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Our research encompassed the prospect draft in baseball and looked at what type of player teams drafted to maximize value. We wanted to know which position returned the best value to the team that drafted them, and which level is safer to draft players from, college or high school. We

Our research encompassed the prospect draft in baseball and looked at what type of player teams drafted to maximize value. We wanted to know which position returned the best value to the team that drafted them, and which level is safer to draft players from, college or high school. We decided to look at draft data from 2006-2010 for the first ten rounds of players selected. Because there is only a monetary cap on players drafted in the first ten rounds we restricted our data to these players. Once we set up the parameters we compiled a spreadsheet of these players with both their signing bonuses and their wins above replacement (WAR). This allowed us to see how much a team was spending per win at the major league level. After the data was compiled we made pivot tables and graphs to visually represent our data and better understand the numbers. We found that the worst position that MLB teams could draft would be high school second baseman. They returned the lowest WAR of any player that we looked at. In general though high school players were more costly to sign and had lower WARs than their college counterparts making them, on average, a worse pick value wise. The best position you could pick was college shortstops. They had the trifecta of the best signability of all players, along with one of the highest WARs and lowest signing bonuses. These were three of the main factors that you want with your draft pick and they ranked near the top in all three categories. This research can help give guidelines to Major League teams as they go to select players in the draft. While there are always going to be exceptions to trends, by following the enclosed research teams can minimize risk in the draft.
ContributorsValentine, Robert (Co-author) / Johnson, Ben (Co-author) / Eaton, John (Thesis director) / Goegan, Brian (Committee member) / Department of Finance (Contributor) / Department of Economics (Contributor) / Department of Information Systems (Contributor) / School of Accountancy (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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In recent years, advanced metrics have dominated the game of Major League Baseball. One such metric, the Pythagorean Win-Loss Formula, is commonly used by fans, reporters, analysts and teams alike to use a team’s runs scored and runs allowed to estimate their expected winning percentage. However, this method is not

In recent years, advanced metrics have dominated the game of Major League Baseball. One such metric, the Pythagorean Win-Loss Formula, is commonly used by fans, reporters, analysts and teams alike to use a team’s runs scored and runs allowed to estimate their expected winning percentage. However, this method is not perfect, and shows notable room for improvement. One such area that could be improved is its ability to be affected drastically by a single blowout game, a game in which one team significantly outscores their opponent.<br/>We hypothesize that meaningless runs scored in blowouts are harming the predictive power of Pythagorean Win-Loss and similar win expectancy statistics such as the Linear Formula for Baseball and BaseRuns. We developed a win probability-based cutoff approach that tallied the score of each game once a certain win probability threshold was passed, effectively removing those meaningless runs from a team’s season-long runs scored and runs allowed totals. These truncated totals were then inserted into the Pythagorean Win-Loss and Linear Formulas and tested against the base models.<br/>The preliminary results show that, while certain runs are more meaningful than others depending on the situation in which they are scored, the base models more accurately predicted future record than our truncated versions. For now, there is not enough evidence to either confirm or reject our hypothesis. In this paper, we suggest several potential improvement strategies for the results.<br/>At the end, we address how these results speak to the importance of responsibility and restraint when using advanced statistics within reporting.

ContributorsIversen, Joshua Allen (Author) / Satpathy, Asish (Thesis director) / Kurland, Brett (Committee member) / Department of Information Systems (Contributor) / Walter Cronkite School of Journalism and Mass Comm (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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This study utilized a literature review and an analysis of Google Trends and Google News data in order to investigate the coverage that American men’s soccer gets from the media compared to that given to other major American sports. The literature review called upon a variety of peer-reviewed, scholarly entries,

This study utilized a literature review and an analysis of Google Trends and Google News data in order to investigate the coverage that American men’s soccer gets from the media compared to that given to other major American sports. The literature review called upon a variety of peer-reviewed, scholarly entries, as well as journalistic articles and stories, to holistically argue that soccer receives short-sighted coverage from the American media. This section discusses topics such as import substitution, stardom, and American exceptionalism. The Google analysis consisted of 30 specific comparisons in which one American soccer player was compared to another athlete playing in one of America’s major sports leagues. These comparisons allowed for concrete measurements in the difference in popularity and coverage between soccer players and their counterparts. Overall, both the literature review and Google analysis yielded firm and significant evidence that the American media’s coverage of soccer is lopsided, and that they do play a role in the sport’s difficulty to become popular in the American mainstream.

ContributorsHedges, Nicholas Kent (Author) / Kurland, Brett (Thesis director) / Reed, Sada (Committee member) / Walter Cronkite School of Journalism and Mass Comm (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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The purpose of this thesis is to cover the multiple aspects of Major League Baseball Expansion from 30 to 32 teams. The thesis can be divided into two parts with the first being the preparation and consideration for expansion, and the second half is about the execution and implementation of

The purpose of this thesis is to cover the multiple aspects of Major League Baseball Expansion from 30 to 32 teams. The thesis can be divided into two parts with the first being the preparation and consideration for expansion, and the second half is about the execution and implementation of adding two expansion teams to the league.
For years, Commissioner Rob Manfred has hinted and brought about the idea of adding two more teams to Major League Baseball (Mitchell). The growth of the game is of utmost importance, and they have made many changes to try to expand the growth of fans the past few years particularly catered to new and young fans. New rules like a pitch clock and mound visit limitations are examples of in game changes made to speed up the game, but they have also experimented with spring training and regular season games internationally or at new venues. In just the past decade, games have been played or planned (due to COVID-19 cancellations) in Monterrey, Mexico City, London, Tokyo, San Juan, Montreal, Las Vegas, Williamsport, and even Iowa. With the exception of the Williamsport Little League Classic and the Field of Dreams game in Iowa, all these locations had games to see what the atmosphere and logistics would be like with expansion in mind as a possibility in the future. With this in mind, this thesis will analyze and come to a conclusion on the following cities for the best fits for expansion: Monterrey, Mexico City, San Juan, Vancouver, Montreal, Las Vegas, Portland, Nashville, Raleigh, and San Antonio.
ContributorsLieberman, Jake Robert (Author) / Eaton, John (Thesis director) / McIntosh, Daniel (Committee member) / School of Accountancy (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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This thesis aims to develop a new way to value players for all teams in the MLB, despite the financial disparity. Displayed in the rest of this paper, is a player valuation model created around each team's salary level, focusing on player’s offensive output. The model functions in a way

This thesis aims to develop a new way to value players for all teams in the MLB, despite the financial disparity. Displayed in the rest of this paper, is a player valuation model created around each team's salary level, focusing on player’s offensive output. The model functions in a way that values players by their ability to help their team score runs and win games by setting parameters for salary expectations based on player performance. This allows for small market MLB teams, like the Cleveland Guardians, to build a roster of players around their specific salary limit, specifically to score the maximum runs and win games. On the contrary, the model also works for big market teams, like the Los Angeles Dodger, allowing them to project their larger salary limit to players and build their ideal roster as well.
ContributorsPearce, Eric (Author) / Lewis, Spencer (Co-author) / Licon, Lawrence (Thesis director) / Eaton, John (Committee member) / Barrett, The Honors College (Contributor) / School of Accountancy (Contributor) / Department of Finance (Contributor)
Created2022-05