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Forecasting Most Valuable Players of the National Basketball Association
FORECASTING MOST VALUABLE PLAYERS OF THE NATIONAL BASKETBALL ASSOCIATION by Jordan Malik McCorey A thesis submitted to the faculty of The University of North Carolina at Charlotte in partial fulfillment of the requirements for the degree of Master of Science in Engineering Management Charlotte 2021 Approved by: _______________________________ Dr. Tao Hong _______________________________ Dr. Linquan Bai _______________________________ Dr. Pu Wang ii ©2021 Jordan Malik McCorey ALL RIGHTS RESERVED iii ABSTRACT JORDAN MALIK MCCOREY. Forecasting Most Valuable Players of the National Basketball Association. (Under the direction of DR. TAO HONG) This thesis aims at developing models that would accurately forecast the Most Valuable Player (MVP) of the National Basketball Association (NBA). R programming language was used in this study to implement different techniques, such as Artificial Neural Networks (ANN), K- Nearest Neighbors (KNN), and Linear Regression Models (LRM). NBA statistics were extracted from all of the past MVP recipients and the top five runner-up MVP candidates from the last ten seasons (2009-2019). The objective is to forecast the Point Total Ratio (PTR) for MVP during the regular season. Seven different underlying models were created and applied to the three techniques in order to produce potential outputs for the 2018-19 season. The best models were then selected and optimized to form the MVP forecasting algorithm, which was validated by predicting the MVP of the 2019-20 season. Ultimately, two underlying models were most robust under the LRM framework, which is considered the champion approach. As a result, two combination models were constructed based on the champion approach and proved to be most efficient. -
1 Una Revisión De Los Sistemas De Valoración De Jugadores De Baloncesto (I)
Una revisión de los sistemas de valoración de jugadores de baloncesto (I). Descripción de los métodos existentes. Martínez, Jose A. Departamento de Economía de la Empresa. Universidad Politécnica de Cartagena. Facultad de Ciencias de la Empresa. Calle Real, 3. 30201. Cartagena. España. Tel.: +34 968 32 57 76; Fax: +34 968 32 70 81. E-mail: [email protected] Cómo citar este artículo: Este artículo es una versión del aceptado para publicación en la Revista Internacional de Derecho y Gestión del Deporte. Martínez, J. A. (2010). Una revisión de los sistemas de valoración de jugadores de baloncesto (I). Descripción de los métodos existentes. Revista Internacional de Derecho y Gestión del Deporte, 10, How to cite this paper: This article is a draft of the accepted paper to be published in the Revista Internacional de Derecho y Gestión del Deporte Martínez, J. A. (2010). Una revisión de los sistemas de valoración de jugadores de baloncesto (I). Descripción de los métodos existentes. Revista Internacional de Derecho y Gestión del Deporte, 10, 1 Una revisión de los sistemas de valoración de jugadores de baloncesto (I). Descripción de los métodos existentes. A review of the basketball player evaluation metrics (I) A description of the existing methods Resumen En este trabajo se realiza una completa revisión de los sistemas de valoración de jugadores de baloncesto que actualmente se utilizan por analistas en todo el mundo, con el fin de describir el gran conjunto de sistemas a disposición de los decisores en los equipos. Así, se pretende facilitar la toma de decisiones directivas racionales, en base a la disposición de un ingente volumen de información sobre la productividad de los jugadores. -
Electronic Journal of Applied Statistical Analysis EJASA, Electron
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Università del Salento: ESE - Salento University Publishing Electronic Journal of Applied Statistical Analysis EJASA, Electron. J. App. Stat. Anal. http://siba-ese.unisalento.it/index.php/ejasa/index e-ISSN: 2070-5948 DOI: 10.1285/i20705948v12n2p362 High performance of professional basketball play- ers and the settings to measure their regularity: evidence from the Spanish ACB League By Rom´anSalmer´on-G´omez,Samuel G´omez-Haro Published: 14 October 2019 This work is copyrighted by Universit`a del Salento, and is licensed un- der a Creative Commons Attribuzione - Non commerciale - Non opere derivate 3.0 Italia License. For more information see: http://creativecommons.org/licenses/by-nc-nd/3.0/it/ Electronic Journal of Applied Statistical Analysis Vol. 12, Issue 02, October 2019, 362-379 DOI: 10.1285/i20705948v12n2p362 