Elementary econometric and strategic analysis of curling matches
John Fry, Mark Austin, Silvio Fanzon

TL;DR
This paper models curling matches using a Markov process, estimating probabilities econometrically, and predicts scoring patterns with analytical and simulation methods, providing insights into strategic decisions like blanking an end.
Contribution
It introduces a Markov model for curling, estimates key probabilities econometrically, and applies maximum entropy principles to predict scoring distributions and strategic decisions.
Findings
Points distribution follows a constrained geometric distribution.
Optimal strategies depend on scoring and possession dynamics.
Statistical analysis confirms model predictions with real match data.
Abstract
We develop a Markov model of curling matches, parametrised by the probability of winning an end and the probability distribution of scoring ends. In practical applications, these end-winning probabilities can be estimated econometrically, and are shown to depend on which team holds the hammer, as well as the offensive and defensive strengths of the respective teams. Using a maximum entropy argument, based on the idea of characteristic scoring patterns in curling, we predict that the points distribution of scoring ends should follow a constrained geometric distribution. We provide analytical results detailing when it is optimal to blank the end in preference to scoring one point and losing possession of the hammer. Statistical and simulation analysis of international curling matches is also performed.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSports Dynamics and Biomechanics
