Airtime
Measure jump height from video by stepping through takeoff and landing frames
翻译准备中
AI 摘要 · 网站内容
尚未收集仓库信息。
尚未检测到更新。GitHub 发布版本后会显示在这里。
Rank every active NBA player head to head (Elo), then compare with a stats robot
翻译准备中
取自仓库 README
正在加载完整 README。
查看完整 README ↗Rank every active NBA player head to head, then see how your list compares with a stats robot. Live at https://ellioshow1.github.io/nba-ranker/
Everything is stored in your browser. Nothing is sent anywhere.
Blends three box-score parts, each standardised across players with 300+ minutes:
Last season and this season are pooled, this season's games counting double, so early in a season it leans on last
season. Per-36 rates are regressed toward a fringe-rotation level with 600 minutes, so small samples can't spike.
Tuning lives in ROBOT in js/stats.js.
scripts/build_data.py pulls every rostered player (with injuries) and their regular-season stats for last season
and this season from ESPN's public JSON endpoints, into data/players.json. The GitHub Action
(.github/workflows/deploy.yml) rebuilds it on every push and daily at 09:00 UTC, then deploys. If ESPN is
unreachable it deploys the committed copy, so refresh that now and then:
python scripts/build_data.py
Double-click start.bat, or run python -m http.server 8771 --bind 127.0.0.1 here and open http://127.0.0.1:8771/
js/elo.js: Elo ratings (replayed from your picks), pairing, progress levelsjs/stats.js: season lines, the robot, filters and presetsjs/share.js: share links (ids packed 3 bytes each, base64url) and the share imagejs/app.js: UIscripts/build_data.py: data build