This project uses multiple linear regression to predict the value of Major League Baseball free agent contracts, inspired by the low volume of published research on this topic. I found one published paper that shared my research goal but its predictive power needed improvement. An in depth comparison of our models is carried out with k-fold cross validation mean square prediction error being used as the main standard. The predictor variables considered in my models were related to performance evaluation and position, and the response variable was inflation-adjusted average annual value of the contract. The result of the project is two linear regression models, one for hitters and one for pitchers.

Background: The idea of ​​achieving success in sport is something both players as well as fans dream of, but few clubs achieve it. Oakland Athletics succeeded in what many thought was impossible when in the 2002 season, they managed to perform better than most of their competitors whilst having one of the leagues smallest budgets, by recruiting undervalued players based on data and statistics. The concept of "moneyball" was coined therefrom and has since then influenced sport organizations more and more. But how the use of data and statistics has affected the governance in sport organizations is relatively unexplored.  Purpose: The purpose is to create an understanding of how data analytics has affected sports organizations  Method: The study is a qualitative multiple-case study based on an abductive approach to intertwine the theoretical framework together with the empirical data in an analysis that results in conclusions. Seven sport organizations within football and hockey have been the basis for the empirical data.  Conclusion: Data analytics has influenced the corporate governance in sport organizations in many ways. Data and statistics have provided an objective approach to investments and acquisitions of players that did not previously exist. As a result, sport organizations can recruit players who fit their strategy and style of play with greater accuracy. Furthermore, sport organizations can use data analytics as a competitive advantage by using resources more efficiently to find undervalued players in the market and experience both financial and sporting success. However, “moneyball” is a combination of objective aspects in terms of data and statistics, together with subjective aspects, where both are important to be able to use it as a competitive advantage. Today, data analytics is incorporated as part of sport operations where it is used as a part of designing strategies, as well as a basis for decision-making regarding investment appraisal and recruitment. / Bakgrund: Tanken om att nå sportslig framgång är något spelare såväl som fans drömmer om, men få klubbar uppnår det. Oakland Athletics lyckades med det som många trodde var omöjligt när de säsongen 2002, lyckades prestera bättre än de flesta av konkurrenterna samtidigt som man förhöll sig till en av ligans minsta budget genom att värva undervärderade spelare baserat på data och statistik. Konceptet “moneyball” myntades därifrån och har sedan dess influerat sportorganisationer mer och mer. Men hur användningen av data och statistik har påverkat styrningen i sportorganisationer är relativt outforskat.   Syfte: Syftet är att skapa förståelse för hur dataanalys har påverkat sportorganisationer.  Metod: Studien är en kvalitativ flerfallsstudie med utgångspunkt i en abduktiv ansats för att sammanfläta den teoretiska referensramen tillsammans med den empiriska datan i en analys som mynnar ut i konklusioner. Sju sportorganisationer inom fotboll och hockey har varit till grund för det empiriska datan.   Slutsats: Dataanalys har influerat verksamhetsstyrningen i sportorganisationer på många sätt. Data och statistik har tillfört ett objektivt synsätt vid investeringar och förvärv av spelare som tidigare inte fanns. Till följd av detta kan sportorganisationer rekrytera spelare som passar deras strategi och spelsystem med större träffsäkerhet. Därtill kan sportorganisationer använda dataanalys som konkurrensfördel genom att mer effektivt nyttja resurserna för att hitta undervärderade spelare i marknaden och uppleva både ekonomiska såväl som sportsliga framgångar. Däremot är “moneyball” en kombination av det objektiva i form av data och statistik tillsammans med det subjektiva, där båda aspekterna är betydelsefulla för att kunna använda det som en konkurrensfördel. Dataanalys är idag en integrerad del i sportsliga verksamheter där det används i utformandet av strategier såväl som underlag vid beslutsfattning gällande investeringsbedömning och rekrytering.

Thesis advisor: Richard McGowan / Can statistical analysis of professional basketball players lead to a more efficient evaluation of a player's worth? Following the recent success of statistic-driven baseball franchises, many basketball executives and followers are beginning to mine the sport's production in search of an all-encompassing player value rating. Teams could thus exploit undervalued players, leading to increased team and fan welfare. My thesis addresses this ongoing debate by examining various player and team statistics in the National Basketball Association (NBA). While I find significant relationships between individual efficiency statistics and team success, I also discover the paramount importance of defensive statistics and balanced team payrolls. This paper proposes a model that would help team executives find players who promote team efficiency, rather than individual production. / Thesis (BA) — Boston College, 2006. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Economics. / Discipline: College Honors Program.

Title: An analysis of a basketball player's movement during the game with special focus on the centre position Objectives: This work aims to analyse and then quantify the movement load on the pivot position and compare the differences between the number of movements of ČEZ Basketball Nymburk and Real Madrid Baloncesto in their final game. Methods: The basis of this empirical study is a quantitative research that uses the method of analysis and comparison. To obtain the data, I have analysed the most frequent movements carried out by players in the game. I have collected the number of movements per each second for four positions. Observed group are centres. Movements were described theoretically, biomechanically, technically, or by using rules. After that I have used the comparison to determine the differences, which were implemented into charts and qualified in detail. Results: Movement analysis confirmed my expectations. In comparison of the pivot of an elite foreign team with the best Czech team, I have noticed significant percentage differences. Real Madrid Baloncesto players were higher in position-specific moves, such as post-up, rebounding, boxing-out, contacts, and screens. Unlike the players of ČEZ Basketball Nymburk, who achieved significantly higher values in less significant movements...