A random forest model that generate profit of $40K in 3000 races based on 10000+ horse-racing records with 98 raw features
-
Updated
Feb 2, 2022 - Jupyter Notebook
#
hkjc
Here are 7 public repositories matching this topic...
天喜數據庫 · 香港賽馬 AI 數據平台 (2016-2026, 67K+ 賽果, 每日自動更新)
-
Updated
Jul 10, 2026 - Python
LightGBM/XGBoost ensemble + Kelly criterion for HKJC horse racing. 2017 quinella +7.9% ROI, 2018 H1 OOS +2.6% ROI.
-
Updated
Jun 17, 2026 - Python
Honest HKJC horse-racing edge-detection research tool — ingests data, models win probabilities, walk-forward validates itself, and concludes NO-GO (no edge vs the market). Native desktop app, NO-BET by default.
flask machine-learning research quant horse-racing backtesting sports-betting hkjc pywebview market-efficiency
-
Updated
Jun 21, 2026 - Python
Improve this page
Add a description, image, and links to the hkjc topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the hkjc topic, visit your repo's landing page and select "manage topics."