Related papers: KabaddiPy: A package to enable access to Professio…
This paper aims to apply network analysis to all players who have participated in the Indian Pro Kabaddi League since its inception. The Kabaddi network has been constructed based on the number of teams and players they have played with.…
Fantasy Premier League engages the football community in selecting the Premier League players who will perform best from gameweek to gameweek. Access to accurate performance forecasts gives participants an edge over competitors by guiding…
This paper presents a structured and comprehensive dataset corresponding to the 2025 Asia Cup T20 cricket tournament, designed to facilitate data-driven research in sports analytics. The dataset comprises records from all 19 matches of the…
Lee Sedol is on a winning streak--does this legend rise again after the competition with AlphaGo? Ke Jie is invincible in the world championship--can he still win the title this time? Go is one of the most popular board games in East Asia,…
Advancements in technology have recently allowed us to collect and analyse large-scale fine-grained data about human performance, drastically changing the way we approach sports. Here, we provide the first comprehensive analysis of…
In fantasy sports, strategic thinking-not mere luck-often defines who wins and who falls short. As fantasy cricket grows in popularity across India, understanding whether success stems from skill or chance has become both an analytical and…
Video storytelling is essential for sports performance analysis and fan engagement, enabling sports professionals and fans to effectively communicate and interpret the spatial and temporal dynamics of gameplay. Traditional methods rely on…
The present work introduces floodlight, an open source Python package built to support and automate team sport data analysis. It is specifically designed for the scientific analysis of spatiotemporal tracking data, event data, and game…
Player tracking data remains out of reach for many professional football teams as their video feeds are not sufficiently high quality for computer vision technologies to be used. To help bridge this gap, we present a method that can…
Computer-aided support and analysis are becoming increasingly important in the modern world of sports. The scouting of potential prospective players, performance as well as match analysis, and the monitoring of training programs rely more…
Sports analytics -- broadly defined as the pursuit of improvement in athletic performance through the analysis of data -- has expanded its footprint both in the professional sports industry and in academia over the past 30 years. In this…
Sports, due to their global reach and impact-rich prediction tasks, are an exciting domain to deploy machine learning models. However, data from conventional sports is often unsuitable for research use due to its size, veracity, and…
The evolution of digital technology and the increasing popularity of sports inspired the innovators to take the experience of users with a proclivity towards sports to a whole new different level, by introducing Fantasy Sports Platforms…
Most historical National Football League (NFL) analysis, both mainstream and academic, has relied on public, play-level data to generate team and player comparisons. Given the number of oft omitted variables that impact on-field results,…
Cricket is a game played between two teams which consists of eleven players each. Nowadays cricket game is becoming more and more popular in Bangladesh and other South Asian Countries. Before a match people are very enthusiastic about team…
Proper training and analytics in eSports require accurately collected and annotated data. Most eSports research focuses exclusively on in-game data analysis, and there is a lack of prior work involving eSports athletes' psychophysiological…
Experts in racket sports like tennis and badminton use tactical analysis to gain insight into competitors' playing styles. Many data-driven methods apply pattern mining to racket sports data -- which is often recorded as multivariate event…
Technological advances have paved the way for collecting high-resolution network data in basketball, football, and other team-based sports. Such data consist of interactions among players of competing teams indexed by space and time.…
Recently, data mining studies are being successfully conducted to estimate several parameters in a variety of domains. Data mining techniques have attracted the attention of the information industry and society as a whole, due to a large…
This paper considers the use of observed and predicted match statistics as inputs to forecasts of the outcomes of football matches. It is shown that, were it possible to know the match statistics in advance, highly informative forecasts of…