "      <td>...</td>\n",
                            "      <td>Joe Allen</td>\n",
                            "      <td>Bojan</td>\n",
                            "      <td>Xherdan Shaqiri</td>\n",
                            "      <td>Saido Berahino</td>\n",
                            "      <td>Eric Maxim Choupo-Moting</td>\n",
                            "      <td>Peter Crouch</td>\n",
                            "      <td>NaN</td>\n",
                            "      <td>76.785714</td>\n",
                            "      <td>75.692308</td>\n",
                            "      <td>1.093407</td>\n",
                            "    </tr>\n",
                            "  </tbody>\n",
                            "</table>\n",
                            "<p>5 rows × 37 columns</p>\n",
                            "</div>"
                        ],
                        "text/plain": [
                            "   match_id                 home_team          away_team  home_goals  \\\n",
                            "0     22342                   Arsenal     Leicester City           4   \n",
                            "1     22343  Brighton and Hove Albion    Manchester City           0   \n",
                            "2     22344                   Chelsea            Burnley           2   \n",
                            "3     22345            Crystal Palace  Huddersfield Town           0   \n",
                            "4     22346                   Everton         Stoke City           1   \n",
                            "\n",
                            "   away_goals  result        home_player1           home_player2  \\\n",
                            "0           3       1          Petr Cech         Sead Kolasinac    \n",
                            "1           2      -1           Mat Ryan             Lewis Dunk    \n",
                            "2           3      -1   Thibaut Courtois        Antonio Rudiger    \n",
                            "3           3      -1    Wayne Hennessey    Timothy Fosu-Mensah    \n",
                            "4           0       1    Jordan Pickford          Phil Jagielka    \n",
                            "\n",
                            "        home_player3       home_player4  ...       away_player8  \\\n",
                            "0       Rob Holding      Nacho Monreal   ...     Wilfred Ndidi    \n",
                            "1    Markus Suttner        Shane Duffy   ...   Kevin De Bruyne    \n",
                            "2        David Luiz        Gary Cahill   ...     Steven Defour    \n",
                            "3        Scott Dann    Jairo Riedewald   ...      Kasey Palmer    \n",
                            "4   Ashley Williams      Michael Keane   ...         Joe Allen    \n",
                            "\n",
                            "       away_player9      away_player10     away_player11  \\\n",
                            "0     Riyad Mahrez     Shinji Okazaki       Jamie Vardy    \n",
                            "1           Danilo      Sergio Aguero     Gabriel Jesus    \n",
                            "2        Jack Cork          Sam Vokes     Jeff Hendrick    \n",
                            "3   Philip Billing         Aaron Mooy      Steve Mounie    \n",
                            "4            Bojan    Xherdan Shaqiri    Saido Berahino    \n",
                            "\n",
                            "                away_player12       away_player13        away_player14  \\\n",
                            "0             Daniel Amartey        Demarai Gray    Kelechi Iheanacho    \n",
                            "1             Bernardo Silva          Leroy Sane      Raheem Sterling    \n",
                            "2              Scott Arfield    Jonathan Walters                   NaN   \n",
                            "3         Rajiv van La Parra      Danny Williams        Collin Quaner    \n",
                            "4   Eric Maxim Choupo-Moting        Peter Crouch                   NaN   \n",
                            "\n",
                            "  home_average_rating away_average_rating rating_diff  \n",
                            "0           80.357143           77.714286    2.642857  \n",
                            "1           74.928571           82.357143   -7.428571  \n",
                            "2           82.285714           77.307692    4.978022  \n",
                            "3           76.384615           73.000000    3.384615  \n",
                            "4           76.785714           75.692308    1.093407  \n",
                            "\n",
                            "[5 rows x 37 columns]"
                        ]
                    },
                    "execution_count": 16,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "# function calls to compute averages, find differences\n",
                "rating_games_2018 = add_averages_to_df(match_data_2018, player_ratings)\n",
                "rating_games_2019 = add_averages_to_df(match_data_2019, player_ratings)\n",
                "rating_games_2018.head()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "The graphs below show the distribution of rating differences for both seasons. The difference in rating is calculated is $D = \\overline{R_{home}} - \\overline{R_{away}}$ where $\\overline{R}$ is the average rating. Very high negative and very positive often arise from the same teams playing each other home and away. For example, when Stoke City played Chelsea away, $D=10.65$. In the reverse fixture, $D= -8.02$. That explains the symmetry of the graph.\n\nThe graph also shows that the distribution of average differences this season is quite similar to last season's."
        },
        {
            "cell_type": "code",
            "execution_count": 17,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "Text(0.5, 0.98, 'Differences in Average Ratings Across Seasons')"
                        ]
                    },
                    "execution_count": 17,
                    "metadata": {},
                    "output_type": "execute_result"
                },
                {
                    "data": {
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\n",
                        "text/plain": [
                            "<Figure size 1584x648 with 2 Axes>"
                        ]
                    },
                    "metadata": {
                        "needs_background": "light"
                    },
                    "output_type": "display_data"
                }
            ],
            "source": [
                "# create figure\n",
                "fig, axes = plt.subplots(nrows = 1, ncols = 2, sharey=True, sharex = True)\n",
                "axes[0].figure.set_size_inches(22,9)\n",
                "\n",
                "# plot each histogram in turn\n",
                "for data,label in zip([rating_games_2018[\"rating_diff\"],rating_games_2019[\"rating_diff\"]],['2017/18','2018/19']):\n",
                "    axes[0] = sns.distplot(data, hist = True, ax = axes[0], label= label)\n",
                "    axes[1] = sns.distplot(data, hist=False, kde = True,kde_kws={\"shade\": True}, ax = axes[1], label= label)\n",
                "\n",
                "# remove x labels\n",
                "axes[0].set_xlabel('')\n",
                "axes[1].set_xlabel('')\n",
                "\n",
                "# remove grids\n",
                "axes[0].grid(False)\n",
                "axes[1].grid(False)\n",
                "\n",
                "# remove y axis\n",
                "axes[0].get_yaxis().set_visible(False)\n",
                "\n",
                "# set graph title\n",
                "fig.suptitle(\"Differences in Average Ratings Across Seasons\")"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "I estimate the conditional distribution of outcomes by binning the differences from the 2017/18 season. Then for each bin, I count the number of matches that fall into it, $k$, and then classify each result as a win, draw, or loss for the higher rated team. The probability of an outcome in a given bin is the number of occurances of a specific outcome (win, loss, or draw) divided by $k$. The two functions below carry this out. "
        },
        {
            "cell_type": "code",
            "execution_count": 18,
            "metadata": {},
            "outputs": [],
            "source": [
                "def estimate_conditional_pdf(data, count):\n",
                "    \"\"\"This function estimates the conditional probability of one bin in the conditional pdf.\n",
                "    \n",
                "    :param DataFrame data: Data frame that satisfies: lower_bound <= rating_diff <= upper_bound.\n",
                "    :param int count: Number or rows in this dataframe.\n",
                "    :return: Returns the following three floats: p(win), p(draw), p(loss).\n",
                "    :rtye float, float, float\n",
                "    \n",
                "    \"\"\"\n",
                "    \n",
                "    # count the number of wins \n",
                "    # home team wins, home team is higher rated OR away team  wins, away team is higher rated\n",
                "    wins =  data[data[\"result\"]==1][data[\"rating_diff\"]>0][\"rating_diff\"].count() \n",
                "    wins = wins +  data[data[\"result\"]==-1][data[\"rating_diff\"]<0][\"rating_diff\"].count()  \n",
                "    # count the number of draws\n",
                "    draws = data[data[\"result\"]==0][\"rating_diff\"].count() # ties\n",
                "    \n",
                "    # count the number of losses\n",
                "    # home team wins, away team is highe rated OR away team wins, home team is higher rated  \n",
                "    losses = data[data[\"result\"]==1][data[\"rating_diff\"]<0][\"rating_diff\"].count()  \n",
                "    losses = losses + data[data[\"result\"]==-1][data[\"rating_diff\"]>0][\"rating_diff\"].count() \n",
                "    \n",
                "    return wins/count, draws/count, losses/count\n",
                "    \n",
                "\n",
                "\n",
                "def estimate_full_conditional_pdf(data, _max, _bins):\n",
                "    \"\"\"This function estimates full conditional pdf given data, max differences, and the number of bins (_bins).\n",
                "    \n",
                "    :param DataFrame data: The match data dataframe.\n",
                "    :param float _max: The maximum rating difference between two teams in any game played and part of the data dataframe parameter.\n",
                "    :param int _bins: The number of bins to be used create the conditional distribution.\n",
                "    :return: Returns a dataframe containing the conditional pdf.\n",
                "    :rtype: DataFrame\n",
                "    \n",
                "    \"\"\"\n",
                "    \n",
                "    columns = [\"Difference\",\"Win\", \"Draw\", \"Loss\", \"Count\",\"Min\",\"Max\", \"Sum\"]\n",
                "    index = range(_bins)\n",
                "\n",
                "    pdf = pd.DataFrame(index = index, columns = columns)  \n",
                "    \n",
                "    bin_width = _max/_bins\n",
                "    lower_bound = 0\n",
                "    upper_bound = bin_width\n",
                "    \n",
                "    # creat bins, estimate pdf for each bin in turn\n",
                "    for i in index:\n",
                "        # obtain number of rows in bin\n",
                "        count = data[data[\"rating_diff\"].apply(abs) < upper_bound]\\\n",
                "                [data[\"rating_diff\"].apply(abs) >= lower_bound][\"rating_diff\"].count()\n",
                "        \n",
                "        # deals with zero difference\n",
                "        if i ==0:\n",
                "            count= count-data[data[\"rating_diff\"]==0][\"rating_diff\"].count()\n",
                "        \n",
                "        # calculate pdf for => rating difference in [lower_bound, upper_bound]\n",
                "        p_win, p_draw, p_loss = estimate_conditional_pdf(data[data[\"rating_diff\"].apply(abs) < upper_bound]\\\n",
                "                                                   [data[\"rating_diff\"].apply(abs) >= lower_bound], count)\n",
                "        \n",
                "        # update pdf table row\n",
                "        pdf.loc[i][\"Difference\"] = \"(\" + str(lower_bound) + \", \" +str(upper_bound)+\"]\"\n",
                "        pdf.loc[i][\"Win\"] = p_win\n",
                "        pdf.loc[i][\"Draw\"] = p_draw\n",
                "        pdf.loc[i][\"Loss\"] = p_loss\n",
                "        pdf.loc[i][\"Count\"] = count\n",
                "        pdf.loc[i][\"Min\"] = lower_bound\n",
                "        pdf.loc[i][\"Max\"] = upper_bound\n",
                "        pdf.loc[i][\"Sum\"] = p_win+p_draw+p_loss\n",
                "        \n",
                "        # update bounds\n",
                "        lower_bound = lower_bound + bin_width\n",
                "        upper_bound = upper_bound + bin_width\n",
                "        \n",
                "    return pdf\n",
                "            "
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "The parameter I have the most control over when trying to estimate the conditional pdf is the number of intervals and, consequently, the interval width. This determines how accurate the estimate is going to be. Since I have just 380 data points in my training set, having very small intervals could result in a lot of empty bins. Having intervals that are too large would miss the point entirely and offer no precision at all. Since the relationship between interval size and accuracy is arguably nonmonotonic, I will estimate several conditional pdfs and then pick out whichever one predicts the most match outcomes correctly for this season. \n\nThe next cell finds 22 conditional pdfs. The minimum interval width I set is 0.5 and the maximum interval widths is 11. This is somewhat arbitrary but having smaller widths would result in empty intervals."
        },
        {
            "cell_type": "code",
            "execution_count": 19,
            "metadata": {},
            "outputs": [],
            "source": [
                "_max = abs(max(match_data_2018[\"rating_diff\"].agg([\"min\",\"max\"]), key = abs))\n",
                "pdf = []\n",
                "for num in np.arange(math.ceil(_max)*2):\n",
                "    pdf.append(estimate_full_conditional_pdf(rating_games_2018,math.ceil(_max),num+1))"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "This is the pdf when the interval width is 1. The sum column is a check to make sure that the probabilities add to 1. "
        },
        {
            "cell_type": "code",
            "execution_count": 20,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/html": [
                            "<div>\n",
                            "<style scoped>\n",
                            "    .dataframe tbody tr th:only-of-type {\n",
                            "        vertical-align: middle;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe tbody tr th {\n",
                            "        vertical-align: top;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe thead th {\n",
                            "        text-align: right;\n",
                            "    }\n",
                            "</style>\n",
                            "<table border=\"1\" class=\"dataframe\">\n",
                            "  <thead>\n",
                            "    <tr style=\"text-align: right;\">\n",
                            "      <th></th>\n",
                            "      <th>Difference</th>\n",
                            "      <th>Win</th>\n",
                            "      <th>Draw</th>\n",
                            "      <th>Loss</th>\n",
                            "      <th>Count</th>\n",
                            "      <th>Sum</th>\n",
                            "    </tr>\n",
                            "  </thead>\n",
                            "  <tbody>\n",
                            "    <tr>\n",
                            "      <th>0</th>\n",
                            "      <td>(0, 1.0]</td>\n",
                            "      <td>0.444444</td>\n",
                            "      <td>0.283951</td>\n",
                            "      <td>0.271605</td>\n",
                            "      <td>81</td>\n",
                            "      <td>1</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>1</th>\n",
                            "      <td>(1.0, 2.0]</td>\n",
                            "      <td>0.407407</td>\n",
                            "      <td>0.320988</td>\n",
                            "      <td>0.271605</td>\n",
                            "      <td>81</td>\n",
                            "      <td>1</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>2</th>\n",
                            "      <td>(2.0, 3.0]</td>\n",
                            "      <td>0.487805</td>\n",
                            "      <td>0.365854</td>\n",
                            "      <td>0.146341</td>\n",
                            "      <td>41</td>\n",
                            "      <td>1</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>3</th>\n",
                            "      <td>(3.0, 4.0]</td>\n",
                            "      <td>0.592593</td>\n",
                            "      <td>0.185185</td>\n",
                            "      <td>0.222222</td>\n",
                            "      <td>27</td>\n",
                            "      <td>1</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>4</th>\n",
                            "      <td>(4.0, 5.0]</td>\n",
                            "      <td>0.5</td>\n",
                            "      <td>0.363636</td>\n",
                            "      <td>0.136364</td>\n",
                            "      <td>22</td>\n",
                            "      <td>1</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>5</th>\n",
                            "      <td>(5.0, 6.0]</td>\n",
                            "      <td>0.766667</td>\n",
                            "      <td>0.2</td>\n",
                            "      <td>0.0333333</td>\n",
                            "      <td>30</td>\n",
                            "      <td>1</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>6</th>\n",
                            "      <td>(6.0, 7.0]</td>\n",
                            "      <td>0.72093</td>\n",
                            "      <td>0.139535</td>\n",
                            "      <td>0.139535</td>\n",
                            "      <td>43</td>\n",
                            "      <td>1</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>7</th>\n",
                            "      <td>(7.0, 8.0]</td>\n",
                            "      <td>0.652174</td>\n",
                            "      <td>0.217391</td>\n",
                            "      <td>0.130435</td>\n",
                            "      <td>23</td>\n",
                            "      <td>1</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>8</th>\n",
                            "      <td>(8.0, 9.0]</td>\n",
                            "      <td>0.782609</td>\n",
                            "      <td>0.130435</td>\n",
                            "      <td>0.0869565</td>\n",
                            "      <td>23</td>\n",
                            "      <td>1</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>9</th>\n",
                            "      <td>(9.0, 10.0]</td>\n",
                            "      <td>0.714286</td>\n",
                            "      <td>0.285714</td>\n",
                            "      <td>0</td>\n",
                            "      <td>7</td>\n",
                            "      <td>1</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>10</th>\n",
                            "      <td>(10.0, 11.0]</td>\n",
                            "      <td>1</td>\n",
                            "      <td>0</td>\n",
                            "      <td>0</td>\n",
                            "      <td>1</td>\n",
                            "      <td>1</td>\n",
                            "    </tr>\n",
                            "  </tbody>\n",
                            "</table>\n",
                            "</div>"
                        ],
                        "text/plain": [
                            "      Difference       Win      Draw       Loss Count Sum\n",
                            "0       (0, 1.0]  0.444444  0.283951   0.271605    81   1\n",
                            "1     (1.0, 2.0]  0.407407  0.320988   0.271605    81   1\n",
                            "2     (2.0, 3.0]  0.487805  0.365854   0.146341    41   1\n",
                            "3     (3.0, 4.0]  0.592593  0.185185   0.222222    27   1\n",
                            "4     (4.0, 5.0]       0.5  0.363636   0.136364    22   1\n",
                            "5     (5.0, 6.0]  0.766667       0.2  0.0333333    30   1\n",
                            "6     (6.0, 7.0]   0.72093  0.139535   0.139535    43   1\n",
                            "7     (7.0, 8.0]  0.652174  0.217391   0.130435    23   1\n",
                            "8     (8.0, 9.0]  0.782609  0.130435  0.0869565    23   1\n",
                            "9    (9.0, 10.0]  0.714286  0.285714          0     7   1\n",
                            "10  (10.0, 11.0]         1         0          0     1   1"
                        ]
                    },
                    "execution_count": 20,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "pdf[10][[\"Difference\",\"Win\",\"Draw\",\"Loss\",\"Count\",\"Sum\"]]"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "For any of these pdfs to be acceptable, they have to at least do better than completely random <br>\nguessing, i.e. guessing $p($win$) = p($draw$) = p($loss$)=1/3$. This is shown below."
        },
        {
            "cell_type": "code",
            "execution_count": 21,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/html": [
                            "<div>\n",
                            "<style scoped>\n",
                            "    .dataframe tbody tr th:only-of-type {\n",
                            "        vertical-align: middle;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe tbody tr th {\n",
                            "        vertical-align: top;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe thead th {\n",
                            "        text-align: right;\n",
                            "    }\n",
                            "</style>\n",
                            "<table border=\"1\" class=\"dataframe\">\n",
                            "  <thead>\n",
                            "    <tr style=\"text-align: right;\">\n",
                            "      <th></th>\n",
                            "      <th>Difference</th>\n",
                            "      <th>Win</th>\n",
                            "      <th>Draw</th>\n",
                            "      <th>Loss</th>\n",
                            "      <th>Count</th>\n",
                            "      <th>Min</th>\n",
                            "      <th>Max</th>\n",
                            "      <th>Sum</th>\n",
                            "    </tr>\n",
                            "  </thead>\n",
                            "  <tbody>\n",
                            "    <tr>\n",
                            "      <th>0</th>\n",
                            "      <td>(0, 11.0]</td>\n",
                            "      <td>0.333333</td>\n",
                            "      <td>0.333333</td>\n",
                            "      <td>0.333333</td>\n",
                            "      <td>379</td>\n",
                            "      <td>0</td>\n",
                            "      <td>11</td>\n",
                            "      <td>1</td>\n",
                            "    </tr>\n",
                            "  </tbody>\n",
                            "</table>\n",
                            "</div>"
                        ],
                        "text/plain": [
                            "  Difference       Win      Draw      Loss Count Min Max Sum\n",
                            "0  (0, 11.0]  0.333333  0.333333  0.333333   379   0  11   1"
                        ]
                    },
                    "execution_count": 21,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "random_pdf = pdf[0].copy()\n",
                "for outcome in [\"Win\",\"Draw\", \"Loss\"]: \n",
                "    random_pdf[outcome] = random_pdf.replace(to_replace='.', value=1/3, regex=True)\n",
                "random_pdf"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "The next step is to test these pdfs in turn. I use the data from this season to do that. This testing dataset has 190 points. I know what the lineups are for these games so I can compute the difference in average rating for each of them.\n\nThe two functions below use the pdf function and the difference in rating to simulate a set of games. So they will basically draw from a uniform distribution and compare the draw to the pdf function to determine an outcome.\n\nSince I know what the result for each game is, each pdf gets a score based on how many results it guesses correctly. "
        },
        {
            "cell_type": "code",
            "execution_count": 22,
            "metadata": {},
            "outputs": [],
            "source": [
                "# extract appropriate probabiilities for a single game\n",
                "def simulate_single_game(data, pdf):\n",
                "    \"\"\"Simulates a single game based on the conditional pdf of matching outcomes on rating differences.\n",
                "    \n",
                "    :param DataFrame data: The dataframe row of relevent game.\n",
                "    :param DataFrame pdf: The dataframe containing the conditional pdf.\n",
                "    :return: Returns 1 for a home win, -1 for an away win, and zero for a draw.\n",
                "    :rtype: int\n",
                "    \n",
                "    \"\"\"\n",
                "    \n",
                "    difference = data[0]\n",
                "    u = data[1]\n",
                "    \n",
                "    # extract appropriate probabiilities for the game based on the difference\n",
                "    # i.e. pick out the relevant row of the full pdf\n",
                "    for i in pdf.index:\n",
                "        if abs(difference) >=pdf[\"Min\"][i] and abs(difference) < pdf[\"Max\"][i]:\n",
                "            p_win, p_draw, p_loss = pdf[\"Win\"][i] , pdf[\"Draw\"][i] , pdf[\"Loss\"][i]\n",
                "\n",
                "    # determine simulated result based on u (a random draw from unif(0,1))\n",
                "    if u <= p_win:\n",
                "        if difference > 0 :\n",
                "            result = 1\n",
                "        else:\n",
                "            result = -1\n",
                "    elif p_win < u <= p_win+p_draw:\n",
                "        result = 0\n",
                "    else:\n",
                "        if difference > 0:\n",
                "            result = -1\n",
                "        else:\n",
                "            result = 1\n",
                "\n",
                "    return result\n",
                "\n",
                "def simulate_games(data, pdf):\n",
                "    \"\"\" Simulates all games by making calls to simulate_single_game based on the conditional pdf of matching outcomes on rating differences.\n",
                "    \n",
                "    :param DataFrame data: The dataframe row of relevent game.\n",
                "    :param DataFrame pdf: The dataframe containing the conditional pdf.\n",
                "    :return: Adds a column to the data dataframe that contains the simulated result.\n",
                "    :rtype: DataFrame\n",
                "    \n",
                "    \"\"\"\n",
                "    \n",
                "    return_df = data.copy()\n",
                "\n",
                "    # set seed, 42 because of the hitch-hikers guide to the galaxy\n",
                "    np.random.seed(42)\n",
                "\n",
                "    # generate ranndom numbers to help simulate each match\n",
                "    num_matches = len(return_df.index)\n",
                "    U = np.random.uniform(0,1,num_matches)\n",
                "\n",
                "    # add random numbers to dataframe\n",
                "    return_df[\"U\"] = pd.Series(U)\n",
                "\n",
                "    # simulate all the games\n",
                "    return_df[\"simulated_result\"] = return_df[[\"rating_diff\",\"U\"]].apply(func=simulate_single_game, pdf= pdf,axis=1)\n",
                "    \n",
                "    # remove the U column\n",
                "    return_df = return_df.drop(\"U\", axis=1)\n",
                "    \n",
                "    return return_df\n",
                "\n",
                "# checks how many times the simulated result equalled the actual result\n",
                "def score_simulation(data):\n",
                "    \"\"\" This function scores the simulation results. It does this by comparinng the simuulated result to the actual results. The score is equal to the \n",
                "    number of matches correctly predicted by the simulation.\n",
                "    \n",
                "    :param DataFrame data: A dataframe containing match data and the simulated results for every game.\n",
                "    :return: The score for the simulation. This is equal to the number of times the simulated result equals the actual/observed results.\n",
                "    :rtype: int\n",
                "    \n",
                "    \"\"\"\n",
                "    return data[data[\"result\"]==data[\"simulated_result\"]].count().max()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "The next cell computes the score for each pdf I chose to test. The best performing pdfs are shown right after."
