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College athletics are a multi-billion dollar industry featuring hard-working student-athletes competing at a high level for national championships across a variety of different sports. Across the college sports landscape, coaches and players are always seeking an edge they can gain in order to obtain a competitive advantage over their opponents.

College athletics are a multi-billion dollar industry featuring hard-working student-athletes competing at a high level for national championships across a variety of different sports. Across the college sports landscape, coaches and players are always seeking an edge they can gain in order to obtain a competitive advantage over their opponents. While this may sound nefarious, the vast amounts of data about these games and student-athletes can be used to glean insights about the sports themselves in order to help student-athletes be more successful. Data analytics can be used to make sense of the available data by creating models and using other tools available that can predict how student-athletes and their teams will do in the future based on the data gathered from how they have performed in the past. Colleges and universities across the country compete in a vast array of sports. As a result of these differences, the sports with the largest amounts of data available will be the more popular college sports, such as football, men’s and women’s basketball, baseball and softball. Arizona State University, as a member of the Pac-12 conference, has a storied athletic tradition and decades of history in all of these sports, providing a large amount of data that can be used to analyze student-athlete success in these sports and help predict future success. However, data is available from numerous other college athletic programs that could provide a much larger sample to help predict with greater accuracy why certain teams and student-athletes are more successful than others. The explosion of analytics across the sports world has resulted in a new focus on utilizing statistical techniques to improve all aspects of different sports. Sports science has influenced medical departments, and model-building has been used to determine optimal in-game strategy and predict the outcomes of future games based on team strength. It is this latter approach that has become the focus of this paper, with football being used as a subject due to its vast popularity and massive supply of easily accessible data.

ContributorsLindstrom, Trent (Author) / Schneider, Laurence (Thesis director) / Wilson, Jeffrey (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05
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Description

College athletics are a multi-billion dollar industry featuring hard-working student-athletes competing at a high level for national championships across a variety of different sports. Across the college sports landscape, coaches and players are always seeking an edge they can gain in order to obtain a competitive advantage over their opponents.

College athletics are a multi-billion dollar industry featuring hard-working student-athletes competing at a high level for national championships across a variety of different sports. Across the college sports landscape, coaches and players are always seeking an edge they can gain in order to obtain a competitive advantage over their opponents. While this may sound nefarious, the vast amounts of data about these games and student-athletes can be used to glean insights about the sports themselves in order to help student-athletes be more successful. Data analytics can be used to make sense of the available data by creating models and using other tools available that can predict how student-athletes and their teams will do in the future based on the data gathered from how they have performed in the past. Colleges and universities across the country compete in a vast array of sports. As a result of these differences, the sports with the largest amounts of data available will be the more popular college sports, such as football, men’s and women’s basketball, baseball and softball. Arizona State University, as a member of the Pac-12 conference, has a storied athletic tradition and decades of history in all of these sports, providing a large amount of data that can be used to analyze student-athlete success in these sports and help predict future success. However, data is available from numerous other college athletic programs that could provide a much larger sample to help predict with greater accuracy why certain teams and student-athletes are more successful than others. The explosion of analytics across the sports world has resulted in a new focus on utilizing statistical techniques to improve all aspects of different sports. Sports science has influenced medical departments, and model-building has been used to determine optimal in-game strategy and predict the outcomes of future games based on team strength. It is this latter approach that has become the focus of this paper, with football being used as a subject due to its vast popularity and massive supply of easily accessible data.

ContributorsLindstrom, Trent (Author) / Schneider, Laurence (Thesis director) / Wilson, Jeffrey (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05
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Description

This report attempts to understand the effects of the many aspects that pertain to a woman’s path into the construction industry and their role in limiting women’s overall representation in the construction industry. More specifically, it aims to understand how upbringing, background, and culture impact women that do pursue careers

This report attempts to understand the effects of the many aspects that pertain to a woman’s path into the construction industry and their role in limiting women’s overall representation in the construction industry. More specifically, it aims to understand how upbringing, background, and culture impact women that do pursue careers in the construction industry. This paper presents some of the current and prominent issues being faced by women in in the construction industry, including those in the trades. These issues then contribute to their lack of representation and forceful exit. Additionally, it assesses personal narratives from a localized group of women who are currently employed at a large construction company. This information and these narratives are analyzed jointly to try and gain a better understanding of the current challenges being faced by women in comparison to those reported previously. This joint comparison allows for a deeper understanding of women’s perception of the construction industry as a whole.

ContributorsContreras, Marisa (Author) / Lou, Yingyan (Thesis director) / Parrish, Kristen (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Social Transformation (Contributor) / Civil, Environmental and Sustainable Eng Program (Contributor)
Created2022-05
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Description
A growing body of research suggests that there is more to course assessment than homework scores and test performance. This paper contributes to the empirical literature in economics and education by evaluating the impact of racial and gender congruency on the performance of ASU students. Expanding on previous research which

A growing body of research suggests that there is more to course assessment than homework scores and test performance. This paper contributes to the empirical literature in economics and education by evaluating the impact of racial and gender congruency on the performance of ASU students. Expanding on previous research which only covered elementary and high school, we are able to draw conclusions and policy recommendations to solve the racial achievement gap in the USA.
ContributorsAlmeida, Alexander (Author) / Aucejo, Esteban (Thesis director) / Larroucau, Tomas (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Economics Program in CLAS (Contributor)
Created2022-05
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ContributorsBuessing, Robert (Author) / Nian, Qiong (Thesis director) / Zhuang, Houlong (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2022-05
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ContributorsBuessing, Robert (Author) / Nian, Qiong (Thesis director) / Zhuang, Houlong (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2022-05
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ContributorsBuessing, Robert (Author) / Nian, Qiong (Thesis director) / Zhuang, Houlong (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2022-05
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ContributorsBuessing, Robert (Author) / Nian, Qiong (Thesis director) / Zhuang, Houlong (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2022-05
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ContributorsBuessing, Robert (Author) / Nian, Qiong (Thesis director) / Zhuang, Houlong (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2022-05
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ContributorsBuessing, Robert (Author) / Nian, Qiong (Thesis director) / Zhuang, Houlong (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2022-05