{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:black;\n           font-size:110%;\n           font-family:Verdana;\n           letter-spacing:0.5px\">\n\n<p style=\"padding: 10px;\n              color:white;\">\n <h1 style=\"color:white;\"><center>Can The Four Factors Defy The Odds?</center></h1>\n<h2 style=\"color:white;\"><center>By: Fabrice Mulumba</center></h2>\n              \n</p>\n</div>","metadata":{}},{"cell_type":"markdown","source":"![Peaky_Blinders_Horse.png](attachment:f89cd0f2-c532-4123-bf01-485fbe8d79c7.png)","metadata":{},"attachments":{"f89cd0f2-c532-4123-bf01-485fbe8d79c7.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"<center><h3><i>In this report we will be manifesting our inner Tommy Shelby of the Peaky Blinders and become horse fanatics and bookmakers.</i></h3></center>","metadata":{}},{"cell_type":"markdown","source":"# <div style=\"background-color:black; padding: 20px; color: white;\">1). Introduction</div>","metadata":{}},{"cell_type":"markdown","source":"Just as Dean Oliver identified the Four Factors of Basketball Success( Shooting, Turnovers, Rebounding, and Free Throws), Barry Meadow identified the Four Factors of Horse Race Handicapping: **Class**, **Condition**, **Class**, **Circumstances**, **Connections**.\nI will create features for each respective factor. From there I will create an adjusted odds for each horse using these factors and use it to find a expected value bet. I will be comparing the model's performance with the public odds by converting the odds to the probability of victory that it supposedly implies. I will use a logistic regression to create the odds. Logistic Regression is highly interpretable and because of that is the most straightforward model to test the efficacy of the Four Factors.\n","metadata":{}},{"cell_type":"markdown","source":" <center><h2>Data Load</h2></center>","metadata":{}},{"cell_type":"code","source":"import numpy as np \nimport pandas as pd \nfrom datetime import datetime\nimport matplotlib.pyplot as plt\nfrom sklearn import preprocessing\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.model_selection import train_test_split\nfrom sklearn import metrics\nfrom sklearn.metrics import log_loss\n\nfrom numpy import mean\nfrom numpy import std\nfrom sklearn.datasets import make_regression\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.model_selection import RepeatedKFold\nfrom sklearn.feature_selection import RFE\nfrom sklearn.tree import DecisionTreeRegressor\nfrom sklearn.pipeline import Pipeline\n\nimport gc\nimport json\nimport shap\nimport os\nimport math\nimport requests\nimport seaborn as sns\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.status.busy":"2022-11-10T06:26:46.267870Z","iopub.execute_input":"2022-11-10T06:26:46.268234Z","iopub.status.idle":"2022-11-10T06:26:46.348840Z","shell.execute_reply.started":"2022-11-10T06:26:46.268206Z","shell.execute_reply":"2022-11-10T06:26:46.347945Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"nyra_complete_2019_df = pd.read_csv('../input/big-data-derby-2022/nyra_2019_complete.csv', low_memory=False)\nnyra_complete_2019_df.columns =['track_id', 'race_date', 'race_number', 'program_number', 'trakus_index', 'latitude', 'longitude', 'distance_id', 'course_type', 'track_condition', 'run_up_distance', 'race_type', 'post_time', 'purse', 'weight_carried', 'jockey', 'odds', 'position_at_finish']\nnyra_race_table_df = pd.read_csv('../input/big-data-derby-2022/nyra_race_table.csv')\nnyra_start_table_df = pd.read_csv('/kaggle/input/big-data-derby-2022/nyra_start_table.csv', header=None)\nnyra_tracking_table_df = pd.read_csv('../input/big-data-derby-2022/nyra_tracking_table.csv')\nhorse_ids_df = pd.read_csv('../input/big-data-derby-2022-global-horse-ids-and-places/horse_ids.csv')\nhorse_names_df = pd.read_csv('../input/big-data-derby-2022-global-horse-ids-and-places/horse_names.csv')","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:26:46.350213Z","iopub.execute_input":"2022-11-10T06:26:46.351583Z","iopub.status.idle":"2022-11-10T06:26:56.164813Z","shell.execute_reply.started":"2022-11-10T06:26:46.351548Z","shell.execute_reply":"2022-11-10T06:26:56.164011Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"nyra_complete_2019_df = nyra_complete_2019_df.rename(columns={'race_number': 'race', 'position_at_finish': 'finishing_place'})\nnyra_race_table_df = nyra_race_table_df.rename(columns={'race_number': 'race'})","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:26:56.165938Z","iopub.execute_input":"2022-11-10T06:26:56.166179Z","iopub.status.idle":"2022-11-10T06:26:56.566949Z","shell.execute_reply.started":"2022-11-10T06:26:56.166156Z","shell.execute_reply":"2022-11-10T06:26:56.566075Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"start_cols = ['track_id','race_date','race','program_number','weight_carried','jockey','odds','finishing_place']\nnyra_start_table_df.rename({i: col for i, col in enumerate(start_cols)}, axis=1, inplace=True)\nnyra_start_table_df['program_number'] = nyra_start_table_df['program_number'].apply(lambda x: x.strip())\n\nnyra_race_table_df['race_date'] = pd.to_datetime(nyra_race_table_df[\"race_date\"], format='%Y-%m-%d')\nnyra_start_table_df['race_date'] = pd.to_datetime(nyra_start_table_df[\"race_date\"], format='%Y-%m-%d')\n\nmerged_nyra_race_start_df = pd.merge(nyra_race_table_df,nyra_start_table_df,on=['track_id','race_date','race'], how='left')","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:26:56.569029Z","iopub.execute_input":"2022-11-10T06:26:56.569328Z","iopub.status.idle":"2022-11-10T06:26:56.597173Z","shell.execute_reply.started":"2022-11-10T06:26:56.569303Z","shell.execute_reply":"2022-11-10T06:26:56.596506Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"merged_horse_names_df = horse_ids_df.merge(horse_names_df, left_on='horse_id', right_on='horse_id')\nmerged_horse_names_df['program_number'] = merged_horse_names_df['program_number'].apply(lambda x: x.strip())\nmerged_horse_names_df['race_date'] = pd.to_datetime(merged_horse_names_df[\"race_date\"], format='%Y-%m-%d')\nmerged_horse_names_df['winner'] = merged_horse_names_df['finishing_place'].apply(lambda x: x == 1)\nmerged_horse_names_df['winner'] = merged_horse_names_df['winner'].astype(int)\nmerged_horse_names_df['top_three_finish'] = merged_horse_names_df['finishing_place'].apply(lambda x: x < 4)\nmerged_horse_names_df['top_three_finish'] = merged_horse_names_df['top_three_finish'].astype(int)","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:26:56.598375Z","iopub.execute_input":"2022-11-10T06:26:56.599036Z","iopub.status.idle":"2022-11-10T06:26:56.629560Z","shell.execute_reply.started":"2022-11-10T06:26:56.599001Z","shell.execute_reply":"2022-11-10T06:26:56.628702Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<h2>Add horse ID to the tracking data</h2>","metadata":{}},{"cell_type":"code","source":"\nmaster_horse_df = pd.merge(merged_nyra_race_start_df,merged_horse_names_df,on=['track_id','race_date','race','program_number','finishing_place'], how='left')\nmaster_horse_df.head(5)","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:26:56.630918Z","iopub.execute_input":"2022-11-10T06:26:56.631188Z","iopub.status.idle":"2022-11-10T06:26:56.667747Z","shell.execute_reply.started":"2022-11-10T06:26:56.631163Z","shell.execute_reply":"2022-11-10T06:26:56.666955Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#merged_nyra_race_start_2019_df.to_csv('merged_nyra_race_start_2019_df.csv')","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:26:56.668739Z","iopub.execute_input":"2022-11-10T06:26:56.668987Z","iopub.status.idle":"2022-11-10T06:26:56.672576Z","shell.execute_reply.started":"2022-11-10T06:26:56.668963Z","shell.execute_reply":"2022-11-10T06:26:56.671761Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<h2>Add Horse Data From Equibase</h2>","metadata":{}},{"cell_type":"code","source":"# CODE TO CREATE HORSE RANK DB\n#appended_horse_rank_list = []\n#appended_horse_rank_df = []\n\n# for i in range(505):\n#     pageCount = i+1\n#     url = f'https://www.equibase.com/Data.cfm/Stats/Horse/Year/Page?year=2018&page={pageCount}&sort=EARNINGS&dir=A&list=N&category=A&attribute_total=1024&set=full&race_breed_type=TB&_=1667399494394'\n#     horse_request = requests.get(url)\n#     horse_request_json = horse_request.json()\n#     horse_request_json['stats'] # Name of the stats keys \n#     #horse_data_df = pd.DataFrame(horse_request_json['stats'])\n#     horse_rank_list = horse_request_json['stats']\n#     appended_horse_rank_list += horse_rank_list\n# appended_horse_rank_df = pd.DataFrame.from_records(appended_horse_rank_list)","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:26:56.673693Z","iopub.execute_input":"2022-11-10T06:26:56.674180Z","iopub.status.idle":"2022-11-10T06:26:56.682565Z","shell.execute_reply.started":"2022-11-10T06:26:56.674146Z","shell.execute_reply":"2022-11-10T06:26:56.681749Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#appended_horse_rank_df.to_csv('2018_Equibase_Horse_Rank.csv')","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:26:56.683776Z","iopub.execute_input":"2022-11-10T06:26:56.684237Z","iopub.status.idle":"2022-11-10T06:26:56.694892Z","shell.execute_reply.started":"2022-11-10T06:26:56.684205Z","shell.execute_reply":"2022-11-10T06:26:56.693945Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#appended_horse_rank_df.tail(20)","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:26:56.700349Z","iopub.execute_input":"2022-11-10T06:26:56.700597Z","iopub.status.idle":"2022-11-10T06:26:56.705956Z","shell.execute_reply.started":"2022-11-10T06:26:56.700573Z","shell.execute_reply":"2022-11-10T06:26:56.704974Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"horse_rank_2018_df = pd.read_csv('../input/2018-equibase-horse-rank/2018_Equibase_Horse_Rank.csv')\nhorse_rank_2018_df = horse_rank_2018_df.rename(columns={'horseName': 'horse_name', 'rank': 'horse_rank_2018','speedFigure': 'speedFigure_2018',  'win': 'horse_win_2018', 'winPercentage': 'horse_winPercentage_2018', 'place': 'horse_place_2018', 'earnings': 'horse_earnings_2018', 'starts': 'horse_starts_2018', 'perStart': 'horse_perStart_2018', 'topThreePercentage': 'horse_topThreePercentage_2018', 'topThree': 'horse_topThree_2018', 'show': 'horse_show_2018'})\nhorse_rank_2018_df['horse_win_volume_2018'] = horse_rank_2018_df['horse_win_2018'] * horse_rank_2018_df['horse_winPercentage_2018']\n","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:26:56.707306Z","iopub.execute_input":"2022-11-10T06:26:56.707721Z","iopub.status.idle":"2022-11-10T06:26:56.801994Z","shell.execute_reply.started":"2022-11-10T06:26:56.707697Z","shell.execute_reply":"2022-11-10T06:26:56.801185Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"master_horse_df = pd.merge(master_horse_df, horse_rank_2018_df, on='horse_name', how='left')","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:26:56.802988Z","iopub.execute_input":"2022-11-10T06:26:56.803327Z","iopub.status.idle":"2022-11-10T06:26:56.842494Z","shell.execute_reply.started":"2022-11-10T06:26:56.803295Z","shell.execute_reply":"2022-11-10T06:26:56.841564Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"master_horse_df.head(20)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:26:56.843768Z","iopub.execute_input":"2022-11-10T06:26:56.844006Z","iopub.status.idle":"2022-11-10T06:26:56.878600Z","shell.execute_reply.started":"2022-11-10T06:26:56.843982Z","shell.execute_reply":"2022-11-10T06:26:56.877787Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# <div style=\"background-color:black; padding: 20px; color: white;\">2). The Four Factors</div>","metadata":{}},{"cell_type":"markdown","source":"# - I. CLASS","metadata":{}},{"cell_type":"markdown","source":"<i>\"There are four primary horse racing classes: claiming races, maiden races, allowance_class races, and stakes races. Under the umbrella of stakes, races are restricted and graded stakes races.</i>\n\n<i>Graded stakes races are further broken down into Grade I, Grade II, and Grade III. A maiden claiming race is the lowest class of horse racing, and Grade I is the highest.</i>\n\n<i>Horse racing classes are used to categorize horses based on their experience and skill levels. This system pits horses at similar stages of their careers against each other to make the races competitive.\"</i> - [Horse Racing Sense Website](https://horseracingsense.com/what-are-different-horse-racing-classes-tips/)\n\n\nClass droppers outperform class risers on average because they are generally facing worse competition than before, while a class riser is doing the opposite.\n\nPurse, power ratings, and speed figures, are also considered class features.","metadata":{}},{"cell_type":"markdown","source":"Steps:\n\n- Add a rank for each class: **STK - Stakes, WCL - Waiver Claiming, WMC - Waiver Maiden Claiming, SST - Starter Stakes, SHP - Starter Handicap, CLM - Claiming, STR - Starter allowance_class, AOC - allowance_class Optionl Claimer, SOC - Starter Optional Claimer, MCL - Maiden Claiming, ALW - allowance_class, MSW - Maiden Special Weight.**\n- For each race mark if the horse is a class riser, dropper, or same\n- Class value column will hold possible values of: 1 (dropper), 0 (same), -1 (riser)","metadata":{}},{"cell_type":"markdown","source":"<h2> Step 1: Add a Rank For Each Class </h2>\nhttps://101horseracing.com/racing/race-classifications/\n\nhttps://www.equibase.com/newfan/codes.cfm","metadata":{}},{"cell_type":"code","source":"race_class = []\nrace_level = []\nmaiden_class = ['MCL', 'MSW']\nclaiming_class = ['CLM', 'WMC', 'SOC', 'WCL']\nallowance_class = ['ALW', 'AOC', 'SHP', 'STR']\nstakes_class = ['STK', 'SST']\n\nfor race_type in master_horse_df[\"race_type\"]:\n    if race_type in maiden_class:\n        race_class.append(1)\n        race_level.append(1)\n    elif race_type in claiming_class:\n        race_class.append(2)\n        race_level.append(2)\n    elif race_type in allowance_class:\n        race_level.append(3)\n        if race_type == 'SHP':\n            race_class.append(3)\n        elif race_type == 'STR':\n            race_class.append(3)\n        elif race_type == 'AOC':\n            race_class.append(3.1)\n        elif race_type == 'ALW':\n            race_class.append(3.2)\n        else:\n            race_class.append(3)\n    elif race_type in stakes_class:\n        race_level.append(4)\n        race_class.append(4)\n    else:\n        race_level.append(\"N/A\")\n        race_class.append(\"N/A\")\n        \nmaster_horse_df[\"race_class\"] = race_class\nmaster_horse_df[\"race_level\"] = race_level ","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:26:56.879491Z","iopub.execute_input":"2022-11-10T06:26:56.879719Z","iopub.status.idle":"2022-11-10T06:26:56.902860Z","shell.execute_reply.started":"2022-11-10T06:26:56.879696Z","shell.execute_reply":"2022-11-10T06:26:56.901972Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"master_horse_df.head(5)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:26:56.904511Z","iopub.execute_input":"2022-11-10T06:26:56.905848Z","iopub.status.idle":"2022-11-10T06:26:56.929342Z","shell.execute_reply.started":"2022-11-10T06:26:56.905803Z","shell.execute_reply":"2022-11-10T06:26:56.928298Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<h2> Step 3: Class value column will hold possible values of: 1 (dropper), 0 (same), -1 (riser)</h2>","metadata":{}},{"cell_type":"code","source":"horse_ids = master_horse_df['horse_id'].unique()\nhorse_ids = sorted(horse_ids)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:26:56.930981Z","iopub.execute_input":"2022-11-10T06:26:56.931354Z","iopub.status.idle":"2022-11-10T06:26:56.937050Z","shell.execute_reply.started":"2022-11-10T06:26:56.931320Z","shell.execute_reply":"2022-11-10T06:26:56.936227Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<h2> Find number of rows with a class value </h2>","metadata":{}},{"cell_type":"code","source":"row_count = len(master_horse_df['race_class'])\nrow_count","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:26:56.938415Z","iopub.execute_input":"2022-11-10T06:26:56.939217Z","iopub.status.idle":"2022-11-10T06:26:56.946825Z","shell.execute_reply.started":"2022-11-10T06:26:56.939186Z","shell.execute_reply":"2022-11-10T06:26:56.945942Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"appended_data = []\nfor horse_id in horse_ids:\n    class_status = []\n    class_value = []\n    filtered_df = master_horse_df.loc[master_horse_df['horse_id'] == horse_id].sort_values('race_date')\n    race_class_values = filtered_df['race_class'].values\n    for index, race_class in enumerate(race_class_values):\n        if index == 0:\n            class_status.append('same')\n            class_value.append(0)\n        elif race_class_values[index - 1]  > race_class_values[index]:\n            class_status.append('dropper')\n            class_value.append(1)\n        elif race_class_values[index - 1]   < race_class_values[index]:\n            class_status.append('riser')\n            class_value.append(-1)\n        else:\n            class_status.append('same')\n            class_value.append(0)\n    filtered_df[\"class_status\"] = class_status\n    filtered_df[\"class_value\"] = class_value\n    appended_data.append(filtered_df)\nappended_data = pd.concat(appended_data)\nappended_data.head(5)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:26:56.947949Z","iopub.execute_input":"2022-11-10T06:26:56.948222Z","iopub.status.idle":"2022-11-10T06:27:08.290361Z","shell.execute_reply.started":"2022-11-10T06:26:56.948196Z","shell.execute_reply":"2022-11-10T06:27:08.289489Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"master_horse_df = appended_data","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:08.291639Z","iopub.execute_input":"2022-11-10T06:27:08.291917Z","iopub.status.idle":"2022-11-10T06:27:08.295880Z","shell.execute_reply.started":"2022-11-10T06:27:08.291892Z","shell.execute_reply":"2022-11-10T06:27:08.295290Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"appended_data = []\nfor horse_id in horse_ids:\n    purse_status = []\n    purse_class_value = []\n    purse_differential = []\n    filtered_df = master_horse_df.loc[master_horse_df['horse_id'] == horse_id].sort_values('race_date')\n    race_class_values = filtered_df['purse'].values\n    for index, race_class in enumerate(race_class_values):\n        if index == 0:\n            purse_status.append('same')\n            purse_class_value.append(0)\n            purse_differential.append(0)\n        elif race_class_values[index - 1]  > race_class_values[index]:\n            purse_status.append('dropper')\n            purse_class_value.append(1)\n            