Matching Items (4)
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- All Subjects: NBA
- All Subjects: Probability
- Creators: Goegan, Brian
Description
The NBA Draft has become one of the most exciting and unique events in sports. Draft decisions are so monumental; so crucial to be right, so disastrous to be wrong. The purpose of this project is to build a model that would help teams to predict which types of players perform at a high level upon entering the league. By using regression analysis to predict the rookie year PER (performance efficiency rating) as a dependent variable, teams would have some idea of whether their rookies were underperforming, excelling, or performing at a level they could expect. The independent variables and their statistical significance could help answer a host of questions that front offices have about players: If a player came from a worse conference, can we expect them to have a harder time adjusting? Will their shorter wingspan have a negative effect on their play in the NBA? Do guards or forwards tend to have higher PERs upon entering the league? To answer these questions, I've gathered data on every first round NBA draft pick from 2001-2014 who played at least one season of Division 1 NCAA basketball. The data consist of anthropometric measurements (height, wingspan, standing reach, etc.), NBA draft combine results (agility drills, sprint times, etc.) and their college statistics per 40 minutes in their final season of college basketball (points, rebounds, assist-to-turnover ratio, etc.). I then separated the data into seven different sets: aggregate, backcourt, frontcourt, guard, wing, forward, and big. For each of these data sets, I built a predictive model for rookie PER. In doing so, I aimed to gain both a broad understanding of what factors lead to translation of college basketball play to professional play, and also a precise understanding of how those factors change for each distinct position.
ContributorsMurphy, Benjamin Joseph (Author) / Goegan, Brian (Thesis director) / Marburger, Daniel (Committee member) / Economics Program in CLAS (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The NBA operates under a unique system with both forms of the salary cap. The league has a team salary cap that sets a limit that teams can spend on their entire roster. The NBA has a soft cap and a luxury tax system, meaning if teams spend over a determined amount, they are taxed for the salaries in excess. The league also has a player salary cap. The 1999 NBA collective bargaining agreement first introduced the individual player salary cap in the league. This cap sets a limit on what the best players can earn, otherwise known as the maximum contract. In an economic system with a soft team cap, the introduction of the player salary cap has important implications. The stated outcome of such a salary cap is to improve competitive balance and better distribute star players throughout the league. This study evaluated the 1990-2015 regular seasons to measure the impact of the player salary cap on competitive balance, the distribution of team payrolls, and the dispersion of star players. In accordance with the Rottenberg's invariance hypothesis, the player salary cap has hurt the players and benefited the owners by redistributing income from one party to the other, without impacting the distribution of talent in the league. The rule change has not affected competitive balance, while team payrolls have converged and star players have become more dispersed throughout the league. These changes hurt the league overall, preventing the maximization of revenues. Despite this inefficiency, the chance of the league moving to eliminate the player salary cap is low.
ContributorsWelu, Brian Andrew (Author) / Marburger, Daniel (Thesis director) / Goegan, Brian (Committee member) / Sandra Day O'Connor College of Law (Contributor) / Department of Economics (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
This paper proposes that voter decision making is determined by more than just the policy positions adopted by the candidates in the election as proposed by Antony Downs (1957). Using a vector valued voting model proposed by William Foster (2014), voter behavior can be described by a mathematical model. Voters assign scores to candidates based on both policy and non-policy considerations, then voters then decide which candidate they support based on which has a higher candidate score. The traditional assumption that most of the population will vote is replaced by a function describing the probability of voting based on candidate scores assigned by individual voters. If the voter's likelihood of voting is not certain, but rather modelled by a sigmoid curve, it has radical implications on party decisions and actions taken during an election cycle. The model also includes a significant interaction term between the candidate scores and the differential between the scores which enhances the Downsian model. The thesis is proposed in a similar manner to Downs' original presentation, including several allegorical and hypothetical examples of the model in action. The results of the model reveal that single issue voters can have a significant impact on election outcomes, and that the weight of non-policy considerations is high enough that political parties would spend large sums of money on campaigning. Future research will include creating an experiment to verify the interaction terms, as well as adjusting the model for individual costs so that more empirical analysis may be completed.
ContributorsCoulter, Jarod Maxwell (Author) / Foster, William (Thesis director) / Goegan, Brian (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Economics (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
This paper analyzes responses to a survey using a modified fourfold pattern of preference to determine if implicit information, once made explicit, is practically significant in nudging irrational decision makers towards more rational decisions. Respondents chose between two scenarios and an option for indifference for each of the four questions from the fourfold pattern with expected value being implicit information. Then respondents were asked familiarity with expected value and given the same four questions again but with the expected value for each scenario then explicitly given. Respondents were asked to give feedback if their answers had changed and if the addition of the explicit information was the reason for that change. Results found the addition of the explicit information in the form of expected value to be practically significant with ~90% of respondents who changed their answers giving that for the reason. In the implicit section of the survey, three out of four of the questions had a response majority of lower expected value answers given compared to the alternative. In the explicit section of the survey, all four questions achieved a response majority of higher expected value answers given compared to the alternative. In moving from the implicit to the explicit section, for each question, the scenario with lower expected value experienced a decrease in percentage of responses, and the scenario with higher expected value and indifference between the scenarios both experienced an increase in percentage of responses.
ContributorsJohnson, Matthew (Author) / Goegan, Brian (Thesis director) / Foster, William (Committee member) / School of Sustainability (Contributor) / Economics Program in CLAS (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05