High performance of professional basketball players and the settings to measure their regularity: evidence from the Spanish ACB League Rom´anSalmer´on-G´omez∗a and Samuel G´omez-Harob aUniversity of Granada. Quantitative Methods Department, Economics and Business School. Campus Cartuja S/N. 18071. Granada (Spain). bUniversity of Granada. Business and Management Department II, Economics and Business School. Campus Cartuja S/N. 18071. Granada (Spain). Published: 14 October 2019 In this paper, we analyse the relationship between performance and regu- larity to avoid the problem to the use of averages in sports statistics given their sensitivity to extreme data. The aim of this work is to establish which statistics discriminate between the high and low performance and regular- ity of basketball players using a performance-regularity index. -
A Starting Point for Analyzing Basketball Statistics
Journal of Quantitative Analysis in Sports Volume 3, Issue 3 2007 Article 1 A Starting Point for Analyzing Basketball Statistics Justin Kubatko, The Ohio State University and basketball- reference.com Dean Oliver, Basketball on Paper and Denver Nuggets Kevin Pelton, Seattle Sonics & Storm Dan T. Rosenbaum, University of North Carolina at Greensboro and Cleveland Cavaliers Recommended Citation: Kubatko, Justin; Oliver, Dean; Pelton, Kevin; and Rosenbaum, Dan T. (2007) "A Starting Point for Analyzing Basketball Statistics," Journal of Quantitative Analysis in Sports: Vol. 3: Iss. 3, Article 1. DOI: 10.2202/1559-0410.1070 ©2007 American Statistical Association. All rights reserved. Brought to you by | University of Toronto-Ocul Authenticated Download Date | 3/2/16 11:03 PM A Starting Point for Analyzing Basketball Statistics Justin Kubatko, Dean Oliver, Kevin Pelton, and Dan T. Rosenbaum Abstract The quantitative analysis of sports is a growing branch of science and, in many ways one that has developed through non-academic and non-traditionally peer-reviewed work. The aim of this paper is to bring to a peer-reviewed journal the generally accepted basics of the analysis of basketball, thereby providing a common starting point for future research in basketball. The possession concept, in particular the concept of equal possessions for opponents in a game, is central to basketball analysis. Estimates of possessions have existed for approximately two decades, but the various formulas have sometimes created confusion. We hope that by showing how most previous formulas are special cases of our more general formulation, we shed light on the relationship between possessions and various statistics. -
The Magicmetric Coaching System and 2011-2012 NBA Player Ratings
The MagicMetric Coaching System in the NBA Overview The MagicMetric is a basketball player rating system created by two math majors who shared coaching duties on several Industrial and Church league teams. It is an Acronym for the Mays And Gantner Index of Contribution (MAGIC), so named for its co creators, Dick Mays and Jeff Gantner. Dick and Jeff created the rating system primarily to rate the players on their own basketball team. But as a player rating system, this measure can also be used to rank the players in any league. This paper provides a complete ranking of all the NBA players for the 2011-2012 season. The casual reader may wish to go straight to the appendix for this listing. The rest of the paper is intended for readers with an interest in coaching. The Magic Metric Coaching Systems, (a.k.a.) Rotation System, is a simple way to decide on player substitutions. It predefines the rotations to be used during the game, based on the Magic Metric player ratings. Although the Rotation System and the Player Rating are two separate ideas, they were conceived at the same time. Technically, the rotation system could be used with a different player rating system. This paper examines the feasibility of actually using the rotation system in the NBA. Introduction The topic of how to rate the performance of basketball players has been the subject of many papers and more than a little controversy. TENDEX, by David Herron may have been the first such rating system. TENDEX used a linear system of weights; however, Mr. -
Notes, Is Most of the Time
