Horse racing as an ML ranking problem: 1.18M runners, walk-forward validation and a very strong market baseline [D]

A machine-learning practitioner built a horse-racing ranking model trained on 1.18 million runners and evaluated it with walk-forward validation, finding that the betting market remains a very strong baseline. The project, posted to a machine-learning forum, revisits the statistical modeling approach used by Bill Benter's team for Hong Kong racing. The author reports the market baseline proved difficult to beat.

Hi 👋 long time lurker It’s been a few years since the last post about Horse Racing within this sub. A few years ago I was reading a popular science book and came across the story Bill Benter and the statistical models his team developed for Hong Kong racing. What stayed with me wasn’t simply the ide