SearcharxivSearch

arXiv subjects

Robyn Ritchie

Publications and source records attributed to Robyn Ritchie.

2 recordsLinked to original sources

Opening the House: Datasets for Mixed Doubles Curling

We introduce the most comprehensive publicly available datasets for mixed doubles curling, constructed from eleven top-level tournaments from the CurlIT (https://curlit.com/results) Results Booklets spanning 53 countries, 1,112 games, and nearly 70,000 recorded shots. While curling analytics has grown in recent years, mixed doubles remains under-served due to limited access to data. Using a combined text-scraping and image-processing pipeline, we extract and standardize detailed game- and shot-level information, including player statistics, hammer possession, Power Play usage, stone coordinates, and post-shot scoring states. We describe the data engineering workflow, highlight challenges in parsing historical records, and derive additional contextual features that enable rigorous strategic analysis. Using these datasets, we present initial insights into shot selection and success rates, scoring distributions, and team efficiencies, illustrating key differences between mixed doubles and traditional 4-player curling. We highlight various ways to analyze this type of data including from a shot-, end-, game- or team-level to display its versatilely. The resulting resources provide a foundation for advanced performance modeling, strategic evaluation, and future research in mixed doubles curling analytics, supporting broader analytical engagement with this rapidly growing discipline.

stat.AP

Pass Evaluation in Women's Olympic Hockey

Passing during power plays in hockey is a crucial component to move one's team closer to scoring a goal. With the use of women's ice hockey event and tracking data from the elimination round games during the 2022 Winter Olympics, we evaluate passing and assess players' risk-reward behaviours in these high intensity moments. We develop a model for probabilistic passing that accounts for the order of arrival to a desired location and potential interceptions along the way. This model is based on a player-specific motion model and a puck motion model that determines how far each player can reach in the time it takes the puck to get to a target. In addition, we model the rink control for each team and the scoring probability of the offensive team. These models are then combined into novel metrics for quantifying where a pass should be made such that it would result in a high scoring opportunity or result in a high chance of maintaining possession. Finally, we use various metrics to evaluate passes made throughout the available power plays and compare them to the optimal options at that time. This can be used to identify players' risk-reward tendencies and can be used by coaches when selecting which players are best suited for a power play given the circumstances of the game.

stat.AP