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International Journal of Computer Science in Sport
Scopus
ISSN 1684-4769 · Sciendo · 122 articles in the index
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Journal Article
Getting NBA Shots in Context: Analysing Basketball Shots with Graph Embeddings
Evaluating the quality of shots in basketball is crucial and requires considering the context in which they are taken. We introduce a graph neural network to process a graph based on player and ball tracking data to compute expected shot quality. We evaluate this model against other models focusing…
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Journal Article
Can machine learning distinguish between elite and non-elite rowers?
A major challenge for sports coaches and analysts is to identify critical elements of athletes’ movement patterns. A potentially relevant tool is machine learning, useful because of its ability to extract patterns from data. In the current study, we employed various deep learning frameworks…
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Journal Article
Two clusterings to capture basketball players’ shooting tendencies using tracking data: clustering of shooting styles and the shots themselves
Studies to understand the shooting preferences of basketball players relied exclusively on data on shot location, which did not lead to concrete understandings because they contained no information on how they moved to that location. Therefore, this study tried to cluster the players' shooting…
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Journal Article
Deep Learning with 3D ResNets for Comprehensive Dual-Lane Speed Climbing Video Analysis
Analyzing dual-lane speed climbing videos provides critical insights into data-driven performance evaluation in sports climbing. This study introduces an enhanced deep learning approach based on 3D ResNets to classify and analyze speed climbing states. Leveraging an annotated dataset of 872…
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Journal Article
Players’ Performance Prediction for Fantasy Premier League, Using Transformer-based Sentiment Analysis on News and Statistical Data
Fantasy sports have become increasingly popular, with millions of players engaging in strategic team management and competition. In the realm of Fantasy Premier League (FPL), effective player analysis and performance prediction are crucial for success in each game. This paper presents an innovative…
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Journal Article
Estimating the Relevance of First Offensive Shot Tactics in Table Tennis via Simulation Based on a Finite Markov Chain Model
Finite Markov chain modelling is a commonly used type of stochastic modelling employed in performance analysis of net games. Finite Markov chains are based on a state transition model which can be used to depict the game structure of net games as a succession of states which are defined as…
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Journal Article
NBA Results Forecast: From League Dynamics Analysis to Predictive Model Implementation
This study presents a machine learning-based approach to predicting the outcosmes of NBA games, with the aim of enhancing decision-making in sports betting and performance analysis. Using a dataset spanning 20 NBA seasons (2003–2023), we incorporated key features such as team statistics, player…
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Journal Article
A Deep Learning Approach Based on Interpretable Feature Importance for Predicting Sports Results
Football match result prediction is a challenging task that has been the subject of much research. Traditionally, predictions have been made by team managers, fans, and analysts based on their knowledge and experience. However and recently there has been an increased interest in predicting match…
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Journal Article
The Use of Momentum-Inspired Features in Pre-Game Prediction Models for the Sport of Ice Hockey
We make a unique contribution to momentum research by proposing a way to quantify momentum with performance indicators (i.e., features). We argue that due to measurable randomness in the NHL, sequential outcomes’ dependence or independence may not be the best way to approach momentum. Instead, we…
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Journal Article
Automatic Detection of Faults in Simulated Race Walking from a Fixed Smartphone Camera
Automatic fault detection is a major challenge in many sports. In race walking, judges visually detect faults according to the rules. Hence, automatic fault detection systems will help a training of race walking without experts’ visual judgement. Some studies have attempted to use sensors and…
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Journal Article
Development of Anthro-Fitness Model for Evaluating Firefighter Recruits’ Performance Readiness Using Machine Learning
The role of firefighters has evolved from traditional tasks like rescuing cats from trees and extinguishing house fires to more complex land, sea, and air rescues. The increasing demands for public safety necessitate rigorous training and high fitness levels for firefighters to manage their daily…
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Journal Article
Modified Bivariate Poisson-Lindley Model: Properties and Applications in Soccer
This paper presents the bivariate Poisson-new XLindley distribution (BPNXLD), which may be used to represent dependent and over-dispersed countdata. Among the characteristics considered are the correlation coefficient, mean, and variance of the distribution. Acomparison with several Bivariate…
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Journal Article
The Success-Score in Professional Football: a metric of playing style or a metric of match outcome?
In the growing field of data analysis in soccer tracking data is analyzed utilizing increasingly complex methods to account for the dynamic, multifactorial nature of the game. One promising approach is the Success-Score combining ball control and space control. The resulting metric is hypothesized…
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Journal Article
Comparison between six-week exergaming, conventional balance and no exercise training program on older adults’ balance and gait speed
We evaluated differences between a six-week exergame-training and a conventional balance training program on the balance and gait speed of older adults’ (>65 years). Forty-two healthy participants were recruited from independent living and community centers and randomized to one of three groups…
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Journal Article
Developing a High-Performance Sports Results Prediction Artificial Neural Network: Case Study on World Championship Boxing
Major sports events are watched by millions around the world and the prediction of event outcomes is a subject of interest to many stakeholders which underlines the relevance of continuous development and improvement of prediction models. This study uses a factorial design methodology to develop…
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Journal Article
A Pilot Study in Sensor Instrumented Training (SIT) - Ground Contact Time for Monitoring Fatigue and Curve Running Technique
This study examines the possibilities of sensor-instrumented training (SIT) in mid-distance running training sessions. Within this framework, variations of ground contact time (GCT) between straight and curved running, as well as GCT as a fatigue indicator, are explored. Seven experienced runners…
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Journal Article
Spin measurement system for table tennis balls based on asynchronous non-high-speed cameras
The spin of the ball plays a crucial role in table tennis tactics. However, it has rarely been measured and reported for the broadcast audience to better understand table tennis matches. This paper introduces a system designed to measure the spin of a table tennis ball without using electrically…
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Journal Article
Advancing Artistic Swimming Officiating and Performance Assessment: A Computer Vision Study Using MediaPipe
Artistic Swimming (AS) requires complete execution and synchronization of movements for performance evaluation. The interest in objective and subjective performance analysis worldwide in sports via valid and reliable Artificial Intelligence (AI) tools is spreading depending on the required analysis…
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Journal Article
The application of Machine and Deep Learning for technique and skill analysis in swing and team sport-specific movement: A systematic review
There is an ever-present need to objectively measure and analyze sports motion for the determination of correct patterns of motion for skill execution. Developments in performance analysis technologies such as inertial measuring units (IMUs) have resulted in enormous data generation. However, these…