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How to use touch_factor method in Airtest

Best Python code snippet using Airtest

ios.py

Source:ios.py

...245        # å½åçæ¬: wda 4.1.4 è·åå°ç/window/sizeï¼å¨ipad+æ¡é¢æ¨ªå±ä¸æ¿å°çæ¯ height * heightï¼éè¦ä¿®æ£246        if self.is_pad and self.home_interface():247            self._size['window_width'] = int(width * self._touch_factor)248    @property249    def touch_factor(self):250        if not self._touch_factor:251            self._display_info()252        return self._touch_factor253    @touch_factor.setter254    def touch_factor(self, factor):255        """256        touch_factor is used to convert click coordinates: mobile phone real coordinates = touch_factor * screen coordinates257        In general, no manual settings are required258        touch_factorç¨äºæ¢ç®ç¹å»åæ ï¼ææºçå®åæ  = touch_factor * å±å¹åæ 259        é»è®¤è®¡ç®æ¹å¼æ¯ï¼ self.display_info['window_height'] / self.display_info['height']260        ä½å¨é¨åç¹æ®åå·ææºä¸å¯è½ä¸åç¡®ï¼ä¾å¦iOS14.4ç7Pï¼é»è®¤å¼ä¸º 1/3ï¼ä½é¨å7Pç¹å»ä½ç½®ä¸åç¡®ï¼å¯èªè¡è®¾ç½®ä¸ºï¼self.touch_factor = 1 / 3.3261        ï¼ä¸è¬æåµä¸ï¼æ éæå¨è®¾ç½®ï¼ï¼262        Examples:263            >>> device = connect_device("iOS:///")264            >>> device.touch((100, 100))  # wrong position265            >>> print(device.touch_factor)266            0.333333267            >>> device.touch_factor = 1 / 3.3  # default is 1/3268            >>> device.touch((100, 100))...

Index.py

Source:Index.py

1from regression import shotRate2import numpy as np3from math import exp, factorial4import operator5import datetime6def matchEstimates(matchData, coefs, probs):7    expectedshots = []8    total_team_touches = []9    for teamId, value1 in matchData.iteritems():10        contributions=[]11        for key in matchData.keys():12            if key != teamId:13                opponent_teamId = key14        won_contest_sum = 015        yellow_card_opp_sum = 016        red_card_opp_sum = 017        accurate_pass_sum = 018        total_tackle_opp_sum = 019        touches_sum = 020        aerial_won_sum = 021        for player_name, value2 in matchData[teamId]["Player_stats"].iteritems():22            for key in matchData[teamId]["Player_stats"][player_name]["Match_stats"].keys():23                if key == "won_contest":24                    won_contest_sum += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["won_contest"])25                if key == "accurate_pass":26                    accurate_pass_sum += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["accurate_pass"])27                if key == "touches":28                    touches_sum += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["touches"])29                if key == "aerial_won": 30                    aerial_won_sum += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["aerial_won"])   31        for player_name, value2 in matchData[opponent_teamId]["Player_stats"].iteritems():32            for key in matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"].keys():33                if key == "total_tackle":34                    total_tackle_opp_sum += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["total_tackle"])35                if key == "yellow_card":36                    yellow_card_opp_sum += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["yellow_card"])37                if key == "red_card":38                    red_card_opp_sum += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["red_card"])39                if key == "second_yellow":40                    red_card_opp_sum += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["second_yellow"])41        42        contributions.append(won_contest_sum)43        contributions.append(accurate_pass_sum)44        contributions.append(total_tackle_opp_sum)45        contributions.append(aerial_won_sum)46        contributions.append(yellow_card_opp_sum)47        contributions.append(red_card_opp_sum)48        total_team_touches.append(touches_sum)49        regression_pred = coefs[0] + coefs[1]*contributions[0] + coefs[2]*contributions[1] + coefs[3]*contributions[2] \50        + coefs[4]*contributions[3] + coefs[5]*contributions[4] + coefs[6]*contributions[5]51        expectedshots.append(regression_pred)52    expectedshots = np.array(expectedshots)53    lambda_ = probs[0]*expectedshots54    estimates = [lambda_, expectedshots, total_team_touches]55    return estimates56def goalProbabilities(lambda_):57    goal_probabilities = dict()58    sum_prob = 059    points_home = 060    points_away = 061    for i in range(5):62        for j in range(5):63            a = str(j) + "-" + str(i)64            prob = exp(-(lambda_[0] + lambda_[1]))*pow(lambda_[0], j)*pow(lambda_[1], i)/(factorial(j)*factorial(i))65            if j > i:66                points_home += 3*prob67            if j < i:68                points_away += 3*prob69            if j ==i:70                points_away += prob71                points_home += prob72            sum_prob += prob73            goal_probabilities.update({a : prob})74    goal_probabilities = sorted(goal_probabilities.items(), key=operator.itemgetter(1))75    print points_home, points_away76def playerPoints(matchData, estimates, coefs, probs):77    lambda_ = estimates[0]78    expectedshots = estimates[1]79    total_team_touches = estimates[2]80    total_team_touches_home = total_team_touches[0]81    total_team_touches_away = total_team_touches[1]82    derivative_home = 083    derivative_away = 084    cross_positions_1 = ["ML", "MR", "AML", "AMR"]85    cross_positions_2 = ["FWL", "FWR", "DR", "DL", "DMR", "DML"]86    87    for i in range(5):88        for j in range(5):89            a = str(j) + "-" + str(i)90            prob = exp(-(lambda_[0] + lambda_[1]))*pow(lambda_[0], j)*pow(lambda_[1], i)/(factorial(j)*factorial(i))91            if j > i:92                derivative_home += prob*(j/lambda_[0] - 1)93            if j < i:94                derivative_away += prob*(i/lambda_[1] - 1)95    exp_pts = dict()            96    # count to keep track of home or away team97    for teamId, value1 in matchData.iteritems():98        clean_sheet_away = 099        clean_sheet_home = 0100        for key in matchData.keys():101            if key != teamId:102                opponent_teamId = key103        if "goals" in matchData[teamId]["aggregate_stats"].keys():104            home_team_goal = float(matchData[teamId]["aggregate_stats"]["goals"])105        else:106            home_team_goal = 0107            clean_sheet_away = 1108        if "goals" in matchData[opponent_teamId]["aggregate_stats"].keys():109            away_team_goal = float(matchData[opponent_teamId]["aggregate_stats"]["goals"])110        else:111            away_team_goal = 0112            clean_sheet_home = 1113        114        if "total_scoring_att" in matchData[teamId]["aggregate_stats"].keys():115            home_team_shots = float(matchData[teamId]["aggregate_stats"]["total_scoring_att"])116        else:117            home_team_shots = 0118        if "total_scoring_att" in matchData[opponent_teamId]["aggregate_stats"].keys():119            away_team_shots = float(matchData[opponent_teamId]["aggregate_stats"]["total_scoring_att"])120        else:121            away_team_shots = 0122        if "total_tackle" in matchData[teamId]["aggregate_stats"].keys():123            home_team_tackle = float(matchData[teamId]["aggregate_stats"]["total_tackle"])124        else:125            home_team_tackle = 0126        if "total_tackle" in matchData[opponent_teamId]["aggregate_stats"].keys():127            away_team_tackle = float(matchData[opponent_teamId]["aggregate_stats"]["total_tackle"])128        else:129            away_team_tackle = 0130        131        if home_team_goal >= away_team_goal:132            if home_team_goal == away_team_goal:133                game_result_home = 1134                game_result_away = 1135            else:136                game_result_away = 0137                game_result_home = 3138        else:139            game_result_away = 3140            game_result_home = 0141        142        for player_name, value2 in matchData[teamId]["Player_stats"].iteritems():143            player_id = str(matchData[teamId]["Player_stats"][player_name]["player_details"]["player_id"])144            date = datetime.datetime.strptime(matchData[teamId]["team_details"]["date"], "%d/%m/%Y").strftime("%m/%d/%Y")145            won_contest = 0146            yellow_card_opp = 0147            red_card_opp = 0148            accurate_pass = 0149            total_tackle_opp = 0150            touches = 0151            aerial_won = 0152            saves = 0153            goals = 0154            assists = 0155            shots = 0156            cross_factor = 0157            player_position = int(matchData[teamId]["Player_stats"][player_name]["player_details"]["player_position_value"])158            player_position_info = str(matchData[teamId]["Player_stats"][player_name]["player_details"]["player_position_info"])159            if  player_position < 5:160                game_time = 0.85/11161                if player_position == 1:162                    defensive_actions = 0.3163                if player_position == 2:164                    defensive_actions = 0.14165                if player_position == 3 and str(matchData[teamId]["Player_stats"][player_name]["player_details"]["player_position_info"]) == "DMC":166                    defensive_actions = 0.14 167            else:168                game_time = 0.15/7169            if player_position_info in cross_positions_1:170                cross_factor = 0.30171            elif player_position_info in cross_positions_2:172                cross_factor = 0.20173            elif player_position_info == "GK" or player_position_info == "Sub":174                cross_factor = 0175            else :176                cross_factor = 0.05177            for key in matchData[teamId]["Player_stats"][player_name]["Match_stats"].keys():178                if key == "won_contest":179                    won_contest += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["won_contest"])180                if key == "accurate_pass":181                    accurate_pass += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["accurate_pass"])182                if key == "touches":183                    touches += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["touches"])184                if key == "aerial_won": 185                    aerial_won += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["aerial_won"])186                if key == "saves":187                    saves += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["saves"])188                if key == "total_tackle":189                    total_tackle_opp += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["total_tackle"])190                if key == "yellow_card":191                    yellow_card_opp += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["yellow_card"])192                if key == "red_card":193                    red_card_opp += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["red_card"])194                if key == "second_yellow":195                    red_card_opp += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["second_yellow"])196                if key == "goals":197                    goals += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["goals"])198                if key == "goal_assist":199                    assists += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["goal_assist"])200                if key == "total_scoring_att":201                    shots += float(matchData[teamId]["Player_stats"][player_name]["Match_stats"]["total_scoring_att"])202            touch_factor = touches/total_team_touches_home203            if home_team_goal != 0:204                goal_factor = goals/home_team_goal205                assist_factor =  assists/home_team_goal206            else :207                goal_factor = 0208                assist_factor = 0209            if home_team_shots != 0:210                shot_factor = shots/home_team_shots211            else :212                shot_factor = 0213            if home_team_tackle != 0:214                tackle_factor = total_tackle_opp/home_team_tackle215            else:216                tackle_factor = 0217            contributions = np.array([won_contest, accurate_pass, touch_factor, aerial_won, saves, total_tackle_opp, yellow_card_opp, red_card_opp, goal_factor, assist_factor, shot_factor, cross_factor, tackle_factor])218            exp_pt_1 = 2*derivative_home*probs[0]*(coefs[1]*won_contest + coefs[2]*accurate_pass + coefs[4]*aerial_won) \219            - derivative_away*probs[0]*(coefs[3]*total_tackle_opp + coefs[5]*yellow_card_opp + coefs[6]*red_card_opp) \220            + derivative_away*probs[1]*saves/(expectedshots[1]*probs[2])*1.5221            exp_pt_2 = game_result_home*touch_factor222            exp_pt_3 = 1.37*game_time223            exp_pt_4 = 1.02*goals224            exp_pt_5 = 1.02*assists225            exp_pt_6 = 2.73*defensive_actions*clean_sheet_home226            exp_pt = exp_pt_1 + exp_pt_2*0.25 + exp_pt_3*0.15 + exp_pt_4*0.05 + exp_pt_5*0.05 + exp_pt_6*0.13227            exp_pts.update({player_id : [player_name, teamId, player_position, contributions, [exp_pt], date]})228        for player_name, value2 in matchData[opponent_teamId]["Player_stats"].iteritems():229            player_id = str(matchData[opponent_teamId]["Player_stats"][player_name]["player_details"]["player_id"])230            date = datetime.datetime.strptime(matchData[opponent_teamId]["team_details"]["date"], "%d/%m/%Y").strftime("%m/%d/%Y")231            won_contest = 0232            yellow_card_opp = 0233            red_card_opp = 0234            accurate_pass = 0235            total_tackle_opp = 0236            touches = 0237            aerial_won = 0238            saves = 0239            goals = 0240            assists = 0241            shots = 0242            player_position = int(matchData[opponent_teamId]["Player_stats"][player_name]["player_details"]["player_position_value"])243            player_position_info = str(matchData[opponent_teamId]["Player_stats"][player_name]["player_details"]["player_position_info"])244            if  player_position < 5:245                game_time = 0.85/11246                if player_position == 1:247                    defensive_actions = 0.3248                if player_position == 2:249                    defensive_actions = 0.13250                if player_position == 3 and str(matchData[opponent_teamId]["Player_stats"][player_name]["player_details"]["player_position_info"]) == "DMC":251                    defensive_actions = 0.13252            else:253                game_time = 0.15/7254            if player_position_info in cross_positions_1:255                cross_factor = 0.30256            elif player_position_info in cross_positions_2:257                cross_factor = 0.20258            elif player_position_info == "GK" or player_position_info == "Sub":259                cross_factor = 0260            else :261                cross_factor = 0.05262            for key in matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"].keys():263                if key == "won_contest":264                    won_contest += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["won_contest"])265                if key == "accurate_pass":266                    accurate_pass += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["accurate_pass"])267                if key == "touches":268                    touches += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["touches"])269                if key == "aerial_won": 270                    aerial_won += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["aerial_won"])271                if key == "saves":272                    saves += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["saves"])273                if key == "total_tackle":274                    total_tackle_opp += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["total_tackle"])275                if key == "yellow_card":276                    yellow_card_opp += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["yellow_card"])277                if key == "red_card":278                    red_card_opp += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["red_card"])279                if key == "second_yellow":280                    red_card_opp += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["second_yellow"])281                if key == "goals":282                    goals += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["goals"])283                if key == "goal_assist":284                    assists += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["goal_assist"])285                if key == "total_scoring_att":286                    shots += float(matchData[opponent_teamId]["Player_stats"][player_name]["Match_stats"]["total_scoring_att"]) 287            288            touch_factor = touches/total_team_touches_away289            if away_team_goal != 0:290                goal_factor = goals/away_team_goal291                assist_factor =  assists/away_team_goal292            else :293                goal_factor = 0294                assist_factor = 0295            if away_team_shots != 0:296                shot_factor = shots/away_team_shots297            else :298                shot_factor = 0299            if away_team_tackle != 0:300                tackle_factor = total_tackle_opp/away_team_tackle301            else:302                tackle_factor = 0303            304            contributions = np.array([won_contest, accurate_pass, touch_factor, aerial_won, saves, total_tackle_opp, yellow_card_opp, red_card_opp, goal_factor, assist_factor, shot_factor, cross_factor, tackle_factor])305            exp_pt_1 = 2*derivative_away*probs[0]*(coefs[1]*won_contest + coefs[2]*accurate_pass + coefs[4]*aerial_won) \306            - derivative_home*probs[0]*(coefs[3]*total_tackle_opp + coefs[5]*yellow_card_opp + coefs[6]*red_card_opp) \307            + derivative_home*saves*probs[1]/(expectedshots[0]*probs[2])*1.5308            exp_pt_2 = game_result_away*touch_factor309            exp_pt_3 = 1.37*game_time310            exp_pt_4 = 1.02*goals311            exp_pt_5 = 1.02*assists312            exp_pt_6 = 2.73*defensive_actions*clean_sheet_away313            exp_pt = exp_pt_1 + exp_pt_2*0.25 + exp_pt_3*0.15 + exp_pt_4*0.05 + exp_pt_5*0.05 + exp_pt_6*0.13314            exp_pts.update({player_id : [player_name, opponent_teamId, player_position, contributions,[exp_pt], date]})315        break316    return exp_pts317def dict_update(dict1, matchUpdate):318    for key, value in matchUpdate.iteritems():319        if key in dict1.keys():320            dict1[key].append(matchUpdate[key][4][0])321        else:322            dict1[key] = matchUpdate[key][4]323def position_update(dict1, matchUpdate):324    # position vector is [others, postion1, position2, position3, position4, position5] 325    for key, value in matchUpdate.iteritems():326        position = int(matchUpdate[key][2])327        if key in dict1.keys():328            dict1[key][position] += 1329        else:330            dict1[key] = []331            for i in range(6):332                if i == position:333                    dict1[key].append(1)334                else:335                    dict1[key].append(0)336def contributions_update(dict1, matchUpdate):337    # contributions vector is [won_contest, accurate_pass, touch_factor, aerial_won, saves, total_tackle_opp, yellow_card_opp, red_card_opp, goals, assists]338    for key, value in matchUpdate.iteritems():339        contributions = matchUpdate[key][3]340        if key in dict1.keys():341            dict1[key] = dict1[key] + contributions342        else:343            dict1[key] = contributions344def player_name_update(dict1, matchUpdate):345    for key, value in matchUpdate.iteritems():346        player_name = matchUpdate[key][0]347        player_team = matchUpdate[key][1]348        if key in dict1.keys():349            if player_team in dict1[key][1].keys():350                dict1[key][1][player_team] += 1351            else:352                dict1[key][1][player_team] = 1353        else:354            dict1[key]=[]355            dict1[key].append(player_name)356            dict1[key].append({player_team: 1})357            