purse_differential.append(race_class_values[index - 1] - race_class_values[index])\n        elif race_class_values[index - 1]   < race_class_values[index]:\n            purse_status.append('riser')\n            purse_class_value.append(-1)\n            purse_differential.append(race_class_values[index - 1] - race_class_values[index])\n        else:\n            purse_status.append('same')\n            purse_class_value.append(0)\n            purse_differential.append(0)\n    filtered_df[\"purse_status\"] = purse_status\n    filtered_df[\"purse_class_value\"] = purse_class_value\n    filtered_df[\"purse_differential\"] = purse_differential\n    appended_data.append(filtered_df)\nappended_data = pd.concat(appended_data)\nappended_data.head(5)","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:27:08.296806Z","iopub.execute_input":"2022-11-10T06:27:08.297603Z","iopub.status.idle":"2022-11-10T06:27:21.867163Z","shell.execute_reply.started":"2022-11-10T06:27:08.297575Z","shell.execute_reply":"2022-11-10T06:27:21.866269Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"master_horse_df = appended_data\nmaster_horse_df['net_class_value'] = master_horse_df['class_value'] + master_horse_df['purse_class_value']\nmaster_horse_df.head(5)","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:27:21.868447Z","iopub.execute_input":"2022-11-10T06:27:21.869466Z","iopub.status.idle":"2022-11-10T06:27:21.893184Z","shell.execute_reply.started":"2022-11-10T06:27:21.869431Z","shell.execute_reply":"2022-11-10T06:27:21.892598Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<center>Our class values include the <b>2018 horse rank data</b>, <b>2019 race class dropper/riser status</b>, and <b>purse dropper/riser status.</b></center>","metadata":{}},{"cell_type":"markdown","source":"# - II. CONDITION","metadata":{}},{"cell_type":"markdown","source":"\"<i>A horse’s condition can only be measured against its own intrinsic ability. Before worrying about how a horse may fit into a field, ask how likely he is to run his usual race, better than usual, or worse than usual. This question can be answered by an analysis of form.</i>\n\n<i>For a horse to be considered in form:</i>\n\n<i>- The horse finished within 3 lengths of the winner last out, in his regular class.</i>\n\n<i>- The horse ran at or near the front of the pack until at least the stretch, or the horse passed several rivals in the stretch</i>\n\n<i>- The horse has been working regularly, with no suspicious breaks.</i>\n\n<i>- The horse shows no gaps in his racing schedule. If he usually races every three weeks, he does not suddenly show an eight-week layoff</i>\n\n<i>- The horse was overmatched last time but ran his usual number</i>\" - [The Skeptical Handicapper By: Barry Meadow](https://www.amazon.com/Skeptical-Handicapper-Using-Brains-Racetrack-ebook/dp/B07NS6N5YZ) **page 193**\n","metadata":{}},{"cell_type":"markdown","source":"Compare race date for each horse, if the gap/layoff is more than 180 day then we consider the horse out of form/condition (-1) with a big layoff, if the gap/layoff is less than 180 days but more than 8 weeks then we consider the horse out of form/condition as well (0) with an above average layoff, if the gap/layoff is less than 8 weeks it is in form with a normal layoff (1)\n\n\"*We recommend that most horses need 8 weeks\nrest following a 16 to 20 week campaign. Even if this can’t\nbe achieved the good news is that even one extra week\nof rest in addition to that which a horse normally gets,\nhas substantial benefits.*\" - [\"Time off racing helps horses race\nfor longer and avoid injuries\"](https://www.racingvictoria.com.au/the-horse/veterinary-care/-/media/281434f1899d4e4db0c093432d9f5efc.ashx)\n\n\nI read that a horse in good form has a short turnaround but reading about the benefits of longer breaks (within reason) lead to me considering a race within 8 weeks as good form.\n\n\"*The horses most likely to make big forward moves are those who are lightly raced.*\" - [The Skeptical Handicapper By: Barry Meadow](https://www.amazon.com/Skeptical-Handicapper-Using-Brains-Racetrack-ebook/dp/B07NS6N5YZ) **page 164**\n","metadata":{}},{"cell_type":"code","source":"def date_difference(date_1, date_2):\n    start = date_1\n    end = date_2\n    diff = end - start\n    x = np.timedelta64(diff, 'ns')\n    days = x.astype('timedelta64[D]')\n    days = days / np.timedelta64(1, 'D')\n    return days","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:21.894198Z","iopub.execute_input":"2022-11-10T06:27:21.894607Z","iopub.status.idle":"2022-11-10T06:27:21.898856Z","shell.execute_reply.started":"2022-11-10T06:27:21.894582Z","shell.execute_reply":"2022-11-10T06:27:21.898066Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"appended_condition_data = []\nfor horse_id in horse_ids:\n    condition_status = []\n    condition_value = []\n    layoff_gap = []\n    filtered_df = master_horse_df.loc[master_horse_df['horse_id'] == horse_id].sort_values('race_date')\n    race_date_values = filtered_df['race_date'].values\n    \n# get the difference between two dates as timedelta object\n    for index, race_class in enumerate(race_date_values):\n        if index == 0:\n            condition_status.append('normal layoff')\n            condition_value.append(1)\n            layoff_gap.append(14)\n        elif date_difference(race_date_values[index - 1], race_date_values[index]) > 180:\n            difference_days = date_difference(race_date_values[index - 1], race_date_values[index]) \n            condition_status.append('big layoff')\n            condition_value.append(-1)\n            layoff_gap.append(difference_days)\n        elif date_difference(race_date_values[index - 1], race_date_values[index]) > 56:\n            difference_days = date_difference(race_date_values[index - 1], race_date_values[index]) \n            condition_status.append('above average layoff')\n            condition_value.append(0)\n            layoff_gap.append(difference_days)\n        else:\n            difference_days = date_difference(race_date_values[index - 1], race_date_values[index]) \n            condition_status.append('normal layoff')\n            condition_value.append(1)\n            layoff_gap.append(difference_days)\n    filtered_df[\"condition_status\"] = condition_status\n    filtered_df[\"condition_value\"] = condition_value\n    filtered_df[\"layoff_gap\"] = layoff_gap\n    appended_condition_data.append(filtered_df)\nappended_condition_data = pd.concat(appended_condition_data)\nappended_condition_data.head(5)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:21.900544Z","iopub.execute_input":"2022-11-10T06:27:21.900901Z","iopub.status.idle":"2022-11-10T06:27:36.083192Z","shell.execute_reply.started":"2022-11-10T06:27:21.900870Z","shell.execute_reply":"2022-11-10T06:27:36.082238Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"master_horse_df = appended_condition_data","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:36.084491Z","iopub.execute_input":"2022-11-10T06:27:36.084758Z","iopub.status.idle":"2022-11-10T06:27:36.090001Z","shell.execute_reply.started":"2022-11-10T06:27:36.084733Z","shell.execute_reply":"2022-11-10T06:27:36.088775Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# - III. CIRCUMSTANCES","metadata":{}},{"cell_type":"markdown","source":"\"<i>Every horse’s circumstances includes:</i>\n\n<i>- Is the horse adding or subtracting blinkers?</i>\n\n<i>- Is the horse adding or subtracting front wraps?</i>\n\n<i>- What weight is the horse carrying?</i>\n\n<i>- Is the horse switching surfaces from his last race?</i>\n\n<i>- Has the horse been recently gelded?</i>\" - [The Skeptical Handicapper By: Barry Meadow](https://www.amazon.com/Skeptical-Handicapper-Using-Brains-Racetrack-ebook/dp/B07NS6N5YZ)","metadata":{}},{"cell_type":"markdown","source":"**Seeing increased weight as a positive circumstance may seem counterintuitive but remember the implications: a horse's increased weight can be attributed to age, form, or any other discrepancy perceived as an advantage. However, this leads to an interesting problem that has had me going back and forth because increasing weight on a horse literally slows it down. So in a vacuum I believe increased weight should be seen as bad circumstance.