Abstract. George Lindsey was one of the first to present run scoring distributions of teams of Major League Baseball. One drawback of Lindsey’s approach is that his calculations represented a situation where the team is average. By use of a multi-nomial/multilevel modeling approach, we look more carefully how run-scoring distributions vary between teams and how run-scoring is affected by different covariates such as ballpark, pitcher quality, and clutch situations. By use of exchangeable models over ordinal regression coefficients, one gets a better understanding which covariates represent meaningful differences between run-scoring of teams
In this work we confirm a Markov chain model of baseball for 2013 Major League Baseball batting data...
Prediction of player performance is a key component in the construction of baseball team rosters. Tr...
This thesis is designed to explore whether a team’s success in any given season can be predicted or ...
Abstract. It has been noted that in many professional sports leagues a good predictor of a team’s en...
Sportscasters typically tell us about the batting average of a particular baseball hitter when runne...
The purpose of my project was to look into a less explored area of baseball analytics, by analyzing ...
The Pythagorean Expectation is widely used in the field of sabermetrics to estimate a baseball team...
While Major League Baseball has long been at the forefront of sports analytics, the most commonly us...
Sabermetrics are the application of statistical analysis to baseball records, especially in order to...
A baseball team\u27s offensive prowess is a function of two types of abilities: batting and baserunn...
The Valparaiso University baseball team, along with many other Division I programs, recruits basebal...
Using play-by-play data from Major League Baseball over the range of ten seasons\ud from 2000 to 200...
It is commonplace around baseball to involve statistical analysis in the evaluation of a player\u27s...
Can one understand the statistics of wins and losses of baseball teams? Are their consecutive-game ...
Baseball, like most other sports, has a set of tenets that began early and have survived virtually u...
In this work we confirm a Markov chain model of baseball for 2013 Major League Baseball batting data...
Prediction of player performance is a key component in the construction of baseball team rosters. Tr...
This thesis is designed to explore whether a team’s success in any given season can be predicted or ...
Abstract. It has been noted that in many professional sports leagues a good predictor of a team’s en...
Sportscasters typically tell us about the batting average of a particular baseball hitter when runne...
The purpose of my project was to look into a less explored area of baseball analytics, by analyzing ...
The Pythagorean Expectation is widely used in the field of sabermetrics to estimate a baseball team...
While Major League Baseball has long been at the forefront of sports analytics, the most commonly us...
Sabermetrics are the application of statistical analysis to baseball records, especially in order to...
A baseball team\u27s offensive prowess is a function of two types of abilities: batting and baserunn...
The Valparaiso University baseball team, along with many other Division I programs, recruits basebal...
Using play-by-play data from Major League Baseball over the range of ten seasons\ud from 2000 to 200...
It is commonplace around baseball to involve statistical analysis in the evaluation of a player\u27s...
Can one understand the statistics of wins and losses of baseball teams? Are their consecutive-game ...
Baseball, like most other sports, has a set of tenets that began early and have survived virtually u...
In this work we confirm a Markov chain model of baseball for 2013 Major League Baseball batting data...
Prediction of player performance is a key component in the construction of baseball team rosters. Tr...
This thesis is designed to explore whether a team’s success in any given season can be predicted or ...