{"id":20021567,"url":"https://github.com/177arc/fpl-advisor","last_synced_at":"2025-05-05T01:30:57.700Z","repository":{"id":48469314,"uuid":"219347789","full_name":"177arc/fpl-advisor","owner":"177arc","description":"Jupyter notebook for interactively analysing Fantasy Premier League (FPL) players and optimising your team's performance","archived":false,"fork":false,"pushed_at":"2021-07-24T09:44:33.000Z","size":2284,"stargazers_count":18,"open_issues_count":0,"forks_count":7,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-04-08T14:45:46.729Z","etag":null,"topics":["fantasy-premier-league","football","fpl","jupyter-notebook","python"],"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":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/177arc.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2019-11-03T18:39:53.000Z","updated_at":"2024-12-22T18:03:07.000Z","dependencies_parsed_at":"2022-08-24T06:21:32.626Z","dependency_job_id":null,"html_url":"https://github.com/177arc/fpl-advisor","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/177arc%2Ffpl-advisor","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/177arc%2Ffpl-advisor/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/177arc%2Ffpl-advisor/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/177arc%2Ffpl-advisor/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/177arc","download_url":"https://codeload.github.com/177arc/fpl-advisor/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252423006,"owners_count":21745529,"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":["fantasy-premier-league","football","fpl","jupyter-notebook","python"],"created_at":"2024-11-13T08:37:12.957Z","updated_at":"2025-05-05T01:30:56.287Z","avatar_url":"https://github.com/177arc.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/177arc/fpl-advisor/master?filepath=advisor.ipynb)\n[![Python 3.8](https://img.shields.io/badge/python-3.8-blue.svg)](https://www.python.org/downloads/release/python-380/)\n\n# Fantasy Premier League (FPL) Advisor\n\n**WARNING: Playing FPL can be highly adictive.**\n\n## Purpose\nThe purpose of the Advisor Jupyter notebook is to help with the selection of team members for the [Fantasy Premier League](https://fantasy.premierleague.com/) (FPL) by attempting to forecast how many points players will earn.  \nIt provides visual analysis and uses linear optimisation to recommend a team with the maximum expected points to improve the performance of your current team.\nThe underlying data comes the [fpl-data project](https://github.com/177arc/fpl-data) which in turn gets it from the FPL API. The data is updated on an hourly basis.\n\nIf you are not familiar with the Fantasy Premier League, you can watch this introduction:\n\n\u003ca href=\"http://www.youtube.com/watch?v=SV_F-cL8fC0\" target=\"_blank\"\u003e\u003cimg src=\"http://img.youtube.com/vi/SV_F-cL8fC0/0.jpg\"\nalt=\"How to play FPL\" width=\"600\" height=\"400\"/\u003e\u003c/a\u003e\n\n## Usage\n\nTo use the FPL Advisor Jupyter notebook interactively, simply open the [advisor.ipynb](advisor.ipynb) notebook on [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/177arc/fpl-advisor/master?filepath=advisor.ipynb) (it may take a bit of time to deploy the notebook).\n\nAlternatively, simply clone the repository and open advisor.ipynb locally.\n\nHere is a screenshot of the interactive chart for analysing players:\n[![FPL Advisor Visualisation](fpl_advisor.png)](https://mybinder.org/v2/gh/177arc/fpl-advisor/master?filepath=advisor.ipynb)\n\nAnd you can use the optimiser for selecting the best players for a wildcard/free hit or recommending transfers for your team:  \n[![FPL Advisor Optimiser](optimiser.png)](https://mybinder.org/v2/gh/177arc/fpl-advisor/master?filepath=advisor.ipynb)\n\nTo explore the FPL data using a neural network, [train_nn_model.ipynb](train_nn_model.ipynb) notebook on [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/177arc/fpl-advisor/master?filepath=train_nn_model.ipynb).\n\n## Contributing\n\n1. Fork the repository on GitHub.\n2. Run the tests with `python -m unittest discover -s tests/unit` to confirm they all pass on your system.\n   If the tests fail, then try and find out why this is happening. If you aren't\n   able to do this yourself, then don't hesitate to either create an issue on\n   GitHub,  send an email to [py@177arc.net](mailto:py@177arc.net\u003e).\n3. Either create your feature and then write tests for it, or do this the other\n   way around.\n4. Run all tests again with with `python -m unittest discover -s tests/unit` to confirm that everything\n   still passes, including your newly added test(s).\n5. Create a pull request for the main repository's ``master`` branch.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2F177arc%2Ffpl-advisor","html_url":"https://awesome.ecosyste.ms/projects/github.com%2F177arc%2Ffpl-advisor","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2F177arc%2Ffpl-advisor/lists"}