{"id":29492587,"url":"https://github.com/paulinhok14/csgo-datascience-project","last_synced_at":"2025-12-30T21:36:57.472Z","repository":{"id":175667908,"uuid":"654269981","full_name":"paulinhok14/csgo-datascience-project","owner":"paulinhok14","description":"📊 Analysis of CS:GO grenade usage patterns and their impact on match outcomes using data science and statistical methods.","archived":false,"fork":false,"pushed_at":"2025-06-27T13:21:07.000Z","size":35034,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-16T05:14:26.961Z","etag":null,"topics":["matplotlib","mlflow","numpy","python","scikit-learn","scipy","seaborn"],"latest_commit_sha":null,"homepage":"","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/paulinhok14.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":"2023-06-15T18:51:00.000Z","updated_at":"2025-06-26T19:53:24.000Z","dependencies_parsed_at":null,"dependency_job_id":"7f5d3f52-4f62-4354-920e-f382b28fc509","html_url":"https://github.com/paulinhok14/csgo-datascience-project","commit_stats":null,"previous_names":["paulinhok14/projeto_ciencia_de_dados_embraer"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/paulinhok14/csgo-datascience-project","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paulinhok14%2Fcsgo-datascience-project","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paulinhok14%2Fcsgo-datascience-project/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paulinhok14%2Fcsgo-datascience-project/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paulinhok14%2Fcsgo-datascience-project/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/paulinhok14","download_url":"https://codeload.github.com/paulinhok14/csgo-datascience-project/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paulinhok14%2Fcsgo-datascience-project/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":271924842,"owners_count":24844493,"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":"2025-08-24T02:00:11.135Z","response_time":111,"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":["matplotlib","mlflow","numpy","python","scikit-learn","scipy","seaborn"],"created_at":"2025-07-15T15:11:06.050Z","updated_at":"2025-12-30T21:36:57.446Z","avatar_url":"https://github.com/paulinhok14.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# CS:GO Grenade Usage Analysis\n\n![CSGO Banner](docs/csgo.png)\n\n## Overview\nThis project analyzes the impact of grenade usage in Counter-Strike: Global Offensive (CS:GO) matches, focusing on the relationship between grenade damage and match outcomes/players rank across different maps.\n\n## Key Findings\n\n1. **Grenade Damage and Match Victory**\n   - Statistical analysis with 90% confidence level shows that teams dealing more grenade damage tend to win matches.\n   - The correlation varies significantly across different maps.\n   - This relationship is not focused on causality analysis (Higher Damage \u003e Wins or Wins \u003e Higher Damage).\n\n2. **Map-Specific Analysis**\n   - Maps like de_overpass and de_cache show stronger correlation (~66.67%) between grenade damage and victory\n   - Analysis includes heat maps of grenade landing positions for strategic insights\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"docs/de_overpass.png\" width=\"400\" alt=\"Overpass Analysis\" style=\"margin-right: 10px;\"/\u003e\n  \u003cimg src=\"docs/de_cbble.png\" width=\"400\" alt=\"Cache Analysis\"/\u003e\n\u003c/p\u003e\n\n## Methodology\n- Data analysis using Python (Pandas, Matplotlib, Seaborn)\n- Statistical tests including:\n  - Proportion comparison tests\n  - Confidence interval analysis\n  - Distribution analysis across different player rankings\n\n## Data Features Analyzed\n- Grenade landing coordinates (X, Y)\n- Damage dealt (HP + Armor)\n- Match outcomes\n- Player rankings\n- Map-specific statistics\n\n## Stack\n- Python 3.10\n- Pandas\n- Matplotlib\n- Seaborn\n- SciPy\n- Scikit-Learn\n- MLFlow\n- Statistical Methods\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpaulinhok14%2Fcsgo-datascience-project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpaulinhok14%2Fcsgo-datascience-project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpaulinhok14%2Fcsgo-datascience-project/lists"}