{"id":23228356,"url":"https://github.com/stefagnone/moneyball_project","last_synced_at":"2025-04-05T18:22:53.566Z","repository":{"id":262818827,"uuid":"888454265","full_name":"stefagnone/Moneyball_Project","owner":"stefagnone","description":"Data-driven analysis inspired by the Moneyball approach, identifying affordable replacements for key Oakland A's players using R and sabermetrics to support cost-effective recruitment.","archived":false,"fork":false,"pushed_at":"2024-12-12T16:48:14.000Z","size":2472,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-11T15:42:35.384Z","etag":null,"topics":["baseball-statistics","data-analysis","data-driven-decision-making","player-replacement-strategy","r-programming","sabermetrics","sports-analytics"],"latest_commit_sha":null,"homepage":"","language":"R","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/stefagnone.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":"2024-11-14T12:32:39.000Z","updated_at":"2024-12-12T16:48:19.000Z","dependencies_parsed_at":null,"dependency_job_id":"138e31b6-85c0-4cd3-ad14-cd85c9f0775e","html_url":"https://github.com/stefagnone/Moneyball_Project","commit_stats":null,"previous_names":["stefagnone/moneyball_project"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stefagnone%2FMoneyball_Project","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stefagnone%2FMoneyball_Project/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stefagnone%2FMoneyball_Project/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stefagnone%2FMoneyball_Project/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/stefagnone","download_url":"https://codeload.github.com/stefagnone/Moneyball_Project/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247379416,"owners_count":20929521,"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":["baseball-statistics","data-analysis","data-driven-decision-making","player-replacement-strategy","r-programming","sabermetrics","sports-analytics"],"created_at":"2024-12-19T01:13:26.847Z","updated_at":"2025-04-05T18:22:53.540Z","avatar_url":"https://github.com/stefagnone.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Moneyball Analysis: Player Replacement Strategy\n\n## Project Overview\nThis project is based on the data-driven approach of the Oakland Athletics baseball team, as featured in the book \"Moneyball\" by Michael Lewis. The analysis aims to identify cost-effective player replacements using sabermetrics, focusing on batting average, on-base percentage, and slugging percentage. The goal is to help the Athletics maintain a competitive edge with limited resources by finding undervalued players who can match or exceed the contributions of key players lost in the offseason.\n\n## Technologies Used\n- **R**: For data manipulation, statistical analysis, and visualization\n- **Data Visualization**: ggplot2 and other R libraries for clear insights\n\n## Repository Structure\n- `Data/`: Contains `Batting.csv` and `Salaries.csv`, with player performance and salary information.\n- `Code/`: Includes `Moneyball.R` with all the R code for data cleaning, analysis, and visualization.\n\n## Key Insights\n- **Data-Driven Strategy**: Emphasis on sabermetrics allows for objective player evaluation, focusing on undervalued statistics like on-base percentage and slugging percentage.\n- **Budget Efficiency**: Highlights players who can replace key contributors (e.g., Jason Giambi, Johnny Damon) within the constraints of a small-market team budget.\n- **Long-Term Impact**: The analysis provides insights into maintaining competitiveness through efficient resource allocation, which has implications for sports management beyond baseball.\n\n## Instructions\n1. Clone this repository.\n2. Run the R script (`Moneyball.R`) in RStudio or any compatible R environment.\n3. Ensure necessary R packages (like `dplyr`, `ggplot2`) are installed.\n4. Review the analysis results, visualizations, and player recommendations.\n\n## Contact\nConnect with me on [LinkedIn](https://www.linkedin.com/in/stefano-compagnone98/) to discuss this project or view my other work in data analysis and sports analytics.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstefagnone%2Fmoneyball_project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstefagnone%2Fmoneyball_project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstefagnone%2Fmoneyball_project/lists"}