**","metadata":{}},{"cell_type":"markdown","source":"<h2> Step 1: Add weight change to the dataframe </h2>","metadata":{}},{"cell_type":"code","source":"# ## WEIGHT CIRCUMSTANCE\nappended_circumstances_data = []\nfor horse_id in horse_ids:\n    weight_status = []\n    weight_circumstances_value = []\n    filtered_df = master_horse_df.loc[master_horse_df['horse_id'] == horse_id].sort_values('race_date')\n    horse_circumstances_values = filtered_df['weight_carried'].values\n# get the difference between two dates as timedelta object\n\n    \n# get the difference between two dates as timedelta object\n    for index, race_class in enumerate(horse_circumstances_values):\n        if index == 0:\n            weight_status.append('same circumstances')\n            weight_circumstances_value.append(0)\n        elif horse_circumstances_values[index - 1] < horse_circumstances_values[index]:\n            weight_status.append('worse circumstances')\n            weight_circumstances_value.append(-1)\n        elif horse_circumstances_values[index - 1] > horse_circumstances_values[index]:\n            weight_status.append('better circumstances')\n            weight_circumstances_value.append(1)\n        else:\n            weight_status.append('same circumstances')\n            weight_circumstances_value.append(0)\n    filtered_df[\"weight_status\"] = weight_status\n    filtered_df[\"circumstances_value\"] = weight_circumstances_value\n    appended_circumstances_data.append(filtered_df)\nappended_circumstances_data = pd.concat(appended_circumstances_data)\nappended_circumstances_data.head(5)\n","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:27:36.091443Z","iopub.execute_input":"2022-11-10T06:27:36.092076Z","iopub.status.idle":"2022-11-10T06:27:49.221997Z","shell.execute_reply.started":"2022-11-10T06:27:36.092045Z","shell.execute_reply":"2022-11-10T06:27:49.221139Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"master_horse_df = appended_circumstances_data","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:49.223063Z","iopub.execute_input":"2022-11-10T06:27:49.223368Z","iopub.status.idle":"2022-11-10T06:27:49.227138Z","shell.execute_reply.started":"2022-11-10T06:27:49.223342Z","shell.execute_reply":"2022-11-10T06:27:49.226369Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#merged_nyra_race_start_2019_df.to_csv('merged_nyra_race_start_2019_df.csv')\nmaster_horse_df['four_factor'] = master_horse_df['class_value'] + master_horse_df['condition_value'] + master_horse_df['circumstances_value']\nmaster_horse_df['net_condition_value'] = master_horse_df['condition_value'] + master_horse_df['circumstances_value']\n#master_horse_df.to_csv('master_horse_df.csv')","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:27:49.228293Z","iopub.execute_input":"2022-11-10T06:27:49.228545Z","iopub.status.idle":"2022-11-10T06:27:49.240287Z","shell.execute_reply.started":"2022-11-10T06:27:49.228522Z","shell.execute_reply":"2022-11-10T06:27:49.239400Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# - IV. CONNECTIONS","metadata":{}},{"cell_type":"markdown","source":"Connections come down to trainers and jockeys. I lack trainer data but will use the 2018 Jockey Data for this 2019 dataset.\nhttps://www.equibase.com/stats/View.cfm?tf=year&tb=jockey","metadata":{}},{"cell_type":"markdown","source":"<h2> Step 1: Create a dataframe of the Equibase 2018 best jockeys list</h2>","metadata":{}},{"cell_type":"code","source":"# appended_jockey_rank_list = []\n# appended_jockey_rank_df = []\n\n# for i in range(15):\n#     pageCount = i+1\n#     url = f'https://www.equibase.com/Data.cfm/Stats/Jockey/Year/Page?year=2018&list=N&sort=EARNINGS&dir=A&page={pageCount}&set=full&attribute_total=1024&race_breed_type=TB&_=1666931895044'\n#     jockey_request = requests.get(url)\n#     jockey_request_json = jockey_request.json()\n#     jockey_request_json['stats'] # Name of the stats keys \n#     #horse_data_df = pd.DataFrame(horse_request_json['stats'])\n#     jockey_rank_list = jockey_request_json['stats']\n#     appended_jockey_rank_list += jockey_rank_list\n# appended_jockey_rank_df = pd.DataFrame.from_records(appended_jockey_rank_list)","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:27:49.248904Z","iopub.execute_input":"2022-11-10T06:27:49.249158Z","iopub.status.idle":"2022-11-10T06:27:49.252648Z","shell.execute_reply.started":"2022-11-10T06:27:49.249134Z","shell.execute_reply":"2022-11-10T06:27:49.252046Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"appended_jockey_rank_df = pd.read_csv('../input/2018-equibase-jockey-data/2018_equibase_jockey_data.csv')\nappended_jockey_rank_df = appended_jockey_rank_df.rename(columns={'jockeyName': 'jockey', 'starts': 'jockey_starts_2018', 'rank': 'jockey_rank_2018', 'win': 'jockey_win_2018', 'winPercentage': 'jockey_winPercentage_2018', 'topThreePercentage': 'jockey_topThreePercentage_2018', 'topThree': 'jockey_top_three_finish_2018'})\nappended_jockey_rank_df['jockey_win_volume_2018'] = appended_jockey_rank_df['jockey_win_2018'] * appended_jockey_rank_df['jockey_winPercentage_2018']\nappended_jockey_rank_df['jockey_topThree_volume_2018'] = appended_jockey_rank_df['jockey_top_three_finish_2018'] * appended_jockey_rank_df['jockey_topThreePercentage_2018']\n\nappended_jockey_rank_df.to_csv('2018_equibase_jockey_data.csv')\n","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:49.253458Z","iopub.execute_input":"2022-11-10T06:27:49.254198Z","iopub.status.idle":"2022-11-10T06:27:49.287330Z","shell.execute_reply.started":"2022-11-10T06:27:49.254163Z","shell.execute_reply":"2022-11-10T06:27:49.286424Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"appended_jockey_rank_df.head(5)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:49.288358Z","iopub.execute_input":"2022-11-10T06:27:49.288625Z","iopub.status.idle":"2022-11-10T06:27:49.303377Z","shell.execute_reply.started":"2022-11-10T06:27:49.288601Z","shell.execute_reply":"2022-11-10T06:27:49.302458Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":" <h2>Step 2: Add a Jockey Rank Column, Total Earnings, Per Start Earnings, Win %, and Top 3% column to the Master Dataframe</h2>","metadata":{}},{"cell_type":"code","source":"master_horse_df = pd.merge(master_horse_df, appended_jockey_rank_df, on='jockey', how='left')","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:27:49.304808Z","iopub.execute_input":"2022-11-10T06:27:49.305154Z","iopub.status.idle":"2022-11-10T06:27:49.331116Z","shell.execute_reply.started":"2022-11-10T06:27:49.305120Z","shell.execute_reply":"2022-11-10T06:27:49.330166Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"master_horse_df.tail(5)","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:27:49.332240Z","iopub.execute_input":"2022-11-10T06:27:49.332510Z","iopub.status.idle":"2022-11-10T06:27:49.355660Z","shell.execute_reply.started":"2022-11-10T06:27:49.332487Z","shell.execute_reply":"2022-11-10T06:27:49.354803Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"master_horse_df.to_csv('master_horse_df.csv')","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:27:49.356942Z","iopub.execute_input":"2022-11-10T06:27:49.357574Z","iopub.status.idle":"2022-11-10T06:27:49.771382Z","shell.execute_reply.started":"2022-11-10T06:27:49.357531Z","shell.execute_reply":"2022-11-10T06:27:49.770304Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"master_horse_df.columns","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.status.busy":"2022-11-10T06:27:49.772470Z","iopub.execute_input":"2022-11-10T06:27:49.772743Z","iopub.status.idle":"2022-11-10T06:27:49.779974Z","shell.execute_reply.started":"2022-11-10T06:27:49.772718Z","shell.execute_reply":"2022-11-10T06:27:49.779083Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"master_horse_df_corr = master_horse_df.corr()\nmaster_horse_df_corr['winner'].sort_values(ascending=True)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:49.781088Z","iopub.execute_input":"2022-11-10T06:27:49.781383Z","iopub.status.idle":"2022-11-10T06:27:49.844697Z","shell.execute_reply.started":"2022-11-10T06:27:49.781357Z","shell.execute_reply":"2022-11-10T06:27:49.843882Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"master_horse_df_corr['odds'].sort_values(ascending=True)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:49.845766Z","iopub.execute_input":"2022-11-10T06:27:49.846395Z","iopub.status.idle":"2022-11-10T06:27:49.854682Z","shell.execute_reply.started":"2022-11-10T06:27:49.846368Z","shell.execute_reply":"2022-11-10T06:27:49.853627Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<h2> Step 3: Create Connections Value </h2>","metadata":{}},{"cell_type":"markdown","source":"The Connection Value with the strongest correlation with 2019 **Winner** appears to be 2018 Jockey **earnings** and the 2018 Jockey **win_volume**. 2018 Jockey **earnings** has the strongest correlation with 2019 **odds** as well. Then it is 2018 Jockey **earnings per start** and 2018 Jockey **win_volume**.","metadata":{}},{"cell_type":"markdown","source":"\n# <div style=\"background-color:black; padding: 20px; color: white;\">3). Selected Features</div>\n\n**Class:** *speedFigure_2018*, *purse_class_value*, *horse_topThreePercentage_2018*, *horse_topThree_2018*, *horse_starts_2018*, *horse_win_2018*, *horse_winPercentage_2018*\n\n**Condition:** *condition_value*, *layoff_gap*\n\n**Circumstances:** *circumstances_value*, *weight_carried*\n\n**Connections:** *jockey_rank_2018*, *jockey_win_2018*, *jockey_winPercentage_2018*, *jockey_topThreePercentage_2018*, *jockey_top_three_finish_2018*\n\n\n","metadata":{}},{"cell_type":"markdown","source":"<h2>FEATURE ENGINEERING</h2>\n\n","metadata":{}},{"cell_type":"markdown","source":"<h2>Remove data with unknown jockeys and horses from the prior year</h2>","metadata":{}},{"cell_type":"code","source":"master_horse_df=master_horse_df.dropna(subset=['jockey_win_2018','jockey_starts_2018', 'horse_win_volume_2018'])","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:49.855981Z","iopub.execute_input":"2022-11-10T06:27:49.856339Z","iopub.status.idle":"2022-11-10T06:27:49.871403Z","shell.execute_reply.started":"2022-11-10T06:27:49.856305Z","shell.execute_reply":"2022-11-10T06:27:49.870325Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<h2>Get the number of horses in the model</h2>","metadata":{}},{"cell_type":"code","source":"number_of_horses_list = master_horse_df['horse_id'].unique()\nlen(number_of_horses_list)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:49.872858Z","iopub.execute_input":"2022-11-10T06:27:49.873209Z","iopub.status.idle":"2022-11-10T06:27:49.880241Z","shell.execute_reply.started":"2022-11-10T06:27:49.873175Z","shell.execute_reply":"2022-11-10T06:27:49.879416Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# CODE TO CREATE HORSE RANK DB\n#appended_horse_rank_list = []\n#appended_horse_rank_df = []\n\n# for i in range(505):\n#     pageCount = i+1\n#     url = f'https://www.equibase.com/Data.cfm/Stats/Horse/Year/Page?year=2018&page={pageCount}&sort=EARNINGS&dir=A&list=N&category=A&attribute_total=1024&set=full&race_breed_type=TB&_=1667399494394'\n#     horse_request = requests.get(url)\n#     horse_request_json = horse_request.json()\n#     horse_request_json['stats'] # Name of the stats keys \n#     #horse_data_df = pd.DataFrame(horse_request_json['stats'])\n#     horse_rank_list = horse_request_json['stats']\n#     appended_horse_rank_list += horse_rank_list\n# appended_horse_rank_df = pd.DataFrame.from_records(appended_horse_rank_list)","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:27:49.881443Z","iopub.execute_input":"2022-11-10T06:27:49.881669Z","iopub.status.idle":"2022-11-10T06:27:49.888635Z","shell.execute_reply.started":"2022-11-10T06:27:49.881647Z","shell.execute_reply":"2022-11-10T06:27:49.887921Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#appended_horse_rank_df.to_csv('2018_Equibase_Horse_Rank.csv')","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:27:49.889578Z","iopub.execute_input":"2022-11-10T06:27:49.889795Z","iopub.status.idle":"2022-11-10T06:27:49.897359Z","shell.execute_reply.started":"2022-11-10T06:27:49.889773Z","shell.execute_reply":"2022-11-10T06:27:49.896488Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#horse_request_json = horse_request.json()\n#horse_request_json.keys()\n#horse_request_json['stats'] # Name of the stats keys \n#horse_data_df = pd.DataFrame(horse_request_json['stats'])\n","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:27:49.898763Z","iopub.execute_input":"2022-11-10T06:27:49.899313Z","iopub.status.idle":"2022-11-10T06:27:49.907323Z","shell.execute_reply.started":"2022-11-10T06:27:49.899285Z","shell.execute_reply":"2022-11-10T06:27:49.906386Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#horse_rank_2018_df = pd.read_csv('../input/2018-equibase-horse-rank/2018_Equibase_Horse_Rank.csv')\n#horse_rank_2018_df = horse_rank_2018_df.rename(columns={'horseName': 'horse_name', 'rank': 'horse_rank_2018', 'win': 'horse_win_2018', 'winPercentage': 'horse_winPercentage_2018', 'place': 'horse_place_2018'})\n","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:27:49.908482Z","iopub.execute_input":"2022-11-10T06:27:49.909144Z","iopub.status.idle":"2022-11-10T06:27:49.916434Z","shell.execute_reply.started":"2022-11-10T06:27:49.909119Z","shell.execute_reply":"2022-11-10T06:27:49.915443Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"stakes_class_df = master_horse_df.loc[master_horse_df['race_level'] == 4]\nallowance_class_df = master_horse_df.loc[master_horse_df['race_level'] == 3]\nclaiming_class_df = master_horse_df.loc[master_horse_df['race_level'] == 2]\nmaiden_class_df = master_horse_df.loc[master_horse_df['race_level'] == 1]\n","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:49.917601Z","iopub.execute_input":"2022-11-10T06:27:49.917845Z","iopub.status.idle":"2022-11-10T06:27:49.930392Z","shell.execute_reply.started":"2022-11-10T06:27:49.917822Z","shell.execute_reply":"2022-11-10T06:27:49.929592Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"master_horse_df_corr = master_horse_df.corr()\nmaster_horse_df_corr['odds'].sort_values(ascending=True)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:49.931670Z","iopub.execute_input":"2022-11-10T06:27:49.931990Z","iopub.status.idle":"2022-11-10T06:27:49.948996Z","shell.execute_reply.started":"2022-11-10T06:27:49.931958Z","shell.execute_reply":"2022-11-10T06:27:49.948285Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"master_horse_df_corr['winner'].sort_values(ascending=True)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:49.949917Z","iopub.execute_input":"2022-11-10T06:27:49.950332Z","iopub.status.idle":"2022-11-10T06:27:49.957466Z","shell.execute_reply.started":"2022-11-10T06:27:49.950307Z","shell.execute_reply":"2022-11-10T06:27:49.956710Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<h2>FEATURES</h2>","metadata":{}},{"cell_type":"code","source":"master_horse_df.shape","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:49.958485Z","iopub.execute_input":"2022-11-10T06:27:49.959204Z","iopub.status.idle":"2022-11-10T06:27:49.967277Z","shell.execute_reply.started":"2022-11-10T06:27:49.959180Z","shell.execute_reply":"2022-11-10T06:27:49.966467Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Model makes use of 977 horses and 1858 rows of race data after removal of null data","metadata":{}},{"cell_type":"markdown","source":"<h2>All Classes</h2>","metadata":{}},{"cell_type":"markdown","source":"<h2> Recursive Feature Elimination </h2>","metadata":{}},{"cell_type":"code","source":"model_df_all_classes = master_horse_df\n#model_df = master_horse_df.loc[master_horse_df['race_level'] < 4]\n#model_df = master_horse_df.loc[master_horse_df['race_level'] > 2]\nmodel_df_allowance_class = master_horse_df.loc[master_horse_df['race_level'] == 3]\n#test_df = model_df\n#test_df.shape\n#model_df = model_df.reset_index()\nmodel_df_all_classes.reset_index(drop=True, inplace=True)\nmodel_df_allowance_class.reset_index(drop=True, inplace=True)\n","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:49.968704Z","iopub.execute_input":"2022-11-10T06:27:49.969063Z","iopub.status.idle":"2022-11-10T06:27:49.976562Z","shell.execute_reply.started":"2022-11-10T06:27:49.969024Z","shell.execute_reply":"2022-11-10T06:27:49.975745Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"four_factor_model_df = model_df_allowance_class[['winner','jockey_rank_2018', 'horse_rank_2018', 'horse_starts_2018', 'layoff_gap', 'circumstances_value', 'net_condition_value','condition_value', 'four_factor', 'horse_show_2018', 'horse_place_2018', 'class_value', 'purse_class_value', 'net_class_value', 'horse_topThree_2018', 'weight_carried', 'horse_win_2018', 'purse_differential', 'horse_winPercentage_2018', 'horse_win_volume_2018', 'speedFigure_2018', 'horse_topThreePercentage_2018', 'jockey_topThreePercentage_2018', 'horse_perStart_2018', 'horse_earnings_2018', 'show', 'jockey_winPercentage_2018', 'jockey_starts_2018', 'place', 'jockey_topThree_volume_2018', 'jockey_top_three_finish_2018', 'jockey_win_2018', 'jockey_win_volume_2018', 'perStart', 'earnings']].copy()\n#model_df = model_df.reset_index()\nfour_factor_model_df.reset_index(drop=True, inplace=True)\nfour_factor_model_df_corr = four_factor_model_df.corr()\nfour_factor_model_df_corr['winner'].sort_values(ascending=True)\n","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:49.977598Z","iopub.execute_input":"2022-11-10T06:27:49.978163Z","iopub.status.idle":"2022-11-10T06:27:49.996007Z","shell.execute_reply.started":"2022-11-10T06:27:49.978128Z","shell.execute_reply":"2022-11-10T06:27:49.995430Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"four_factor_model_df.groupby(\"winner\")[\"horse_winPercentage_2018\"].mean()\n","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:49.996849Z","iopub.execute_input":"2022-11-10T06:27:49.997524Z","iopub.status.idle":"2022-11-10T06:27:50.004048Z","shell.execute_reply.started":"2022-11-10T06:27:49.997499Z","shell.execute_reply":"2022-11-10T06:27:50.003280Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"four_factor_model_df.groupby(\"winner\")[\"jockey_winPercentage_2018\"].mean()\n","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:50.005225Z","iopub.execute_input":"2022-11-10T06:27:50.005491Z","iopub.status.idle":"2022-11-10T06:27:50.016240Z","shell.execute_reply.started":"2022-11-10T06:27:50.005468Z","shell.execute_reply":"2022-11-10T06:27:50.015665Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"four_factor_model_df.groupby(\"winner\")[\"speedFigure_2018\"].mean()\n","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:50.017132Z","iopub.execute_input":"2022-11-10T06:27:50.017507Z","iopub.status.idle":"2022-11-10T06:27:50.028001Z","shell.execute_reply.started":"2022-11-10T06:27:50.017484Z","shell.execute_reply":"2022-11-10T06:27:50.027208Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"four_factor_model_df.groupby(\"winner\")[\"condition_value\"].mean()","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:50.029105Z","iopub.execute_input":"2022-11-10T06:27:50.029368Z","iopub.status.idle":"2022-11-10T06:27:50.039962Z","shell.execute_reply.started":"2022-11-10T06:27:50.029344Z","shell.execute_reply":"2022-11-10T06:27:50.039294Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"logistic_regression= LogisticRegression(solver='lbfgs', max_iter=3000)\n#===========================================================================\n# perform a scikit-learn Recursive Feature Elimination (RFE)\n#===========================================================================\nfrom sklearn.feature_selection import RFE\n# here we want only one final feature, we do this to produce a ranking\n\nX = four_factor_model_df[[\n'jockey_rank_2018', 'horse_rank_2018', 