2025-12-09 –, Ernst-Curie
Padel has been one of the fastest-growing sports in the Netherlands in recent years. While it initially benefited from the rating facilities of its ‘big brother’ tennis, the KNLTB decided in 2024 to develop a dedicated, tailor-made rating system for padel, which has been in effect since 2025. The development process involved extensive analyses, simulations, and probability modeling on data from more than 300,000 padel matches, complemented by recommendations from the field.
In this presentation, the audience will be taken through the technical development process, as well as the unique characteristics of padel that were crucial in creating an effective rating system.
Elo systems are widely used to estimate player levels in situations where everyone plays against different opponents. The principle is simple: after each match, your rating shifts based on the expected win probability. Beating a stronger team increases your rating more than beating a weaker one.
In the Netherlands, padel initially used the existing tennis rating system. But tennis and padel have different characteristics that make this challenging. In tennis, a rating gap often translates quite predictably into a win probability. In padel, more factors come into play: mixed-gender teams, asymmetric pairings (e.g., two men versus a man and a woman), and the sport’s specific match dynamics.
Developing an effective padel rating system is a real-world problem. We found that data analysis is crucial, but without sport-specific knowledge and context, conclusions can be misleading.
We analyzed data from more than 300,000 padel matches and tested a range of models—from standard Elo variants to fully custom-built algorithms. Each system was evaluated on, amongst other things, two core metrics: speed (how quickly a system converges to a realistic player level) and efficiency (how stable ratings remain without unnecessary fluctuations).
This presentation will walk through the technical process, the model comparisons, and the padel-specific decisions that led to a rating system designed to work in real competition.
Max Brouwer (MSc) is a Data Scientist at the Royal Dutch Lawn Tennis Association (KNLTB). He graduated cum laude from the University of Groningen in 2021, earning a Master’s degree in Sport Science with a focus on applying computer vision and machine learning techniques to tennis.
At the KNLTB, Max contributes to both the Sport Science Team and the Data Team. In the Sport Science Team, he works on projects involving sensor technology, load monitoring, and match analysis. In the Data Team, his expertise extends to recreational tennis and padel, including the development of the new padel rating system.