{"id":27971999,"url":"https://github.com/marco210210/football-analytics","last_synced_at":"2026-02-27T12:33:19.005Z","repository":{"id":291741981,"uuid":"975672925","full_name":"Marco210210/Football-Analytics","owner":"Marco210210","description":"Football Analytics is a project that collects, analyzes, and visualizes performance data for football teams and players during the Serie A 2017/18 season, using database structures and machine learning models to provide insights into match events and player actions.","archived":false,"fork":false,"pushed_at":"2025-05-06T15:25:29.000Z","size":34725,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-27T00:37:22.078Z","etag":null,"topics":["data-analytics","data-preprocessing","data-visualization","football-analytics","football-performance-analysis","machine-learning","mongodb","mplsoccer","python","sports-data"],"latest_commit_sha":null,"homepage":"","language":"Python","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/Marco210210.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,"zenodo":null}},"created_at":"2025-04-30T17:47:48.000Z","updated_at":"2025-07-10T17:19:02.000Z","dependencies_parsed_at":"2025-07-26T22:34:31.165Z","dependency_job_id":"8f1d349b-48ca-496b-b284-b196fa00e063","html_url":"https://github.com/Marco210210/Football-Analytics","commit_stats":null,"previous_names":["marco210210/football-analytics"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Marco210210/Football-Analytics","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Marco210210%2FFootball-Analytics","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Marco210210%2FFootball-Analytics/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Marco210210%2FFootball-Analytics/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Marco210210%2FFootball-Analytics/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Marco210210","download_url":"https://codeload.github.com/Marco210210/Football-Analytics/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Marco210210%2FFootball-Analytics/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":271121168,"owners_count":24702723,"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","status":"online","status_checked_at":"2025-08-19T02:00:09.176Z","response_time":63,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["data-analytics","data-preprocessing","data-visualization","football-analytics","football-performance-analysis","machine-learning","mongodb","mplsoccer","python","sports-data"],"created_at":"2025-05-07T22:37:03.188Z","updated_at":"2026-02-27T12:33:18.931Z","avatar_url":"https://github.com/Marco210210.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n# Football Analytics – Serie A 2017/18\n\n**Football Analytics** is a comprehensive project designed to collect, analyze, and visualize performance data for football teams and players during the Serie A 2017/18 season. The project uses a sophisticated database structure and machine learning models to provide insights into match events, player actions, and team performance.\n\n---\n\n## 🌐 Project Overview\n\nThe goal of this project is to build a system that allows for detailed analysis of football events, focusing on Serie A 2017/18 matches. By utilizing Kaggle's Soccer Match Event Dataset and additional data from FBref via web scraping, this project offers:\n\n- **Data Preprocessing**: Cleaning and transforming raw football data.\n- **Database Design**: Creating a robust database to store match events, player stats, and more.\n- **Analysis**: Detailed analysis of events like passes, shots, and actions during the match.\n- **Visualization**: Interactive visualizations of player movements, actions, and performance metrics.\n\n---\n\n## 🛠️ Technologies \u0026 Tools\n\n- **Languages**: Python\n- **Libraries**: Pandas, NumPy, Scikit-learn, mplsoccer, Electron\n- **Database**: MongoDB (NoSQL)\n- **Data Sources**: Kaggle, FBref\n- **Machine Learning Models**: Not specified in the current document\n- **Visualizations**: mplsoccer for football-specific data visualizations\n\n---\n\n## 📁 Repository Structure\n\n```\nFootball_Analytics/\n├── code/                     → Source code and implementation files\n│\n├── dataset.r                 → Compressed dataset (ZIP file, includes all relevant datasets)\n│\n├── docs/                     → Documentation\n│   ├── Football_Analytics.pptx  → PowerPoint presentation about the project\n│   ├── Football_Analytics_RAD.pdf  → Requirement Analysis Document\n│   └── Project_Documentation_Football_Analytics.pdf  → Final project documentation\n│\n└── README.md                 → Project documentation (this file)\n```\n\n---\n\n## 🚀 How to Use\n\n1. Clone the repository:\n   ```bash\n   git clone https://github.com/Marco210210/Football-Analytics.git\n   ```\n\n2. Download the dataset from Kaggle or via the provided link in the `dataset/` directory. The dataset is not included in this repository due to size limitations.\n\n3. Explore the code in the `code/` directory for the data preprocessing and analysis scripts.\n\n4. The `Football_Analytics.pptx` file provides an overview of the project, while the PDF documents in `docs/` offer detailed documentation and requirement analysis.\n\n---\n\n## 📄 Documentation\n\n- [Project Report (PDF)](docs/Project_Documentation_Football_Analytics.pdf)\n- [Requirement Analysis Document (PDF)](docs/Football_Analytics_RAD.pdf)\n\n---\n\n## 👥 Contributors\n\n- [Arcangeli Giovanni](https://github.com/GiovanniArcangeli)\n- [Ciancio Vittorio](https://github.com/VittorioCiancio)\n- Di Maio Marco\n\n---\n\n## 📄 License\n\nThis project is licensed under the [CC BY-NC-SA 4.0 License](https://creativecommons.org/licenses/by-nc-sa/4.0/)  \n[![License: CC BY-NC-SA 4.0](https://licensebuttons.net/l/by-nc-sa/4.0/88x31.png)](https://creativecommons.org/licenses/by-nc-sa/4.0/)  \n\nYou may share and adapt this work for non-commercial purposes only, **as long as you give appropriate credit** and **distribute your contributions under the same license**.  \nFor commercial use, **explicit permission from the authors is required**.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmarco210210%2Ffootball-analytics","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmarco210210%2Ffootball-analytics","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmarco210210%2Ffootball-analytics/lists"}