'horse_starts_2018', 'layoff_gap', 'circumstances_value', 'horse_show_2018', 'horse_place_2018', 'class_value', 'purse_class_value', 'net_class_value', 'horse_topThree_2018', 'weight_carried', 'horse_win_2018', 'horse_winPercentage_2018', 'horse_win_volume_2018', 'speedFigure_2018', 'horse_topThreePercentage_2018', 'jockey_topThreePercentage_2018', 'horse_perStart_2018', 'horse_earnings_2018', 'show', 'jockey_winPercentage_2018', 'jockey_starts_2018', 'place', 'jockey_topThree_volume_2018', 'jockey_top_three_finish_2018', 'jockey_win_2018', 'jockey_win_volume_2018', 'condition_value'\n]]\n\ny = four_factor_model_df['winner']\nX_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.2,random_state= 42)\n\nn_features_to_select = 1\nrfe = RFE(logistic_regression, n_features_to_select=n_features_to_select)\nrfe.fit(X_train, y_train)\n\n#===========================================================================\n# now print out the features in order of ranking\n#===========================================================================\nfrom operator import itemgetter\nfeatures = X_train.columns.to_list()\nfor x, y in (sorted(zip(rfe.ranking_ , features), key=itemgetter(0))):\n    print(x, y)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:50.040772Z","iopub.execute_input":"2022-11-10T06:27:50.041462Z","iopub.status.idle":"2022-11-10T06:27:53.795377Z","shell.execute_reply.started":"2022-11-10T06:27:50.041436Z","shell.execute_reply":"2022-11-10T06:27:53.794722Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# <div style=\"background-color:black; padding: 20px; color: white;\">4). Model Creations</div>\n","metadata":{}},{"cell_type":"markdown","source":"We will be comparing 2 different versions of the Four Factor Logistic Regression model. One founded on the trial and error of different factors using Recursive Feature Elimination, and the other using class variances as a feature.\n\n**RFE Four Factor Model**: 'horse_topThree_2018', 'horse_starts_2018', 'speedFigure_2018', 'jockey_win_2018','jockey_top_three_finish_2018', 'jockey_topThreePercentage_2018', 'jockey_winPercentage_2018', 'jockey_topThree_volume_2018', 'jockey_starts_2018', 'jockey_win_volume_2018', 'horse_topThreePercentage_2018', 'horse_winPercentage_2018', 'circumstances_value','weight_carried',  'condition_value','layoff_gap'\n\n**CV Four Factor Model**: 'purse_class_value','class_value', 'circumstances_value', 'condition_value',  'weight_carried', 'speedFigure_2018','horse_topThreePercentage_2018', 'horse_topThree_2018', 'horse_starts_2018', 'horse_win_2018', 'horse_winPercentage_2018','jockey_rank_2018', 'jockey_winPercentage_2018','jockey_topThreePercentage_2018', 'jockey_win_2018'\n","metadata":{}},{"cell_type":"markdown","source":"<h2>1. Pass in model data</h2>","metadata":{}},{"cell_type":"markdown","source":"<center><h1>All Classes</h1></center>","metadata":{}},{"cell_type":"markdown","source":"<h2>Model Creation Using RFE</h2>","metadata":{}},{"cell_type":"code","source":"X = model_df_all_classes[[\n'horse_topThree_2018', 'horse_rank_2018', 'horse_starts_2018', 'speedFigure_2018', 'jockey_win_2018','jockey_top_three_finish_2018', 'jockey_topThreePercentage_2018','jockey_winPercentage_2018', 'jockey_topThree_volume_2018', 'jockey_starts_2018', 'jockey_win_volume_2018', 'horse_topThreePercentage_2018', 'horse_winPercentage_2018', 'circumstances_value','weight_carried',  'condition_value','layoff_gap'\n]]\n\ny = model_df_all_classes['winner']\nX_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.2,random_state= 42)\nlogistic_regression= LogisticRegression(solver='lbfgs', max_iter=3000)\nlogistic_regression.fit(X_train,y_train)\nall_classes_rfe_four_factor_pred = logistic_regression.predict_proba(X)[:, 1]\nall_classes_rfe_four_factor_pred_test = logistic_regression.predict_proba(X_test)[:, 1]\n#preds_test.append(pred_test)\nall_classes_rfe_loss = log_loss(y, all_classes_rfe_four_factor_pred)\nall_classes_test_rfe_loss = log_loss(y_test, all_classes_rfe_four_factor_pred_test)\n\nprint('All Classes RFE Log loss: ', all_classes_rfe_loss)\nprint('All Classes Test RFE Log loss: ', all_classes_test_rfe_loss)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:53.796278Z","iopub.execute_input":"2022-11-10T06:27:53.796859Z","iopub.status.idle":"2022-11-10T06:27:54.025458Z","shell.execute_reply.started":"2022-11-10T06:27:53.796833Z","shell.execute_reply":"2022-11-10T06:27:54.024695Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<h2>CV Four Factors Value Model Creation</h2>","metadata":{}},{"cell_type":"code","source":"X = model_df_all_classes[[\n'purse_class_value','class_value', 'circumstances_value', 'condition_value',  'weight_carried', 'speedFigure_2018','horse_topThreePercentage_2018', 'horse_topThree_2018', 'horse_starts_2018', 'horse_win_2018', 'horse_winPercentage_2018','jockey_rank_2018', 'jockey_winPercentage_2018','jockey_topThreePercentage_2018', 'jockey_win_2018'\n]]\n\ny = model_df_all_classes['winner']\nX_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.2,random_state= 42)\nlogistic_regression= LogisticRegression(solver='lbfgs', max_iter=3000)\nlogistic_regression.fit(X_train,y_train)\nall_classes_four_factor_pred = logistic_regression.predict_proba(X)[:, 1]\nall_classes_four_factor_pred_test = logistic_regression.predict_proba(X_test)[:, 1]\n#preds_test.append(pred_test)\nall_classes_loss_four_factor = log_loss(y, all_classes_four_factor_pred)\nall_classes_test_loss_four_factor = log_loss(y_test, all_classes_four_factor_pred_test)\n\nprint('All Classes Log loss: ', all_classes_loss_four_factor)\nprint('All Classes Test Log loss: ', all_classes_test_loss_four_factor)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:54.026650Z","iopub.execute_input":"2022-11-10T06:27:54.027107Z","iopub.status.idle":"2022-11-10T06:27:54.228486Z","shell.execute_reply.started":"2022-11-10T06:27:54.027077Z","shell.execute_reply":"2022-11-10T06:27:54.227748Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<center><h1>Allowance and Non Selling Class</h1></center>","metadata":{}},{"cell_type":"markdown","source":"<h2>Model Creation Using RFE</h2>","metadata":{}},{"cell_type":"code","source":"X = model_df_allowance_class[[\n'horse_topThree_2018', 'horse_starts_2018', 'horse_win_2018', 'horse_topThreePercentage_2018', 'speedFigure_2018', 'jockey_win_2018', 'jockey_top_three_finish_2018', 'jockey_topThreePercentage_2018','jockey_winPercentage_2018', 'jockey_starts_2018', 'circumstances_value','weight_carried',  'condition_value','layoff_gap'\n]]\n\ny = model_df_allowance_class['winner']\nX_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.2,random_state= 42)\nlogistic_regression= LogisticRegression(solver='lbfgs', max_iter=3000)\nlogistic_regression.fit(X_train,y_train)\nallowance_class_rfe_four_factor_pred = logistic_regression.predict_proba(X)[:, 1]\nallowance_class_rfe_four_factor_pred_test = logistic_regression.predict_proba(X_test)[:, 1]\n#preds_test.append(pred_test)\nallowance_class_rfe_loss = log_loss(y, allowance_class_rfe_four_factor_pred)\nallowance_class_test_rfe_loss = log_loss(y_test, allowance_class_rfe_four_factor_pred_test)\n\nprint('Class 3 RFE Log loss: ', allowance_class_rfe_loss)\nprint('Class 3 Test RFE Log loss: ', allowance_class_test_rfe_loss)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:54.229659Z","iopub.execute_input":"2022-11-10T06:27:54.230091Z","iopub.status.idle":"2022-11-10T06:27:54.414536Z","shell.execute_reply.started":"2022-11-10T06:27:54.230061Z","shell.execute_reply":"2022-11-10T06:27:54.413688Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":" allowance_class_rfe_four_factor_regression_df = pd.DataFrame({'coeff': logistic_regression.coef_[0]}, \n             index=X.columns).sort_values('coeff')","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:54.416870Z","iopub.execute_input":"2022-11-10T06:27:54.417098Z","iopub.status.idle":"2022-11-10T06:27:54.421973Z","shell.execute_reply.started":"2022-11-10T06:27:54.417075Z","shell.execute_reply":"2022-11-10T06:27:54.421103Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<h2>CV Four Factor Values Model Creation</h2>","metadata":{}},{"cell_type":"code","source":"X = model_df_allowance_class[[\n'purse_class_value','class_value', 'circumstances_value', 'condition_value',  'weight_carried', 'speedFigure_2018','horse_topThreePercentage_2018', 'horse_topThree_2018', 'horse_starts_2018', 'horse_win_2018', 'horse_winPercentage_2018','jockey_rank_2018', 'jockey_winPercentage_2018','jockey_topThreePercentage_2018', 'jockey_win_2018'\n]]\n\ny = model_df_allowance_class['winner']\nX_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.2,random_state= 42)\nlogistic_regression= LogisticRegression(solver='lbfgs', max_iter=3000)\nlogistic_regression.fit(X_train,y_train)\nallowance_class_four_factor_pred = logistic_regression.predict_proba(X)[:, 1]\nallowance_class_four_factor_pred_test = logistic_regression.predict_proba(X_test)[:, 1]\n#preds_test.append(pred_test)\nallowance_class_loss_four_factor = log_loss(y, allowance_class_four_factor_pred)\nallowance_class_test_loss_four_factor = log_loss(y_test, allowance_class_four_factor_pred_test)\n\nprint('Class 3 Four Factor Log loss: ', allowance_class_loss_four_factor)\nprint('Class 3 Four Factor Test Log loss: ', allowance_class_test_loss_four_factor)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:54.423053Z","iopub.execute_input":"2022-11-10T06:27:54.423516Z","iopub.status.idle":"2022-11-10T06:27:54.618326Z","shell.execute_reply.started":"2022-11-10T06:27:54.423483Z","shell.execute_reply":"2022-11-10T06:27:54.617361Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# <div style=\"background-color:black; padding: 20px; color: white;\">5). Model Insights v. Public Odds</div>\n","metadata":{}},{"cell_type":"markdown","source":"<h2>LOG LOSS</h2>\n\n**It is the log loss that we care about. A better log loss than the public odds points to a potentially profitable EV betting system.