        },
        {
            "cell_type": "code",
            "execution_count": 23,
            "metadata": {},
            "outputs": [],
            "source": [
                "scores = []\n",
                "for i in range(len(pdf)):\n",
                "    scores.append(score_simulation(simulate_games(match_data_2019,pdf[i])))\n",
                "\n",
                "random_guess_score = score_simulation(simulate_games(match_data_2019,random_pdf))"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 24,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/html": [
                            "<div>\n",
                            "<style scoped>\n",
                            "    .dataframe tbody tr th:only-of-type {\n",
                            "        vertical-align: middle;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe tbody tr th {\n",
                            "        vertical-align: top;\n",
                            "    }\n",
                            "\n",
                            "    .dataframe thead th {\n",
                            "        text-align: right;\n",
                            "    }\n",
                            "</style>\n",
                            "<table border=\"1\" class=\"dataframe\">\n",
                            "  <thead>\n",
                            "    <tr style=\"text-align: right;\">\n",
                            "      <th></th>\n",
                            "      <th>Bins</th>\n",
                            "      <th>Bin Width</th>\n",
                            "      <th>Score</th>\n",
                            "    </tr>\n",
                            "  </thead>\n",
                            "  <tbody>\n",
                            "    <tr>\n",
                            "      <th>15</th>\n",
                            "      <td>16</td>\n",
                            "      <td>0.687500</td>\n",
                            "      <td>90</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>16</th>\n",
                            "      <td>17</td>\n",
                            "      <td>0.647059</td>\n",
                            "      <td>90</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>18</th>\n",
                            "      <td>19</td>\n",
                            "      <td>0.578947</td>\n",
                            "      <td>90</td>\n",
                            "    </tr>\n",
                            "  </tbody>\n",
                            "</table>\n",
                            "</div>"
                        ],
                        "text/plain": [
                            "    Bins  Bin Width  Score\n",
                            "15    16   0.687500     90\n",
                            "16    17   0.647059     90\n",
                            "18    19   0.578947     90"
                        ]
                    },
                    "execution_count": 24,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "num_bins = np.arange(math.ceil(_max)*2)+1\n",
                "bin_widths = math.ceil(_max)/num_bins\n",
                "bin_score_info = pd.DataFrame({\"Bins\":num_bins, \"Bin Width\":bin_widths, \"Score\":scores})\n",
                "bin_score_info[bin_score_info[\"Score\"]==bin_score_info[\"Score\"].max()]"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 25,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "72"
                        ]
                    },
                    "execution_count": 25,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "random_guess_score"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 26,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "[<matplotlib.axis.XTick at 0x7f3ea3c42be0>,\n",
                            " <matplotlib.axis.XTick at 0x7f3ea3c42470>,\n",
                            " <matplotlib.axis.XTick at 0x7f3ea3c42390>,\n",
                            " <matplotlib.axis.XTick at 0x7f3ea3c71a90>,\n",
                            " <matplotlib.axis.XTick at 0x7f3ea3c54a90>]"
                        ]
                    },
                    "execution_count": 26,
                    "metadata": {},
                    "output_type": "execute_result"
                },
                {
                    "data": {
                        "image/png": 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\n",
                        "text/plain": [
                            "<Figure size 1440x864 with 2 Axes>"
                        ]
                    },
                    "metadata": {
                        "needs_background": "light"
                    },
                    "output_type": "display_data"
                }
            ],
            "source": [
                "def plot_pdf_scores(bin_score_info, title=''):\n",
                "    \"\"\"This function produces a plot relating bin width, the  number of bins, and the scores for each pdf etimate on a single figure.\n",
                "    \n",
                "    :param DataFrame bin_score_info: The scores for each simulation/pdf result.\n",
                "    :param str title: The title for the plot.\n",
                "    :return: Returns an axes object with the plot on it.\n",
                "    :rtype: Axes\n",
                "    \n",
                "    \"\"\"\n",
                "    \n",
                "    # create scatter points\n",
                "    points = plt.scatter(bin_score_info[\"Bins\"], bin_score_info[\"Bin Width\"],\n",
                "                         c=bin_score_info[\"Score\"], s=75, cmap=\"Blues\")\n",
                "\n",
                "    # create color map\n",
                "    cbar = plt.colorbar(points)\n",
                "    cbar.set_label(\"Score\", rotation=270)\n",
                "    # set limit\n",
                "    plt.gca().set_xlim([0-0.2,22.3])\n",
                "    plt.gca().set_ylim([0.3,11+0.3])\n",
                "    \n",
                "    # set titles\n",
                "    plt.gca().set_title(\"PDF Score as a Function of Bin Width and the Number of Bins\" + title)\n",
                "    plt.gca().grid(False)\n",
                "    \n",
                "    # do regression \n",
                "    ax_scores = sns.regplot(\"Bins\", \"Bin Width\", data=bin_score_info, scatter=False, color=\".01\",truncate=True)\n",
                "\n",
                "    # set size\n",
                "    ax_scores.figure.set_size_inches(20,12)\n",
                "\n",
                "    return ax_scores\n",
                "\n",
                "ax_scores = plot_pdf_scores(bin_score_info, ' [testing data]')\n",
                "\n",
                "for arrow_coord in [(19, 1),(17, 1),(16, 1)]:\n",
                "    plt.gca().annotate('Best Scoring PDFs: 90', xy=arrow_coord, xytext=(15, 4),\n",
                "                arrowprops=dict(facecolor='grey', shrink=0.005),\n",
                "                )\n",
                "\n",
                "plt.gca().annotate('Worst Scoring PDF: 83', xy=(1.25,11), xytext=(5, 8),\n",
                "            arrowprops=dict(facecolor='grey', shrink=0.005),\n",
                "            )\n",
                "\n",
                "plt.gca().set_xticks([0,5,10,15,20])"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "The graph above shows the scores for the pdf against the number of bins and bin width. Like I suspected, the relationship between those two factors and the score is not monotonic. The maximum score occurs at $n_{bins}$=$[16, 17, 19]$. Unsurprisingly, the worst score corresponds to zero bins where we do no conditioning at all. All the scores are higher than the purely random score which is $72$.\n\nThe graph below show the same graph for the training dataset.\n"
        },
        {
            "cell_type": "code",
            "execution_count": 27,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "[<matplotlib.axis.XTick at 0x7f3ea3c58ac8>,\n",
                            " <matplotlib.axis.XTick at 0x7f3ea3c7a978>,\n",
                            " <matplotlib.axis.XTick at 0x7f3ea3c7afd0>,\n",
                            " <matplotlib.axis.XTick at 0x7f3ea627d9e8>,\n",
                            " <matplotlib.axis.XTick at 0x7f3ea627deb8>]"
                        ]
                    },
                    "execution_count": 27,
                    "metadata": {},
                    "output_type": "execute_result"
                },
                {
                    "data": {
                        "image/png": 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1kmR+8ValPy5PIykut4SktsLk0sl4bz5HUrfiTyGEt0lOWEIvz/0ayd0EVtf3uLnbsgaSIcRLSIY5b0NykrUmHwf+o7Sv/p3kj+t1MQ14guQE7B7guv6+sDR//CMk4dIKkvoDq0dR/AA4O4TwVmlOeE+fJDlBe5nkRH4GSUHGAVnH31dP54UQVoWk8v8jJMHR1wbal178kaRo38MxxmKpz0tJTnTeiDG+sKYXlWog/B+S/bKYZDpR9xPf1UPLl4YQHl+Hfn0faCLZZ38iuZtEv/Sjbz39gqRuy/IQQp/z+GOMj5LUufhxad0vMrCim1+mW02c0onzx0nCooUkx11/QoS1mUYygus1oJHkTkDEGOeTFKD8IsnveD5JONmvv40G2fG8B8l32SqSu8r8tEd9hl6V+nst8HLp997bNJ/LSE7cV5IEVv3+/llXMbkzzjkkRX+Xktz95VF6v1X210imh7xC8h1ZrqESY3wG+C7J/nmdpHbNg91eez/J3VheCyGsvrvPhvruliStp1SxuL4jWCVJkjTYlaZLRJJRYv+2uqhutShNy1kAXBRj7FmgdlP3pYEkAKkjKR69oQJUSdIaGFxIkiRpUCpN5XmYZLrUv5GMINo1xti21hdKkoYUa1xIkiRpsHovyVSnepLaM2cYWkhS5YQQvgOcRXKHpn273XL8FOD/khQxrgEu73Y76/EktxofRTL1b3JvU3B744gLSZIkSZLUp1LB73kkd147JcY4p3TXp2XAkaWf9yOpIzSiVBz/fuB/Y4zTQwgXA38XYzxmINu1OKckSZIkSepTjPGBUoHrngokRc4BRgKLS6HFNiTF7lffKv1a4MAQwoBud17tU0UaSG47tpj+3/ZLkiRJklQdaklu4/4Ivd9VqJptBWxRyQ784he/4IorrljTouUxxuV9vT7GWAwhnAvcWrpD4HDg5NLiHYGFMcZ86bn5EMKiUnu/b6td7cHFwSRDVCRJkiRJQ9eRJLdlH0q2WraidelWI5or2omLLrqo/Wc/+1njihUrei76GnB5X68PIaSBLwCnxxgfDCEcDlwXQth7Q/Wx2oOLxQBvvdVKoWCtDkmSJEkaSmpqUmy5ZTOUzv2GmC22GtHMsR/5Hgte73Ngw0YxdtuR3PfLTzd+7GMfO/K73/3ugh6L+9up/YHtY4wPApTCi1ZgL5J6GDuEEGpLoy1qge2BNU036VW1Bxd5gEKhaHAhSZIkSUPXkC0NsOD15by6eFlF+3DppZcuuPTSS+eu48sXAGNDCCHGGEMIewFjgJdijMtCCH8FLgCml/77lxhjv6eJQPUHF5IkSZIkVa9UTfKo1LYHIITwQ+BMkmDi3hDC0hjjPiGEfwJuDCEUSk/9SIxxdRrzj8CUEMK/A28BkwfaTYMLSZIkSZLUpxjjp4BPraH9GuCaXl7zHHDo+mzX26FKkiRJkqRByxEXkiRJkiRVSiqVPCq17SrgiAtJkiRJkjRoOeJCkiRJkqRKSaUqWJzTEReSJEmSJEnrxeBCkiRJkiQNWk4VkSRJkiSpUizO2SdHXEiSJEmSpEHLERebWE1tDfWN9aTrSru+CJ0dnXS2d1a2Y5IkSZKkTS9VU8HinNUxlsHgYhOqTdfSNKwJgNTqITkpkiCjPk327WwFeydJkiRJ0uBTHfHKENHU3EQqlfpbaFGSSqWoqamhoamhQj2TJEmSJGlwcsTFJpKuS8Na6p6kUinqGuroaOvYdJ2SJEmSJFWWxTn75IiLTaSmtn+7OlVTHQeOJEmSJEmbgiMuNpFisdjPJ767qb6+ltpayOehszO/YTsmSZIkSaoci3P2qTp6OQTkunJ9PqeQL/QScKRIpYp0dKxiiy3qaWxMv6tOhiRJkiRJQ5EjLjaRYqFIritHum7NoUOxWOy1vkVXV47m5iauvPJKRo8ezaGHHsbee+9NR0cX+Tx0dTkKQ5IkSZI0NBlcbELtre00DWuiNl0LJAU5V4+w6Mh2kM+tOYAoFqGjo5OxY8cyb948br31Fu6++9fst99+vPe972XYsCZyuSIdHTn6OyNFkiRJkjQYVLA459ruIDGIGFxsYm2r2qiprUlGXtSkKOQLdHV2rbG2RXeFQorddtuNefPmAdDR0cEjjzzCI488wo477shhh72XPfbYnY6OLrq6iuRyhU3wbiRJkiRJ2rgMLiqgkC/Qme8c0Gvy+SLjx4/n/vvvf9ey+fPnM3/+fDKZDAcccADve9/h1NfXkM32XVdDkiRJklRBqVQFi3NWx4gLi3NWia6uPKNGjaK+vr7X52SzWZYuXUo6XUtXl3NGJEmSJEnVz+CiirS3d7Dzzjv3uvzQQw/ljDM+TGtrlwU7JUmSJElDgsFFVall9913X/OS2lqOPfZYOjry1reQJEmSpGqRSlX2UQUMLqpIV1ee3XffY43L8vk8M2fOpLGxltra6jj4JEmSJEnqi8FFFcnlCgwfPpxMJgNAU1MTBx54YHn5yy+/zN13300mU0eqSpIzSZIkSZLWxruKVJn29g522WUXFi1aREtLC5lMhi233JL77rsPgL/85S9sueWWHHTQwbS2dlW4t5IkSZKktUrVVPCuItUxlsHgourUcsghhzB69Gg6O4usWNHBe95zMG+99RaPP/44APfffz8jR45k111395aokiRJkqSqVh3xisq6uvLssMMOdHQU6ezMUywWyWa7OOGEE95RuPOWW25h6dI3aWqqrWBvJUmSJElrZXHOPhlcVJl8vsCyZdl33O40ny/S2trF2WefzZgxYwAoFArMmDGDjo42GhoMLyRJkiRJ1cngYojI5Qq0t+eZNGkSI0aMAKCjo4MpU6ZQW1ukvt7wQpIkSZJUfQwuhpDOzjy5HLS0tNDQ0ADAypUrmTZtGo2NtdTVGV5IkiRJ0qCyujhnpR5VoDp6qX7r6MiTTjdw8cUXU1ubBBWvv/46119/PZlMmtpaf+WSJEmSpOrhWewQ1N6eZ8stR3HmmWeW215++WXuuusumpvTpKqkAIskSZIkDXmpVAVHXFTHuaHBxRCVzeYYN25XjjvuuHLbE088wcMPP0xzs3fBlSRJkiRVB4OLISybzXHQQe/hoIMOKrf97ne/48UXXyCTMbyQJEmSJA1+BhdDWLFYJJvt4oMf/CC77757uf2WW25hyZI3aGy0WKckSZIkVVQqBTUVejhVRINBPl+ktbWLs88+hzFjxgBQKBSYMWMGnZ1tNDQYXkiSJEmSBi+Di81ALlegvT3HpEmTGDFiBACdnZ1MmTKF2toi9fWGF5IkSZJUEd4OtU/V0Uutt87OPLkctLS00NjYCMDKlSuZOnUqjY211NUZXkiSJEmSBh+Di81IR0eedLqBiy66mNraJKh44403uO6668hk0tTWejhIkiRJkgYXz1Q3M+3tebbccivOPPOsctsrr7zCXXfdRSaTJlUlxVkkSZIkaUhIpSr7qAIGF5uhbDbHuHG7cNxxx5XbnnjiCR5++E80N3ubVEmSJEnS4GFwsZnKZnMcdNB7OOigg8pts2bN4oUXnieTMbyQJEmSpE3C4px9qo5eaoMrFpPbpB5//AfZY489yu233norS5a8QWOj4YUkSZIkqfIMLjZjhUKRbLaLs846m+22267UVmDGjBl0dLTS0OCdRiRJkiRJlWVwsZnL5Qq0teW4+OKLGTFiBACdnZ1MnTqV2toi9fWGF5IkSZK00aSoYHHOSr/5/jG4EF1deXI5uOSSS2hsbARg5cqVTJ06lcbGWurqDC8kSZIkSZVhcCEAOjry1NbWc/HFF1NbmwQVb7zxBjNnziSTSVNb66EiSZIkSRucxTn7VB291CbR3p5nxIitOOuss8ptc+fO5c4776S5OU1NTZWMI5IkSZIkDRkGF3qHtrYcO+88juOPP77c9uSTT/LQQw95m1RJkiRJ0iZncKF3yWbzHHjgQbznPe8pt/3+97/n+eej4YUkSZIkbUgVK8xZelQBgwu9S7FYpLW1i+OOO57x48eX22+77TbefPN1mpos1ilJkiRJ2jQMLrRGhUKRbLaLM888i+23377UVuDaa6+lvT1LQ4PhhSRJkiRp4zO4UK9yuQJtbTkuuuhiRo4cCUBnZydTpkyhpqZIfb3hhSRJkiStF+8q0qfq6KUqpqsrTy5XpKWlhcbGRgBWrVrF1KlTaGioJZ32EJIkSZIkbTyedapPHR15amvrmTRpErW1ySiLN998k+uum0lzcx21tR5GkiRJkrRuKlmY0+KcGkLa2/NsscWWnH322eW2uXPncscdd9DcnKampjoOeEmSJElSdTG4UL+1teXYaadxfPCDJ5TbnnrqKf74xz+SyaSr5U46kiRJkqQqYnChAclmuzjggAM4+OCDy21/+MMfiPE5mprSFeyZJEmSJFWhVKqCxTmr4+qzwYUGpFiE1tYujj32OMaPH19uv+2223jjjddpbPROI5IkSZKkDcfgQgNWKBTJZrs488yz2H777QEoFovMnHkt7e2tNDQYXkiSJElSv1SqMGe5QOfgZ3ChdZLLFWhry3HxxRczcuRIADo7O5k6dSo1NQXq6w0vJEmSJEnrz+BC66yrK09XV5GWlktoamoCYNWqVUyZMoWGhlrSaQ8vSZIkSdL68cxS66WjI09tbR0XX3wxtbXJKIslS5Ywc+a1NDfXUVvrISZJkiRJvapYYc7SowpURy81qLW359liiy0555xzym3z5s3j9ttvp7k5TU1NdcybkiRJkiQNPgYX2iDa2nLsuONOnHDCCeW2OXPm8OCDD5LJpKul5oskSZIkbVqOuOhTdfRSVSGbzbH//gdwyCGHlNtmz57Nc889R1NTuoI9kyRJkiRVK4MLbTDFIrS2dnHMMccSQii33377bbz++ms0NXmnEUmSJEnSwBhcaIMqFIpks118+MNnssMOOwBQLBaZOfNa2tpaaWgwvJAkSZKkslSqso8qsEmCixDCd0IIr4QQiiGECd3ax4cQHgohPF/67x6boj/auHK5Am1tOS666CK23HJLALq6upgyZQqpVIH6esMLSZIkSVL/bKoRF7cARwHzerT/N/CTGON44CfAzzZRf7SRdXXl6ews0tLSQlNTEwCtra1MnTqFhoYa0mkH+0iSJElSMvKhUsU5HXFRFmN8IMY4v3tbCGEb4EDg2lLTtcCBIYTRm6JP2vg6O/PU1NQxadIk0umkOOeSJUuYOXMmzc111NYaXkiSJEmS1q6SZ447AgtjjHmA0n8Xldo1RLS35xk+fATnnHNOuW3evHncfvvtNDenqampjoRPkiRJklQZXvLWRtfWlmfs2B058cQTy21z5szhgQceIJNJV8voJEmSJEna8CzO2adKBhfzgR1CCLUApf9uX2rXEJPN5pg4cX8OPfTQctsDDzzAs88+Q1NTuoI9kyRJkiQNZhULLmKMbwB/BS4oNV0A/CXG+Gal+qSNp1iE1tYuPvCBYwghlNvvuOMOXn99MU1N3mlEkiRJ0uaoUoU5a6iWSRib6naoPwwhLADGAveGEJ4uLfpH4JMhhOeBT5Z+1hBVKBTJZrs488wz2WGHHQAoFovMnDmTbHYVDQ2GF5IkSZKkd0oVi8VK92F9jANeWbp0FYVCVb+PzUpdXS0NDSmuuuoq3nrrLQCam5v5h3/4RwqFGjo78xXuoSRJkqTBoKYmxahRwwB2AeZWtjcb3DjglXDpTF59c1VFOrDT6GHEn58Pg3z/Vse4EA0pXV15OjuLtLRcQlNTEwCtra1MnTqFhoYa0mkPS0mSJEmbCYtz9skzRFVEZ2eempo0kyZNJp1OinMuWbKEa6+9lubmOmprPTQlSZIkSQYXqqD29jzDh4/gnHPOJVVK+l599VVuu+02mpvrqKmpjvRPkiRJkrTxGFyootracowdO5YTTzyx3Pb0008ze/ZsMpl0tYxckiRJkqR1kkqlKvqoBgYXqrhsNse+++7HYYcdVm578MEHeOaZp2lqSlewZ5IkSZKkSjO4UMUVi0l4cfTRH2DPPfcst99555289toiwwtJkiRJQ5YjLvpmcKFBoVAoks128eEPf5ixY8cCUCwWue6668hmV9LYWFvhHkqSJEmSKsHgQoNGLlcgm81x4YUXstVWWwHF3TBRAAAgAElEQVTQ1dXF1KlTgTz19YYXkiRJkrS5MbjQoNLVlaezs0hLSwuZTAaA1tZWpkyZQkNDDXV1HrKSJEmShpBUhR9VwLNADTqdnXlSqTSTJk0inU7qWyxdupQZM2aQydRRW+thK0mSJEmbC88ANSi1t+cZNmwE5557brlgzPz587n11ltpbk5TU1Ml0aAkSZIkrYXFOftmcKFBq60tx/bbj+Wkk04qtz3zzDP84Q+zyWTSVMlnTJIkSZK0HgwuNKi1teWYMGFfDjvssHLbH//4IM8887S3SZUkSZKkzYDBhQa1YhGy2RxHH/0B9tprr3L7nXfeyeLFi2hq8k4jkiRJkqpXKlXJ6SKVfvf9Y3ChQa9QKJLNdnHGGWcwduxYAIrFItddN5PW1pU0NhpeSJIkSdJQZXChqpDLFchmu7jooovYaqutSm05pk6dSrGYp77e8EKSJElS9bE4Z98MLlQ1uroKdHYWaGlpIZPJAJDNZpk6dQoNDTXU1Xk4S5IkSdJQ45meqkpHR55UKs2kSZNJp5PinEuXLmXGjBlkMnXU1npIS5IkSdJQ4lmeqk57e55hw4Zz3nnnlYc2zZ8/n1tvvZXm5jpqaqpjuJMkSZIkpajgVBGq49zJ4EJVqa0tz3bb7cCHPnRyue2ZZ57h97+fRSaTrprquJIkSZKktTO4UNVqa8uxzz778N73vrfc9tBDD/H003NoakpXsGeSJEmS1E+pCj+qgMGFqlaxCNlsjve///3svffe5fa77rqLxYsX0tTknUYkSZIkqdoZXKiqFQpFWltznHba6ey4444AFItFrrvuOlatWklDg+GFJEmSJFUzgwtVvXy+QFtbFxdeeCGjRo0CIJfLMW3aVCBneCFJkiRp0KpYYc7SoxoYXGhI6Ooq0NFRYPLkFpqbmwHIZrNMmTKFuroa6uoMLyRJkiSpGhlcaMjo7MyTStUyadIk6urqAFi2bBkzZlxDJpMmnfZwlyRJkjTIVHK0hSMupE2vvT1Pc/MWnHvueeVhTwsWLOCWW24hk6mjpqY6PpiSJEmSpITBhYactrYc2223PSeffHK57dlnn+X3v59FJpOullBRkiRJkoTBhYaotrYce++9D+973+Hltoceeog5c56iqSldwZ5JkiRJ0t9YnLNvBhcakopFyGZzHHXUUey9997l9l//+tcsWrTA8EKSJEmSqoTBhYasQqFIa2sXp512OjvttBMAxWKR66+/nlWrVtDY6J1GJEmSJGmwM7jQkJbPF2hr6+KCCy5g1KhRAORyOaZNm0ahkKO+3vBCkiRJUuU4VaRvBhca8rq6CnR0FGhpaaG5uRmAbDbL1KlTqK9PUVdneCFJkiRJg5XBhTYLnZ15IM2kSZOpq6sDYNmyZcyYMYNMJk067UdBkiRJUgWkKvyoAp6tabPR3p6juXkY5513XnlI1IIFC/jVr35FJlNHTU2VfGolSZIkaTPirRW0WWlryzNmzPaccsop3H777QA899xzzJr1O4466v20tnZRLFa4k5IkSZI0CIUQvgOcBYwD9o0xzgkhjANu6fa0kcAWMcatSq+ZC7SXHgCfizH+ZiDbNbjQZqetLcdee+3NsmXLePDBBwH405/+xJZbbsmECfvS2pqrcA8lSZIkbS4qWSRzHbZ7C/ADYPbqhhjjXGD/1T+HEL7Pu7OGs2OMc9atl04V0WaoWIRsNseRRx7JPvvsU26/++67WbBgPk1NFuuUJEmSpJ5ijA/EGOf3tjyEUA9cBPzvhtyuIy60WSoUirS25jjttNNYuXIlr776KsVikRtuuIG/+7uPMmzYFrS35yvdTUmSJElDXIp1GvmwwbYN8POf/3zsd7/73Z6Ll8cYlw9wlacBC2OMj/dovyaEkAIeAL440PU64kKbrXy+QGtrFxdccAFbb701ALlcjmnTplIodFFf78gLSZIkSUPfzJkzZwOv9Hj8yzqs6u9492iLI2OME4GDSbKSHw90pQYX2qzlcgU6OgpMntxCc3MzAG1tbUyZMoX6+hR1dYYXkiRJkoa2888//0hglx6P7w9kHSGE7YH3A9d0b189tSTG2AH8FDh8oP0zuNBmr7MzT7FYw+TJk6mrqwPgrbfe4pprrqGpKU067cdEkiRJ0saxujhnpR4Al1566YIY49wej4FOE7kEuDPGuHR1QwihOYQwovTvFHA+8NeB7iPPyCSgoyNPJjOM888/v/zhXbhwIbfc8isymTpqaioz50ySJEmSBosQwg9DCAuAscC9IYSnuy2+hHdPE9kWmBVCeBKYA4wHPj7Q7aaKxeK69XhwGAe8snTpKgqFqn4fGiQymTQxPsvtt99ebjv00EM5+uijWbWqi+r+uEiSJEnVpaYmxahRwyCZujC3sr3Z4MYBrxz02TuYvzRbkQ7sOCrDY1ecAoN8/zriQuqmrS3HXnvtzRFHHFFue/jhh3niiSdoavImPJIkSZK0qRlcSN0Ui5DN5jjiiCOYMGFCuf3uu+9m4cL5NDVZrFOSJEmSNiWDC6mHQqFIa2uOU089lZ133rncfsMNN7By5QoaGw0vJEmSJG0Yg6E452BncCGtQT5foLW1i/PPP5+tt94agFwux7Rp08jnu6ivN7yQJEmSpE3B4ELqRS5XoKOjwOTJLTQ3NwPQ1tbG1KlTqK9PUVdneCFJkiRp/Tjiom8GF9JadHbmKRZraGlpoa6uDoC33nqLa665hqamNOm0HyFJkiRJ2pg865L60NGRp7FxGOeff0E5kVy4cCG/+tXNZDJ11NRUR0opSZIkSdXI4ELqh/b2HNtuO4ZTTz2t3BZj5P7776O5uY4qGWElSZIkabCp5DSRKjmRMbiQ+qmtLceee+7JkUceWW7785//zF//+lcymXQFeyZJkiRJQ5fBhdRPxSJkszkOP/xwJkyYUG7/zW/uZv78V2lqMryQJEmSpA3N4EIagEKhSGtrjlNOOZWdd9653H7DDTfw9ttv0djonUYkSZIk9Z93FembwYU0QPl8gWy2i/PPP5+tt9661JZn+vTp5PNdNDQYXkiSJEnShmJwIa2DXK5AR0eBlpYWhg0bBkBbWxtTplxNXV2KujrDC0mSJEn9kKrwowoYXEjrqLMzT6FQw+TJk6mrqwNg+fLlTJ8+naamNOm0Hy9JkiRJWl+eWUnroaMjT1NTMxdccEF5ftiiRYu4+eabyGTqqKmpkghTkiRJkgYpgwtpPbW15dlmmzGcdtpp5bbnn3+e++67l+bmumq5NbIkSZKkCkhRweKcVTJXxOBC2gDa2nKEsCdHHXVUue2RRx7hL395nEzG26RKkiRJ0royuJA2gGIRstkc73vf+9h3333L7ffccw+vvjqPpibDC0mSJEnv5u1Q+2ZwIW0ghUKR1tYcJ598CuPGjSu333jjjaxYsYzGRu80IkmSJEkDZXAhbUD5fIG2thznnXc+o0ePLrXlmT59Ovl8Jw0NhheSJEmSNBAGF9IG1tWVp6Mjz+TJkxk2bBgA7e3tTJkyhXQ6RV2d4YUkSZKkRCpVyekilX73/WNwIW0EnZ15CoUaWlpaqK+vB2D58uVMnz6NpqY06bQfPUmSJEnqD8+epI2koyNPQ0OGCy64gJqa5KO2ePFibr75JjKZOmpqqiTelCRJkrTxpCr8qAIGF9JG1N6eZ/TobTnttNPKbc8//zz33vtbmpvrqqaKryRJkiRVisGFtJFlsznGjw8cddRR5bZHH32Uxx9/jEzGeheSJEmStDYGF9ImkM3meO9738e+++5bbvvtb3/LvHlzaWpKV7BnkiRJkiqpcoU5U1UzAtzgQtoECoUi2WyOk08+hXHjxpXbb7rpJlasWEZjoyMvJEmSJGlNDC6kTSSfL9DWluP8889n9OjRpbY806dPJ5/vpKHB8EKSJEna3Djiom8GF9Im1NWVp709z+TJLQwfPhyA9vZ2rr76atJpqKszvJAkSZKk7gwupE2sszNPoZBi8uTJ1NfXA7BixQqmT59OU1OadNqPpSRJkiSt5hmSVAEdHXkaGpq54IILqKlJPoaLFy/mpptuJJOpo6amOoZsSZIkSVo/ThXpm8GFVCHt7TlGj96W0047vdz2wgsv8Nvf3kNzc13VfIlIkiRJ0sZkcCFVUDabY489xnP00UeX2x577DEee+wxMhnrXUiSJElDXiVHW1TJxVKDC6nCstkchx56GBMnTiy33Xvvb5k7dy6ZTLqCPZMkSZKkyjO4kCqsWCySzeb40Ic+xC677FJuv/nmm3jrrWU0NjryQpIkSdLmy+BCGgTy+QLZbI7zzjuPbbbZptSW55prppPLddDQYHghSZIkDVmpCj2qhMGFNEh0deVpb88zefJkhg8fDkB7eztTpkwhnYb6esMLSZIkSZsfgwtpEOnszJPPp2hpaaG+vh6AFStWMH36dBob06TTfmQlSZIkbV48C5IGmY6OPA0NTVx44YXU1CQf0cWLF3PjjTfQ3FxHbW0VjemSJEmStFaVuqNI+c4iVcDgQhqE2trybL31Npx++unlthdffJF77rmHTKauar5gJEmSJGl9GVxIg1Q2m2P33cdz9NFHl9see+wxHnvsUW+TKkmSJA0Rjrjom8GFNIhlszkOPfQwJk6cWG679957mTv3ZZqaDC8kSZIkDX0GF9IgViwWyWZznHTSh9hll13K7TfffDPLly+lsdE7jUiSJEka2gwupEEuny/Q1pbjvPPOY5tttim15Zk+fTq5XAcNDYYXkiRJUrVKpSr7qAYGF1IV6OrK096eZ/LkyQwfPhyAjo4Orr76atJpqK83vJAkSZI0NBlcSFWiszNPPp+ipaWFhoYGAN5++22mTZtGY2Mt6bQfZ0mSJKnaWJyzb57pSFWkoyNPfX0TF154ITU1ycf3tdde48YbbySTqaO2tjq+eCRJkiSpvwwupCrT3p5n1KjRnHHGGeW2F198kXvu+Q2ZTF3VpKaSJEmS1B8GF1IVymZz7LbbHnzgAx8otz3++OM8+ugjZDLeJlWSJEmqFhbn7JvBhVSlstkchxxyKPvvv3+57b777uPll18yvJAkSZI0ZBhcSFWqWCySzXZx4oknseuuu5bbf/Wrm1m2bAmNjd5pRJIkSRrskpEPlSrOWel33z8GF1IVy+eLZLM5zj33XLbddlsACoUC11xzDV1d7TQ0GF5IkiRJqm4GF1KVy+XytLfnmTRpMsOHDwego6ODKVOmkE5Dfb3hhSRJkqTqZXAhDQGdnXnyebjkkktoaGgA4O2332bq1Kk0NtaSThteSJIkSYORxTn7ZnAhDREdHXnq6hq58MILqalJPtqvv/46N9xwA5lMmtraKvlWkiRJkqRuDC6kIaS9Pc+oUaP58Ic/XG576aWX+M1v7iaTqSNVLZGqJEmStJlIpVLU1FTmUS3nBwYX0hCTzebYddfdOeaYY8ptf/nLX3j00Ue8TaokSZKkqmNwIQ1B2WyOgw8+hAMOOACAdDrNttuOoVgsVrhnkiRJkjQwXn6VhqBisUg228UJJ5xILpfjfe87nGHDhpPN5irdNUmSJEndVLJIZpXMFDG4kIaqfL5INpvj9NPPIJttp60tX+kuSZIkSdKAGVxIQ1gul+ett1pxhogkSZI0OKVSlSuSaXFOSYOCoYUkSZKkauaIC2kz9MMffpcxY7bj3HMvBODTn/4E22yzLZ///FcA+NGPrmT06NGcf/7F67Wd66+fwWmnnUljY+O7lj344Gz+53/+i0KhSD6f4+yzz+eMM85ar+0BXHbZp/jqV7/O8OHD12s9ixcv4qKLzmGnnXYml+ti4sQD+MxnPs/rr7/GRRedw84770xnZyeZTIYzzzyXk046BYC77rqdn/70B2y99TYA7Lbb7nzlK//R63ZWrFjOl7/8OZ577hlOOukUPv3pz5WXfeITl7J06RIaGpL9d+WVP2bLLbfilltu5Oabb6CmppampiY++9kvscsuu67X+5UkSZIGK4MLaTM0YcJEfve7ezn33AspFAosX76c1tbW8vI5c57kU5/6TL/Wlc/nqa2tXeOy66+/lg9+8EPvCi5yuRxXXPF1rrpqCttssy2dnZ289tqidX9DJAVJi8Ui3/nOD9drPd3tsMMOXH31DHK5HP/8z//E7NmzGD9+T3bYYQd++csZACxcuIAvfemzFAoFTj75NACOOeb4dwQQa1Nf38DHPvZPvPLKi7z88kvvWv7Vr/4ne+659zvajj/+RM4442wAHnjg9/zoR1fyve/9aH3eqiRJkirE4px9M7iQNkP77TeRH/3oewC88srL7LrrbixduoS3336bxsZG5s17hfHjA8VikZ/+9If86U8PkkqlaGn5KMce+0Eef/xRfvnLqxg1amtefPF5rrpqKv/+75/njTfeoFDIc8klH2PZsmUsWfImn/rUPzBixEh+9KOflbefzbaSz+cZMWIEAPX19ey00zgAli1byre//U0WLVoIwGWXfZ59953IzJnTufPO2wA49dQzOPfcC1m8eBGXXfYpDjjgPTz99JN885vf5ROfuJT/+Z9ptLVlueyyT7Hffvvz1FNPMnr0aL71re/S0NDIs88+zbe+9X9pbGxiv/32509/epBp067vdX+l02kmTNiPBQvmM378nu9YtsMOY/nkJ/+VH//4ynJwMRBNTU1MnLg/CxfO7/drmpuHlf/d1tZWNXMTJUmSpHVhcCFthrbeejS1tbW89tprPPXUE0yYsC9vvvkmTz/9JM3Nw9httz2oq6tj1qz7eOGFyNVXX8uKFcv52McmM3HigQA8++zTTJ16HdtvvwOzZt3H1luP5tvf/gEAq1atYtiwYVx33TX88Ic/Y+TIke/Y/hZbjOCII47irLNO5aCDDubww4/kuONOoKamhu9//zsccMCBfPOb3yGfz9PW1sZzzz3LXXfdzs9/PoViscill17C/vsfyPDhW/Dqq/P4whe+ymWXff5d73PBgvlcfvnX+dznvsxXvvJ5Zs26nxNO+BDf+MbX+Oxnv8S++07kv/6r75EK7e3tPPbYI3z0o/+wxuXjx+/JvHnzyj/ff/9vefLJJwA455zzOfnk07jllhsByiMl+usb3/gaNTW1HH30MbS0fLQcUtx00/Vcd9015HI5fvCD/xrQOiVJkqRqMiiCixDCKcD/BVIkBUMvjzHeXNleSUPbvvtOZM6cJ5gz50nOO+8ilix5g6eeepJhw4YxYcJ+ADz55F857rgTqK2tZautRnHAAQfy3HNPk8k0s9de+7D99jsAsOuuu/OTn/yAn/70hxx++JFMnHhAn9v//Oe/wksvvcijjz7MtddO45FHHuZLX7qcxx9/hC9/+WsA1NbWMmzYMJ588q8cddQHaGpqAuD97/8ATzzxV4444ijGjNmOCRP2XeM2tttue/bYIwAQwp4sXryIlStXks1m2XffiUAy7eKPf5y9xtcvXLiQSy65kFQKjjji/bz3vYezePG7p7QUe1RAXdNUkYEGFpBMExk9ehuy2Va+9KXPcvfdd5ZraZx11rmcdda53HPP3UyZ8ovyPpMkSVJ18a4ifav4XUVCCClgGjApxrg/cDEwJYRQ8b5JQ9mECfsxZ86TvPzyi+y6627ss8++PP30Uzz11JPlk/q13ZFkdYgAsNNOO/OLX0xjt91257//+8f88pdX9asPu+22O+eddxFXXvlTZs26fy3P7L0jayr8uVpdXV353zU1teTz+XeFDGuzusbFL385o9fRFgAvvBAZN25cv9fbX6NHJwU+M5lmjj/+RJ599ul3Pee44z7I7NmzNvi2JUmSpMFisIQDBWBE6d8jgcUxxkIF+yMNefvtN5EHH3yA4cNHUFtbyxZbjGDlypU8/fRT5REX++9/APff/1vy+TxvvfUWf/3rX9hrr33eta4lS96koaGRE074EBdcMInnn38OgEwmQzbb+q7nZ7NZHn/80fLPL7wQGTNmDAAHHXRweVpFPp+ntXUVEyceyOzZs2hvb6etrY0//OF3TJy4/zq97y222IJMJsOcOU8BcN9996zTelZbvHgRP/nJ9znrrPPWaz095XI5li9fXv73H/84m1133Q2A+fNfLT/vj398gLFjd9qg25YkSdKms3rERaUe1aDiU0VijMUQwrnArSGEVmA4cHKFuyUNebvuujsrVizn+ONPKLftttvutLVlyzUpjjrqA8yZ8xSXXHIBqVSKj3/8U4watTXz5s19x7peeulFfvrTH5BK1ZBOp8v1Jk477cNcdlnymu7FOaHIjBlT+fa3v0FDQyNNTY186UuXA/DP/3wZV1zxde6441Zqamq57LLPM2HCfpx00in8/d9PBpLinOPH77nGaRv98fnP/ztXXPGfNDY2ccABBzFs2LC+X9TNwoUL+chHLizfDvWss87rszDn2mpcnH32qbS2tpLLdTF79u/53vd+zJgx2/HpT3+CfD5HPl/gPe85hFNP/TCQ1Ld49NE/k06nGT58eHnfSZIkSUNRaiDDpjeGEEIauBv4aozxwRDC4cC1wN4xxlV9vHwc8MrSpasoFCr7PiRVj2w2SyaTAWDatKtZunQJ//Ivl1W4V5IkSeqppibFqFHDAHYB5la2NxvcOOCVk658kEXL2yvSge1HNvLrfz0cBvn+rfiIC2B/YPsY44MApfCiFdgLeKSiPZM0JD300ANMm3Y1+XyOMWO244tfvLzSXZIkSdJmKpVKHpXadjUYDMHFAmBsCCHEGGMIYS9gDPBShfslaYg69tgPcuyxH6x0NyRJkiT1Q8WDixjjayGEfwJuDCGsLsj5kRjjskr2S5IkSZKkja+SRTKrY8hFxYMLgBjjNcA1le6HJEmSJEkaXAbL7VAlSZIkSZLeZVCMuJAkSZIkaXNkcc6+OeJCkiRJkiQNWo64kCRJkiSpQlKpyhXnrFxR0IFxxIUkSZIkSRq0DC4kSZIkSdKg5VQRSZIkSZIqxOKcfXPEhSRJkiRJGrQccSFJkiRJUoVYnLNvjriQJEmSJEmDlsGFJEmSJEkatJwqIkmSJElShVics2+OuJAkSZIkSYOWwYUkSZIkSRq0nCoiSZIkSVKFJFNFKnVXkYpsdsAccSFJkiRJkgYtR1xIkiRJklQhFufsmyMuJEmSJEnSoGVwIUmSJEmSBi2nikiSJEmSVDGpihXnhOqYK+KIC0mSJEmSNGg54kKSJEmSpAqxOGffHHEhSZIkSZIGLYMLSZIkSZI0aDlVRJIkSZKkCkmlKlecs3JFQQfGEReSJEmSJGnQcsSFJEmSJEkVYnHOvjniQpIkSZIkDVoGF5IkSZIkadByqogkSZIkSRVicc6+OeJCkiRJkiQNWo64kCRJkiSpQhxx0TdHXEiSJEmSpEHL4EKSJEmSJA1aThWRJEmSJKlCUqnkUaltVwNHXEiSJEmSpEHLEReSJEmSJFWIxTn7ZnAhSZIkSZL6FEL4DnAWMA7YN8Y4J4QwDril29NGAlvEGLcqvWY8MAUYBSwFJscYXxjIdg0uJEmSJElSf9wC/ACYvbohxjgX2H/1zyGE7/POrOG/gZ/EGKeHEC4GfgYcM5CNWuNCkiRJkqQKWl2gc1M/BirG+ECMcX5vy0P4/+zdeXycdbn///c9M9kza9pS2goBpDdioVAohdKWAoW2k4aDB1RU5ABq1fM9oiI/5Yiix10UERXwIK6ooEfPUdJMW6ClK2UTKPvN1kKzL22WWZPJ3L8/koa0tk3SJrlnkteTxzxI7jsz95XplnnP9bk+Zr6kj0j6Vd