Intentionally fouling a team during their offensive possession is a strategy that basketball teams have employed for many years. Though popularized in the National Basketball Association (NBA), the technique has also made its way into Collegiate Basketball in recent years. The purpose of intentionally fouling is often to slow down opponent scoring and expose poor ...Read More

The NFL draft is an opportunity for teams to draft new players, address positional needs, and strengthen their roster for the upcoming season. Teams often trade players or compensation packages to secure certain prospects, which can be critical for team success. Wide receivers were selected as the focus of this study because the position is ...Read More

This study develops a predictive model for elite badminton match outcomes to identify the key performance drivers in the sport. Using a comprehensive dataset of 3,761 men’s singles matches from the BWF World Tour (2018-2021), features have been engineered to capture player skill, via custom Elo rating system, experience, recent form and match context. The ...Read More

Prior academic research in Formula One, most notably M¨uhlbauer (2010), concluded that starting grid positions were the strongest determinants of race outcomes while only examining the top eight finishers (fewer than 40%) of the competitors over a shortened sample of 4 seasons (2006–2009). This truncated sample approach limited the generalizability of its findings and likely ...Read More

In the NFL, “quarterback pressure” refers to defensive actions that disrupt a passer’s timing, decisions, and positioning. Numerous quantitative measures have been proposed, with mixed effectiveness. We introduce the Pocket Reduction Speed Score (PRSS), a geometric, tracking-based metric that quantifies how quickly the quarterback’s pocket shrinks. We apply the metric to player-tracking data from the ...Read More

Multi-Model Consensus: an Ensemble Approach to Basketball Predictions, authored by: Shivam Gupta, ‘26, Lambert High School, GA, and advisor Stephanie Beaulieu, Lambert High School, GA. Read More

With millions on the line every match, top soccer clubs still make critical substitution decisions based largely on intuition. This paper introduces an AI-powered Decision Support System (DSS) that brings data-driven rigor to one of the game’s most crucial tactical moments. Using fuzzy logic to model expert coaching knowledge, our system provides real-time substitution priorities ...Read More

A runner’s primary lead off first base creates leverage to steal second but also exposure to pickoffs. We develop a nested sequence of logistic models to estimate (i) pickoff attempts, (ii) pickoff success given an attempt, (iii) steal attempts given no pickoff, and (iv) steal success given an attempt, using 2024 MLB data and Baseball ...Read More

Forecasting touchdowns for NFL wide receivers is a challenging but valuable problem in football analytics and player evaluation. Touchdowns are notoriously volatile, influenced by red zone usage, quarterback play, and situational variance, making year-to-year outcomes difficult to predict. This study develops a temporal linear regression model to project wide receiver touchdown totals using a feature-rich ...Read More

Wharton Sports Analytics Journal Open Access · ISSN 3070-4065 2025 MONEYBALL ACADEMY, ROOKIE REVIEW Optimizing Lead Distance  AUTHOR Jack Whitney-Epstein, University of Pennsylvania (Moneyball Academy) Jackson Hubbard, University of Pennsylvania (Moneyball Academy) Lila Dodson, University of Pennsylvania (Moneyball Academy) William Deflorio, University of Pennsylvania (Moneyball Academy) Zach Sissman, University of...Read More

Tennis is one of the few sports in which the server initiates every point, making the serve the only stroke entirely under a player’s control. A powerful, well-placed serve can create immediate advantages, but identifying which characteristics most effectively translate serves into winning points remains unclear. Read More

Injuries in the NBA have become consequential not only for team success but for the financial costs those teams suffer. This study develops a machine learning framework that predicts next-game injury risk using publicly available box-score data, player attributes, and injury history, then translates these probabilities into expected financial costs. Combining five datasets from 2010-2022, ...Read More

This paper offers a simulation-based framework for predicting placements in official World Cube Association (WCA) competitions. Currently, the WCA uses psych-sheet rankings, which only present a competitor’s best average of five (Ao5) and singular solve. Our goal is to create a simulation framework that uses recent performance to estimate realistic placement probabilities. We construct kernel ...Read More

The United States Tennis Association (USTA) has historically used point-per-round rankings to determine competitive tournament entry and seeding, but this system often rewards participation over quality of play and can be distorted by random draw effects. Alternative systems such as Universal Tennis Rating (UTR) and World Tennis Number (WTN) use algorithmic predictive modeling based on ...Read More