Add to ORKGThis paper explores how changing various end game statistics effects a given teams probability of winning a game in the National Football League (NFL). Data from the 2000-2016 NFL seasons is split into two subsets, one for teams winning at halftime, another for losing teams. Using this data an empirical model is estimated to study how the determinants of a team’s success differ between the two sets of data. Overall, the factors which determine a team’s outcome are consistent between the two subsets, varying primarily by magnitude of the effect
In this paper, we use estimators of variable importance from the ensemble learning technique of rand...
We examine whether the predictions of minimax in zero-sum games holds under highly incentivized cond...
This is an analysis on National Football League (NFL) data for the 2013-2014 regular season. The mai...
Although analytics has become commonplace within the sports industry and is growing within the Natio...
This dissertation considers the most important aspects of success in the National Football League (N...
The purpose of this research is to explain the value of turnovers lost, turnovers gained, total yard...
This analysis is to determine if the winner against the spread of NFL regular season games can be pr...
How much does a fumble affect the probability of winning an American football game? How balanced sho...
Abstract. An econometric analysis of the 2016 National Football League season is conducted with resp...
A quarterback is often seen as the key component to a winning football team. This study is meant to ...
Trailing in sports is associated with losing, but can trailing operate as a powerful motivator that ...
We consider the question of how important winning the first game of the season is to making the play...
American football has undergone many significant changes since its first recorded game between Rutge...
Given the 2019 NCAA football data, this thesis explores the effect of several variablessuch as oppon...
This research is based on the Five Factors that were devised by Bill Connelly of SBNation. The Five ...
In this paper, we use estimators of variable importance from the ensemble learning technique of rand...
We examine whether the predictions of minimax in zero-sum games holds under highly incentivized cond...
This is an analysis on National Football League (NFL) data for the 2013-2014 regular season. The mai...
Although analytics has become commonplace within the sports industry and is growing within the Natio...
This dissertation considers the most important aspects of success in the National Football League (N...
The purpose of this research is to explain the value of turnovers lost, turnovers gained, total yard...
This analysis is to determine if the winner against the spread of NFL regular season games can be pr...
How much does a fumble affect the probability of winning an American football game? How balanced sho...
Abstract. An econometric analysis of the 2016 National Football League season is conducted with resp...
A quarterback is often seen as the key component to a winning football team. This study is meant to ...
Trailing in sports is associated with losing, but can trailing operate as a powerful motivator that ...
We consider the question of how important winning the first game of the season is to making the play...
American football has undergone many significant changes since its first recorded game between Rutge...
Given the 2019 NCAA football data, this thesis explores the effect of several variablessuch as oppon...
This research is based on the Five Factors that were devised by Bill Connelly of SBNation. The Five ...
In this paper, we use estimators of variable importance from the ensemble learning technique of rand...
We examine whether the predictions of minimax in zero-sum games holds under highly incentivized cond...
This is an analysis on National Football League (NFL) data for the 2013-2014 regular season. The mai...