Sports Sciences Commons^™

Analyzing Sports Training Data With Machine Learning Techniques, Rehana Mahfuz, Zeinab Mourad, Aly El Gamal

The Summer Undergraduate Research Fellowship (SURF) Symposium

In the sports industry, there has not been enough effort in analyzing the personalized monitoring data of athletes collected during training sessions. This research is an attempt to find meaningful patterns in the Purdue Women’s Soccer training data that could help the coach design more efficient training sessions. We are specifically interested in studying this problem as an unsupervised learning problem. Our initial attempt is to cluster the players as well as drills into groups using k-means, c-means and spectral clustering algorithms, combined with feature transformation and reduction steps. These basic algorithms serve as a benchmark to measure performance improvements …