358def summary_update(dict_1, matchUpdate):359    for key, value in matchUpdate.iteritems():360        contributions = matchUpdate[key][3]361        position = matchUpdate[key][2]362        pts = matchUpdate[key][4][0]363        date = matchUpdate[key][5]364        updated_array = np.append(contributions, position)365        updated_array = np.append(updated_array, pts)366        if key in dict_1.keys():367            dict_1[key][date] = updated_array368            369        else:370            dict_1[key] = {}371            dict_1[key][date] = updated_array372            373            374def roster_update(dict1, matchUpdate):375    for player_id, value in matchUpdate.iteritems():376        team_id = value[1]377        if team_id in dict1.keys():378            if player_id in dict1[team_id].keys():379                if value[2] < 5:380                    dict1[team_id][player_id][0] += 1/38.0381                else:382                    dict1[team_id][player_id][1] += 1/38.0383            else:384                dict1[team_id][player_id] = [0, 0]385                if value[2] < 5:386                    dict1[team_id][player_id][0] += 1/38.0387                else:388                    dict1[team_id][player_id][1] += 1/38.0389        else:390            dict1[team_id] = dict()391            dict1[team_id][player_id] = [0, 0]392            if value[2] < 5:393                dict1[team_id][player_id][0] += 1/38.0394            else:395                dict1[team_id][player_id][1] += 1/38.0396    397def aggregate_to_mean_contribution(dict1, aggregate_dict):398    for player_id, player_data in aggregate_dict.iteritems():399        beta = 0.9400        num_starts = 0401        num_subs = 0402        sorteddates = aggregate_dict[player_id].keys()403        sorteddates.sort()404        for date in sorteddates:405            match_data = aggregate_dict[player_id][date]406            contribution = match_data[:-2]407            if match_data[-2] < 5:408                if num_starts == 0:409                    player_start = contribution410                    num_starts += 1411                else:412                    player_start = beta*player_start + (1-beta)*contribution413                    num_starts += 1414            else:415                if num_subs == 0:416                    player_sub = contribution417                    num_subs += 1418                else:419                    player_sub = beta*player_sub + (1-beta)*contribution420                    num_subs += 1421        if num_starts > 0:422            player_start = player_start423        else:424            player_start = 0*player_sub425        if num_subs > 0:426            player_sub = player_sub427        else:428            player_sub = 0*player_start429        430        dict1[player_id] = [player_start, player_sub]      431def match_contributions(dict1, mean_contribution_dict, team_roster_dict):432    for team_id, home_players in team_roster_dict.iteritems():433        count_home = 0434        for player, appearances in home_players.iteritems():435            if count_home > 0:436                home_contribution = home_contribution + mean_contribution_dict[player][0][:-5]*appearances[0] \437                + mean_contribution_dict[player][1][:-5]*appearances[1]438            else:439                home_contribution = mean_contribution_dict[player][0][:-5]*appearances[0] \440                + mean_contribution_dict[player][1][:-5]*appearances[1]441            442            count_home += 1443        dict1[team_id] = home_contribution444def game_result(home_team_id, away_team_id, teamMeanContribution_dict, coefs, probs):445    home_team_contribution = teamMeanContribution_dict[home_team_id]446    away_team_contribution = teamMeanContribution_dict[away_team_id]447    448    expectedshots_home = coefs[0] + coefs[1]*home_team_contribution[0] + coefs[2]*home_team_contribution[1] + \449    coefs[3]*away_team_contribution[5] + coefs[4]*home_team_contribution[3] + coefs[5]*away_team_contribution[6] + \450    coefs[6]*away_team_contribution[7]451    expectedshots_away = coefs[0] + coefs[1]*away_team_contribution[0] + coefs[2]*away_team_contribution[1] + \452    coefs[3]*home_team_contribution[5] + coefs[4]*away_team_contribution[3] + coefs[5]*home_team_contribution[6] + \453    coefs[6]*home_team_contribution[7]454    expectedshots = np.array([expectedshots_home, expectedshots_away])455    expectedshots = [1.2, 1]*expectedshots456    lambda_ = probs[0]*expectedshots457    home_win_prob = 0458    draw_prob = 0459    away_win_prob = 0460    461    for i in range(10):462        for j in range(10):463            prob = exp(-(lambda_[0] + lambda_[1]))*pow(lambda_[0], j)*pow(lambda_[1], i)/(factorial(j)*factorial(i))464            if j > i:465                home_win_prob += prob466            if j < i:467                away_win_prob += prob468            if j == i:469                draw_prob += prob470    sum_prob = home_win_prob + away_win_prob + draw_prob471    home_win_prob = home_win_prob/sum_prob472    away_win_prob = away_win_prob/sum_prob473    draw_prob = draw_prob/sum_prob...

