Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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- All Subjects: Analytics
Description
This paper attempts to introduce analytics and regression techniques into the National Hockey League. Hockey as a sport has been a slow adapter of analytics, and this can be attributed to poor data collection methods. Using data collected for hockeyreference.com, and R statistical software, the number of wins a team experiences will be predicted using Goals For and Goals Against statistics from 2005-2017. The model showed statistical significance and strong normality throughout the data. The number of wins each team was expected to experience in 2016-2017 was predicted using the model and then compared to the actual number of games each team won. To further analyze the validity of the model, the expected playoff outcome for 2016-2017 was compared to the observed playoff outcome. The discussion focused on team's that did not fit the model or traditional analytics and expected forecasts. The possible discrepancies were analyzed using the Las Vegas Golden Knights as a case study. Possible next steps for data analysis are presented and the role of future technology and innovation in hockey analytics is discussed and predicted.
ContributorsVermeer, Brandon Elliot (Author) / Goegan, Brian (Thesis director) / Eaton, John (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The National Basketball Association is the world's most recognized professional basketball league. Athletes such as Kobe Bryant and Lebron James have transcended from being high school standouts to global icons, but their careers might not have panned out the same way if they weren't allowed to declare for the draft immediately upon graduating high school. In 2005, the NBA and the NBA Players Association agreed to implement an age limit for athletes declaring for the NBA Draft. Although this was supposed to reduce the quantity of younger players declaring for the draft, the rule has been ineffective as the average age of lottery picks, also known as the first 14 picks of the draft, has decreased since the rule's implementation. Adam Silver, the current commissioner of the NBA, has been vocal about potentially raising the minimum draft-eligible age once more because of NBA team executives calling recent draft picks unfit for the NBA. The purpose of this research is to examine if lottery picks are indeed "NBA ready" upon being drafted, and if there is a correlation between the age at which they are drafted, the pick at which they were selected, the length of their career, and their career success. Various statistical analysis techniques are utilized, such as the calculation of R-squared values and correlation coefficients, and the usage of t-tests and multiple regressions. Box score statistics such as minutes per game, points per game, rebounds, and assists as well as advanced metrics such as player efficiency rating, win shares, box plus/minus, and value over replacement player were the focal point of this study. Players drafted with lottery selections from the 1985-2016 drafts had their career statistics compiled and examined for this analysis in order to adequately conduct the regressions. The results indicate that although lottery picks are having a decreasing immediate impact upon being drafted, the younger an athlete is drafted, the more long-term success they can expect to achieve in the NBA.
ContributorsKender, Mitchell Edward (Author) / McIntosh, Daniel (Thesis director) / Eaton, John (Committee member) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05