ViTs for Action Classification in Videos: An Approach to Risky Tackle Detection in American Football Practice Videos

• URL: http://arxiv.org/abs/2604.01318v1
• Date: Wed, 01 Apr 2026 18:43:56 GMT
• Title: ViTs for Action Classification in Videos: An Approach to Risky Tackle Detection in American Football Practice Videos
• Abstract summary: We present a method for detecting risky tackles in American football practice videos.<n>Our work contains 733 single-athlete-dummy tackle clips, each temporally localized around first point contact.<n>Using a Vision transformer-based model with imbalance-aware training, we obtain risky recall of 0.67 and Risky F1 of 0.59.
• Score: 0.5046831208137846
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Early identification of hazardous actions in contact sports enables timely intervention and improves player safety. We present a method for detecting risky tackles in American football practice videos and introduce a substantially expanded dataset for this task. Our work contains 733 single-athlete-dummy tackle clips, each temporally localized around first point contact and labeled with a strike zone component of the standardized Assessment for Tackling Technique (SATT-3), extending prior work that reported 178 annotated videos. Using a Vision transformer-based model with imbalance-aware training, we obtain risky recall of 0.67 and Risky F1 of 0.59 under crossvalidation. Relative to the previous baseline in a smaller subset (risky recall of 0.58; Risky F1 0.56 ), our approach improves risky recall by more than 8% points on a much larger dataset. These results indicate that the vision transformer-based video analysis, coupled with careful handling of class imbalance, can reliably detect rare but safety-critical tackling patterns, offering a practical pathway toward coach-centered injury prevention tools.

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