Recent advancements in sports analytics are increasingly focused on leveraging machine learning and data-driven approaches to address complex challenges in player evaluation, injury prediction, and game strategy. For instance, new models are being developed to simulate counterfactual scenarios in football, allowing teams to assess player transfers with greater accuracy by considering tactical contexts and player interactions. In injury management, innovative survival modeling techniques are enhancing the ability to predict injury timelines for athletes, providing actionable insights that could improve player health and team performance. Additionally, research is uncovering the predictive power of biomechanical data in baseball, revealing how a pitcher's movements can inform pitch type anticipation without relying on ball-flight information. These developments not only refine scouting and training methodologies but also hold significant commercial potential by improving decision-making processes in player recruitment and injury prevention, ultimately driving competitive advantages in professional sports.
Gauging an individual's skill level is crucial, as it inherently shapes their behavior. Quantifying skill, however, is challenging because it is latent to the observed actions. To explore skill unders...
Injury occurrence in football poses significant challenges for athletes and teams, carrying personal, competitive, and financial consequences. While machine learning has been applied to injury predict...
Evaluating football player transfers is challenging because player actions depend strongly on tactical systems, teammates, and match context. Despite this complexity, recruitment decisions often rely ...
As sports training becomes more data-driven, traditional dart coaching based mainly on experience and visual observation is increasingly inadequate for high-precision, goal-oriented movements. Althoug...
Defensive coverage schemes in the National Football League (NFL) represent complex tactical patterns requiring coordinated assignments among defenders who must react dynamically to the offense's passi...
Evaluating badminton performance often requires expert coaching, which is rarely accessible for amateur players. We present adminSense, a smartwatch-based system for fine-grained badminton performance...
How much can a pitcher's body reveal about the upcoming pitch? We study this question at scale by classifying eight pitch types from monocular 3D pose sequences, without access to ball-flight data. Ou...
We present a practical, reproducible framework for identifying undervalued football players grounded in objective mispricing. Instead of relying on subjective expert labels, we estimate an expected ma...
Serves, especially first serves, are very important in professional tennis. Servers choose their serve directions strategically to maximize their winning chances while trying to be unpredictable. On t...