/nUyTNkXRf35fcJ2mOaZqTh3NdOi4AAAAAAJjA7r777hm33nrr/ofbLMtqG+ZDXSKp1rKsp/s+f1ff5z2SZFlWj2madX3Hm4f6oHRcAAAAAAAwgd1///2bJe3Y7/a5w3ioa9XXbTGSCC4AAAAAAHDI3l1FnLpJ0hVXXLFQ0nH73X48nO/DNM1pks6T9IcBh3dJmm6aprvva9ySpvUdHzKWigAAAAAAMIGtXLmyZuXKlTuP8GGullRtWVbr3gOWZTWZpvmspA9J+n3f/5+xLGvIy0QkggsAAAAAABxzuIMyR+raw2Ga5k8k/aukqZIeNk2z1bKs9/advlrSdQe426ck/dY0zZsl7ZF01XDrJLgAAAAAAACDsizrOh04nJBlWTMPcvwVSfOO5LrMuAAAAAAAAFmLjgsAAAAAABziMgy5HFor4tR1h4uOCwAAAAAAkLXouAAAAAAAwCG5NJzTKXRcAAAAAACArEVwAQAAAAAAshZLRQAAAAAAcEjvUhFn1mywVAQAAAAAAOAI0XEBAAAAAIBDDENyMZzzkOi4AAAAAAAAWYvgAgAAAAAAZC2WigAAAAAA4BDDMBwczpkba0XouAAAAAAAAFmLjgsAAAAAABxiyLkhmbnRb0HHBQAAAAAAyGIEFwAAAAAAIGuxVAQAAAAAAIcYff85de1cQMcFAAAAAADIWnRcAAAAAADgEJfRe3Pq2rmAjgsAAAAAAJC1CC4AAAAAAEDWYqkIAAAAAAAOMQxDhuHQcE6HrjtcdFwAAAAAAICsRXDhoEymR93dXU6XAQAAAABA1mKpiIN6ejKqr6+T3++XzxfImTYdAAAAAMDIMIzem1PXzgV0XDispyejlpZW1dbWKJGI5cxvHAAAAAAAxgIdF1kilUqpvr5BXm+pgsEyeTz80gAAAADAeGcYhlwM5zwkXh1nEdu21dHRqXg8oWAwKJ/P73RJAAAAAAA4iqUiWSidTqu5uVn19bVKpZJOlwMAAAAAgGPouMhi8XhCyWSdfD6vgsGQXC630yUBAAAAAEYQwzkHR8dFlstkMmpra1dtbY1isU5JttMlAQAAAAAwZui4yBFdXd1qbGxScXGnysomKS8v3+mSAAAAAABHyDAMx4Zk5spwTjoucoht24rF4qqtrVFb227ZdsbpkgAAAAAAGFUEFzmopyej1tbdqq2tVSIRy4b8UQIAACAASURBVJl1SQAAAAAADBdLRXJYKpVSfX2DSkqKFQyGlJ9f4HRJAAAAAIBhYDjn4Agucpxt24pGY4rHE/L5vAoEgnK7+WUFAAAAAIwPvMIdJ/buPhKNxhQIBOTz+XNm0AoAAAAATFQuGXI59NrNpdx4zciMi3EmnU6rpaVFtbW7FItFxfapAAAAAIBcRnAxTqVSXWpsbFRDQ71SqUTOrF0CAAAAAGAgloqMY3u3T00kEiopKVEwGFJeXr7TZQEAAAAA+hh9N6eunQsILiaATMZWZ2dU8XhcPp9Pfn+AAZ4AAAAAgJzAq9cJpKcnoz172tTZGe0b4OmTYbBaCAAAAAAcYxjObayQIzMFeNU6Ab0zwLNGsVinGOAJAAAAAMhWBBcT2N4BnvX1dUom47kStgEAAAAAJhCWikxwti3F4wklEkmVlBQrGAwpP7/A6bIAAAAAYEJwGb03p66dCwguIKl3B5JoNKZ4PCGfzyu/PyiPh98eAAAAAABn8coU+8hkMmpra1c0GpPf37sDCQM8AQAAAABOIbjAAaXTabW27lZnZ6eCwZBKS71OlwQAAAAA445hyLFdRXJlziFvpeOQurq61dTUqLq6GiUSsZz5jQ0AAAAAGB/ouMCgbFtKJJJKJhtUXFykYDCkgoJCp8sCAAAAgJzX23Hh3LVzAcEFhsy2bcVicSUSSXm9XgUCDPAEAAAAAIwuXnVi2DKZjNrb2xWLxRQI+OXz+RngCQAAAAAYFUMOLkzTNCXNllQ68LhlWb8a6aKQG9LptFpaWtXR0aFQqHeAp207XRUAAAAA5A7DMBwczpkba0WGFFyYpvllSTdL2i4pPuCULYngYoLr6upWY2OTotGoysomyePJc7okAAAAAMA4MdSOi89JOsuyrOdGsxjkLtu2FY3GlEymFAqF5PV6JeVGegcAAAAATnEZvTenrp0LhjqYICHpldEsBONDOp1Wc3OTGhrq1d3d5XQ5AAAAAIAcd9COC9M0B4YaX5X0U9M0vy6pceDXWZaVGZ3SkKtsW4rF4komaxQMhuT3B5wuCQAAAACQow61VCSt3hkW0js9/x8fcN7oO+8ehbowDvT0ZNTS0qJ4PKZQqEwFBYVOlwQAAAAA2cXB4ZwaB8M5jxuzKjCuxeMJJZN1CgYD8vuDOTO5FgAAAADgvIMGF5ZlvbX3Y9M0b7As64f7f41pmtdL+tEo1YZxJJPJqLV1t2KxuCZPnqT8fLovAAAAAMCQc9sa5MpbykMdznnzQY5/ZaQKwcSQTCZVW1un3btbZNuMRwEAAAAAHNoht0M1TfOCvg/dpmmer30DmeMldY5WYRi/MpmM9uxpUzye0KRJZSosLHa6JAAAAABAljpkcCHpl33/L5T0qwHHbUkNkj4zGkVhYkilUqqvr5fX61MoFJLLxZxXAAAAABOLS4ZcDs0BdOXIYpFDBheWZR0nSaZp/s6yrKtGqwjTNAsl3SZpiaSkpG2WZa0creshe2Qyttrb25VIxBUKlam0tFS2Pfj9AAAAAAATw2AdF5Kk0Qwt+tyi3sBipmVZtmmaR43y9ZBlurq61djYqM7ODgWDIbZOBQAAADAhGIZzu5KO5XVN05wmyWtZljXgmFfSTEmvWpZ10FEUBw0uTNPcpd4lIYdkWdYxwyv3n65TKukqSTMsy7L7HrPxSB4Tucm2bcVicSUSSfn9Pvn9AbndQ8rWAAAAAADZ7TZJj0uyJMk0TVPSFkluSYZpmpWWZW050B0P9arwygEfz5X0b5J+IuktScdK+g9Jvzvi0qUTJLVK+lrfANCopK8crGCMf3uHd0ajUQWDIXm9PqdLAgAAAAAcmXMlXT/g8y9JqrYs62rTND8g6ft9X/NPDhpcWJa1ce/HpmneIWmpZVm1A46tlrRG0q1HVrs86t2h5BnLsv4/0zTnSaoyTfPdlmV1HOFjI4d1d6fV3Nykzs4OhUIhFRUVM/8CAAAAwLhiGIYMh9aKjPF1/QMzBfXOuNw72/J/JN19sDu6hniBaerthBgoKmn6UCs8hLckpSXdJ0mWZT0uqUW961wwwdm2lEgkVV9fr8bGBqXT3U6XBAAAAAAYvjbTNN8lSaZpzpR0tKTH+s7lqzcXOKChDhB4QNIDpml+S1KNpHdJ+s++40fEsqwW0zQfkXSRpAf7voEpkl4/0sfG+JHJ2OrsjCoejysQCMjvD8gwhpq7AQAAAEB2mijDOSVVSbrPNM371DuKotqyrLa+cwslvXywOw71ld+nJG2T9HNJT/f9//G+4yPhU5K+bJrm85Lul/TRAd8A0K+nJ6PW1t2qqdmlWKxTQ5gfCwAAAABw3hclvSjpk+ptVFg54FyDpM8d7I6GndtDA8ol7WhtjSqTyb3vo7u7WzU1u5TJZJwuJScZhqHi4iK2TwUAAADGKZfLUFlZqSQdJ2mns9WMuHJJO74ceVWtcWeWxJcV5+k74ZnSGD2/pmleJunj6l3FUSPpl5Zl/c9g9zvUdqiLLMva1PfxBQf7Osuy1g+/XODIDdw+1estVSAQksfD9qkAAAAAcodhGHJNgOGcpmmulHSTejf4eF29O4z+yDTNgGVZvzjUfQ/1Ku9OSbP6Pv7lQb7GVu+OIIBjMpmM2ts7FIvFFQwG5fP5JDm0SAwAAAAAcCDXS3qfZVlP7z1gmuZWSb+XdHjBhWVZswZ8fNwIFAmMqnQ6rZaWZsXjMZaPAAAAAEB2mTYwtJAky7KeNk1zxmB3PORwTtM0v2ia5jzTNOm/R06wbSkWi6uurk5tbbuV4zNcAAAAAIxze3cVceo2hnaapnnCwAOmaR4v6e3B7jhYILFE0lclGaZpPiZpo6RNkh6zLCt1mMUCoy6T6d19JBaLq6wspMLCYqdLAgAAAICJ7KOSuvY71i3pysHueMjgwrKsi03TdEs6Q737qi6U9FlJJaZpPiVpo2VZXzmskoExkEwmVV9fL5/Pp2AwJJfL7XRJAAAAANDPMIwxHZK5/7XHimVZ203TzDNNc4GkaZLq1NsUsWuw+w66BMSyrB5JT/TdbjVNM6De/VavlzRfEsEFslomY6utrV3xeFyhUJlKS0vFChIAAAAAGDumab5H0gOSSiTtUu+WqDHTNCsty3rlUPcdNLgwTbNM0qIBt6MlbZN0i6TNR1Y6MHa6urrV2NioWCyqUGgSW6cCAAAAwNi5S9IvLMu6Ze8B0zS/1Hf8/EPd8ZCv3EzTfFFSkXpnW2yR9HPLsqwjLhdwiG3b6uyMKpFIKhQKyev1iq1TAQAAADjFpUF2zRjla4+h09Q7R3OgWyXdONgdB6uzTr1tHMeqt41jhmmaTDlEzkun02publJDQ726upgzCwAAAACjrEbSgv2OLew7fkiDDee8qG845xz1LhP5jKQ/mKb5lnqXiWy2LOvvh1Uy4LC9W6cmk0kFg0H5fAHHhuIAAAAAmJgmynBOSV+W9HfTNFepdwvUYyWtkPSRwe44aGeIZVk9lmU9aVnWrZZlXSrpJEl/Ve+WJf97RGUDWaCnJ6OWllbV19cqlUo4XQ4AAAAAjDuWZT0g6UxJlqSQpFcknWFZVtVg9z2c4ZynqncJyTr1zr4AxoVEIqm6unr5fF62TgUAAACAEWZZ1muSvjHc+w1lOOdJknZI2iTpJ5I2WZa143CKBLJdJpMZsHVqSKWlXrZOBQAAADBqXJJcDq1YH8vhnKZp/koH2RnBsqxrDnXfwTouvilpo2VZ9YdZG5CTerdObVJnZ6fKyiYpLy/f6ZIAAAAAIJcNHMJpqHcDkH+RdN9gdxxsOOf9R1YXkLts2+4b3lnD8E4AAAAAo8IwnOu4GMuXN5Zl3bz/MdM0z5b01cHu69R2sUDO2Du8s66uVslk3OlyAAAAAGBcsCzrMfXO0jwkggtgiJLJpOrr69XS0qR0Ou10OQAAAACQc0zTNEzTnNz3cYGkfzFN85DZxKC7igB4RyZjq729Q7FYXMFgUF6vj+UjAAAAAA6bYcix1xRjeVnTNPMlfV/SJyQVm6YZl3SPpC9alpU51H2HHFyYpumXZEoqHXjcsqz1w64YyHHpdFrNzc2KRjsVCoVUVFTM7iMAAAAAcHBfkzRN0omSXpR0hqTbJH1H0g2HuuOQggvTNK+WdIekqKSBi/xtSccPu1xkrV3tSa17fbdea+n9ZZ45qVgXvjukGf5ChyvLTolEUnV19fJ6SxUMlsnjoYkJAAAAwNC5HBzOOcbXvULS2ZZlNZumKcuydpim+W+SntNIBBeSvi3pcsuyVh9hochij77Vpv97sUndmd5ESpKeqY/qhcao/vW9R+mcY/2O1petbNtWR0en4vGEAoGAfD4/y0cAAAAAYF9llmU173csLSl/sDsOdTinR9KDw60KuaO+I6X/e7FJXQNCC6n3466M9L8vNqqhM+VUeTkhnU6rpaVFtbU1SiRiY7peDAAAAACyXK1pmtP7PnaZpnmOpD9K+r/B7jjU4OL7kr4y2KRP5K4Nb+5R+hDjUNIZacOOtrErKIelUinV1zeosbFB6XS30+UAAAAAyGK9wzmdu42huyS9d++3LekPkl6Q9PnB7jjUpSKflzRV0hdN02wdeMKyrGOGXiey1WutcR1qjGtG6p97gcHZtq3Ozqji8bgCgYD8/oAMg9wPAAAAwMRkWdbPBnw8rDkEQw0urhxWRcg5riFEbU4NjMllPT0ZtbbuVjQaVSgUUklJKbuPAAAAAOjnMowhvR4brWvngiEFF5ZlbRztQuCsU6aWatOOPUof5EW1x5BOPar0wCcxqFSqSw0NjSop6VQoVKa8vEHnzwAAAAAAdIjgwjTNmyzL+nbfx9842NdZlnXzaBSGsbXwuIC27Nyz72TOAVyGtOC4wNgWNc7Ytq1oNKZEItG3fCTI7iMAAAAAMIhDdVzMGPDxu0a7EDgrVJSna8+crl89VStbUnffwIs8V+/UlI/Pna5gUZ6TJY4be5ePxONxlZVNUkFBodMlAQAAAHCIoaHvmjEa184FBw0uLMv69ICPrxmbcuCk90wp0VcvOF7b3m7TC40xyZBmTSnROccE5Csc6jgUDFUikVRdXZ0CAb8CgSDDOwEAAADgAIb9atQ0zSmSFkh6ybKsV0a+JDjJV+jR0pmTtHTmJKdLmRAymYx2796jWCyuSZPKVFhY7HRJAAAAAJBVDhlcmKY5XdJPJZ0saZukH0raJKlHUsA0zassy7p/1KsExrlUKqX6+nr5fD6FQmV0XwAAAAAThGH03py6di4Y7NXRzyXtkfR59S5/WSvp45ZlTZH0fklfHt3ygIkjk7HV1tau2toaJRIxp8sBAAAAgKwwWHAxX9KnLctaLenfJR0l6W+SZFnW3yUdO7rlARNPKtWl+voGtbY2y7YzTpcDAAAAYBS5DMPRWy4YLLjIsyyrS5Isy4pL6rQsa+CGmbnxXQI5xrb3dl/UKpmMO10OAAAAADhmsOGcHtM0z9c7AcX+n7tHrTIA/bMv/H6/gsEQsy8AAAAATDiDBRdNkn414PPW/T5vGvGKAOwjk7G1Z0+b4vGEJk+epIKCIqdLAgAAADBCDDk4nNOZyw7bIYMLy7LKx6gOAINIpVKqq6tXIOBXIBCSkSPr0QAAAADgSAzWcQEgi2QyGe3evUeJREJlZWV0XwAAAAA5zmX03py6di5gwTyQgxKJpOrq6tXa2qxMpsfpcgAAAABg1NBxAeSoTCajtrZ2xeNxhUIhlZSUKndWqQEAAADINaZp/lDSZZLKJZ1iWdYLfccLJd0maYmkpKRtlmWt7Du3s+9Ysu9hvmRZ1trhXJfgAshxXV3damxsUnFxp8rKJikvL9/pkgAAAAAMkWEYcjk0v+4w5ub9TdLtkjbvd/wW9QYTMy3Lsk3TPGq/85fvDTkOB8EFMA7Ytq1YLK5kskaBQEB+f5DhnQAAAACG5O67755x66237n+4zbKstoEHLMvaIkmmafYfM02zVNJVkmZYlmX3fV3jSNZHcAGMIz09GbW27lY0GlNZWUjFxSWybaerAgAAAHAwhuHgdqh9173//vv376CQpP+S9PUhPMwJklolfc00zfMlRSV9ZW/I0ecPpmkakrZI+vL+gchgGM4JjEOpVEr19Q1qbGxQOt3tdDkAAAAAstgVV1yxUNJx+91+PMS7eyQdL+kZy7LOlPQlSf9rmqav7/xCy7JmS5qr3qF8PxtufXRcAOOUbdvq7IwqkUgqEAjI5/OzfAQAAADAP1m5cmXNypUrdx7m3d+SlJZ0nyRZlvW4aZotkmZKesqyrF19x1Omad4p6YHhXoCOC2CcS6fTamlpUV1drZLJuGNtaAAAAAD+mctw9nakLMtqkfSIpIskyTTNmZKmSHrdNM0S0zT9fccNSVdIenbYz9GRlwkgFySTSdXV1aupqUnpdNrpcgAAAADkGNM0f2KaZo2kGZIeNk3zxb5Tn5L0ZdM0n5d0v6SP9s2xOErSBtM0n5P0gnq7MP59uNdlqQgwgdi2rY6ODsXjcQWDQXm9PpaPAAAAAA4y+v5z6trDYVnWdZKuO8DxNyUtPsjx0w+zvH50XAATUDqdVnNzs+rre5ePAAAAAEC2IrgAJrBEIqn6+no1N7N8BAAAAEB2YqkIMMFlMvsuH/H5/E6XBAAAAEwYIzUk83CvnQvouAAgad/lI6lUwulyAAAAAEASHRcA9hOPJ5RM1svrLVUwGJLbzV8TAAAAAJzDKxIA/ySTyai9vUOxWFyhUEher1dyaNIxAAAAMJ4ZDi4VyZUNBlkqAuCgepePNKm+vk5dXUmnywEAAAAwAdFxAeCQbHvv8pE6+XxeBQJBlo8AAAAAI8QwDBkOtT44dd3houMCwJBkMhm1tbWrtrZG0WinJNvpkgAAAABMAAQXAIaluzutpqZGNTTUK5Vi+QgAAACA0UW/N4Bhs20pFosrkUjK7/cpGAzJMMhBAQAAgOFyybnhnLnyE3yu1AkgC2UyGe3Z06ba2holErGcmUoMAAAAIHfQcQHgiKVSXaqvb5DX61UoFGJ4JwAAADBEhuHctqS58sYjHRcARoRt2+ro6GB4JwAAAIARRXABYET1Du9sUkNDvbq7u5wuBwAAAECOo58bwIizbVuxWFzJZI2CwaB8vkDO7BENAAAAjCWXYcjl0M/KTl13uOi4ADBqenoyamlpVV1drZLJeM6soQMAAACQPei4ADDqksmk6urq5fWWKhgsk8fDXz0AAACA1Dsg06ntUHPljUVePQAYE73DOzsVjyf6lo/4nS4JAAAAQA5gqQiAMZVOp9Xc3Ky6ulqlUgmnywEAAACQ5ei4AOCIRCKhurp6+XxeBYMhuVxup0sCAAAAxpxhOLdkI1eWitBxAcAxmUxGbW3tqq2tUTwezZm/OAEAAACMHTouADiuq6tbDQ2NKi2NKhSaxPBOAAAATBguGXLJoe1QHbrucNFxASAr2Latzs6oamtrFI12SrKdLgkAAABAFiC4AJBV0um0mpqa1NBQr3S62+lyAAAAADiMfmwAWce2bcVicaVStQoGg/J6fTIYgAEAAIBxiOGcg6PjAkDWGrh1KsM7AQAAgImJjgsAWS+ZTKqhoVHFxR0KBkMqKCh0uiQAAABgRLiM3ptT184FBBcAcsLe5SOJRFKlpaUKBoPyePKcLgsAAADAKCO4AJBTMpmMOjo6FItF5ff75fcH5HK5nS4LAAAAwCghuACQk3p6Mtq9e486OzsVCDDAEwAAALnJMCSXQz/H5sqPzwznBJDTurvfGeCZSMRy5i9fAAAAAENDcAFgXEgmk6qvb1BDQ726ulJOlwMAAABghLBUxCHbtz+r6uoHdNJJJ+vUU2fT4g6MANu2FY3GFI8n5Pf7FAgEmX8BAACArGbIuSUbufIqlODCId/73re0YcM6SdKMGe/S8uUrtGxZWEcdNdXhyoDcl8lktGdPm6LRKPMvAAAAgBzHUhGHfOELX9Ts2adLkmpqdukXv7hLl19+ia6//jN6+OEHlUrR6g4cKeZfAAAAINu5DMPRWy4wbNt2uoYjUS5pR2trVJlM7n0f3d3d2rjxEa1a9XetXbtabW17+s+Vlnq1ZMnFqqio1Eknncy7xcARMgxDxcVFCoXKlJ9f4HQ5AAAAGAKXy1BZWakkHSdpp7PVjLhySTv+9Gytol09jhRQmu/WB0+bLmX580tw4aDu7m7V1OxSJpNROp3Wtm1bFYlU6dFHt6in553fuMcff4LC4UotXbpcwWDIwYqB3OdyueTzeRUIBOV2s1oOAAAgmxFcjC6Ci7FRrnESXAy0e3er1q5drUikSjt2vNl/3O12a/78BaqoqNTZZ58rj4cXXcDh8ng8CgQC8vn8dDQBAABkqYkQXPx5u7PBxQdmE1yMtnKNw+BiL9u29corL6m6ukoPP/ygotHO/nPBYEhLly5XOFyp448/YaxKBsadgoICBYNBlZSUKHfmKgMAAEwMBBeji+BibJRrHAcXA6VSKW3evFGRSJWefPJxDfx1e8973quKikpdeOHF8nq9o1kyMC4x/wIAACA7TYTg4i8OBxeXE1yMunJNkOBioIaGBq1ZU63Vq1eptram/3h+foEWLVqsiopKnXHGXLlcbBoDDIfL5ZLf71MgEJTL5Xa6HAAAgAmP4GJ0EVyMjXJNwOBiL9u2tX37M4pEqvTII+uUSCT6zx111FQtX16h5ctXaPr0GSNVMjAh5OfnKRQKqaSkVCwfAQAAcA7BxegiuBgb5ZrAwcVA8XhMjzyyTtXVVXruuWf3OXfaaXNUUVGpxYsvVFFR0RFfC5gI9i4fCQZDKigodLocAACACWlCBBfP1SnmUHBRku/W5adOk7L8+SW4cNBIBhcD7dr1tiKRVVqzplrNzU39x4uKinXBBUsUDlfq1FNns5MCMAQsHwEAAHAOwcXoIrgYG+UiuDionp4ePfXUE4pEqrRp0wZ1d3f3n5sx4xiFwyu0bFlYU6YcNSrXB8aT3uUjZSotLVVu/7UJAACQOyZCcPFXh4OLywguRl25CC6GpKOjXQ89tFaRyCpZ1sv9x10ul8488yxVVFyiBQsWqaCAHRWAgzEMQyUlxSormyyPx+N0OQAAAOMewcXoIrgYG+UiuBi2N954XZFIldaujaitra3/uNfr00UXLVU4XCnTPImlJMBBeDwehUKhvu2H+XMCAAAwWgguRhfBxdgoF8HFEV3/0Ue3KBKp0mOPPaqennf+sJxwwomqqFihiy5armAw6Eh9QDYzDKm4uFhlZZOUl5fvdDkAAADj0kQILv7v+XpHg4v3nXK0lOXPL8GFg5wOLgZqbW3R2rWrFYlUaefOHf3HPR6P5s9foHC4UmefPZ/2eGA/brdLwWBQPl+ALiUAAIARRnAxugguxka5CC5GlG3beumlFxWJVOnhh9cqFov1nwuFQlq2rELhcKXKy49zsEog+xQVFSoUCqmoqJjhnQAAACNkIgQXf3M4uLiU4GLUlYvgYtQkk0lt2vSIqqur9PTTT2ng75WTT56lcLhSS5ZcrNLSUgerBLLH3uGdwWBI+fkMugUAADhSBBeji+BibJSL4GJMNDTUa/XqVYpEVqm+vq7/eH5+gc47b7EqKi7RnDlnyuVyOVglkB1cLpd8Pq/8/iDLqwAAAI4AwcXoIrgYG+UiuBhTmUxGzz77jKqrH9CGDeuUSqX6z02derSWL6/Q8uUrNG3adAerBLKDx+NRIOCXz+eXYRDqAQAADNdECC7+/oKzwcW/zCK4GG3lIrhwTCwW1fr1DysSqdLzzz+3z7k5c85UOFypxYsvUGFhoUMVAtkhPz9PwWBIpaVep0sBAADIKQQXo4vgYmyUi+AiK7z99k5FIqu0enW1Wltb+o8XF5fowguXKByu1KxZp7LrAiYsw5AKCxngCQAAMBwTIbh44MUGR4OLS947Vcry55fgwkHjKbjYK51O68knH1d1dZW2bNmodDrdf+6YY45VOFypZcvCmjRpsoNVAs4xDEOlpSUKhcrk8eQ5XQ4AAEBWI7gYXQQXY6NcBBdZq729TQ89tFbV1Q/otdde7T/ucrk0b945Cocrde65C5Wfn+9glYAz3G6XAoGA/P4A8y8AZL1Fi87S8ce/W7Zty+126fOf/6JOOWX2sB/nz3/+oy655F8PuIx069bNuueeu5TJ2OrpSevyy6/QpZdedsS133DDdfra174tr/fIluvV19fpIx95v4455lil092aPft0feELN6qxsUEf+cj7deyxx6qrq0vFxcX613/9gJYvXyFJikSqdOedt2vSpCmSpBNOeLe++tVvHPQ67e1t+spXvqRXXnlJy5ev0PXXf6n/3EMPrdG99/5ahmGorGyybr75mwoEAurq6tK3vvU1WdbL8vn8+sY3vqujj552RN8vkC0ILkZXrgQXjLvHqPH7A7r88g/q8ss/qNdes1RdXaWHHlqj9vZ2bdu2Vdu2bZXf79dFFy1TRUWlTjzRdLpkYMz09GTU2rpbnZ2dCoVCKikplcRSKgDZqaCgQL/5zR8lSY8/vk3//d936Gc/u3vYj/PnP9+niy8O/1NwkU6ndcst39YvfvFbTZlylLq6utTQUHeQRxka27Zl27Z++MOfHNHjDDR9+nT95jd/VDqd1mc/+2lt3rxBM2eepOnTp+vXv+59fmpra3TTTV9UJpNRRcUlkqQLLrhonwDiUPLzC/Txj39aO3a8rjfffKP/eDqd1u2336rf//5/FAgEdOedt+uvf/2TPvaxT2rVqr/L6/XqT3/6mx5+eK3uuuun+sY3vjti3zeA0WVIcuptrFz56ZPgAmPixBNNfe5zpv7f//ustm7drEikSo899qja29v1l7/8SX/5y5904okzFQ5X6uKLl8nvDzhdMjAmurq61djYpOLiTgWDIRUUMMwWQHaLxWL7dC/88Y+/0/r1D6u7u0uLFp2vj33sk0okErr55hvV1NSkTKZHk7iecQAAIABJREFUV1/9ce3evVstLc267rpPyu8P6Kc//e/+x4jHY+rp6ZHf75ck5efn65hjyiVJu3e36gc/+K7q6molSTfccKNOOWW27r//96qufkCSVFl5qT7wgQ+rvr5ON9xwnU4//Uy9+OJz+u53b9V//MdK3XPPvUok