{"id":13477747,"url":"https://github.com/yssefunc/sport_analytics","last_synced_at":"2025-03-27T06:30:50.578Z","repository":{"id":217081801,"uuid":"308039493","full_name":"yssefunc/sport_analytics","owner":"yssefunc","description":"Sports betting analytics ","archived":false,"fork":false,"pushed_at":"2021-01-25T20:28:27.000Z","size":1740,"stargazers_count":11,"open_issues_count":0,"forks_count":7,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-10-30T10:41:21.318Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/yssefunc.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-10-28T14:19:03.000Z","updated_at":"2024-04-05T00:07:56.000Z","dependencies_parsed_at":null,"dependency_job_id":"9ef585be-30fc-4907-b2ba-36c4d56cf74a","html_url":"https://github.com/yssefunc/sport_analytics","commit_stats":null,"previous_names":["yssefunc/sport_analytics"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yssefunc%2Fsport_analytics","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yssefunc%2Fsport_analytics/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yssefunc%2Fsport_analytics/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yssefunc%2Fsport_analytics/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/yssefunc","download_url":"https://codeload.github.com/yssefunc/sport_analytics/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245797247,"owners_count":20673811,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-07-31T16:01:47.048Z","updated_at":"2025-03-27T06:30:49.290Z","avatar_url":"https://github.com/yssefunc.png","language":"Jupyter Notebook","readme":"# Sport Analytics\nSimple betting analytics with Python. It has two parts which are data-preprocessing(code/preprocess.ipynb) and exploratory data analysis(code/eda.ipynb).\n\nArticle - 1: https://medium.com/analytics-vidhya/sports-analytics-in-python-part-1-12e4907da227 \u003cbr\u003e\nArticle - 2: https://medium.com/analytics-vidhya/exploratory-data-analysis-in-sports-analytics-part-2-5ba6aa50cd5\n\n\n# Bet Options\nThe list below contains the most popular type of bets on football.\n| 1  |2 |3|4|5|6|7|8|\n|--------------|--------------|--------------|--------------|--------------|--------------|--------------|--------------|\n|0.5_under_half\t|0.5_above_half|mutual_goal|MS_2_under_2_5\t|MS_1_above_3_5|MS_0_above_4_5|away_goal_concede|win_half_full|\n|1.5_under_half\t|1.5_above_half|MS_1_under_1_5|\tMS_0_under_2_5|MS_2_above_3_5|win|sum_concede|win_half_full_home|\n|2.5_under_half\t|2.5_above_half|MS_2_under_1_5|MS_1_above_2_5|MS_0_above_3_5|draw|win_half|win_half_full_away|\n|0.5_under_final|0.5_above_final|MS_0_under_1_5|MS_2_above_2_5|MS_1_under_4_5|lose|draw_half|-|\n|1.5_under_final|1.5_above_final|MS_1_above_1_5|MS_0_above_2_5|MS_2_under_4_5|home_goal|lose_half|-|\n|2.5_under_final|\t2.5_above_final|MS_2_above_1_5|MS_1_under_3_5|MS_0_under_4_5|\taway_goal|one_zero|-|\n|3.5_under_final|3.5_above_final|MS_0_above_1_5|MS_2_under_3_5|MS_1_above_4_5|sum_goal|one_two|-|\n|4.5_under_final|4.5_above_final|MS_1_under_2_5|MS_0_under_3_5|MS_2_above_4_5|home_goal_concede|zero_two|-|\n\n# Installation\nUse the package manager pip to install foobar. \n```\npip install ipywidgets\npip install nbextensions\npip install plotly\n```\n\u003cp align=\"left\"\u003e\n  \u003cimg src=\"https://github.com/yssefunc/sport_analytics/blob/main/img/prob.png\"\u003e\n\u003c/p\u003e\n\n\u003chr style=\"width:40%\"\u003e\n\n# Usage\nWhen you run the code, you will see the sample dashboard like this.\n![Algorithm schema](https://github.com/yssefunc/sport_analytics/blob/main/img/gif.gif)\n\n\n\n\n\n","funding_links":[],"categories":["Jupyter Notebook"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyssefunc%2Fsport_analytics","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fyssefunc%2Fsport_analytics","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyssefunc%2Fsport_analytics/lists"}