**","metadata":{}},{"cell_type":"markdown","source":"<center><h1>CV Four Factor Model vs Public Odds</h1></center>","metadata":{}},{"cell_type":"markdown","source":"<center><h2>All Classes</h2></center>","metadata":{}},{"cell_type":"code","source":"X = model_df_all_classes[[\n'odds'\n]]\n\ny = model_df_all_classes['winner']\nX_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.2,random_state= 42)\nlogistic_regression= LogisticRegression(solver='lbfgs', max_iter=3000)\nlogistic_regression.fit(X_train,y_train)\nall_classes_odds_pred = logistic_regression.predict_proba(X)[:, 1]\nall_classes_odds_pred_test = logistic_regression.predict_proba(X_test)[:, 1]\n#preds_test.append(pred_test)\nall_classes_loss_odds = log_loss(y, all_classes_odds_pred)\nall_classes_test_loss_odds = log_loss(y_test, all_classes_odds_pred_test)\n\nprint('All classes Log loss: ', all_classes_loss_odds)\nprint('All classes Test Log loss: ', all_classes_test_loss_odds)\n","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:54.619283Z","iopub.execute_input":"2022-11-10T06:27:54.619561Z","iopub.status.idle":"2022-11-10T06:27:54.646804Z","shell.execute_reply.started":"2022-11-10T06:27:54.619535Z","shell.execute_reply":"2022-11-10T06:27:54.645913Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"all_classes_loss_differential = all_classes_loss_four_factor - all_classes_loss_odds\nall_classes_test_loss_differential = all_classes_test_loss_four_factor - all_classes_test_loss_odds\nprint('All classes Log loss differential: ', all_classes_loss_differential)\nprint('All classes Test Log loss differential: ', all_classes_test_loss_differential)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:54.647633Z","iopub.execute_input":"2022-11-10T06:27:54.647886Z","iopub.status.idle":"2022-11-10T06:27:54.652878Z","shell.execute_reply.started":"2022-11-10T06:27:54.647861Z","shell.execute_reply":"2022-11-10T06:27:54.652043Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<center><h2>Allowance and Non Selling Class</h2></center>","metadata":{}},{"cell_type":"code","source":"X = model_df_allowance_class[[\n'odds'\n]]\n\ny = model_df_allowance_class['winner']\nX_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.2,random_state= 42)\nlogistic_regression= LogisticRegression(solver='lbfgs', max_iter=3000)\nlogistic_regression.fit(X_train,y_train)\nallowance_class_odds_pred = logistic_regression.predict_proba(X)[:, 1]\nallowance_class_odds_pred_test = logistic_regression.predict_proba(X_test)[:, 1]\n#preds_test.append(pred_test)\nallowance_class_loss_odds = log_loss(y, allowance_class_odds_pred)\nallowance_class_test_loss_odds = log_loss(y_test, allowance_class_odds_pred_test)\n\nprint('Class 3 Log loss: ', allowance_class_loss_odds)\nprint('Class 3 Test Log loss: ', allowance_class_test_loss_odds)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:54.653843Z","iopub.execute_input":"2022-11-10T06:27:54.654108Z","iopub.status.idle":"2022-11-10T06:27:54.682370Z","shell.execute_reply.started":"2022-11-10T06:27:54.654082Z","shell.execute_reply":"2022-11-10T06:27:54.681411Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"allowance_class_loss_differential = allowance_class_loss_four_factor - allowance_class_loss_odds\nallowance_class_test_loss_differential = allowance_class_test_loss_four_factor - allowance_class_test_loss_odds\nprint('Class 3 Log loss differential: ', allowance_class_loss_differential)\nprint('Class 3 Test Log loss differential: ', allowance_class_test_loss_differential)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:54.683794Z","iopub.execute_input":"2022-11-10T06:27:54.686140Z","iopub.status.idle":"2022-11-10T06:27:54.691520Z","shell.execute_reply.started":"2022-11-10T06:27:54.686101Z","shell.execute_reply":"2022-11-10T06:27:54.690690Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<center><h1>RFE Four Factor Model vs Public Odds</h1></center>\n","metadata":{}},{"cell_type":"markdown","source":"<h2>All Classes</h2>","metadata":{}},{"cell_type":"code","source":"all_classes_rfe_odds_loss_differential = all_classes_rfe_loss - all_classes_loss_odds\nall_classes_test_rfe_odds_loss_differential = all_classes_test_rfe_loss - all_classes_test_loss_odds\nprint('RFE Log loss - Odds differential: ', all_classes_rfe_odds_loss_differential)\nprint('Test RFE Log loss - Test Odds differential: ', all_classes_test_rfe_odds_loss_differential)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:54.694414Z","iopub.execute_input":"2022-11-10T06:27:54.694670Z","iopub.status.idle":"2022-11-10T06:27:54.700448Z","shell.execute_reply.started":"2022-11-10T06:27:54.694645Z","shell.execute_reply":"2022-11-10T06:27:54.699725Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<h2>Class 3</h2>","metadata":{}},{"cell_type":"code","source":"allowance_class_rfe_loss_differential = allowance_class_rfe_loss - allowance_class_loss_odds\nallowance_class_rfe_test_loss_differential = allowance_class_test_rfe_loss - allowance_class_test_loss_odds\nprint('Class 3 RFE Log loss differential: ', allowance_class_rfe_loss_differential)\nprint('Class 3 Test RFE Log loss differential: ', allowance_class_rfe_test_loss_differential)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:54.701639Z","iopub.execute_input":"2022-11-10T06:27:54.702148Z","iopub.status.idle":"2022-11-10T06:27:54.710392Z","shell.execute_reply.started":"2022-11-10T06:27:54.702115Z","shell.execute_reply":"2022-11-10T06:27:54.709454Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# <div style=\"background-color:black; padding: 20px; color: white;\">6). Model Results</div>","metadata":{}},{"cell_type":"markdown","source":"Both models failed to beat the full dataset of race data. The **RFE Four Factor Logistic Regression Model** outperformed the Public (odds) on **Allowance and Non Selling races** on both full and test data. The **CV Four Factor Logistic Regression Model** did a better job than the RFE model on the full **Allowance and Non Selling** dataset but failed to beat the odds on the test data.\n\n**I will use our RFE Four Factor Logistic Regression Model to create better odds for Allowance and Non Selling Races.**","metadata":{}},{"cell_type":"markdown","source":"<h2>Model Interpretation</h2>","metadata":{}},{"cell_type":"code","source":"allowance_class_rfe_four_factor_regression_df","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:54.711843Z","iopub.execute_input":"2022-11-10T06:27:54.712488Z","iopub.status.idle":"2022-11-10T06:27:54.726066Z","shell.execute_reply.started":"2022-11-10T06:27:54.712454Z","shell.execute_reply":"2022-11-10T06:27:54.725084Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"The negative coefficient for **2018 horse starts** on 2019 leads me to believe that the lightly run horses perform the best. An increase in **weight carried** impacting the probability of victory makes sense in a vacuum despite increased weight implying increased form or another perceived advantage. What really has me curious is the **jockey starts** for 2018 with the very slight negative coefficient. Does this indicate that increased experience only indicates so much? This could allude to the grueling life of a jockey indicating that just simply having raced more often in the prior year does not indicate better future performance.","metadata":{}},{"cell_type":"markdown","source":"# <div style=\"background-color:black; padding: 20px; color: white;\">7). Odds Creation</div>","metadata":{}},{"cell_type":"markdown","source":"![Peaky_Blinders_Betting_Shop.jpeg](attachment:4c394201-a02e-4470-9b57-15f8e3b5e760.jpeg)","metadata":{},"attachments":{"4c394201-a02e-4470-9b57-15f8e3b5e760.jpeg":{"image/jpeg":"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"}}},{"cell_type":"markdown","source":"[Betting Odds Explained](https://www.bettingexpert.com/academy/betting-fundamentals/betting-odds-explained#al-probmoneyline)\n\n[Odds Calculator](https://www.oddsshark.com/tools/odds-calculator)\n","metadata":{}},{"cell_type":"markdown","source":"We are now at the point where we have the data available to create our odds. Horse races use fractional odds but we can convert these to probabilites and by extension determine what the public views as each horse's probability of victory. Converting horse odds to probabilities.