O’Donoghue, P. Ball, D. Eustace, J. McFarlan, B. Nisotaki, M.
Published in
International Journal of Computer Science in Sport
The current investigation compared 12 models of outcomes of international rugby union matches and then used the most accurate model to investigate performances within the 2015 Rugby World Cup. The underlying linear regression models were used within a simulation package that introduced random variability about performance evidenced by the residual ...
Stuart, Morgan
Published in
International Journal of Computer Science in Sport
Sports informatics and computer science in sport are perhaps the most exciting and fast-moving disciplines across all of sports science. The tremendous parallel growth in digital technology, non-invasive sensor devices, computer vision and machine learning have empowered sports analytics in ways perhaps never seen before. This growth provides great...
Serrien, B. Clijsen, R. Anders, S. Goossens, M. Baeyens, J-P.
Published in
International Journal of Computer Science in Sport
In sports biomechanics and motor control, a thorough study of coordination variability is important to understanding how the human movement system is organized. From a more applied sport science perspective, knowledge about performance variability is essential regarding the evaluation of true sport specific effects of any intervention. While there ...
Wenninger, S. Lames, M.
Published in
International Journal of Computer Science in Sport
The aim of this study was to identify the impact of different tactical behaviors on the winning probability in table tennis. The performance analysis was done by mathematical simulation using a Markov chain model. 259 high-level table tennis games were evaluated by means of a new simulation approach using numerical derivation to remove the necessit...
Carey, D. L. Ong, K. Morris, M. E. Crow, J. Crossley, K. M.
Published in
International Journal of Computer Science in Sport
The ability of machine learning techniques to predict athlete ratings of perceived exertion (RPE) was investigated in professional Australian football players. RPE is commonly used to quantifying internal training loads and manage injury risk in team sports. Data from global positioning systems, heart-rate monitors, accelerometers and wellness ques...
Soto Valero, C.
Published in
International Journal of Computer Science in Sport
Baseball is a statistically filled sport, and predicting the winner of a particular Major League Baseball (MLB) game is an interesting and challenging task. Up to now, there is no definitive formula for determining what factors will conduct a team to victory, but through the analysis of many years of historical records many trends could emerge. Rec...
Mangan, S. Collins, K.
Published in
International Journal of Computer Science in Sport
AIM: The current investigation aimed to create an objective rating of Gaelic football teams and to examine factors relating to a team's rating. METHOD: A modified version of the Elo Ratings formula (Elo, 1978) was used to rate Gaelic football teams. A total of 1101 competitive senior Inter County matches from 2010-2015 were incorporated into calcul...
Carey, D. L. Ong, K. Whiteley, R. Crossley, K. M. Crow, J. Morris, M. E.
Published in
International Journal of Computer Science in Sport
To investigate whether training load monitoring data could be used to predict injuries in elite Australian football players, data were collected from athletes over 3 seasons at an Australian football club. Loads were quantified using GPS devices, accelerometers and player perceived exertion ratings. Absolute and relative training load metrics were ...
Yaldo, L. Shamir, L.
Published in
International Journal of Computer Science in Sport
The wage of a football player is a function of numerous aspects such as the player’s skills, performance in the previous seasons, age, trajectory of improvement, personality, and more. Based on these aspects, salaries of football players are determined through negotiation between the team management and the agents. In this study we propose an objec...
Hvattum, L. M.
Published in
International Journal of Computer Science in Sport
Ordinal regression models are frequently used in academic literature to model outcomes of soccer matches, and seem to be preferred over nominal models. One reason is that, obviously, there is a natural hierarchy of outcomes, with victory being preferred to a draw and a draw being preferred to a loss. However, the often used ordinal models have an a...
