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baseball 16 football 9 soccer 7 basketball 6 college football 5 golf 5 performance 5 competitive balance 4 game theory 4 probability 4 ratings 4 sports statistics 4 statistics 4 NFL 3 cluster analysis 3 home advantage 3 passing 3 ranking 3 simulation 3 strategy 3 volleyball 3 ANOVA 2 BCS 2 Bayesian hierarchical model 2 Gibbs sampler 2 Hall of Fame 2 MCMC 2 Markov chain 2 Monte Carlo 2 NCAA basketball 2 bias 2 formation 2 game-long process 2 hockey 2 modeling 2 multiple regression 2 offensive baseball performance 2 paired comparison 2 prediction 2 quantitative reasoning 2
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Undetermined 447
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Article 447
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Undetermined 446 English 1
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Jensen Shane T. 6 James, Piette 5 Alamar, Benjamin 4 Annis David H. 4 Annis, David 4 Jim, Albert 4 Joel, Oberstone 4 Nobuyoshi, Hirotsu 4 Ray, Stefani 4 W, Fellingham Gilbert 4 A, Yates Philip 3 Alexander, Braunstein 3 Ann, Kovalchik Stephanie 3 B, Jones Marshall 3 Brian, Macdonald 3 C, Alamar Benjamin 3 C, Thomas Andrew 3 Costa, Constantinou Anthony 3 D, Noubary Reza 3 Drew, Pasteur R. 3 Elliott, Fenton Norman 3 Fellingham Gilbert W. 3 Fellingham, Gilbert 3 J, Bracewell Paul 3 Rendleman Richard J. 3 Swartz Tim B. 3 Vittorio, Addona 3 West, Brady 3 Andreas, Groll 2 Andrew, Hoegh 2 Anthony, Bedford 2 Anthony, Kay 2 B, Swartz Tim 2 Baumer, Ben 2 Benjamin, Alamar 2 Bracewell, Paul 2 Brad, Null 2 Brian, Skinner 2 Cheng Edward K. 2 Connolly Robert A. 2
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Journal of Quantitative Analysis in Sports 447
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RePEc 447
Showing 171 - 180 of 447
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An Alternative to the NFL Draft Pick Value Chart Based upon Player Performance
Michael, Schuckers - In: Journal of Quantitative Analysis in Sports 7 (2011) 2, pp. 1-14
In this paper, we consider the National Football League Pick Value Chart and propose an alternative. The current Pick Value Chart was created approximately 20 years ago and has been used since to determine the value of draft selections for trading of draft selections. For this paper, we analyze...
Persistent link: https://www.econbiz.de/10009145349
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Reconsideration of the Best Batting Order in Baseball: Is the Order to Maximize the Expected Number of Runs Really the Best?
Nobuyoshi, Hirotsu - In: Journal of Quantitative Analysis in Sports 7 (2011) 2, pp. 1-12
In previous studies for analyzing the batting order of baseball games, the order is evaluated by its expected number of runs scored in a game, under the Markov chain model on the DEsopo and Lefkowitz runner advancement model. However, the order to maximize the expected number of runs may not be...
Persistent link: https://www.econbiz.de/10009145350
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Optimal Dynamic Clustering Through Relegation and Promotion: How to Design a Competitive Sports League
L, Puterman Martin; Qingchen, Wang - In: Journal of Quantitative Analysis in Sports 7 (2011) 2, pp. 1-34
This paper investigates how the structure of a relegation-promotion system impacts the competitiveness of a sports league. It proposes a rigorous mathematical model of a multi-division hierarchical sports league made up of teams with intrinsic skill levels (ISLs) that change from year to year....
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Defining the Performance Coefficient in Golf: A Case Study at the 2009 Masters
Andrew, Hoegh - In: Journal of Quantitative Analysis in Sports 7 (2011) 2, pp. 1-11
Unlike many other sports where only the top ten or twenty participants have a realistic shot at victory, when 144 players tee it up at a PGA tournament every participant has a legit chance at winning. In golf, even the greatest players lose more often than they win, and long-shots and unknowns...
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The Relationship between Leader Experience and Team Performance in Cross-Sectional and Longitudinal Designs
Thomas, Timmerman - In: Journal of Quantitative Analysis in Sports 7 (2011) 2, pp. 1-17
The purpose of this study was to examine the relationship between leader experience and team performance. Major League Baseball managers from 1903 to 2006 provided the context within which the relationships were studied. Experience was conceptualized in terms of games managed and seasons managed...
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An Extension of the Pythagorean Expectation for Association Football
H, Hamilton Howard - In: Journal of Quantitative Analysis in Sports 7 (2011) 2, pp. 1-18
This publication presents a formulation of an extension to the Pythagorean expectation for association football and other sports in which a draw result is a nontrivial event. Instead of estimating win percentage as in baseball, the extended Pythagorean estimates points won per game. A...
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NFL Prediction using Committees of Artificial Neural Networks
David John A.; Drew, Pasteur R.; Saif, Ahmad M.; … - In: Journal of Quantitative Analysis in Sports 7 (2011) 2, pp. 1-15
This paper analyzes the ability of a neural network model to predict the outcome of NFL games. This model uses only readily available statistics, such as passing yards, rushing yards, fumbles lost, and scoring. A key component of this model is the use of statistical differentials to compare...
Persistent link: https://www.econbiz.de/10009145355
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Comparing English Premier League Goalkeepers: Identifying the Pitch Actions that Differentiate the Best from the Rest
Joel, Oberstone - In: Journal of Quantitative Analysis in Sports 6 (2010) 1, pp. 1-19
The Opta Index is a prestigious performance measure used to assess English Premier League (EPL) football players. Although the Opta model is proprietary, the general structure uses a multiattribute collection of subjectively weighted pitch measures that either rewards or penalizes a player with...
Persistent link: https://www.econbiz.de/10008557463
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Predicting Overtime with the Pythagorean Formula
Rosenfeld Jason W.; I, Fisher Jake; Daniel, Adler; … - In: Journal of Quantitative Analysis in Sports 6 (2010) 2, pp. 1-19
In 1980, Bill James created the Pythagorean win expectation formula with a somewhat counterintuitive idea in mind. James believed, and his formula proved, that a baseball team's current runs scored to runs allowed ratio was better than a team's current record at predicting a team's future...
Persistent link: https://www.econbiz.de/10008557470
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Revisiting the Hot Hand Theory with Free Throw Data in a Multivariate Framework
Jeremy, Arkes - In: Journal of Quantitative Analysis in Sports 6 (2010) 1, pp. 1-12
Despite the conventional wisdom of the existence of the hot hand" in basketball, studies have found no or weak evidence for the hot hand in game situations, although stronger evidence in controlled settings. Almost all studies have tested for the hot hand in univariate frameworks, often with...
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