playerRating.py

Source:playerRating.py

1import json2import numpy as np3from regression import *4from shotEffectiveness import estimateProbabilities5from Index import *6from collections import OrderedDict7import operator8import unicodedata9file_pointer = open("/Users/shubhampawar/epl_data/xml_stats/season16-17/season_stats.json", "rb")10data = json.load(file_pointer, object_pairs_hook=OrderedDict)11# previous two seasons data and current season data12file_pointer = open("/Users/shubhampawar/epl_data/xml_stats/season17-18/season_stats.json", "rb")13data.update(json.load(file_pointer, object_pairs_hook=OrderedDict))14# file_pointer = open("/Users/shubhampawar/epl_data/xml_stats/season15-16/season_stats.json", "rb")15# data.update(json.load(file_pointer, object_pairs_hook=OrderedDict))16# file_pointer = open("/Users/shubhampawar/epl_data/xml_stats/season14-15/season_stats.json", "rb")17# data.update(json.load(file_pointer, object_pairs_hook=OrderedDict))18total_shots = []19won_contest = []20yellow_card_opp = []21red_card_opp = []22accurate_pass = []23total_tackle_opp= []24touches = []25aerial_won = []26shots = 027goals = 028onTarget = 029saves = 030blocks = 031aggregate_stats_dict = dict()32player_stats_dict = dict()33for matchId, value1 in data.iteritems():34    for teamId, value2 in data[matchId].iteritems():35        for key in data[matchId].keys():36            if key != teamId:37                opponent_teamId = key 38        for key in data[matchId][teamId]["aggregate_stats"].keys():39            if key in aggregate_stats_dict.keys():40                aggregate_stats_dict[key] +=141            else:42                aggregate_stats_dict.update({key: 1})43        total_shots.append(int(data[matchId][teamId]["aggregate_stats"]["total_scoring_att"]))44        45        if "total_scoring_att" in data[matchId][teamId]["aggregate_stats"].keys():46            shots += float(data[matchId][teamId]["aggregate_stats"]["total_scoring_att"])47        if "goals" in data[matchId][teamId]["aggregate_stats"].keys():48            goals += float(data[matchId][teamId]["aggregate_stats"]["goals"])49        if ("ontarget_scoring_att" in data[matchId][teamId]["aggregate_stats"].keys()) and ("blocked_scoring_att" in data[matchId][teamId]["aggregate_stats"].keys()):50            onTarget += float(data[matchId][teamId]["aggregate_stats"]["ontarget_scoring_att"]) + float(data[matchId][teamId]["aggregate_stats"]["blocked_scoring_att"])51        if ("ontarget_scoring_att" in data[matchId][teamId]["aggregate_stats"].keys()) and not("blocked_scoring_att" in data[matchId][teamId]["aggregate_stats"].keys()):52            onTarget += float(data[matchId][teamId]["aggregate_stats"]["ontarget_scoring_att"])53        if not("ontarget_scoring_att" in data[matchId][teamId]["aggregate_stats"].keys()) and ("blocked_scoring_att" in data[matchId][teamId]["aggregate_stats"].keys()):54            onTarget += float(data[matchId][teamId]["aggregate_stats"]["blocked_scoring_att"])55        if ("ontarget_scoring_att" in data[matchId][teamId]["aggregate_stats"].keys()) and ("goals" in data[matchId][teamId]["aggregate_stats"].keys()):56            saves += float(data[matchId][teamId]["aggregate_stats"]["ontarget_scoring_att"]) - float(data[matchId][teamId]["aggregate_stats"]["goals"])57        if ("ontarget_scoring_att" in data[matchId][teamId]["aggregate_stats"].keys()) and not("goals" in data[matchId][teamId]["aggregate_stats"].keys()):58            saves += float(data[matchId][teamId]["aggregate_stats"]["ontarget_scoring_att"])59        if "blocked_scoring_att" in data[matchId][teamId]["aggregate_stats"].keys():60            blocks += float(data[matchId][teamId]["aggregate_stats"]["blocked_scoring_att"])61        won_contest_sum = 062        yellow_card_opp_sum = 063        red_card_opp_sum = 064        accurate_pass_sum = 065        total_tackle_opp_sum = 066        touches_sum = 067        aerial_won_sum = 068        for player_name, value3 in data[matchId][teamId]["Player_stats"].iteritems():69            for key in data[matchId][teamId]["Player_stats"][player_name]["Match_stats"].keys():70                # if key in player_stats_dict.keys():71                #    player_stats_dict[key] +=172                # else:73                #    player_stats_dict.update({key: 1})    74                if key == "won_contest":75                        