**Data source:** Personal database of 1v1 basketball matches compiled from YouTube — player names, match dates, results, and scores recorded manually and via YouTube metadata.
**Tools:** Python (Elo algorithm), Chart.js (visualization), [1v1-hoops.com](http://1v1-hoops.com) (the full interactive version is here if you want to explore other players)
Elo formula: Standard 1500 base, K=32, with bonuses for PPV wins,
opponent dominance weight, and recency decay. Happy to share the
Python if anyone wants to fork it.
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**Data source:** Personal database of 1v1 basketball matches compiled from YouTube — player names, match dates, results, and scores recorded manually and via YouTube metadata.
**Tools:** Python (Elo algorithm), Chart.js (visualization), [1v1-hoops.com](http://1v1-hoops.com) (the full interactive version is here if you want to explore other players)
Elo formula: Standard 1500 base, K=32, with bonuses for PPV wins,
opponent dominance weight, and recency decay. Happy to share the
Python if anyone wants to fork it.