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Abstract

This study describes the process of modernizing the approach of the Southern Methodist University (SMU) Men's Soccer coaching staff through the use of location and tracking data from their matches in the 2019 season. This study utilizes a variety of modeling and analysis techniques to explore and categorize the data and use it to evaluate the types of plays that are most often correlated with victories. This study's contribution to college soccer analytics includes the implementation of a model to determine individual players' performance, the production of team-level metrics, and visualizations to increase the efficiency of the coaching staff's efforts. This research can serve as a blueprint for college soccer programs to utilize data science in their coaching.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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