4rrhhut06qmn6fnnn9PkyZP1ve/dqoKCQr388ov63ve+qcLCIp166ml67LGtuvfePx/0OfB4PJo161TV1OzSzJkn7XNu+vQZ+sxnPq+f/ey2/uBiOIqKijR79mmqrd11gLO2ksmEbNuvWCym6dPfJUnasmWjrr12pSRp8eILddttt8i2bWaLARg3CC4wpvLy8rR48QVavPgCtbS0aO3aiCKRKr311k699tqruv32W3XHHbdrwYJFCocrddZZZ8vj4bcpxjfbthWLxZVIJOXzeRUMhuRyuZ0uCwD6pVIpXX31h9XVlVJra4tuv/3nkqQnnnhMu3bt0i9+8VvZtq0bb7xezz77tNra9mjSpMn6wQ9ulyRFo1GVlpbqT3/6g37yk/9WILDvGxQ+n18LFizSZZdV6owz5urccxdqyZKlcrlc+vGPf6jTT5+j7373h+rp6VEikdArr7ysSKRKd9/de92VK6/WaafNkdfr09tvv6X//M+v6YYbbvyn76OmZpe+/vVv60tf+oq++tUbtWHDei1dGtZ3vvNf+uIXb9Ipp8zWXXf9dNDnI5lM6h//eFIf+9gnD3h+5syT9NZbb/V/vn79Q3ruue2SpPe//wpVVFyiv/3tL5KkSy+9fAi/Ar1hyRe+cKOuuuoKFRUVasaMY/q7OJqbmzRlylH9X1dSUqr29vZ/ep4BIFdl1StC0zS/Junrkk6xLOsFh8vBKJs0aZI+8pGr9OEPf1QvvviCIpEqrVv3oGKxmDZsWK8NG9arrGySli0Lq6Kisv+dF2C8ymQyamtrVzwe79s+leUjALLDwKUiL7zwnL71ra/p3nv/pCeeeExPPvmYrrnmI5KkRCKumpq3deqpp+uOO27XnXf+ROeeu1CzZ58+6DVuvPGreuON1/XUU4/rvvvu1ZNPPq6bbvq6nn76SX3lK/8lSXK73SotLdVzzz2rRYvOV1FRkSTpvPPO1/btz2rBgkWaOvVozZp1ygGvcfTR0/qXpprmSaqvr1NnZ6fi8Xj/zI6LLlqmRx/dfMD719bW6uqrPyzDkBYsOE/nnHOu6uv/eUnL/jPkDrRUZKiBxV7pdFp/+9tf9etf/0HTpk3Xbbfdonvv/bWuvvrjB9ypimYLIHcYhuFYh1SudGZlTXBhmuYcSWdLetvpWjC2DMPQrFmnaNasU3Tddddr48b1ikSq9I9/PKXW1hb94Q+/0x/+8DvNmnWKKiou0QUXLOmbBwCMT11d3WpqalI0yvIRANln1qxT1d7epra2PbJtW1deefUBh2j+8pf3atu2rfr5z3+ms846W9dc84lBH/uEE96tE054t5YurdD733+Jbrrp6wf5yoMPZT/Q4M+98vLe2c3J5XKrpyf1TyHDoeydcTGY116zVF5ePuTHHYrXXrP6apghqTcM+f3vfyNJmjJlipqaGjVlylFKp9OKxaLy+fwjen0AcFJWjLI3TbNA0h2S/l2H+pcI415hYaGWLg3r9tvv0v/8z9917bUr+6div/DC8/r+97+tSy5Zpm9+82t6+umnxu2OLMDe5SN1dXXavbtFmYwzk6YBYH9vvbVTmUyPfD6/5s07R9XVDygej0vqXbKwZ0/vLIuCgt5/0z/0oY/q1VdfkSQVFxcrHo/902PG43E9/fRT/Z+/9pqlqVOnSpLOOGNu/7KKnp4exWJRzZ49R5s3b1AymVQikdCmTY9o9uzTDuv78fl8Ki4u1gsvPC9JWrfuwcN6nL3q6+t0xx0/1mWXffCIHmd/kydP0c6db2rPnj2SpCeffFzHHnucJOnccxdp9epVkqQNG9Zpzpy5OfMuKoDe/lonb7kgWzouviHp95Zl7TBNdpZAr6OPnqZrr/2Err76Y3rmmX8oEqnShg3rlUqltHZtRGvXRnT00dO0fPkKhcMrNHXq0U6XDIy4TCajPXvaFIvF2H0EgGP2zriQeoPVm276L7ndbp111tnauXOHPvWpayRJRUXFuvnmb6qmZpfuvPN2GYZLHo+nf97EJZe8TzfccJ3KyibtM5xTsvXHP/5OP/jBd1RQUKiiosL+bovPfvYG3XLLt7Vq1d/lcrl1ww03atasU7V8+Qp94hNXSeodzjlz5kkHXLYxFDfeeLNuueVbKiws0umnn9G3VG/oamtrdc01H+7fDvWyyz446GDOQ824uPzySsViMaXT3dq8eaN+9KOf6bjjjtc113xC//Efn5DH49FRRx2tm276miRpxYp/0Te/ebM++MFL5fP59PWvf2dY9QNAtjOG0x43GkzTPEfStyVdaFmWbZrmTkkrhjjjolzSjtbWqDKZ3GvU6O7uVk3NLroGhiEajWr9+odUXV2lF198vv+4YRiaM+dMVVRUatGi8w/ZJgrkKsMwVFRUqGAwqKKi4gOuaQYADF88HldxcbEk6d57f6PW1hZ97nM3OFwVAElyuQyVlZVK0nGSdjpbzYgrl7Sj+qVGxbuc6a4tzner4uSjpCx/frMhuLhR0nWSuvoOzZDUKOkay7IG69UrF8HFhLVz5w5FIqu0dm21Wltb+4+XlJTowgsvVjhcqfe+dxatkhh3DMNQcXER8y8AYISsW/eg7r33N+rpSWvq1KP15S9/XcFg0OmyAGhiBBeRl5oU73YouMhzK3zyFCnLn1/Hg4v90XGB4Uqn03riicdUXf2Atm7drHQ63X+uvPw4LV++QkuXhjVp0iQHqwRGnsvlUmlpiQKBoPLy8p0uBwAAYMQRXIyuXAkusmXGBXDYPB6P5s9foPnzF6itrU0PPrhakUiVXn/9Ne3cuUN33fVT3X33nZo37xyFw5U699yF+0wVB3JVJpNRR0enotGYfD6v/P6gPB7+WgcAAMglLjm3a0ZW7NYxBFnXcTFM5aLjAgfx6quWIpEqPfjgGnV0tPcfDwQCuuiiZQqHK3XiiTMdrBAYWW63W36/Tz6fX243AQaA4XO5DAUCRUokUurutpVO8zMKAGdNhI6LNQ53XCzLgY4LggsHEVyMja6uLm3ZskmRSJWeeOKxfZ7vmTNNVVRcoosuWsp+5xg3PB6PAgG/fD6/DCNXcnQA2aCw0K3XX7fU3Nysc889V5Khri4CDADOIbgYXQQXY6NcBBcYhubmJq1ZE1EkUqVdu97uP56Xl6cFC85TOLxCZ511ttxut4NVAiMjPz9Pfn9AXq+PIbUABmUYks9XqDvvvEPt7e1yuVy66qqrFApNUTKZHvwBAGAUTITgYu3LzY4GF0vfM1nK8ueXXmJMKJMnT9FHP3q1rrzy3/TCC8+purpK69Y9pEQirkceeViPPPKwJk2arGXLwgqHK3XMMcc6XTJw2Lq6utXc3KyOjnYFAkGVlnqdLglAFiso8OjNN99Qe3vv8sqioiJNmzZN7e0physDAEx0dFw4iI6L7JBIJLRhw3pFIlV65pl/7HPulFNmq6KiUhdcsETFxSUOVQgcOcOQCgoKFQgEVFJSIokODAD78vny9dvf/lb19fWSpAsuuECnnXaGkkln3gUEAGlidFw86HDHxcV0XADZr6ioSMuXV2j58grV1tZozZpqRSKr1NjYoOef367nn9+uH//4h1q8+EKFw5U67bTT5XIxNwC5xbalZDKpxsZGFRcXqaxsEluoAuiXn+9WS0trf2jh8Xg0d+5Zise7Ha4MAAA6LhxFx0X2ymQy+sc/nlQkUqWNGzeoq+udNtlp06YrHF6hZctWaOrUqQ5WCRw+t9ulYDAony/A/AsAKinx6O9//5teffVVSdKZZ56p8847X4kE3RYAnEXHxeii4wLIYS6XS3PnztPcufPU2dmpdeseVHV1lV5++UXV1dXqnnv+W7/85d0644y5Cocrdd55i1VQUOh02cCQ9fRk1NLSqmg0pkmTylRQUOR0SQAckpfnVnd3V39oYRiGFi5cqDTzOAFgbBi9y3qdunYuILgABuH1enXppZfp0ksv05tvvqHVq1dp7dqIdu/eraeeekJPPfWESktLtWTJUoXDlXrPe07mHWzkjGQyqbq6Ovl8PgWDIblc7KgDTDQej/TII5v6P585c6Y8njzFYiQXAIDswFIRB7FUJHel02k99tijikSqtHXrZvX0vNPaVV5+nMLhSi1bFlYoVOZglcDw5OfnKRQKqbTUq9z+pwHAULndLhUXu3Xrrbcq3ddisXLlShUX+9XVxTIRAM6bCEtFHn6lWYluZ14TFuW5tOSk7F8qQnDhIIKLw9PVk1GsO6N8t6GSPOffHd6zZ7ceemiNqqtX6Y03Xus/7na7dc455yocrtT8+Qvk8dDghOxnGAbDO4EJpLDQraefflIbNmyQJE2fPl1XXvlRdXZ2OVsYAPQhuBhduRJc8EoKOSPW3aNttVG91Z6SyzCUsW35C906++hSzfAVOFZXMBjSBz7wYb3//R/Sq69aikSq9OCDa9TZ2aEtWzZpy5ZNCgSCWrp0ucLhSp1wwrsdqxUYjG3bisXiSiZrFAgE5PcHZBjsogOMR4ZhqLAwT0888UT/sYULF6mrizdUAADZhY4LB9FxMXTx7h799dXdSnbb2v9X2u0ytPhdpTohmD3DBVOplLZs2aRIpEpPPvn4Pr/GJ530HoXDlVqyZKl8Pp+DVQKDKyjIVygUUklJKctHgHGmsNCj11+39MADf5ckBQIBffrT/66OjiR/3gFkjYnQcbHOcrbj4kKTjgtgRDxWFz1gaCFJPRlbG3dFday/UB5XdgzFLCgo0IUXXqQLL7xIzc1NWrOmWtXVVaqp2aVXXnlZr7zysn72sx9r4cLzFA5X6swzz5Lb7fyyF2B/qVSXGhoaVVLSqbKySfJ48pwuCcAIKShwa+vWLf2fz59/rlKpNKEFACDrEFwg63VnMtrRljpgaDHQzvak3p1FXRd7TZ48RR/96DW68sqr9dxz2xWJVGn9+oeVSMS1bt1DWrfuIU2ZMkXLlq1QOLxCM2a8y+mSgX3Ytq1oNKZEIqFgMCifL8DOOUCOKyjwaNeuXWptbZUkFRYWavbsU5ltAQAOMPr+c+rauYDgAlkv0W33vkg6xFtA6YytjlR2L7kxDEOzZ5+m2bNP02c/+wVt3Lhe1dVVevbZp9XU1KTf/e5X+t3vfqXZs09XOLxC55+/RMXFxU6XDfTr6cmopaVVnZ1RBYMBlZSUKmc2/wawj/x8Q5s2vbMF6plnnqlUKp2TS28BAOMfwQWyXr679x3fQ3EbUr4nd15AFRcXa/nyFVq+fIVqa2sUiVRp9epqNTU1avv2Z7R9+zP68Y9/qPPPv1DhcKVmzz6dd7iRNVKplBobm1RQ0K5gMKDi4hIRYAC5Iz/fo46ODr399tuSJJfLpfnz5yuRyO43AAAAExfBBbJeocetsmKPmmLpQ37dcX7ndhY5EtOnz9AnPvFpXXvtSj399FOqrq7Spk2PKJFIKBJZpUhklaZPn6FwuFLLloV11FFTnS4ZkG3bSiaTamhoVFFRoQKB3gCDtfFA9vN4bD300DvdFqeccop6emz19BBcAIATDKP35tS1cwHBBXLCvKNLFXmzTQf6mcrtMjQzWKCSvNwebul2uzV37jzNnTtPHR0dWrfuQUUiVXr55ZdUW1ujX/ziLt1zz881d+48hcOVWrjwPBUU5GZYg/HDtm3F4wklEkkVFxcpEAioqKiYAAPIUh6PS7ad0UsvvdR/bNGiRUof+r0BAAAcRXCBnHB0ab6WlPv1yFsdsu3enURcLkO2bcsMFWj+dK/TJY4on8+n973vcr3vfZfrzTdfVySySmvXrtaePbv1xBOP6YknHlNpqVdLllysiopKnXTSySwlgaNs21YsFlc8nlBxcZGCwaAKC4sIMIAsk5dnaOvWLf1LMI8//ngVFRUrGu12uDIAAA7OGGx2QJYrl7SjtTWak8Okuru7VVOzS5kMrZlDlcnYeqszpfZkj/I9Lh3ny1dRjndaDFU6nda2bVsViVTp0Ue3qKenp//c8cefoHC4UkuXLlcwGHKwSqCXy2WouLhYwWBI+fl0BgHZwOUyVFqapx/96Efq6urdPeSaa65RIDBZqRQtFwCyk8tlqKysVJKOk7TT2WpGXLmkHRtfbVWi25nXhEV5Lp03s0zK8ueX4MJBBBc4XLt3t+rBB9eouvoB7djxZv9xt9ut+fMXKByu1DnnnCuPh6YqOMvlcsnrLVUgEJTHk+d0OcCEVljo1vPPb9dDDz0oSZoyZYquvfZj6uhIOVwZABwcwcXoypXgglc1QA4Khcp0xRUf0Qc/+GG98spLqq6u0sMPP6hotFObN2/U5s0bFQyGtHTpcoXDlTr++BOcLhkTVCaTUXt7h6LRqHw+n/z+gNxu/ukBxpphSIWFeXrssW39xxYuXKSurp5D3AsAMCYcHM6ZKxvD0XHhIDouMJJSqZQ2b96o6uoH9NRTT+yzhex73nOywuFKLVmyVF7v+JoHgtzi8Xjk9/vk8/nlck2MZV5ANigs9Ojtt9/UX/7yF0mS1+vVZz7zGbW3J5lFAyCrTYiOi9dalXSo46Iwz6XzTqTjAsAYKSgo0JIlF2vJkovV0NCgNWuqtXr1KtXW1ujll1/Syy+/pJ/+9MdatGixKioqNWfOmXK7eeGIsZVOp9XauludnZ0KBILyen1OlwRMCPn5bm3evLn/87PPPlvJZDehBQAgJ9Bx4SA6LjDabNvW9u3PKBKp0vr1DyuZTPafmzLlKC1fXqFwuFLTp89wsEpMVL2t60UKhYJsoQqMooICj9raWvTrX/9KkpSfn6/rr79e0Wh3Tv78BGBimQgdF5ted7bjYtG7s7/jguDCQQQXGEvxeEzr169TJFKl5557dp9zp502RxUVlVq8+EIVFRU5VCEmKsMwVFpaolCojAGewCgoLc3TX//6F73xxhuSpHnz5mnBgkVKJJhvASD7EVyMLoKLsVEuggtg2HbteluRyCqtWVOt5uam/uNFRcW64IIlCocrdeqps2U4NiUIE5Hb7VIgEJDfH5BhuJwuBxgX8vLcymRS+ulPfyKpNyi8/vrr1d1tKJ3m5w8A2W8iBBebX9/taHCx8N0hKcufX4ILBxFcwGk9PT166qknFIlUafPmjerq6uo/N2PGMQqHV2jZsrCmTDnKwSox0eTn5ykYDKm0tFQ5M+oayFJFRW49/PCD2r59uyTp5JNPVji8QvF42uHKAGBoCC5GV64EFwznBCYwt9utefPO0bx556ijo10PPbRWkcgqWdbLqql5W3fffafuuefnmjt3nsLhSi1ceJ7y8/OdLhvjXFdXt5qaGhWNdioYDKmgoNDpkoCc5Ha75HYbeuGFF/qPnXfeeUqTWQAAcgzBBQBJks/n12WXfUCXXfYBvfHG64pEqrR27Wq1te3R449v0+OPb5PX69PFFy9TOFypmTNNlpJg1Ni2FIvFlUgk5fN5FQgE5XbzTxYwHPn5hrZt26aent5ZFsccc4x8Pp86O7sdrgwAMJDL6L05de1cwFIRB7FUBNmuu7tb27ZtVSRSpW3btvb/8CtJJ5xwoioqVuiii5YrGAw6WCUmAo/Ho1AoxPapwBC5XIa83nzddttt/TtKXXnllZo8eZpSKVouAOSOibBUZOsbzi4VOfeE7F8qQnDhIIIL5JLW1hatXbtakUiVdu7c0X/c4/Fo/vwFqqi4RPPmnSOPh3fFMXqKiopUVhZSQQG73wCHUljokWW9qOrqaklSKBTSJz/5SbW3pxyuDACGZyIEF4++scfR4GL+CUEpy59fXmEAGJKyskn68Ic/qg996Eq9/PJLqq5+QOvWPahoNKpNmzZo06YNKisr09KlYYXDlSovP87pkjEOJRIJ1dXVqbTUq2AwRFAGHERBgUdbt27t/3zBggVKpdj+FACQm+i4cBAdF8h1qVRSGzduUCRSpX/840kN/Pvk5JNnqaKiUhdeeHHf7hDAyPJ4PAoGg/L5fGL3EeAdBQUeNTTs0n333SdJKi4u1uc+9zm1t6eU4z/3AZiA6LgYXbnScUFw4SCCC4wnDQ0NWrNmlSKRVaqrq+0/XlBQoPPOO1/hcKXmzDlTLpfLwSox3hhG7/KRUKiM3UeAPl5vvn7/+3tVW9v7d/HixYs1Z85cJZN0XADIPRMhuNj2xh4l0w4FFx6XziG4GHXlIrgAskomk9Gzzz6jSKRKGzas6x8KJ0lTpx6t5csrtHz5Ck2bNt3BKjHeuFwu+f0+BQJBuVxup8sBHJOf71Y83q67775bUm9n0he+8AXF4z3q6eHnDQC5h+BidBFcjI1yEVwAWSsej2n9+odVXV2l55/fvs+5008/Q+FwpRYvvkBFRQxaxMjIz89TKFSm0tJS5fY/b8DhKSnxqKrqAf3/7N13nNP3ne/7108/9a4ZOhjGNNEDBgOhmGYY5jfIseOStik3xZuySez43rP37j33cc/u45zz2OwJie1407xxkk1Zb5KbYjG/oRjbmGKqC2BAYKrpDDBdXbp/iBEDppqRftLo8/RjHjzm9xtJH2uKpLc+38933759ANxzzz0sWLCIaFS6LYQQ5akSgovNB5sNDS5mjvBDid+/ElwYSIILUUmOHTuCrq9g5UqdpqZz+eNOp4tFi+5H00JMmDAJRZFZBeLOKIqCy+WkuroPZrPF6HKEKBqzWUVVUzz99NP5WRZPPPEE2ayFZFKCCyFEeZLgorAkuCiOGiS4EKKspFIptm3bgq6vYMOGdSSTyfy5oUOHUVe3jLq6evr06WtglaI3UFUTfr8fn8+PoshsFdH7ORwq69a9yvbt2wEYNWoUDz74EB0dKYMrE0KID0+Ci8KS4KI4apDgQoiy1dLSzMsvr6ah4SX274/kj5tMJqZPn0l9/QPMnj0Xq9VqYJWi3OWWj1ThcrmR3UdEb6WqCk6nheXLv0cqlQsqvvzlL+N2B0gkpNtCCFG+KiG42HKombhBwYXNbGLG8NIPLsxGFyCEqFw+n5+HH36Mhx9+jAMH9qPrYVavbqSlpYXNmzexefMmvF4fS5YsRdNCjB4dNLpkUYYSiSRnzpzB4WglEAjgcDhl/oXodSwWE9u2bc2HFgMHDqRPnz60tiYMrkwIIYS4c9JxYSDpuBDig5LJJJs2raehIczmzZuu+P0YOXIUmhZiyZI6/H6/gVWKcmUyKbhcLgKBKiwW6eQRvYOiKPh8Np555hk6OjoA+MQnPsGgQcOIx2WZiBCivEnHRWHdbsdFMBj8HvAwudonRiKR3ZeO24EfAPcDMeCNSCTy+KVzo4FfAdXAeeBzkUjkwO3UKYt+hRAlxWKxMG/eQv7lX37An/7UwNe+9k2GDasB4L33DvDss9/nwQfr+K//9e/ZtGlD/t1FIW5FJpOlra2dEyeOc/HieTIZaaEX5c9mU9m7d28+tPD5fAwfPoJEQv4+CiFEOVAM/u82/QW4Dzh61fF/IRdYjI5EIhOB/6fbuZ8A/xqJREYD/wr89LbvI+m4MI50XAhxa7LZLO++u5uGhpdYu3YNnZ0d+XPV1X2ordWorw/lAw4hbpXFYsbn8+P1emWApyhbPp+N559/nqamJgDq6uoYO3YCsZgEc0KI8lcJHRdbD7UY2nExfbgPbvP+DQaDR4BlkUhkdzAYdAPHgSGRSKT9qq/rB+wHqiORSDoYDKrkui5GRSKRc9wimXEhhCh5iqIwYcJEJkyYyLe//RTr1r2CrofZsWM758838bvf/Tu/+92/M2HCRDQtxKJFiy8NYhTixpLJFE1NTbS2thAIVOF2e4wuSYjbYrOZOXHiZD60sNlsTJ48mbY2mW0hhBDlQlFyH0bdNsDPfvazIcuXL7/6dHMkEmm+hasZQS6M+H+DweACoB34r5FIZANwF3AiEomkAS6FFycvHZfgQgjRO9ntdmprNWprNU6dOomur6CxcQWnT59i9+5d7N69i2eeWc78+Qupr3+AyZPvwWSSd9LFjSUSSc6ePUNLSwuBgB+n04XsQCLKgcWi8Prr6/KfT5s2jXg8VZadqEIIIYzz4osvrr/G4X8E/tstXNwMDAfeikQi/0cwGJwBhIPB4Mieqk+ezQshytbAgYP40pce5/e//wvPPPMjamvrsNlsxONxVq1q5Fvf+hqf+MRDvPDC85w6ddLockWJy2YhFotx+vQZTp06SSzWadi7H0LcCqtVpaOjnSNHjgC5raQ/+tFZpFISWgghhLg9n/zkJ+eSWy7S/ePpW7z4USAF/AdAJBLZAjQBo4H3gcGXlohw6d9Bl47fMplxYSCZcSFEz2tvb2ft2tXo+grefXfXFeemTp2GpoWYN28hdrvdoApFuVAUBafTQXV1H9mBRJQkp1Nl5cpGdu/eDcDEiROprV1KZ6fMthBC9B6VMONi+2FjZ1xMu/vOZlxc+nw18L1IJLL60i4im4CRkUikORgMvgb8WyQS+U0wGPwb4EuRSGTB7dQpwYWBJLgQorCOHDmMrq9g1aoGzp8/nz/ucrlYtGgJmhZi/PgJKPK2urgBVTXh9/vx+fwywFOUDLPZhNUK3//+9/PPI77xjb/DYnGQSEhwIYToPSS4KKzbDS6CweCzwMeBAeS6Ks5HIpHxwWBwOPACuS1Pk8D/HYlEGi9dZgy57VADwEVy26FGbqdOCS4MJMGFEMWRSqXYunUzuh5mw4bXr9hCtabmburqllFbq9GnTx8DqxSlzmazUV1dhdPporwfOkVv4HCobNq0gTfeeAOAu+++m0cffYz29qTBlQkhRM+qhODizSOthgYX99R4ocTvXwkuDCTBhRDF19zczJo1K9H1MAcO7M8fV1WVGTM+Sn19iFmz5mKxWAysUpQqRVGztD7KAAAgAElEQVRwu11UVVVjNsvPiDCGyaTg8Vj5/ve/TzweB+Dzn/88VVX9icdTN7m0EEKUFwkuCqtcggvZVUQIUVH8fj+PPvpJHn30kxw4EKGhIczq1StpbW1h06YNbNq0Ab/fz+LFS9G0EKNGjTa6ZFFCstksbW3tRKMx/H4/Xq9PlhqJorNaVd588618aNG3b18GDRpES0vc4MqEEEKIwpCOCwNJx4UQpSGRSLBx43p0PcyWLW9c8Ts5evQY6utDLF5ci9frM7BKUYocDjtVVVU4HE5ZPiKKQlHA57Pz3HPP0draCsBDDz3E3XePIhaTbgshRO9TCR0XbxnccTFFOi6EEKL0Wa1WFixYxIIFi2hqOsfKlToNDS/x/vvH2L9/H/v37+O5555mzpx5aNoypk+fiaqqRpctSkA0GuPkyVM4nQ4CgSpsNtmtRhSW1WrmwIH38qGFy+Vi7Nix0m0hhBCiV5OOCwNJx4UQpSubzbJ79050PczatS/T2dmRP9enT1/q6uqpq1vG0KHDDKxSlBKTyYTL5cTvD2C12owuR/RSXq+VX/7yl5w+fRqARYsWMXnyPUSjspOIEKJ3qoiOi6MGd1wMK/2OCwkuDCTBhRDlIRqNsm7dq+h6mDff3H7FuYkTP0J9fYiFC+/H6XQZVKEoJSaTCY/Hg9/vlwGeokdZrSptbRf5+c//DQCLxcJTTz1FR0eSdLr8ngcJIcStkOCisCS4KI4aJLgQQhTRiRPHWbmyAV1fwZkzp/PH7XY78+cvQtNCTJ48BZPJZGCVohSoqgmfz4fX60NVZWWmuHMul5m//OXPHDhwAIB7772X++6bL90WQoheTYKLwpLgojhqkOBCCGGATCbDm29uR9fDvPbaqyQSl9eXDxo0GE1bxtKlyxgwYICBVYpSYDabCQQCeDxe2YFEfGgWiwokeOaZZ4Dc1rxPPvkkqZRKKiXBhRCi96qU4CKRMub1rNWsSHBRBDVIcCGEMFhbWxtr165B18Ps2bM7f1xRFKZOvRdNCzFv3nwZ3FjhZAcScSccDpVXXnmZt956C4AxY8awbNkDdHbKTiJCiN5NgovCKpfgQnpXhRDiDnk8Hh588OM8+ODHOXz4ELoeZtUqnQsXLrB9+1a2b9+K2+1m0aIl1Nc/wNix4+Sd9wrUtQOJ2+2iqqpa5l+IW6aqJlTVxM6dO/PH5s2bR8qgJ7lCCCF6lqLkPoy67XIgHRcGko4LIXqvVCrF5s2b0PUwGzeuJ52+3MpdU3M3mhaitraO6uo+BlYpjKKqJvx+Pz6fH0WReSjixux2lR07trJu3ToAhgwZwmc+8ze0tSUMrkwIIQqvEjou3j5mbMfF5KGl33EhwYWBJLgQojJcvHiRNWsaaWgIc/Dge/njqqoyc+YsNC3ErFlzsFjkHfhKY7NZCQSqcLvdsnxEXJOiKHi9Vp5++mmi0SgAn/70p+nffwjxuCwTEUL0fhJcFFa5BBeyVEQIIQosEAjw2GOf5tFHP0Uksg9dD7NmzSra2lrZuHE9Gzeux+8PsGTJUurrH2DEiJFGlyyKJB5PcObMGVpbW/D5fJe21C2Tnk1RFDabyu7du/OhRSAQYNiwGlpaYgZXJoQQoqcoGPfoXy7POqTjwkDScSFE5YrH42zY8Dq6Hmbr1s10/1scDI5F05axeHEtXq/PwCpFMSmKgt1ux+fz4XJJgCFyfD47P/3pT7hw4QIAy5YtY/ToscRispOIEKIyVELHxTsGd1x8RDouhKgcyUyGfU1Rdp7tJJbKEHCYmTrAxVCvTQYxig+w2WwsWrSYRYsWc/bsGVau1NH1MMePv08kspdIZC/PPfc0c+fOo77+AaZNm46qqkaXLQoom80SjUaJxWLYbDb8fj8ul9vosoSBbDYzx44dzYcWDoeDiRMn0dYWv8klhRBClBVpubgp6bgwkHRc9B7tiTT/uaeJzmSGVLffKYuiUOO3oY0MYJLwQtxENptl58530PUwr7zyMtFoZ/5cv379qK2tp74+xJAhdxlYpSgWRQGr1UYg4MfpdEsAWoE8Hgu/+93veP/99wG47777mDZthnRbCCEqSkV0XLxvcMfFXaXfcSHBhYEkuOg9frv7HE2dSa71nTQrCjMGu5k+yFP0ukT56uzs5LXX1qLrYd5++60rzk2aNJn6+hALFtyP0+k0qEJRLIoCdrudPn36YLXajS5HFInVaiYWa+UnP/kJkBvm+9RTTxGNZkin5XmDEKJySHBRWOUSXMhSESHu0NmOJBeiqWuGFgCpbJYdpzqYNsCNySTvmIpb43Q60bQQmhbixInj6HqYxsYGzp49w86db7Nz59s8/fT3WLBgEZoW4iMfmSLvyPdS2SxEozFOnDiJz+clEKiSLVQrgNlMfvtTgIkTJ5JOZyW0EEKIXkhBMXClSHk8f5TgQog7dLw1TuYmnUvpTJbmRJoqu/zKids3ePAQvvKVr/HFLz7Om29up6EhzOuvv0o0GkXXV6DrKxg8eAh1dcuoq6unf/8BRpcsCiCTyXDxYjOdnVGqq6twOFxGlyQKxGw2kcmk2bdvX/7YfffdR0p2PxVCCFGh5FWUEMWgAOW3mkmUGFVVuffeGdx77wxaW1tZu3Y1uh5m7949nDhxnH/7t5/w85//lHvvnYGmhZg7dx42m83oskUPi8fjnD59Go/HS1VVFSaTDG3tbSwWhfXrX8/vNjRy5EhsNjsdHZJcCCGEqEwSXAhxhwZ7bZgU5YZdF6qi4LfJiwvRc7xeLw899AgPPfQIhw4dRNfDrFrVyMWLF9i6dTNbt27G7faweHEt9fUhgsGxspSkF8lksrS0tBCNdlJdXY3L5aa8R1aJLiaTgsWi8tZbl2fbSLeFEEL0boqS+zDqtsuBLJIV4g71d1kIOMzX/WUyKwpTBrhkvoUomOHDR/B3f/cEf/5zA//8z99j7tz5qKpKe3sbf/7zH/nylz/P5z//KV588bdcvHjB6HJFD0okkpw+fYYzZ06TSiWNLkf0AKvVxPbt20kmc9/P/v37069ff+JxSS6EEEJULtlVxECyq0jv0RZP8+KeJmKpD26HepfPRmhkQIILUVQXL15g1apGdD3MoUMH88dVVWXWrDnU14eYOXM2ZrM03vUWqmrC5/Ph8/ll+UiZUhTweu388IfP0t7eDsAjjzzC0KHDicUkuBBCVKZK2FVk9/E2Q3cVmTDEAyV+/0pwYSAJLnqXRDrDnqYou852Ek9n8NtU7hnopsaXW0oihBGy2SyRyF4aGsKsWbOK9va2/LlAoIra2jo0LcTw4SMMrFL0JLPZjN/vx+v1yfKgMmO3mzly5CB/+tP/B4DH4+Gb3/wmLS0xWQokhKhYElwUlgQXxVGDBBdCCHFL4vE469evQ9fDbNu2he5//8eOHUd9/QMsWrQEj8djYJWip9hsVgKBAC6XG8pkq7NK5/XaeOGFn3P27FkAlixZwoQJHyEWSxtcmRBCGEeCi8KS4KI4apDgQgghbtuZM6dZuVJH18OcOHE8f9xqtXHfffOprw9xzz3TUFVZclDOFAXsdgeBgB+n0yXv2pcwm83MxYtn+eUvfwmA1Wrlqaeeoq0tUZbPcYQQoqdUTHCRNii4UCW4KIYaJLgQQogPLZvNsnPn2zQ0vMSrr64lGo3mz/Xr15+6uno0LcTgwUMMrFLcKUVRcDodBAJV2Gx2o8sR1+B2W/jjH//AoUOHAJg5cyazZ88lGpVuCyFEZZPgorAkuCiOGiS4EEKIHtHZ2cmrr76Mrq/gnXfeuuLc5MlT0LQQ8+cvwul0GlShuFMmkwmXy0kgUIXFYjW6HHGJxaKSTsd47rkfArmg6TvfeYpkElIpeY4ghKhslRBcvHu83dDgYvyQ0r9/JbgwkAQXQohSdfz4++j6ChobV3Du3Nn8cYfDyYIFi6ivDzFp0mQZ/limTCYTXq8Hny8gO8uUAIdDZc2aVezcuROA8ePHU1dXT2en7CQihBASXBSWBBfFUYMEF0IIUTDpdJrt27ei62HWr19HIpHInxsyZCiatoylSzX69etvYJXiw1JVFZ/PK1uoGkhVTdjtCsuXL88/H/j617+O1eoikZBlIkIIIcFFYUlwURw1SHAhhBBF0drawpo1q9D1FUQie/PHTSYT06ZNp74+xJw587DZbAZWKT6My1uoelEUk9HlVBS7XWXr1jfYsGEDAMOGDeMTn/gk7e1JgysTQojSUAnBxZ4TxgYX4waX/v0r/aFCCCFuidfr4+GHH+Phhx/j4MH30PUwq1bpNDc3s3XrZrZu3YzH4+X++5dQX/8AweAYWUpSJlKpFE1NTbS2tuD3B3C7PfK9KwKTScFmM7N9+/b8sfvum0cyWX5vxgghhBCFJB0XBpKOCyFEuUsmk2zatAFdD7N58ybS6cut7SNGjETTQixZUkcgEDCwSnG7bDYbgUAAl8sFSIBRKHa7mX37dqPrOgDV1dU8/vjjtLTEDa5MCCFKR6V0XCQN6riwlEnHhQQXBpLgQgjRm5w/38SqVY3oepgjRw7nj6uqyuzZc9G0EDNnzpJhkGVCURTsdjuBgB+n00V5P10oPYoCXq+dH//4RzQ3NwPwsY89yIgRo4nFZCinEEJ0keCisMoluJBnj0IIIXpEdXUfPv3pz/KpT/0Ne/a8i66HWbt2Ne3t7bz++mu8/vprVFVVUVuroWkh7r57uNElixvIZrNEo1FisRhOp4NAIIDd7pAAo4fYbGYOHz6UDy2cTifjx4+TbgshhBDiGqTjwkDScSGE6O3i8Rjr1r2GrofZsWMb3R9zxo2bgKaFuP/+JbjdbgOrFLfCZFJwOp34/QFsNrvR5ZQ9j8fKr3/975w8eRKABQsWMGXKNGIx2UlECCG6q4iOi5MGd1wMKv37V4ILA0lwIYSoJKdPn2LlygYaGsKcOnUyf9xqtTFv3nw0LcTUqfdiMsmuFqXMZDLhdrvx+/1YLFajyylLVqtKR0czzz//PJDb1eWpp56iszNNOi3PCYQQojsJLgpLgoviqEGCCyGEKCuZTIa3334LXQ/z2mtricVi+XMDBgykrq6eurplDBo02MAqxc2oqgmPx4PPF5C5JbfJ5TLz0kt/JRKJADB16lTmz19INCrdFkIIcbVKCC72nuwwNLgYO8gFJX7/SnBhIAkuhBCVrrOzg1deeZmGhjC7dr1zxbkpU6aiaSHmz1+Iw+EwqEJxM6qq4vN58fn8mEyq0eWUPItFRVFSPP30D/LHnnjiSbJZM8mkBBdCCHE1CS4KS4KL4qhBggshhOgVjh07SmPjChobG2hqOpc/7nS6WLTofjQtxIQJk1AU2Z6zFJnNZvx+P16vF0WR5T7X43CovPbaK+zYsQOAYDDIAw98jI4O2UlECCGuRYKLwpLgojhqkOBCCCF6lXQ6zbZtW9D1MOvXryOZTObPDR06jLq6ZdTV1dOnT18DqxTXY7GY8fsDeDweCTCuoqoKTqeZ5cuXk0rlgoqvfOUruFx+EgnpthBCiGuphOBi3yljg4sxAyW4KLQaJLgQQoheq7W1hTVrVtHQEGb//n354yaTienTZ1Jf/wCzZ8/FapUhkaXGarXg9wdwuz3SJXOJ3a7y1lvbefXVVwEYNGgQn/vc52htTRhcmRBClC4JLgqrXIILmaYlhBCiZHm9Ph5++DEefvgx3nvvALoeZvXqRpqbm9m8eRObN2/C6/WxZMlSNC3E6NFBo0sWlyQSSc6ePUtLSzN+fwCXy13RAYaiKNjtFrZs2ZI/dt9995FIyJsXQghR6ZRLH0bddjmQjgsDSceFEELcvmQyyaZN62loCLNlyxuk05db7EeOHIWmhViypA6/329gleJqNpuNQMCPy+UxuhRD2O1mDh7cz1//+hcA/H4/X/va12ltjVHeT8WEEKKwKqHjImJwx0WwDDouJLgwUCaTprn5IolEgkQiQSaTIZPJUubfEyGEKJqmpiZWrdLR9TBHjx7JHzebzcyZcx+aFmL69JmyXWeJUBSwWm34/f6K68Dw+Wz87Gc/4/z58wBomsaYMROIxWQopxBC3IgEF4UlwUVx1FDGwUV3ipIbSJdMJkmlUqRSKZLJBIlEkmQykQ80yvz7JYQQBZHNZnn33d3oepi1a1fT0dGRP1dd3YfaWo36+hDDhtUYV6S4gs1mxefzV8QMDJvNTFPTaX79638HwG638+STT9LWlij75y9CCFFoFRFcnDY4uBggwUWh1dBLgovrURTIZiGVygUauXAj16GRTKZIJpP5QKPMv5eiCDKZLM2JNFnAb1VRTb37xYKoTLFYjNdff5WGhpfYsWP7FefGj59IfX2IRYsW43K5DapQdGe1WvD5/L16FxK328J//ueLHD16FIA5c+YwY8ZHiUZlJxEhhLgZCS4KS4KL4qihlwcXN6IouReiqVSSdDp1KcjoCjWSpNNpstlsRd434kqZbJa3z3Sy61wn6ezlITzj+9qZ1t+NSQIM0UudOnWSxsYGGhtXcOrUyfxxm83G/PkL0bQQU6ZMxWTqnS+Yy4nVasHr9eHxeDCZVKPL6TFWq0oi0cGPfvQjILcjzlNPPUUsliWdlhlXQghxMxJcFJYEF8VRQwUHFzfSfelJ91Cj61+Zp1E5stksa4+2crQ1ztXPkVUTDHBaqBvhx9TLW7VFZctkMrz99ps0NIR57bW1xOPx/LmBAwexdGk9mraMgQMHGVilALBYzHi9Xtxub6+YTeJ0qjQ26rz77rsATJo0iSVLaunslG4LIYS4FZUQXOw/3WlocDF6gBNK/P6V4KLCdF96kk6nSKXSlwKN5KV5GrL0pLc52ZZg5eEWUtf5HTGbFOYP9TDcby9yZUIYo729nVdeWYOuh9m9e9cV56ZOnYamhZg3byF2u/xOGElVTXg8HjweL1arzehyPhSz2YTVCsuXL88/pn7zm9/EZLKTTEpwIYQQt0KCi8KS4KI4apDgosdcXnqSIp1OkkymSKWSl3Y96Vp6krkUahhdrbhVqw41c7Q1ccOv6e8y87FRVUWqSIjScfToEXQ9zMqVOufPN+WPu1wuFi5cTH19iPHjJ/b64ZGlzGQy4XI58fl82O2Osnr8sdtVNm1az+bNmwEYPnw4jzzyKO3tSYMrE0KI8lEJwcWBM8YGF6P6S3BRaDVIcFEUuVAjc2nXk+RVnRqy9KSU/efeJlriN15H7bAofHZ83yJVJETpSaVSbN26GV0Ps2HD66RSl7eoHDashrq6ZSxdWk+fPn0MrLKyKYqC0+nA6/XidJb+YFWTScHjsbJ8+XISiVx4/IUv/G8EAn2Jx2ULVCGEuFUSXBRWuQQX5b94VBRFNguKYsJqtV3Rstv1JmRuC9dcoNG9S0OWnhjPblZvGlzYZDChqHBms5lZs+Ywa9YcmpubWbNmJboe5sCB/Rw9eoSf/OQ5nn/+x8yY8VE0LcTs2XOxWCxGl11RstksHR2ddHZGsVov4vP5cLvdJbsTidVqYseOHfnQol+/fgwYMIDW1vhNLimEEEKIq0nHhSiYrnkauQGhl7s0unY9SaXSlwKNTFm1/pabAxeirD/eft0ZF6oCMwa5mdDXWeTKhCh9+/dH0PUwq1evpLW1JX/c5/OxZEkdmhZi1KjRBlZY2S4P8vRgNpdOkKQo4PPZ+eEPf0hbWxsADz/8MMOGjSAWk24LIYS4HZXQcfGewR0XI8ug40KCC2GIrqUnXZ0al3c9kaUnPS2dyfKHyHna4xmu7rtQyC0TeWxMNVa1NN+1FKIUJBIJNm5cj66H2bLlDTKZy79No0cH0bQQixfX4vP5DayycqmqCZfLhdfrw263Gx6G2+1mjh07zB//+AcA3G433/rWt2hpiRlemxBClBsJLgpLgoviqEGCi16la+lJ11aul4ONrl1PEvlAo8x/dosqlkqz+kgL5zovvdOXBRSFgE1lyd0+3FbV0PqEKCfnzp1l5UodXQ/z/vvH8sctFguzZ99HfX2I6dNnoqrye1VsJpOCw9E1B8NFLp4tPq/Xxi9+8QJnzpwB4P7772fSpCnEYrKTiBBC3K6KCC7OGhxc9JPgotBqkOCiYnTfyjUXaFy560kqlZJ5GjdxMZbiZHtu7sgAt5U+DhlzI8SHlc1m2b17J7oeZu3al+ns7Mif69OnL0uXamhaiKFDhxlYZWVSFAW73Y7f7yt6gGGzmWlpaeKFF14AcoHWU089RXt7Up6rCCHEhyDBRWFJcFEcNUhwIei+lWsyv/SkK9TIzdjIzdOQnxMhRCFEo1Fee+0VdD3MW2/tuOLcxImT0LQQCxfej8tV+rth9Ca5AMOGz+cv2n3vcpn585//xHvvvQfA9OnTmTt3HtGodFsIIcSHIcFFYUlwURw1SHAhbkJRLi89SadT+XkauS6NJOl0Rro0hBA95sSJ46xc2YCur+DMmdP543a7nfnzF6FpISZPnoJJdvMpGkVRsNls+P0+XC5PwW7HYlHJZhM8++wz+dt98snvkEoppFI33t1JCCHEtVVCcHHwbNTQ4GJEPweU+P0rwYWoWN2XnqTTqfyuJ5fnachWrkKIDy+TybBjxzZ0Pcy6da+RSFzeBnPgwEHU14dYunQZAwYMMLDKyqIoYLXaCAT8BQkwHA6VtWvX8PbbbwMwbtw4NG0ZnZ2yk4gQQnxYElwUlgQXtygYDFYDvwZGAHHgPeBvI5HIuVu4eA0SXIgCuLz0JEU6/cFdT3JdGhn5uRNC3JK2tjbWrl2DrofZs2d3/riiKEydei+aFmLevPnYbHYDq6wcigI2m51AwN9jMzBU1YTDYWL58uWk07llIV/96tew2z0kEhJcCCHEh1URwcW5KCmDgguzqjCib+kHF6UwmS8L/EskEnkNIBgM/i/gn4EvGVmUqGzZbO4FhcViwWKxYO/2WqJr6Un3rVxz8zS6dj2RrVyFEFfyeDw8+ODHefDBj3P48CEaG1ewapXO+fPn2b59K9u3b8XtdrNo0RLq6x9g7NhxKErxBkpWmmwWYrEYp0+fwel04Pf7cTicd7RVqcWisHnz5nxocdddd+HzeWlrS/ZQ1UIIIUTlMrzj4mrBYPBh4GuRSOT+W/jyGqTjQpSIrtcY3QON3CyNxKUujbQEGkKIvFQqxZYtb6DrYTZuXE8qdfld+Zqau9G0EEuXalRVVRtYZWVQFAWn00EgUPWhul5MJgWPx8rTTz9NNBoF4DOf+Qz9+g0mHpduCyGEuBPScVFY5dJxUVLBRTAYNAGrgZcikcizt3CRGiS4EGVAUS4HGqlUmkQint/GNZ1OSaAhRIW7ePEia9Y00tCwgoMHD+SPq6rKzJmz0LQQs2bNwWKxGFhl72cymXC7Xfj9ASwW6y1fzm43s3//HlasWAFAVVUVf/u3X6WlJVaoUoUQomJUQnBxyODgYngZBBelsFSkux8C7cBzRhciRE/KZkFVzaiqGZuN/LZ83Xc86Qo2ugINGQ4qROUIBAI89tinefTRT7F/fwRdD7N69Ura2lrZuHE9Gzeux+8PUFtbh6aFGDFipNEl90qZTIbW1jba2zvweNz4/QHM5puHRTabysaNG/Ofz549WzothBBCiB5UMh0XwWDwe8AkIBSJROI3+/pLapCOC9ELXR4Omsx3aXQtO8lt6yrLToTo7RKJBBs2vE5Dw0ts27aFTObydprB4Fg0bRmLF9fi9foMrLJ3U1UTHo8Hn89/3QDDZjNz5sxxfve73wHgcDh44oknaW2Ny99oIYToARXTcWHQ61mzqTw6LkoiuAgGg/8DmAXURyKRztu4aA0SXIgK88Euja5ZGl3DQaVLQ4je5ty5s6xc2UBDwwqOHz+WP26xWLjvvvloWohp06ajqqqBVfZeqmrC6/Xi9foxm69sVvV4rPz2t7/h+PHjAMybN49p06YTjaaNKFUIIXodCS4KS4KLWxQMBscDu4H9QPTS4cORSOShW7h4DRJcCAHkAo1slksdGqkPLD1JpVKXAo3MHU3OF0IYJ5vNsnPnO+h6mFdeeZlo9HLW369fP2pr69G0Zdx111ADq+y9VFXF5/Pi8fgwm81YrWai0RZ++tOf5s8/9dT/TjSaJp3O3OTahBBC3AoJLgpLgoviqEGCCyFuKrf0JHONLVxzy09KYQvXTDbL8bYEzfE0VpPCMJ8Vh1nePRbiejo7O1m37hUaGsK8/fabV5ybNGkymhZi4cJFOJ0ugyrsvVRVxe/3MWhQX1asCLNv3z4ApkyZwsKF90u3hRBC9KBKCC4On4sZGlzc3dcOJX7/SnAhRAW7cgvXK7s0kskUiUSiKANCT7YlePloC+lMLsDoah8ZXWVn9hAPpq5ChRDXdOLEcXQ9TGNjA2fPnskfdzgczJ+/EE0LMXnyPSjyu9Rj3G4Xd93Vn2eeeSb/9/Hb3/42YCWZlOBCCCF6igQXhSXBRXHUIMGFEAXRtfQkmUySyaRIJlNXDAhNpdI9svSkKZrkrwcucq2uatUEI/w25g+V4YNC3Ip0Os2bb26noSHM66+/SiKRyJ8bNGgwmhairq6e/v0HGFhl7zB8+F1s376Vbdu2ATBq1CgefPAhOjpkNxEhhOhJElwUlgQXxVGDBBdCFN21lp4kk7lA43aXnjQcbOZEW+K651UFHhtbjccqy0aEuB2tra2sXbsaXQ+zd++e/HFFUZg2bTqaFuK+++Zhs9kNrLI82e02gsHh/OAH3yeZTALwxS9+kWxWxWQyY7c7ZJaQEEL0kEoILo40GRtc1PQp/eDCfPMvEUKIK+VWc5iwWKxYLFYcjtzxK5eeJPO7n3QNCE0mk1csPUlmMpxqv35oAZAFDjbHmNxP1ukLcTu8Xi8PPfQIDz30CIcOHUTXw6xa1cjFixfYtm0L27Ztwe32cP/9S6ivDzFmzDhZSnKL+vWrZvv27fnQYuDAgVRX92HXrn0oioLL5SIQqMJisRpcqRBCCNE7SMeFEKIoui89SZiHbl0AACAASURBVKdzS01aOmO8+O4pYrEkyVSadCZDKp3NzbnoZlI/BzMHeQyqXIjeI5VKsXnzRhoawmzatIF0+vIshrvvHo6mhaitraOqqtrAKkub2awyceIYfvjDZ+no6ADg0Ucfxen0cvr0ufzXmUwmvF4PPl/gA1uoCiGEuHWV0HFx1OCOi2Fl0HEhwYUQwjDpTJbn3joNKCjZDEomjZJJQTaTm6WRSJBJJbmnv5NRfpuhu54I0dtcvHiBVasa0fUwhw4dzB9XVZVZs+agaSE++tHZ8qL7KgMH9qO5uYm//OUvQK6z5etf/wY7d+695haoXVuo+nx+TCZZ8iaEELdLgovCkuCiOGqQ4EKIstZ4qJldZzvp/nRfIfcgZVbApip8YXwVKmlSqXR+QGgikbg0IDQjv/9C3IFsNkskspeGhjBr1qyivb0tfy4QqGLJkqXU14cYPnykgVWWBkVR+MhHxvDCCy9w7lyuu6K2tpYhQ4Zx/PjpG17WbDbj9/vxer0oiqkY5QohRK8gwUVhSXBRHDVIcCFEWetIpnlh5zmiyQxXv1dpNsH9w3xM7v/B+RZdA0JzO5wku+16kizaNq5C9DbxeJz169eh62G2bdtyxe/P2LHj0LQQixYtwev1Glilcfr2rUJR0vz6178GwGaz8cQTT7JnzwESieQtXYfVasHvD+B2e2SmiBBC3IKKCC7OGxxcVEtwUWg1SHAhRNlrT6RZe7SFAxdimEwKmSx4rCYWDPUyuspxW9d19SyN7tu43u6OJ0JUsjNnTrNypY6uhzlx4nj+uNVqZe7c+dTXh5g69V5UtXKWP4wfP4o///lPHD58GIBZs2YxadJkDh8+fpNLfpDNZiMQ8ONyucn1mQkhhLgWCS4KS4KL4qhBggsheo1YKkNLPI1NVfDZ1B59N7LrqnIdGilSqVygEY/HJdAQ4gay2SzvvPMWuh7m1VfXEo1G8+f69etPXV09mhZi8OAhBlZZeH6/l+pqLz/60Y+A3PDNJ598ksOHj9PREb3Jpa9NURTsdjuBgB+n0yVbqAohxDVUQnBx7Hzc0OBiaLUNSvz+leBCCFHxFIVLQUYu1Egk4vkOjXQ6I0tOhLiks7OTV199GV1fwTvvvHXFucmTp6BpIebPX4TT6TSowsIZPbqG1157lV27dgEwceJE5s9fwP79R+74uhVFwel0EAgEsNsdEmAIIUQ3ElwUlgQXxVGDBBdCiALoWnKSSuVmaCQSyUsdGoluMzQy8gJDVKzjx99H11ewcuUKzp49mz/ucDhZsGAR9fUPMGnSR3rFHAen08Hw4UP4wQ9+QCaTm8bzta99jQsX2mhubu2x2zGZFJxOJ35/AJvN3mPXK4QQ5UyCi8KS4KI4apDgQghRRJdnaCQ+EGgkk0my2Wz+hY0QlSCdTrNjxzYaGl5i/fp1JBKJ/LkhQ4aiactYulSjX7/+BlZ5Z2pqhrBr19ts2rTp0uc1fPzjD/PuuwcKcnsmkwm324XfH8BisRbkNoQQolxUQnDx/gVjg4u7qiS4KLQaJLgQQpSA3C4n2XygkUzmdjeJxxOkUikymYwsNxG9XmtrKy+/vApdD7Nv3978cZPJxLRp06mvDzFnzjxsNpuBVd4eq9XCuHGjePrpHxCPxwH47Gc/Szarcu7chYLetqqa8Hg8+HwBzGZzQW9LCCFKlQQXhSXBRXHUIMGFEKKEdW3bmkgkPjAQNJ1Oy0BQ0WsdPPgeuh5m1apGmpsv5o97PF4WL65F00IEg2NKfinJkCEDOHHiGCtXrgSgT58+fOlLX+Kdd/YV7XdXVVX8fh9erw+TqXJ2cRFCCKiM4OK4wcHFEAkuCq4GCS6EEAXW3Jnkj2+e5KV3ztART9HXY+MT0wZRP7E/VrPpQ11n10DQXHeG7HAieq9kMskbb2xE18O88cZG0ul0/tyIESOprw+xeHEdgUDAwCqvTVVNTJo0hh//+Me0tLQA8LGPfYyqqr6cPHn2JpfueWazGb/fj9frRVE+3N8eIYQoNxJcFJYEF8VRgwQXQogCOtkc48u/foeOeIpE+vLfGbvFxLBqJz/+1EQc1p57B1RRci/00unUVfMzZIcTUf4uXDjPqlWNNDS8xJEjh/PHVVVl9uy5aFqImTNnlcyyiAED+tDZ2c4f/vB7AFwuF9/85rfYtWsfqVT6JpcuHKvVgt8fwO32lHzHihBC3CkJLgpLgoviqEGCCyFEAX32hTc51NTJtf7EWFWF+on9+S+1Iwtaw+WBoEnS6csDQROJJIlEPN+dUeZ/z0UFyWaz7N27B10P8/LLq2hvb8+fq6qqorZWQ9NC3H33cMNqVBSYOHEMv/nNrzl16hQACxcuZMSI0Rw7dtKwurqz2Wz4/X5cLpd0YAgheq2KCC4uGhxcBCS4KLQaJLgQQhRI5HQ7X/3tTmKp6+8SYjObaPzmjB7turhVVwcaXUtOEomELDkRZSMej/H66+vQ9TDbt2+94ud13LgJaFqI++9fgtvtLmpd1dV+7HYLL7zwcyC3TOM73/kOkchhYrF4UWu5GavVgtfrxe32oKql0a0ihBA9RYKLwiqX4EIe3YQQ4jrePdVGlhs/iJhNCkfOdzJ2oKdIVV3W9frOYrFgsViw23Ofd3WO52ZopEinU/ldTnLdGsl8h4aEGsJoNpudxYtrWby4ltOnT7Ny5Qp0fQUnT55gz57d7Nmzm2ef/T7z5s1H00JMnXovJlPhuwv69aumoWFF/vPJkyfT3t5RcqEFQCKRpKnpPBcvNuPxuPF4vNhsNuTXWwghyoeCLP27EQkuhBDiOlRFufQgcv1n/1nArJbWA03XixVVNX/g3deruzRSqXS3Lo0k6XSabDYjXWzCEAMGDOALX/gyn/vcF3nnnbfQ9TCvvrqWWCzGmjWrWLNmFf37D6Curp66umUMHjykIHV4vW4ymTQHDhwAQFEUZs+ew4kTZwpyez0lnU7T3NxCa2sbTqcDn8+H3e4AeTIshBCizMlSESGEuI5TLTE++fyOK4ZyXs1rN9PwzRmYTeX/wqBr69ZkMnnFbidd/8rSE2GEzs4OXnnlZRoawuza9c4V5yZPvof6+geYP38hDoejx25zxIihbN68iTfffBOAMWPGUFu7lH37DvXYbRSDoijY7Xb8fh9OpwsJMIQQ5ahSloqkr78yuaBUE2WxVESCCyGEuIGn/vgu2440k7xGeGG3mPjirLv47My7DKiseLq6NFKp3G4n3bs0cqGGLD0RxXHs2FEaG1fQ2NhAU9O5/HGn08XChfejaSEmTpx0Rztt2O02Ro++m+9/f3l+69Yvf/krtLfHuHix5Y7/H4ygKEq3QZ7FnRUihBB3qhKCixPNxgYXg/0SXBRaDRJcCCEKqCOe4psv7ubI+U6iydwjikkBq2ri/rF9+L/qRmGq4O0Ic10aWVKp5KWP9BUDQmULV1EI6XSabdu20NAQZsOGdSSTyfy5u+4aiqYtY+nSevr27Xfb1z1s2CAikb2sW7cOgMGDB/OpT32aXbsiPVa/US4HGD5cruLP5RFCiA9DgovCkuCiOGqQ4EIIUWCZbJYthy7y57dPc6EzybAqB49OHcSYAfLO5fV0n6WRSl3eujUeT5BKpchkMhJmiB7R0tLMyy+vpqEhzP79+/LHTSYT06fPRNNCzJlzH1ar9abXZbGYmTAhyLPPPkNnZycAn/jEJ7FaHZw9e75g/w/FpihgtV7uwLiTDhUhhCi0SgguThocXAyS4KLgapDgQgghykbXHI3cMpNcmBGLxUkkEjIUVNyxAwf2o+thVq9upKXl8rIOr9fH4sW11Nc/wOjRwetefvDgfpw7d4ZwOAyA3+/nq1/9Ku+8s49MxqBnlAVms1nx+wMSYAghSpYEF4UlwUVx1CDBhRBCEE2k2XOylUw2S3CAB6/DYnRJt6xruUluEGhXZ0buo2sYaJk/VokiSyaTbNq0noaGMFu2vJGfVQEwcuQoNC3EkiV1+P3+/HGTSWHSpLE8//zPuHDhAgCapjFgwBBOnDhd9P+HYurqwAgE/LKERAhRciS4KCwJLoqjBgkuhBAVLJXO8OzLB/njtuOYTLnNWxPpLPeP68s/LBuDy1aeu153HwiaSqVIp6/ctjWVSslAUHFLmpqaWLVKR9fDHD16JH/cbDYze/ZcNC3EjBkfZdCg/qTTCX73u98CYLfbeeKJJ9i9ez/JZMqg6otLUcBms19aQiK7kAghSkMlBBenWowNLgb6JLgotBokuBBCVKhsNst3/mMnmw9dIJa88tHOqioM6+Pk11+5F5tFNajCwrjRQNBkMkk6nSabzcrjgrhCNpvl3Xd3o+th1q5dTUdHR/5c3759eeedd2hoaODYsWMAzJkzh/HjJ3LkyAmjSjZM1zaqgYAfp9NFeT9VFEKUOwkuCqtcgovyfCtOCCEEO442s+XQxQ+EFpDrunj/QpQV75zi4WlDDKiucLLZ3Asri8WKxXLlwEVF4VJ3Rm7r1tx2rYn8v5lMJr/8RFQWRVGYMGEiEyZM5Fvf+g6vv/4qDQ1hduzYxkc/+lHa29vzoYWqqsycOZODB48ZXLUxstks0WiUWCyG0+nA5/PhcLiMLksIIUQFk+BCCCHK1H9ueZ9YMn3d87Fkht++8X6vCy5uJJsFk0nFZruyy6T70pN0OpXv0sjN1EiSTCZl6UkFsdvtLFlSx5IldZw6dZJJk8awY8eO/PkJEyawY8cOvvvd/4WmhZgyZSomk8nAio2RzWbp6OikszOK1WrB4/Hicrkxm+XpoxBC9CxZmncz8sgjhBBl6vjFGDd7id3UnihKLaWuK4swmy2YzRZstsvnLi89SZFOJ0kmU6RSyfw8jdzSE9nxpLcaNWokffv2Y+/evfljU6dO5fHHH2fNmjWsWtXIwIGDWLq0Hk1bxsCBgwys1hjZbJZ4PEE83sTFixdwOp14PB7pwhBCCFE0ElwIIUSZ6uexse9U2w2/xu8sn91FjHJ56YkFi8WC3X75XNf2rclkbp7G5VAjKUtPeol+/arZtGlj/ns4YsQIPB4v99wzndOnz7Br105OnTrJL37xPL/4xfNMnToNTQsxb95C7N1/WCpEOp2hra2d9vaObl0YLsxm+VsjhBAflqLkPoy67XIgwzmFEKJMrd/fxP/5h910Jq69XMRmNvGNRSP47KyhRa6s9+t6kE+lUvkBod27NGTpSXmw2ayMHTuCH/zgByQSue6kL3zhCySTWZqaLgJw7NgRdH0FjY0NnD/flL+sy+Vi4cLF1NeHGD9+Ikq5PPMrAFU14fP58Hp9qKq8JyaE6FmVMJzzdGvC0OGcA7xWKPH7V4ILIYQoU5lMli++sIO9p9pIpK58tFNN0M9j5/dfn4HbLi8kiqlrnkZuQOiVu550X3qSCzWMrray3XXXQI4cOcjLL78MQP/+/fn85z/Pzp2RDwROqVSKbdu20NAQZsOGdaRSl7dIHTasBk0LUVur0adPn6L+P5QSs9mM3+/H6/VVdJAjhOhZElwUlgQXxVGDBBdCiAoWTaT5x7/u4dV9TZhNuRcKqUyWiUO8fPfRCVS7bTe5huLoTKZp6kxiVU30d1kq9kXN1UtPrhwSKktPiklVVSZNCvKv//qvtLXlllw9/PDDeDx+Tp06d8PLtrQ0s2bNKnQ9zP79kSuuc8aMj6JpIWbPnovFUpnLJ2w2K4FAAJfLjQycE0LcqUoILs4YHFz0l+Ci4GqQ4EIIIWhqi7P9yEUyWZg4xMtdVU6jSwKgLZ7ij3ua2HW2E7MJMllwWkyERldz72CP0eWVjO67nuSWn6S6dWkkSKfTEmj0sIED+9HaeoE//elPAHg8Hr7xjW+wc2eEdPr6u/Vc7cCBCA0NYdasWUlLS0v+uM/nY8mSOjQtxKhRo3u8/lKnKAoOh51AIIDD4ZTuIiHEhybBRWFJcFEcNUhwIYQQJak9keZfNr5PazzN1X+irapC3cgqFg33G1NcGVEUSKdznRmpVJpEIi6Bxh1SFIVJk8bwq1/9kjNnzgCwePFihg0bzvvvn/pQ15lIJNi0aQMNDS+xZcsbZDKXn4GOHh1E00IsXlyLz1dZP/OKouByOfH7A9hslTfMVAhx5yohuDjbmiBt0EO5qkA/CS4KrgYJLoQQoiT9cU8TG4+1XPeB2GxS+Mf5w/DY1OIW1ksoyuXhoMmkdGjcjj59ApjN8Ktf/QoAq9XKk08+yd69B4nH73wL4aamc6xcqaPrYY4dO5o/brFYmDNnHpq2jOnTZ6KqlfOzbzKZcLtd+P0BLBar0eUIIcqIBBeFJcFFcdQgwYUQQpScTDbLf1lzmMQNHoUtJoX60QEW3h0oYmW9X/dAo2uGRjye69JIpdJXdAJUAovFzPjxozh37iJnzzaRTKYYN24kL730Vw4ePAjAjBkzmDJlKocPH+/R285ms+zevRNdD7N27ct0dnbkz/Xp05elSzU0LcTQocN69HZLmclkwuNx4/P5JcAQQtwSCS4Kq1yCCxk1L4QQosfFUhnSNwmUk5ksZzuSRaqocmSzoKpmVNWMrdtsVkXh0latcWKxGNFojGQyNxC0vN/DuDGTyQTA6dPHmTRpEu3tnSSTiXxooSgKs2fP5ujRkz1+24qiMHHiR5g48SN861tPsW7dq+h6mDff3E5T0zl+85tf8Zvf/IqJEyehaSEWLrz/0kDL3iuTydDS0kp7ezsejwefz4/ZXJlDTIUQoouCYtgo43IZoSzBhRBCiB5nU003/RqTAh6rPAwVSzabW6pgsVhwOt35zoxEIk48ngszYrH4pSCj9yQZ6XQumNF1nVdeeYWpU6dy8uTlkGLcuHEkk2na2zsLWofD4WDpUo2lSzVOnjxBY+MKGhsbOH36FLt27WTXrp0888xy5s9fhKaFmDx5Sj506Y3S6QzNzS20tbXh9Xrxev2YzfL3QAghxLXJUhEhhBAF8fM3T7PzTAfX++tsMSn8/Zwh9HNJu3gp6BoCGo/HiMVidHZGSSYTpI0ac95DTCYTU6aM53/+z/9xzfNf/OKXMJutHDt2suiBTSaT4c03t6PrYV577VUSiXj+3MCBg9C0ZdTVLWPAgIFFrcsIqmqSDgwhxDVVwlKRc21JQ5eK9PVYoMTvXwkuhBBCFMTp9gTf23T8mnMuLCaFif2dfGHyAAMqu+xCR4IXt50gvPMM7fE0AaeFR6YO5OEpA3HZKvvdX0WBZDJ5qRsjSmdnZ9nOyJgxYzL/9E//dM1zw4YNY8GCBfTr14+zZ89z9uyF29oOtae0t7ezdu1qGhrC7NmzO39cURTuuWca9fUh5s1b0Ot35lBVE263G6/Xh9Vqu/kFhBC9ngQXhXW7wUUwGPwe8DC52idGIpHdl44fAWKXPgD+PhKJrLrZuVslwYUQQoiCOdoc4+dvnSaazJDOZjEpCpks3DvIzWPj+6KajFtZebI5xpf+/W06EmmS3Z4tWFWFfl4bP//cZLz2yg4vusvNyMjtWhKNdhKNRssmyJg2bSLf/e53SaVS1/2agQMH8tnPfo62tnYOHXq/iNV90OHDh2hsXMGqVTrnz5/PH3e73SxatARNCzFu3HgUpVxWJt8+k8mEy+XE5/Njt9t79RwWIcSNSXBRWB8iuJgDHAXWA8uuCi7yn191meueu1XyjEwIIUTBDPPb+cf5w3jvQoxT7QmsqsL4vk48JdDN8A9/2UtrLMXVuXcineVMS5x/WfUe//1jY4wprgTlZmRYsVisuFzuawQZMVKpFNls6Q37TKfTWCyW6wYXTqeTpUvr6Ojo4OjRE0Wu7oPuvns4X//6t3j88a+zZcsb6HqYDRtep729nb/+9U/89a9/oqbmbjQtRG1tHdXVfYwuucdlMhna2trp6OjA4XDg9/txOJwl97MlhBA9pVyi6EgksgEgGAwW9XaNf+YohBCiV1MUhVHVDkZVO4wuJe/guQ6OnI9+ILToksxkWX/gPC3RJD6HrLe/lmsHGbldS5LJJLFYjHg8fmk4ZtbQgZ/pdBqr1Uo0Gv3Auf79+/PpT3+alpZ23nvvmAHVXZ/ZbGb27LnMnj2XixcvsmZNIw0NKzh48ABHjhzmRz96lp/+9F+ZOXMWmhZi1qw5WCy96+c1k8nS0dFJZ2cUp9OBz+fD6XRJgCGEED3sZz/72ZDly5dffbg5Eok038bV/DYYDCrABuAfrrrsjc7dlAQXQgghKs6+0+3cbJWKxWziUFMnU+7yFaeoMtd91xIAn+/ynIxkMkEikSQez4UZxV5ikk5nrrljxdixY3nggQc4duwUFy7c1vOnogsEAjz22Kd59NFPsX9/BF0Ps3r1StraWtm4cT0bN67H7/ezZEkdmhZi5MhRRpfco7LZDwYYDoeT8nmPUgghrk9RjPtr1rXq8MUXX1x/jdP/CPy3W7yquZFI5P1gMGgDngaeA/7mFs7dEgkuhBBCVByzqnDT8QDZ3BDRUpDJZMkA5hKp51Zls2A2WzCbLTi6NdwkEvErZmWk05mCBhldS0W6W7hwIVOnTmX//iN0dn6wE6NUKYpCMDiGYHAMX//6t9iw4XV0Pcy2bVtobm7m97//D37/+/9g9Ogx1NeHWLy4Fq+394Rv3QMMh8Oe78CQAEMIIe7MJz/5ybnLly8/ftXhW071I5HI+5f+jQeDwR8BL93KuVslwYUQQoiKc+8wP6mbTcFSIDjAXZyCrmPX6Xb+sOsMkXOdAPRzW3lwXB8WjKjCVMaDGa1WG1arDbfbAxQ+yMhkMvngwmq18sgjj9CnT1/27j1IMnn9gZ2lzmazsWjRYhYtWsy5c2dZubKBhoYwx4+/z/79+9i/fx/PPfc0c+fOQ9NC3HvvDFRVNbrsHpHNZunsjBKNxrDb7fj9EmAIIcSdePzxx48//vjjRz7MZYPBoAswRyKRlkvLQT4JvH2zc7dDdhURQghRkf5pRYRXIk3EUx98/LBbTHx+5l18YdZdBlSWs2r/eX791qkPbCdrUxWmDvby7dl39dpdJXJLSxLEYlGi0SjJZOqOgoyRI4fS2Khz8eJFPvOZz5BIpDh27JShczcKJZvNsnPnO+h6mFdeefn/b+/Oo+Oq77uPv++9s48Wy7vxJgz4EhubHccYA2ax8chySShNk5DStCdPkrZPnjRNQk+3JD1PkjaH0ywNPWnSPknI0jZNKEGWbMxqMBgwOAbHy8XYeLfxNtJoNPvMff6QLGyQZAtr5o6kz+scHXPuHWm+mkTnzv3M9/f9kU6nes9NmDCRO+5oIhZbwfTpMzyscugZhkEwGKS+vp5oNIphmF6XJCJDZDTsKnIi+e5h4ZViGjCuxgfnvqvId4APApOB48AJoBn4FWD1fG0DPuM4zmHbtmf1d24wdSq4EBGRUSlbKHHfQ9t47UCCTL6ES/fF22+ZLJ0zgb+842LPuhqOdeX47KrXz9im9XRBn8GnF0zj+pljKlxZ5Z2ak5HLZclms6TTGXK5LKXSue9ecuGF09i7903mzZvHoUNHOXbsZHmLrhKpVIp1656ktbWFzZs3nXFu/vwriMWaueWWW3s6FUYOv99HbW0ttbV1+Hwja1ipyGik4KK8BhtceEXBhYiIjFqu6/LbQ508vPkIx5I5pjeE+MCVU7h4grc3cj/7zWFaneMUBmgyuLAhxD8uH1kDGM+FYUChUOgd9JlKpcnncxSL/b9YjY3TaGio44039tHZmaxgtdXj4MEDrF69ira2VRw9+lbv8XA4zJIltxKLNXP55VeOqC4eyzKJRCLU19cTCoW1E4nIMDUqgosuj4OLqIKLcmtEwYWIiIwwX3psF9uPpQZ8TNAy+MmHLqtQRf0rllwSmQIByyAarPzorFMdGdlslmw20xNk5M9YWhIKBSmVSuRy+YrXV22KxSKbNr1Ma2sLzzzzNLlctvfc1KnTWL58BcuXNzFp0mQPqxxahmEQCgWpq9MyEpHhSMFFeSm4qIxGFFyIiMgI8/Wn3uQ3hwfuDIgGLH74u3MqVNG7ZQslHtywn19uOkwmX6Togj0pyidvbOS6Ru+WsBgGZLNZOjsTdHYmKRaLntVS7To7O3niibW0trawffvW3uOGYXDttQuIxZpZvPgmgsGgh1UOLZ/PR21tDdFoDaFQSF0YIsOAgovyUnBRGY0ouBARkRFm/Z52vv/SQTL9rBUxDVgyq4FPLphW4cq6ZQsl/uTnr7HrWIrsO2oM+kw+f/tFrJg/yZPaTlcsFkgmk3R2Jsjl8iNyGOdQ2b17F6tXr2LNmjbi8bdngNTU1HLbbUtpamrm0kvnjJilJKZpEAyGqKurIxKJYJojY7cVkZFoNAQXJz0OLsYquCi7RhRciIjICFMolvjfLa9zMp3v8xPhoGXwjeWXMKXOm0/Cf/riAf5t/b53hRanBHwmj/zJtdSHq2cwYiqVJJFIkE6n9Z5hAIVCgRdeeI7W1lU8//yzZ3SsXHjhLJqaVrJs2XIaGsZ6WOXQsiyLmpootbW1moUhUoUUXJSXgovKaETBhYiIjEDHunJ85fHdJLLF3s6LkM/EAL5w00wum1TjWW0rvvsiJ7r6nxcR9Jl84oYZfNSjjpD+GAZkMhk6OxMkk8kBB3oKxOMnWbt2DW1tLeza9UbvccuyuP76G4jFmlm4cBE+X+Vnm5TDqS1Va2triUajWNbI+L1EhjsFF+Wl4KIyGlFwISIiI1Sp5LL5cCcbDyTIF13mTIqyaOYYgj7vhgsWiiVuvP95znbVXfq+8Xxl5aUVqakvyVSWn7e9xIOPbOBkIsX4MTV8/M6FfGjZtUTCAQqFPF1d3V0Y+XzfnS3SzXVdHGc7ra0tPPbYoySTnb3nGhrGsnTpHTQ1NTNr1sUeVjm0LMsiGo30dGFEvC5HZFQbDcFFPOVtcNEQUXBRbo0ouBAREakY13VZfP/zFAe47hrAB66czBeWenMjezyeZOVnHuB4PEkmV+g9Hg76uWBCPf/zc+5ZhwAAGzpJREFU7T9hTG0Y6P59UqkuOju1jORcZLNZ1q9fR2trCxs3vnjG3JD3vW8OsVgzt966lLq6Og+rHDqGYRAIBHq6MGpGTHeJyHCi4KK8FFxURiMKLkRERCrqLx/axjM7T/bbdRH2m3zz9y7j8mne3Lx+9C//nQ2v7qbQx1IQv9/itgWX8q9/d88Zx7uXkaTp7OzUMpJzdPToW6xe3crq1as4cGB/7/FAIMDixTfT1NTM1Vdfi2WNjMGXlmUSiXR3YYTDUa/LERk1RkNw0Z4qehpcjIlYUOWvr4ILERERGZSdR5N84iev9Tmc028azJ4U5Qcfu9yTHSgOvBVnyR/9E9l8od/HBP0+Nvz0PsY39D0n5PRlJLlc/7M8zle2UGTXiTSFksvU+hDjItUzzHQwXNfltdc209rawlNPPU46ne49N3HiRO64YwWx2AqmTZvuYZVDp7sLw09tbR3RaBSfb3j+7yYyXCi4KC8FF5XRiIILERGRinvpzTh/9fAOSq5LOl/CNCBgmcyeXMP9d82hNuRNS33rM1v4wj/9imQq2+9jaqMhHvir3+fma+0Bf5brlujq6qKjo4NsNjtk26mWSi6P7DjGc3vaMc3ucKdYdGlsCPOxq6ZQ79FrNxRSqRRPPfU4bW2rePXV35xx7vLLryQWW8GSJbcRiYyMuRGWZRKNvr0jSfdCKREZSgouykvBRWU0ouBCRETEE9lCiaed42w/kiTkN1kyezz2ZO92OwFYs34rn7v/vwcOLiJBvvd397D4qnOdweGSTqfo6Oggnc5QKp3fMpIfv3KI376VJPeOH2MCtQGL+25uJBoY/ssrDhzYT1vbKtasWcXRo0d7j4fDYZYsuY2mpmbmz7/Ck86coXZqFkZdXR2RSAS/36+BryJDZDQEFx1pb4OL+rCCi3JrRMGFiIiI9IgnurjuI/9ANtf/UpFw0M+mX/w10XBwUD97KLZTPdCR4dvP7XtXaHGKz4BbLmqg6dIJg/7ZQy1TKHI8lccyDCbVBDDfY8BQLBZ5+eWXaGtr4dln15HL5XrPTZs2neXLV7B8eRMTJ04aqtI9ZVkmoVCImppawuEwPp9PIYbIeVBwUV4KLiqjEQUXIiIicpq/uP+/aXn6tTN2FDklFPTzkdi1fPnTzef1HIVCno6OdhKJzkF1YPzitbfYsK+Dgb4j6jf52jLvthbN5Iusck6w5a0uLNOg5LoETIMlsxp4//S68+qQSCQSPP74o7S1tbBjx/be46Zpcs0119HU1MwNN9xEMDi4UKlavTPEsKzhuwxIxCsKLspLwUVlNKLgQkRERE6TyeX5w7/5MZt37CeV6f503zAgHAyw8PJZfP9L9+D3Dc1SjHw+R3t7nGSy65wCjO+9eIDtx1IDPsYEvrli9pDUN1jZYokHXjhIeybPO2evBiyD66bVEps9fkiea9euN2hra+HRR1fT3h7vPV5bW8ftty8jFmvGti8dEUtJoDvECIfDRKM1BIMhAgEtJxE5FwouykvBRWU0ouBCRERE3sF1XZ7bvIuftLzAoaPtTJ8ylnubF3LdvMay3Ahnsxna2+OkUqkB35OcS8dFjd/kqx51XDz1Zpynd7eT7+d38JsGn1k4bUh3QMnn82zY8BxtbS1s2PAcxWKx99xFF11MLNbM0qXLaWho6D2eyhXZdCBBe6ZAXcjimmn1RIbRXBDTNAkEAkQiYcLhMMFgCMMwvS5LpCopuCgvBReV0YiCCxEREakC3TMw0sTjcVKpdJ+7kBxMZPjW+uqdcfH1dXvo7K84wDLg+hn1LJ89rizPf+LEcR59dDVtbS3s2fPm289rWVx//WKamlbQ2TCbNieOaRhkiyUClknJdVl+6QRi7xs/7Do0DMPANE3C4RCRSJRQKEQgEFA3hkiP0RBcJDLeBhd1IQUX5daIggsRERGpIoYBqVQXiUSCdDr9riGeD246xJYj/ewqErS47ybvdhX568d2c7Z3VJeOD/MHV04pax2u67J9+zba2lp4/PFHSSaTved8kXrGvG8hY+YsJjRuau/xgGXyO5dN4NZLhmYpy/nqyhbJF0vUhXy9296eC9M08ft9RCIRQqEQoVAYy7IUZMiopeCivBRcVEYjCi5ERESkShWLBVKpFMlkJ5lMllKpRKnk0rLjOOv3xHtvaItFl1ljw9xz5RTqQt4NcPzKU3vIvnO4xWkM4OqptXxwTuU6QrLZDM88s47W1hZefvklOC1aCU+aRcPcG6ifvQArFCXkM7l/pY3P9G7Zxeb9HfznxoPsi2cwDYOABUvnTOKDV00mYA2uLsMA07QIhYKEwxFCoSDBYLhMlYtUp9ERXJQ8CycNA+pCJlT566vgQkRERKTMDANyuRypVBednUlyuRyZQpHdJ9IUSy5T64M0hIdubsR71bLjGC8d6KTYz9uqgGXwR1dPYUZ9qLKFATuPdfFPqzfx1pZniW9bT77jWO85w/JTd/HVTJp/I5+7exmXXVBX8foAHtt+jAc3HCD3ji4bv2UwoyHMl1fagw4vTmcYBj6fRSQSIRKJEA5HNBtDRjwFF+Wl4KIyGlFwISIiIsOKSzabJZXqoqsrRT6fH9SWquXUkSnwnQ0HSPfRdeE3DWaOCfLxq6Z4MkfitcMJ/t+LB8kUSrhuidTB14lvfZaOnRtxC7nexzWMn8jvrGhm+fIVTJ06rWL1daTz/OnPt/Q72DRgmfze1VNovnzykDzfqW6MSKR7p5JQKITP5xvw5sd1Xdpe2ce/tG1lx4F2LNNg8dwpfGbFZVx+YXUssRF5JwUX5aXgojIaUXAhIiIiw1R3J0aebDZDKtVFJpOhUCj2OdizUo4mc/z01SMkskVct7vGkgtzJkS467IJ+D1ahnEkkeWrj+96VzBQzKVJ7NxIfOt6UodeP+PclVdeTSzWzM0330I4XN4lFg9vPswvNx0m31+7CtAQ8fO9j84vy/NblkkoFCIarSEcjuD3nxliuK7LfT9+kUde2kMqW+g9bhgQ9Ft84973c+f7LyxLbYNVLLmk80XCfgtrEPNBZGQaDcFFZ9bb4KI2qOCi3BpRcCEiIiIjhOu65HIZMpkMXV0pMpmMJyGG67ocSGQ5lMhimQazx0U8nb1xytce38X+9ky/A0Rrcye5uPM11qxp49ixo73HI5Eot9xyG7FYM/PmzS9Lx8i3ntjNht3xAR9jAD//46sGNazzvTg14DMUChEMhggE/Dy/4zhffPAlTiaz5PvoqAn5Ldb/451MrPduhsbJrhwPvnSQtTuOUyy5GMCNF4/lD98/jQs8WJ4k1UHBRXkpuKiMRhRciIiIyAh0aneSeDzeE2B4XZH3DnVk+Men3iRXKJ0RXhh0L8X4i5sbmdEQplgssnHji7S1tfDss+vI5/O9j50+fQaxWDPLlzcxfvzQDRn9wfq9PLH9+IC7slimwc/+6MqKL7UxDIMv/OgF9p1IEwqFMX1+sgWDTBFyhRLZfBHTgD+NXcZnV5anI+RsjiWzfOo/f0tntsDpI0JMoztU+fZdc5g1PuJJbadL54q8sq+DTL7IRROiXFgFNY10oyG4SHocXNQouCi7RhRciIiIyIjmkkwmicdPksvlz/7wEe5IIstDW46w7a0uLMOg6LrYE6PcNX8SF9S9+1P5RKKDxx57lNbWFl5/fUfvcdM0ue6699PUtJJFixYTCATOq67thzv5+po3+t2VxTBgQeMY/vy2i87red6rZV9aRTbfXZtpGoQCPoJ+q2enkhCmz8/cmeN54NNLME2j4jdR9/16B5v2d/S7JeSMhhA/vOfyyhZ1mpLr8v1n9/JfGw9hmQYu3UtaGseF+UqzzcxxCjDKRcFFeSm4qIxGFFyIiIjIKOC6JRKJBO3t7RQKhbN/wwiXyRfpzBapCVqE/dY5fc8bb+ykra2FtWtX097e3nu8rq6epUvvIBZrZvZs+z3V47ouf/PrHew5kabQx/vSoGXyf++8lBljvVmKEftK2xmzLd7JNA1umDOFr35sAYFAgFAoSCAQxO/3EQgEMU2zbDdWx5M57nlw84DzQYI+k2/dNYfZE6PlKeIsvvHoG6zeepRM/sxgygCiQYsHP34lUzxezrI/nuahV4+w+UAC0zBYfPFYVl42kbHR8wvlvKbgoryGS3BhffnLX/a6hvMxBvhsOp1T+6SIiIiMaIZhEAqFqK2twTAgn895OsTTaz7LJBqw8A9ie9GxY8exYMFC7r77w8yebZPJpDl06CCZTJpt27by618/xDPPPE0ul2Pq1OmEQud+I2oYBgtnjWXHkSSd6QKnFrME/SZBn8EXl13EJRNrBv17DpXdRxLsOdrZ7/mQ3+JDiy9i1qRaCoVCz5yV7u17E4kEXV1d5HKZntDMxTAMrPPY2vV0zltJnt0VHzC4CFgG9sQoF02ofHBxqD3D19fsJFvou75CySWZLXDjJeMqXNnbVm89yt+27sQ5mqQ9XaA9XWDHkSS/3vIWc6fUMrku6Fltp5Rcly2Hk2w5nOR4V46JNYFzGr5qGAaRSADg20D7WR4+3IwBPpsrut0pmAdfBhDwGVDlr686LkRERESGoXw+Rzx+kq6uLr0POg8nThzn0UdX09bWwp49b/Ye9/l8LFq0mFismQULFuLznftw0j0nUmzc0062UGLW+AjXXTgGn0e7sZyy+0gHn/7es2Rz717KYhjQEA3wH1+8naDv7N0rhmFgmgY+n49gsLszIxDw4/cH8Pv9g/5AcfuRJF94eDvpfP/bAkf8Jp+/bRY3XVz5cODf1u/lxxsO9NlJc0rAMnjyc9d7sgvK60e7+OyvtvW7TCnsN/nZvVdQH/ZXuLK3bTqQ4FvP7OnZzrj7/3MAf3DNBayYM3HA7x01HRceFWAwPDouvB8PLSIiIiKD5vcHmDRpMplMhnj8JKlUelR3YLxX48aN5yMf+Rgf/vA9bNu2ldbWR3jiibV0dXWxbt1TrFv3FOPGjWPZshixWDONjWffMrRxXITGKpt5MGtyPX/3oav5+/96BaA3wAgHLMJBH9/+xKJzCi2ge1lMsehSLObIZnNAJ4Zh9HZhBINBQqEQfr8fn6870BhobsbsiVH8ljlgcFEouVwzo35Qv/NQeSuRHTC0gO4tgzP5ItFg5W+v/vOVQ+SK/b92Jddl9bZj/P7VF1SwqrdtOdzJ1x7fRbaPjpofbTyE60Lz3IHDCxF1XIiIiIgMc2fuQJJVgHGeMpkMzzzzFK2tLbzyysYzzs2dO49YbAW33rqUmhrvln68V4lUjrZX9vKb3SfwWwa3zJvG4ssm47fOLbQYLNM0MQwDv99PMBjA7w8QCHQHGj6fvzfQePjVI/zg+f1k+ugaCPpMVs6byKdumFmWGs/mh8/v54fP7zvrDI4nP7cQs8I7xgB84AevkMgMPPdm7uQavnP33ApVdKY/e2gbe+OZfs+HfCY//eh8gr6+u5JGQ8dFV9b1tOMiGjSgyl9fBRciIiIiI4ZLV1eSeDze80m4nK8jRw6zevUq2tpWcfjwod7jwWCQm25aQizWzFVXXYPp8VKQ4cQwwDC6A41AINC7zGSNE+eRrccpYJHKlSi5LqWSy232eD675EJPlmEAHE1kufv7L5PrJ7jwmdA8fzJfXHZxhSvrduf3X6YzWxzwMe+bVMN3f6/ywcXhRJY/e2hbv68ddC9l+T+LZ7LowoY+zyu4KK/hElxoqYiIiIjIiGEQjdYSidTQ2ZmgvT1OPq8dSM7H5MlT+PjHP8G99/4xmzdvorW1haeffoJsNsvatWtYu3YNkydPYfnyFSxf3sQFF0z1uuSq57rdu+QApNNp0uk0ANeON7DfX8fGfZ0kci4T66PccMkEpjREKRULmIbPk61aJ9YFufvqC/jVbw6/a1cR04Bo0MfHr59e2aJOM39qHc/vjvd74xuwDBY0erPMpiOdx2caAwYXxZJLx1k6RkY6Dxp13n5u7556UNRxISIiIjJClUpFOjra6ejooDjAGngZnK6uJE8++ThtbS1s2fLaGeeuuuoaYrFmbr75lkHtSiL9OzU/49SSk0DATyAQ6FluYvX82/15bLlubVzX5WcvHeRHG/ZDz3DJXKHE3Atq+dum2Z5uhbrtSCef/58d/Q7nDPlMfnrvFTREKj+c81gyxyd/uXXAZTZhv8nnb76Q6/qZYTIaOi5SOW87LiKB6u+4UHAhIiIiMsKd2oEkmezS/IshtnfvHtraWlizpo0TJ473Ho9Eotx66200Na1k7tx5GF5+pDqCndrhxDTNM+Zn+P2+3kDDsqwhCzTyxRJbDnaSzRdpHB/xNLA43a82H+bfNxwgXyxx6rbIZ4LPNPlS7BKumznGs9q+0OKw42hXv+drAhY/+eh8fP0sBVJwUV4KLiqjEQUXIiIiImdlGJBOp4jH46TT6Yq32490hUKBjRtfpLW1hfXr11EovN36PmPGTGKxZu64I8b48RM8rHJ0MU0DwzCxLItAwE8wGMTvD5zRpTGS/g52HuviF5sOs+VQJ6YBi2Y18MHLJ3serrx5IsUXV73e5+DVgGXw5zfO5IZZY/v9/tEQXKQ9Di7CCi7KrhEFFyIiIiKD4JJMJonHT5LL5b0uZkRqb2/nscfW0NbWws6dr/ceN02TBQsW0tS0kkWLFuP3V751X87s0ggEAgSDwd5lJ5bl6+3SgPItPRltdp9I8d31+9gbT+MzDUou1Id8/K+F0/tdInKKgovyUnBRGY0ouBAREREZtFKpSCLRQXt7u+ZflNHOnQ6trS2sXbuGRKKj93h9fT23334HTU3NXHKJ7WGFckr3bidGT7Bh9nZn+P3+0/47MKRLT0abI4ksR5M5akMWjQ3hc1pCNSqCi7zHwYVfwUW5NaLgQkREROQ9KxTyxONxkskkpZICjHLJ5XI899yztLW18OKLG854rWfPtonFmrn99mXU13s3i0AGdqpTo3vpSYBAIIDfHzhjnsbwvrWqTgouykvBRWU0ouBCRERE5Lxlsxni8ZOkUmkN8Cyz48ePsWZNG21tLezbt7f3uN/vZ9GiG2lqaubaaxf07pQh1e30pSfBYFCBxhBTcFFeCi4qoxEFFyIiIiJDwjAgleoiHo+TyWR0s1VmruuydesWWltbeOKJx0il3t55Yfz4CdxxR4xYrJkZM2Z6WKW8Vwo0hsZoCC4yeTwNLkLd43aq+vVVcCEiIiIi75JMdmqAZwVlMhnWrXuS1tYWNm16+Yxz8+bNJxZr5pZbbiMarfGoQhkq71xy8vZuJz4CgQCmaSrQOI2Ci/JScFEZjSi4EBERESkL1y2RSCRIJDoUYFTQoUMHWb26ldWrV3HkyOHe46FQiJtuuoWmppVcccWVmKbpYZUy1N4eCuonGAwQDIZ6BoOO7u6M0RBcZAveBhfB7lVpVf36Dvfg4iLgjXi8S8GFiIiISJm4rks6naKzs5NsNod3b7FHl1KpxNatW3jyycd54YUN5PO53nMTJ05iyZJbuPnmW5kwYaKHVUp5GZgmvd0Y3SGGH8vq3u1kNHRnmKZBQ0MU4GJgl8flDLVGeoILLym4KL8bgGe9LkJERERERETKajGw3usihthY4A2gweM64nQHQyc9rqNfwz24CALXAoeBose1iIiIiIiIyNCygCnARiDrcS3lMBao87iGBFUcWsDwDy5EREREREREZATTRB8RERERERERqVoKLkRERERERESkaim4EBEREREREZGqpeBCRERERERERKqWggsRERERERERqVoKLkRERERERESkaim4EBEREREREZGq5fO6gHKxbXs28GNgHHAC+APHcXZ6W5WIt2zb3gNker4A7nMc51HPChLxiG3b9wN3AY3APMdxfttzXNcOGbUG+LvYg64dMkrZtj0O+AlwEZAF3gA+6TjOMV0zRCpnJHdcfA94wHGc2cADwL96XI9Itfhdx3Gu6PnSG08ZrR4GbgT2vuO4rh0ymvX3dwG6dsjo5QLfcBzHdhxnPrAL+Ieec7pmiFTIiAwubNueCFwF/EfPof8ArrJte4J3VYmISLVwHGe94zj7Tz+ma4eMdn39XYiMdo7jnHQc5+nTDr0AzNQ1Q6SyRmRwAUwHDjqOUwTo+fdQz3GR0e5ntm2/Ztv2v9i2PcbrYkSqiK4dIv3TtUNGPdu2TeDTwCPomiFSUSM1uBCRvi12HOdy4FrAAL7rcT0iIlL9dO0Q6fbPQBL9DYhU3EgNLvYDU23btgB6/r2g57jIqHWqBdhxnCzwL8AibysSqSq6doj0QdcOkd7htZcAH3Icp4SuGSIVNSKDC8dxjgKbgQ/3HPow8BvHcY55V5WIt2zbjtq2Xd/z3wbw+3T/nYgIunaI9EXXDhGwbfurwNXAnT0Bnq4ZIhVmuK7rdQ1lYdv2pXRvT9QAxOnensjxtioR79i2PQv4FWD1fG0DPuM4zmFPCxPxgG3b3wE+CEwGjgMnHMeZq2uHjGZ9/V0AzejaIaOYbdtzgd8CrwPpnsNvOo7zAV0zRCpnxAYXIiIiIiIiIjL8jcilIiIiIiIiIiIyMii4EBEREREREZGqpeBCRERERERERKqWggsRERERERERqVoKLkRERERERESkaim4EBERqVK2bX/Ptu2/9boOERERES9pO1QREREP2ba9B5gEFIE88DzwKcdx9ntYloiIiEjVUMeFiIiI95odx6kBpgBvAf/scT0iIiIiVcPndQEiIiLSzXGcjG3bvwS+BWDb9o+AA47j/I1t2zcDPwW+CdxHd4fGXzmO88Oex8aA+4HpQAL4puM491f8lxAREREZYuq4EBERqRK2bUeADwEv9POQyUA9MBX4Y+AB27Ybes79O/BJx3FqgcuAJ8tcroiIiEhFqONCRETEew/btl0AaoCjwLJ+HpcH/t5xnALQZtt2ErDpDjrywBzbtl91HCcOxCtQt4iIiEjZqeNCRETEe3c6jjMGCAJ/BqyzbXtyH4870RNanJKiO+wAuAuIAXtt215n2/bCslYsIiIiUiEKLkRERKqE4zhFx3Eeont+xQ2D/N6NjuP8DjAReBj4RRlKFBEREak4LRURERGpErZtG8BKoAHYDqw4x+8LAHcDqxzH6bBtO0F3+CEiIiIy7KnjQkRExHstPfMqEsBXgXsdx9k6yJ/xMWBPT2jxKeCeIa5RRERExBOG67pe1yAiIiIiIiIi0id1XIiIiIiIiIhI1VJwISIiIiIiIiJVS8GFiIiIiIiIiFQtBRciIiIiIiIiUrUUXIiIiIiIiIhI1VJwISIiIiIiIiJVS8GFiIiIiIiIiFQtBRciIiIiIiIiUrUUXIiIiIiIiIhI1fr/nj8AU330IG8AAAAASUVORK5CYII=\n",
                        "text/plain": [
                            "<Figure size 1440x864 with 2 Axes>"
                        ]
                    },
                    "metadata": {
                        "needs_background": "light"
                    },
                    "output_type": "display_data"
                }
            ],
            "source": [
                "scores_train = []\n",
                "for i in range(len(pdf)):\n",
                "    scores_train.append(score_simulation(simulate_games(match_data_2018,pdf[i])))\n",
                "    \n",
                "num_bins_train = np.arange(math.ceil(_max)*2)+1\n",
                "bin_widths_train = math.ceil(_max)/num_bins_train\n",
                "bin_score_info_train = pd.DataFrame({\"Bins\":num_bins_train, \"Bin Width\":bin_widths_train, \"Score\":scores_train})\n",
                "bin_score_info_train[bin_score_info_train[\"Score\"]==bin_score_info_train[\"Score\"].max()]\n",
                "\n",
                "ax_scores_train = plot_pdf_scores(bin_score_info_train, \" [training data]\")\n",
                "\n",
                "for arrow_coord in [(13, 1)]:\n",
                "    plt.gca().annotate('Best Scoring PDF: 180', xy=arrow_coord, xytext=(15, 4),\n",
                "                arrowprops=dict(facecolor='grey', shrink=0.005),\n",
                "                )\n",
                "\n",
                "plt.gca().annotate('Worst Scoring PDF: 153', xy=(1.25,11), xytext=(5, 8),\n",
                "            arrowprops=dict(facecolor='grey', shrink=0.005),\n",
                "            )\n",
                "\n",
                "plt.gca().set_xticks([0,5,10,15,20])"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "The graph below plots all the PDFs against the difference in player ratings. The three estimates that got the highest scores after the simulation are in bold while all the other estimates are lightly visible in the background."
        },
        {
            "cell_type": "code",
            "execution_count": 28,
            "metadata": {},
            "outputs": [],
            "source": [
                "def format_pdf_for_plot(pdfs, outcome ):\n",
                "    \"\"\"This function creates a dataframe that has rows that correspond to the probability of an outcome\n",
                "    vs the difference in average rating.\n",
                "    \n",
                "    :param list pdfs: A list containing all the pdf estimates. Every element in the list is a dataframe.\n",
                "    :param str outcome: The outcome to focus on: \"Win\", \"Draw\", \"Loss\"\n",
                "    :return: Probability of outcome vs difference for every pdf, each row corresponds to pdf\n",
                "    :rtype: DataFrame\n",
                "    \n",
                "    \"\"\"\n",
                "\n",
                "    out_list = []\n",
                "    \n",
                "    for pdf in pdfs:\n",
                "        q = np.linspace(0,1,len(pdfs))\n",
                "        for i in pdf.index:\n",
                "            q[math.floor(pdf[\"Min\"][i]*2):math.ceil(pdf[\"Max\"][i])*2]  = pdf[outcome][i]\n",
                "        out_list.append(q)\n",
                "        \n",
                "    out_df = pd.DataFrame(out_list)\n",
                "    \n",
                "    return out_df\n",
                "\n"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 29,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "image/png": 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\n",
                        "text/plain": [
                            "<Figure size 1584x1008 with 1 Axes>"
                        ]
                    },
                    "metadata": {
                        "needs_background": "light"
                    },
                    "output_type": "display_data"
                }
            ],
            "source": [
                "wins = format_pdf_for_plot(pdf, \"Win\")\n",
                "draws = format_pdf_for_plot(pdf, \"Draw\")\n",
                "losses = format_pdf_for_plot(pdf, \"Loss\")\n",
                "\n",
                "new_columns = dict(zip(np.arange(22),np.arange(22)/2))\n",
                "\n",
                "wins = wins.rename(columns = new_columns)\n",
                "wins = wins.rename(new_columns, axis='index')\n",
                "losses = losses.rename(columns = new_columns)\n",
                "losses = losses.rename(new_columns, axis='index')\n",
                "draws = draws.rename(columns = new_columns)\n",
                "draws = draws.rename(new_columns, axis='index')\n",
                "\n",
                "ax_pdf = plt.subplot()\n",
                "\n",
                "n_bins = [16/2, 17/2, 19/2]\n",
                "for i in np.arange(22)/2:\n",
                "    if i in n_bins:\n",
                "        wins.loc[i].plot(\"line\", color =sns.hls_palette(10)[5], ax =ax_pdf )\n",
                "        draws.loc[i].plot(\"line\", color =sns.hls_palette(10)[7], ax =ax_pdf)\n",
                "        losses.loc[i].plot(\"line\", color =sns.hls_palette(10)[9], ax =ax_pdf)\n",
                "    else:\n",
                "        wins.loc[i].plot(\"line\", color =sns.hls_palette(10)[5], ax =ax_pdf, alpha =0.16)\n",
                "        draws.loc[i].plot(\"line\", color =sns.hls_palette(10)[7], ax =ax_pdf, alpha =0.16)\n",
                "        losses.loc[i].plot(\"line\", color =sns.hls_palette(10)[9], ax =ax_pdf, alpha =0.16)\n",
                "\n",
                "ax_pdf.grid(False)\n",
                "ax_pdf.figure.set_size_inches(22,14)\n",
                "\n",
                "ax_pdf.set_xlabel('Difference')\n",
                "ax_pdf.set_ylabel('Probability')\n",
                "\n",
                "ax_pdf.set_xticks([0,5,10])\n",
                "ax_pdf.set_yticks([0.5,1])\n",
                "\n",
                "ax_pdf.set_title(\"Probability vs Difference in Average Team Rating\")\n",
                "\n",
                "for title,text_coord, color in zip([\"Win\", \"Draw\", \"Loss\"],[(17/2,1),(18/2,0.25),(20/2, 0.07)],[sns.hls_palette(10)[5],sns.hls_palette(10)[7],sns.hls_palette(10)[9]]):\n",
                "    plt.gca().text(text_coord[0], text_coord[1], title, color = color, fontsize=12)\n"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "As the difference in team rating increases, the probability of winning consistently increases. This graph is basically the conditional distribution I set out to find in the first place. This is much easier to interpret than the tables I showed before."
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "### Conclusion\n\nWhile the estimation results are not particularly predictive, they are better than guessing at random. The web scraping part of the code works very well though. I intend to use it to produce a more complete dataset of Premier League matches and results for the past 27 years of the competition and all I need are the match IDs for those games. "
        }
    ],
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