arXiv:2510. 20454v2 Announce Type: replace Abstract: Intransitive player dominance, where player A beats B, B beats C, but C beats A, is common in competitive tennis.
arXiv:2609.07617v1 Announce Type: new Abstract: With the rise of live sports betting in recent years, tennis forecasting has expanded from pre-match prediction to models that update win probabilities...
arXiv:2608. 02081v1 Announce Type: new Abstract: In this paper, we study prediction problems for paired comparison data, for example, predicting the win probability between two unmatched players and ranking all the players according to the order of their strengths by using win probability data between two matched players.
arXiv:2607. 23509v1 Announce Type: new Abstract: We present two approaches for predicting tennis match outcomes using topological data analysis and graph theory on ATP singles matches from 2000-2025.
The paper introduces the Hierarchical Possession-aware Graph Pointer Network (HPGPN) for selecting pass receivers in football analytics. HPGPN treats the task as a variable-size candidate prediction problem, modeling current player interactions, local event context, and possession-level temporal dynamics using a graph representation. Experiments on public football event and freeze-frame datasets show that HPGPN improves pass receiver selection performance, with ablation studies confirming the value of graph-based interaction modeling, fixed event context, and dual-branch dynamic possession-history modeling.
The paper introduces PART, a multimodal predictive framework for tennis that combines physiological, training, sleep, questionnaire, jump, and video data from nine collegiate players to assess overall wellness, injury risk, physical capability, and playing style. Using machine learning and deep learning, PART provides holistic athlete assessments and forecasts specific injury risks to body areas such as elbows and knees. Evaluation shows strong performance in predicting wellness and injury risk, with potential benefits for recreational players who often injure themselves due to poor technique.
arXiv:2609.25569v1 Announce Type: new Abstract: Soccer tactics are interactive: an attacking action changes the opponent's defensive problem, and the observed response depends on the multi-agent matc...
arXiv:2608. 03416v1 Announce Type: new Abstract: Large language models (LLMs) are now regularly asked to forecast real-world events, but comparisons are often difficult because models receive different information, use different tools, and are evaluated under different rules.
Soccer tactics are interactive: an attacking action changes the opponent's defensive problem, and the observed response depends on the multi-agent match state. We introduce SambaGraph, an action--reac...
PACIFIER is a graph‑learning framework that generates intervention sequences to reduce opinion polarization in online social networks modeled by the Friedkin‑Johnsen framework. It uses history‑aware node representations and both greedy and reinforcement‑learning strategies to score actions, supporting multiple moderation types and continuous opinions. Trained on small synthetic graphs, PACIFIER transfers effectively to large real‑world Twitter networks, outperforming baselines by up to 35.3% and achieving near‑oracle performance while being significantly faster.
CHAMP is a cross‑domain matchmaking framework for Multiplayer Online Battle Arena games that tackles cold‑start, distribution shift, and data‑scarcity issues by using hybrid player profiles and a Domain‑Aware Win‑rate Network (DAWN). DAWN learns mode‑conditioned representations through a shared network, achieving 67.73% win‑rate prediction accuracy and improving match balance in large‑scale A/B tests. The system reduces imbalanced matches, notably cutting 5‑minute kill crushing rates by up to 20.73% for lower‑tier players.
arXiv:2609.24467v1 Announce Type: new Abstract: Music festival lineups emerge from complex relationships among artists, genres, releases, labels, and past performances, making the prediction of futur...
arXiv:2608.29563v1 Announce Type: cross Abstract: School coaches prepare for opponents with game film and intuition. The analytics tools of professional teams stay out of reach. We ask how far public...