\n\nFrom the Big Data Derby page: *odds - Odds to win the race passed as an integer. Divide by 100 to derive the odds to 1. Example - 1280 would be 12.8-1*. aka .078125\n\nImplied probability\t=\tdenominator / (denominator + numerator)\n\nFractional odds\t=\t( 1 / implied probability ) -1\n","metadata":{}},{"cell_type":"code","source":"model_df_allowance_class['model_probability_of_victory'] = allowance_class_rfe_four_factor_pred\n\nmodel_df_allowance_class['public_probability_of_victory'] = model_df_allowance_class['odds'].apply(lambda x:  1 / (1 + (x / 100)))\nmodel_df_allowance_class['model_odds'] = model_df_allowance_class['model_probability_of_victory'].apply(lambda x: (100 * ((1 / x) - 1))).round(decimals = 0).astype('Int64')\nmodel_df_allowance_class['good_odds'] = model_df_allowance_class['model_probability_of_victory'] > model_df_allowance_class['public_probability_of_victory']\n","metadata":{"_kg_hide-output":true,"execution":{"iopub.status.busy":"2022-11-10T06:27:54.727075Z","iopub.execute_input":"2022-11-10T06:27:54.727381Z","iopub.status.idle":"2022-11-10T06:27:54.739776Z","shell.execute_reply.started":"2022-11-10T06:27:54.727355Z","shell.execute_reply":"2022-11-10T06:27:54.738791Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"model_df_allowance_class = model_df_allowance_class[['horse_name', 'jockey', 'public_probability_of_victory', 'model_probability_of_victory','winner', 'odds', 'model_odds', 'good_odds']].copy()\n","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:54.742115Z","iopub.execute_input":"2022-11-10T06:27:54.742524Z","iopub.status.idle":"2022-11-10T06:27:54.747367Z","shell.execute_reply.started":"2022-11-10T06:27:54.742497Z","shell.execute_reply":"2022-11-10T06:27:54.746672Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<center><h2>20 Winning Horses Examples</h2></center>","metadata":{}},{"cell_type":"code","source":"model_df_allowance_class.loc[model_df_allowance_class['winner'] == 1].head(20)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:54.748592Z","iopub.execute_input":"2022-11-10T06:27:54.748917Z","iopub.status.idle":"2022-11-10T06:27:54.770605Z","shell.execute_reply.started":"2022-11-10T06:27:54.748890Z","shell.execute_reply":"2022-11-10T06:27:54.769482Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"<center><h2>20 Winning Horses with Good Odds</h2></center>","metadata":{}},{"cell_type":"code","source":"model_df_allowance_class.loc[(model_df_allowance_class['winner'] == 1) & (model_df_allowance_class['good_odds'] == True)].head(20)","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:54.771978Z","iopub.execute_input":"2022-11-10T06:27:54.772804Z","iopub.status.idle":"2022-11-10T06:27:54.796338Z","shell.execute_reply.started":"2022-11-10T06:27:54.772734Z","shell.execute_reply":"2022-11-10T06:27:54.795542Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"winner_count = model_df_allowance_class.loc[model_df_allowance_class['winner'] == 1].shape[0]\ngood_odds_count_and_lost = model_df_allowance_class.loc[(model_df_allowance_class['good_odds'] == True) & (model_df_allowance_class['winner'] == 0)].shape[0]\ngood_odds_and_winner_count = model_df_allowance_class.loc[(model_df_allowance_class['winner'] == 1) & (model_df_allowance_class['good_odds'] == True)].shape[0]\ngood_odds_count_and_lost_cost = good_odds_count_and_lost * 100\ngood_odds_and_winner_payout = model_df_allowance_class.loc[(model_df_allowance_class['winner'] == 1) & (model_df_allowance_class['good_odds'] == True)]['odds'].sum()\n\nallowance_class_rfe_model_profit = good_odds_and_winner_payout - good_odds_count_and_lost_cost","metadata":{"execution":{"iopub.status.busy":"2022-11-10T06:27:54.798086Z","iopub.execute_input":"2022-11-10T06:27:54.798834Z","iopub.status.idle":"2022-11-10T06:27:54.809031Z","shell.execute_reply.started":"2022-11-10T06:27:54.798798Z","shell.execute_reply":"2022-11-10T06:27:54.808294Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print('Number of bets with good odds in Class 3: ', good_odds_count_and_lost)\nprint('Number of winning horses in Class 3: ', winner_count)\nprint('Number of bets with good odds and the winner: ', good_odds_and_winner_count)\nprint('\\n')\nprint('Good odds and the winner payout (Betting $100): $' + str(good_odds_and_winner_payout))\nprint('Good odds and the horse lost cost (Betting $100): -$' + str(good_odds_count_and_lost_cost))\nprint('\\n')\nprint('Model Profit: $' + str(allowance_class_rfe_model_profit))","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-10T06:27:54.810061Z","iopub.execute_input":"2022-11-10T06:27:54.810373Z","iopub.status.idle":"2022-11-10T06:27:54.823698Z","shell.execute_reply.started":"2022-11-10T06:27:54.810347Z","shell.execute_reply":"2022-11-10T06:27:54.822942Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# <div style=\"background-color:black; padding: 20px; color: white;\">8). Ways to Improve My Model</div>\n","metadata":{}},{"cell_type":"markdown","source":"[](http://)The best way to measure ways to improve this model is to take it one factor at a time. For **Class** I would create my own custom power rating, compare the speed figures across different surfaces (I will elaborate more on that next), and look into the horses' pedigree. For **Circumstances** I would look into how the horses perform on different surfaces historically and determine if the horse is at an advantage or disadvantage for the surface of the next race. For **Condition** I would look into pooling each horses' workout data/history and look for gaps. I would also eliminate the generalization on layoff gaps in my model and instead see if there is an irregular layoff gap based on that horse's average gap. And for **Connections** I would add trainer data for each horse, the same way I did for jockey data. I also would not limit my model to only horses with jockey data from the year prior. ","metadata":{}},{"cell_type":"markdown","source":"# <div style=\"background-color:black; padding: 20px; color: white;\">9). Conclusion</div>\n","metadata":{}},{"cell_type":"markdown","source":"I strongly believe that the **Four Factors** concept Barry Meadow spoke of in \"The Skeptical Handicapper\" is the key to horse racing success from all sides. With my limited resources and limited domain knowledge I was able to use the Four Factors as a guide in this submission to beating the public odds on allowance_class level races. With a deeper dataset I know there is a consistent measure of beating the odds across allowance_class and Stakes races. I created and shared [custom datasets with the 2018 Equibase data](https://www.kaggle.com/competitions/big-data-derby-2022/discussion/364175) to compsensate and it certainly helped me. As the access to new data grows, I would love to see the different variations on Four Factor formulas for success that arise. New **Condition** metrics will impact a horse's workout and care. A better appreciation of **Circumstances** will impact how stakeholders view a horse's individual performance. While a higher assisgned weight indicates underyling positives, more weight does literally slow a horse down, the advantage lies in a horse who *should* have a higher assigned weight but does not because the [official rating (OR)](https://news.paddypower.com/guides/2022/02/01/horse-racing-weights-race-horses-betting-handicaps/) overlooked other factors. **Connections** metrics may do a better job of quantifying the impact specific trainers and jockeys have. Improved **Class** metrics may do a better job of being an indicator of future performance. \n\nThis model merely scratches the surface but I do believe that every trainer, jockey, annd owner should view training, maintenance, fellow competition, and performance in terms of the Four Factors.","metadata":{}},{"cell_type":"markdown","source":"![Tommy_Shelby_Horse.jpeg](attachment:0bf84c4e-9d60-4503-ad3e-e8df364a0568.jpeg)","metadata":{},"attachments":{"0bf84c4e-9d60-4503-ad3e-e8df364a0568.jpeg":{"image/jpeg":"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"}}},{"cell_type":"markdown","source":"<center><h3><i>And now our careers as horse fanatic bookmakers has come to an end! Hope you enjoyed the journey!</i></h3></center>","metadata":{}},{"cell_type":"markdown","source":"# <div style=\"background-color:black; padding: 20px; color: white;\">10). References</div>\n\n\n1. \"The Skeptical Handicapper\" By: Barry Meadow https://www.amazon.com/Skeptical-Handicapper-Using-Brains-Racetrack-ebook/dp/B07NS6N5YZ\n2. \"Complete Column Names\" https://www.kaggle.com/competitions/big-data-derby-2022/discussion/355304\n3. \"Dataset with Global Horse IDs\": https://www.kaggle.com/datasets/themarkgreen/big-data-derby-2022-global-horse-ids-and-places\n4. \"Horse ID check logic\": https://www.kaggle.com/code/asksawant/bdd-horse-id-check/notebook\n5. \"Recursive Feature Elimination Example\": https://www.kaggle.com/code/carlmcbrideellis/recursive-feature-elimination-rfe-example/notebook\n6. \"Recursive Feature Learning Tutorial\": https://machinelearningmastery.com/rfe-feature-selection-in-python/\n7. \"Horse Racing Sense\": https://horseracingsense.com/what-are-different-horse-racing-classes-tips/\n8. \"Time off racing helps horses race for longer and avoid injuries\": https://www.racingvictoria.com.au/the-horse/veterinary-care/-/media/281434f1899d4e4db0c093432d9f5efc.ashx\n9. \"Betting Odds Explained\": https://www.bettingexpert.com/academy/betting-fundamentals/betting-odds-explained#al-probmoneyline\n10. \"Odds Calculator\" https://www.oddsshark.com/tools/odds-calculator\n11. \"How are horse weights given?\" https://news.paddypower.com/guides/2022/02/01/horse-racing-weights-race-horses-betting-handicaps/\n12. \"Create Beautiful Notebooks: Formatting Tutorial\": https://www.kaggle.com/code/shubhamksingh/create-beautiful-notebooks-formatting-tutorial#beauty","metadata":{}}]}