won_contest_sum += float(data[matchId][teamId]["Player_stats"][player_name]["Match_stats"]["won_contest"])76                if key == "accurate_pass":77                    accurate_pass_sum += float(data[matchId][teamId]["Player_stats"][player_name]["Match_stats"]["accurate_pass"])78                if key == "touches":79                    touches_sum += float(data[matchId][teamId]["Player_stats"][player_name]["Match_stats"]["touches"])80                if key == "aerial_won": 81                    aerial_won_sum += float(data[matchId][teamId]["Player_stats"][player_name]["Match_stats"]["aerial_won"])   82            83        won_contest.append(won_contest_sum)84        accurate_pass.append(accurate_pass_sum)85        touches.append(touches_sum)86        aerial_won.append(aerial_won_sum)87        for player_name, value3 in data[matchId][opponent_teamId]["Player_stats"].iteritems():88            for key in data[matchId][opponent_teamId]["Player_stats"][player_name]["Match_stats"].keys():89                if key == "total_tackle":90                    total_tackle_opp_sum += float(data[matchId][opponent_teamId]["Player_stats"][player_name]["Match_stats"]["total_tackle"])91                if key == "yellow_card":92                    yellow_card_opp_sum += float(data[matchId][opponent_teamId]["Player_stats"][player_name]["Match_stats"]["yellow_card"])93                if key == "red_card":94                    red_card_opp_sum += float(data[matchId][opponent_teamId]["Player_stats"][player_name]["Match_stats"]["red_card"])95                if key == "second_yellow":96                    red_card_opp_sum += float(data[matchId][opponent_teamId]["Player_stats"][player_name]["Match_stats"]["second_yellow"])97            98        total_tackle_opp.append(total_tackle_opp_sum)   99        yellow_card_opp.append(yellow_card_opp_sum)100        red_card_opp.append(red_card_opp_sum)101shots_data = np.transpose(np.array([total_shots, won_contest, accurate_pass, total_tackle_opp, aerial_won, yellow_card_opp, red_card_opp]))102#print shots_data.shape103coefficients = shotRegression(shots_data)104#print total_shots[0], won_contest[0], accurate_pass[0], total_tackle[0], touches[0], aerial_won[0], yellow_card_opp[0], red_card_opp[0]105probabilities = estimateProbabilities(shots, goals, onTarget, saves, blocks)106playerRatings = dict()107playerPosition = dict()108playerIdNameData = dict()109playerMatchSummary = dict()110playerMeanContributions = dict()111teamMeanContribution = dict()112teamRoster = dict()113for matchId, value in data.iteritems():114    estimates = matchEstimates(data[matchId], coefficients, probabilities) 115    #lambda_ = estimates[0]116    #goalProbabilities(lambda_)117    playerData = playerPoints(data[matchId], estimates, coefficients, probabilities)118    position_update(playerPosition, playerData)119    summary_update(playerMatchSummary, playerData)120    player_name_update(playerIdNameData, playerData)121    roster_update(teamRoster, playerData)122    aggregate_to_mean_contribution(playerMeanContributions, playerMatchSummary)123    dict_update(playerRatings, playerData)124match_contributions(teamMeanContribution, playerMeanContributions, teamRoster)125#result = game_result("13", "16", teamMeanContribution, coefficients, probabilities)126#print result127 128#playerRatings = sorted(playerRatings.items(), key=operator.itemgetter(1))129#print playerRatings130ratings_file = "playerRatings.csv"131positions_file = "playerPositions.csv"132contributions_file = "playerContributions.csv"133player_name_file = "playerNameId.csv"134team_roster = "teamRoster.csv"135mean_starts_contributions_file = "playerStartsMeanContributions.csv"136mean_subs_contributions_file = "playerSubsMeanContributions.csv"137team_mean_contributions_file = "teamMeanContributions.csv"138csvfiles = [ratings_file, positions_file, contributions_file, player_name_file]139fp = open(ratings_file, 'wb')140fp.write("Player_id, Ratings\n")141for player, ratings in playerRatings.iteritems():142    ratings_string = ""143    for rating in ratings:144        ratings_string += "," + str(rating)145    fp.write(str(player) + ratings_string +  "\n")146fp.close()147fp = open(positions_file, 'wb')148fp.write("Player_id, Others, Goalkeeper, Defender, Midfielder, Forward, Substitute\n")149for player, positions in