Tennis Technology and Training
A data and analytics research group will soon release a paper that studies momentum swings in tennis. “Live Counter- Factual Analysis in Women’s Tennis Using Automatic Key- Moment Detection” uses machine learning to predict how certain events in a match will play out before they occur. The paper defines some new metrics for tennis that could potentially extend the state of the art of data analysis in tennis.
We’ve all seen it. A player is in control of a tennis match, seemingly cruising to victory and then – what seems like out of nowhere – their opponent gets an unexpected hold or break. Doubts start to set in. Before you know it, you’re watching a final-set decider.
Capturing Momentum in Tennis
The analysis techniques asks a series of “what-if” questions to determine the impact of events that can occur in the course of a tennis match. For example, if a player wins or loses the next point – how does that change the likelihood of winning the game, set, and match? The research paper describes an automatic method to determine key moments in a match using new “leverage” and “momentum” metrics.
A pre-release publicity announcement indicates that the leverage metric quantifies how important individual points are. Momentum, on the other hand, is a metric that characterizes which player is in control at specific points in the match. In combination those two metrics can identify the inflection points in a match where momentum swings actually occur.
From a player perspective, every point matters. Some points matter more than others. I think most of us already understand that, but soon there may be a quantitative method for determining exactly which ones.
I am eagerly anticipating the release of the full paper.
- Capturing Momentum in Tennis, The Analyst, March 4, 2022.
- Live Counter-Factual Analysis in Women’s Tennis using Automatic Key-Moment Detection. The paper hasn’t been released yet, but it will be at that link once it does.
