The use of machine learning in sport outcome prediction: A review
The increase in the volume of structured and unstructured data related to more than just
sport events leads to the development and increased use of techniques that extract …
sport events leads to the development and increased use of techniques that extract …
Modeling player and team performance in basketball
In recent years, analytics has started to revolutionize the game of basketball: Quantitative
analyses of the game inform team strategy; management of player health and fitness; and …
analyses of the game inform team strategy; management of player health and fitness; and …
Searching for the GOAT of tennis win prediction
SA Kovalchik - Journal of Quantitative Analysis in Sports, 2016 - degruyter.com
Sports forecasting models–beyond their interest to bettors–are important resources for
sports analysts and coaches. Like the best athletes, the best forecasting models should be …
sports analysts and coaches. Like the best athletes, the best forecasting models should be …
Big data analytics for modeling scoring probability in basketball: The effect of shooting under high-pressure conditions
In this paper, we analyze the shooting performance of basketball players by examining the
factors that may generate high-pressure game situations. Using play-by-play data from the …
factors that may generate high-pressure game situations. Using play-by-play data from the …
[PDF][PDF] Predicting Win-Loss outcomes in MLB regular season games–A comparative study using data mining methods
CS Valero - International Journal of Computer Science in Sport, 2016 - sciendo.com
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 …
Baseball (MLB) game is an interesting and challenging task. Up to now, there is no definitive …
[LLIBRE][B] Basketball data science: With applications in R
P Zuccolotto, M Manisera - 2020 - books.google.com
Using data from one season of NBA games, Basketball Data Science: With Applications in R
is the perfect book for anyone interested in learning and applying data analytics in …
is the perfect book for anyone interested in learning and applying data analytics in …
Complex networks for community detection of basketball players
In this paper a weighted complex network is used to detect communities of basketball
players on the basis of their performances. A sparsification procedure to remove weak …
players on the basis of their performances. A sparsification procedure to remove weak …
Modelling the dynamic pattern of surface area in basketball and its effects on team performance
Because of the advent of GPS techniques, a wide range of scientific literature on Sport
Science is nowadays devoted to the analysis of players' movement in relation to team …
Science is nowadays devoted to the analysis of players' movement in relation to team …
Marginal contribution of game statistics to probability of winning at different levels of competition in basketball: Evidence from the Euroleague
MU Özmen - International Journal of Sports Science & …, 2016 - journals.sagepub.com
In this study, we analyse the marginal contribution of team level game statistics to the
probability of winning a basketball game at various competitive levels considering data from …
probability of winning a basketball game at various competitive levels considering data from …
A calibration method with dynamic updates for within-match forecasting of wins in tennis
S Kovalchik, M Reid - International Journal of Forecasting, 2019 - Elsevier
In-match predictions of player win probabilities for professional tennis matches have a wide
range of potential applications, including betting, fan engagement, and performance …
range of potential applications, including betting, fan engagement, and performance …