playerPosition.iteritems():150    positions_string = ""151    for position in positions:152        positions_string += "," + str(position)153    fp.write(str(player) + positions_string + "\n")154fp.close()155''' fp = open(contributions_file, 'wb')156# contributions vector is [won_contest, accurate_pass, touch_factor, aerial_won, saves, total_tackle_opp, yellow_card_opp, red_card_opp, goals, assists]157fp.write("Player_id, won_contest, accurate_pass, touch_factor, aerial_won, saves, total_tackle_opp, yellow_card_opp, red_card_opp, goals, assists\n")158for player, contributions in playerContributions.iteritems():159    contributions_string = ""160    for contribution in contributions:161        contributions_string += "," + str(contribution)162    fp.write(str(player) + contributions_string + "\n")163fp.close() '''164fp = open(player_name_file, 'wb')165fp.write("Player_id, Player_name, Player_team1, Appearances1, Player_team2, Appearances2\n")166for player, playerInfo in playerIdNameData.iteritems():167    player_name = unicodedata.normalize("NFKD", playerInfo[0]).encode('ascii', 'ignore')168    player_team_info_string = ""169    for team, appearances in playerInfo[1].iteritems():170        player_team_info_string += "," + str(team) + "," + str(appearances)171    fp.write(str(player) + "," + player_name + player_team_info_string + "\n")172fp.close()173fp = open(contributions_file, 'wb')174fp.write("Player_id, Date, won_contest, accurate_pass, touch_factor, aerial_won, saves, tackles, yellow_card, red_card, goal_factor, assist_factor, shot_factor, cross_factor, tackle_factor, Position, Rating\n")175for player, matchData in playerMatchSummary.iteritems():176    for date, contributions in matchData.iteritems():177        contributions_string_ = ""178        for contribution in contributions:179            contributions_string_ += "," + str(contribution)180        fp.write(str(player) + "," + str(date) + contributions_string_ + "\n") 181fp.close()182fp = open(team_roster, 'wb')183fp.write("Team_id, Player_id, Start_prob, Sub_prob\n")184for team, roster in teamRoster.iteritems():185    for player_id, data in teamRoster[team].iteritems():186        fp.write(str(team) + "," + str(player_id) + "," + str(data[0]) + "," + str(data[1]) + "\n")187fp.close()188fstart = open(mean_starts_contributions_file, 'wb')189fsub = open(mean_subs_contributions_file, 'wb')190fstart.write("Player_id, won_contest, accurate_pass, touch_factor, aerial_won, saves, tackles, yellow_card, red_card, goal_factor, assist_factor, shot_factor, cross_factor, tackle_factor\n")191fsub.write("Player_id, won_contest, accurate_pass, touch_factor, aerial_won, saves, tackles, yellow_card, red_card, goal_factor, assist_factor, shot_factor, cross_factor, tackle_factor\n")192for player, mean_data in playerMeanContributions.iteritems():193    mean_start_contribution_string = ""194    mean_sub_contribution_string = ""195    for contribution in mean_data[0]:196        mean_start_contribution_string += "," + str(contribution)197    for contribution in mean_data[1]:198        mean_sub_contribution_string += "," + str(contribution)199    fstart.write(str(player) + mean_start_contribution_string + "\n")200    fsub.write(str(player)  + mean_sub_contribution_string + "\n")201fstart.close()202fsub.close()203fp = open(team_mean_contributions_file, 'wb')204fp.write("Team_id, won_contest, accurate_pass, touch_factor, aerial_won, saves, total_tackle_opp, yellow_card_opp, red_card_opp\n")205for team, contributions in teamMeanContribution.iteritems():206    contributions_string = ""207    for contribution in contributions:208        contributions_string += "," + str(contribution)209    fp.write(str(team) + contributions_string + "\n")210fp.close()211fp = open("info_file.csv", "wb")212fp.write("Constant, Won_contest, accurate_pass, tackle_opp, aerial_won, yellow_card, red_card\n")213count = 0214for coefs in coefficients:215    if count == 0:216        fp.write(str(coefs))217        count = 1218        continue219    fp.write("," + str(coefs))220fp.write("\n")221fp.write("P(G|S), P(onTarget|shot), P(saveOrBlock|onTarget)\n")222count = 0223for prob in probabilities:224    if count == 0:225        fp.write(str(prob))226        count = 1227        continue228    fp.write("," + str(prob))229fp.write("\n")...

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