6 shaq and kobe Why study sports? The obvious answer—sports are interesting. Of course we are not saying that other topics examined in economics are not interesting. Well . maybe we should say this. Someone should at some point say that a few topics ex- amined by economists—mind you, we are not naming names and we are just say- ing a few—are really not interesting. The topics are not interesting to us, our stu- dents, or probably most non-economists. We are not even sure these topics are interesting to most other economists. So we are drawn to sports because we find this subject to be interesting. There is more to the story. As we noted at the onset, with sports you have numbers. Oo- dles and oodles and oodles—that is a scientific term which means “a whole bunch” or “lots and lots”—of numbers are generated in the world of sports. Each and every day a game is played somewhere. In that game people record the actions of each individual player. This record, or the data, can be used by economists to address an assortment of interesting and entertaining questions.1 What is the purpose of tracking all the data collected in sports? We talked about this in Chapter One. Still, we wanted to mention another great answer to this ques- tion which was provided by Allen Barra: “Stat Nerds” they snort contemptuously at me, and probably at you, too, if you’re smart enough to have picked up this book—but the truth is that they depend as much on numbers as anyone else when it comes to making decisions. -
Baumer and Zimablist Sabermetric Revolution
The Sabermetric Revolution Benjamin Baumer, Andrew Zimbalist Published by University of Pennsylvania Press Benjamin Baumer. and Andrew Zimbalist. The Sabermetric Revolution: Assessing the Growth of Analytics in Baseball. Philadelphia: University of Pennsylvania Press, 2013. Project MUSE. Web. 21 Aug. 2015.http://muse.jhu.edu/. For additional information about this book http://muse.jhu.edu/books/9780812209129 Access provided by University of Michigan @ Ann Arbor (4 Dec 2015 21:10 GMT) PREFACE ichael Lewis wrote Moneyball because he fell in love with a story. Te Mstory is about how intelligent innovation (the creative use of statistical analysis) in the face of market inefciency (the failure of all other teams to use available information productively) can overcome the unfairness of baseball economics (rich teams can buy all the best players) to enable a poor team to slay the giants. Lewis is an engaging storyteller and, along the way, introduces us to intriguing characters who carry forward the rags-to-riches plot. By the end, the story of the Oakland A’s and their general manager, Billy Beane, is so well told that we believe its portrayal of baseball history, economics, and competitive success. Te result is a new Horatio Alger tale that reinforces a beloved American myth and, all the better, applies to our national pastime. Te appeal of Lewis’s Moneyball was sufciently strong that Hollywood wanted a piece of the action. With a compelling script, smart direction, and the handsome Brad Pitt as Beane, Moneyball became part of mass culture and its perceived validity—and its legend—only grew. Tis book will attempt to set the record straight on Moneyball and the role of “analytics” in baseball. -
The Magicmetric Coaching System Background by Dick Mays PLAYER
The MagicMetric Coaching System Background by Dick Mays The MagicMetric is a player rating system invented by Dick Mays and Jeff Gantner, two friends who were both mathematicians and basketball enthusiasts. The reason the metric was invented was to remove arguments about playing time among players on an Industrial League basketball team. Everyone on the team had paid $50 and there was a logical argument that all players deserved equal playing time for their money. To be competitive, the best players needed to be on the court a higher percentage of the time. If some players were to get more playing time than others, then there had to be a justification for it. Dick and Jeff researched existing metrics, such as TENDEX, and were surprised to discover very little formal reasoning was used to determine the relative value of the various types of contribution on the basketball court. Being mathematicians, Dick and Jeff created their own measurement, called the Magic Metric, to be used to value the contributions of players relative to each other: Another paper describes the reasoning behind the values used in the Metric. It can be found here; http://www.upct.es/~beside/Textos/MagicMetric.pdf After establishing a way of measuring the relative contribution of players, the problem remained as to how to divide playing time among the players, so that each player got some time, but that the good players would have more time in close games. However, if the game was a blowout, if either team was way ahead of the other, it was desirable that all players would have approximately equal playing time. -
View the Manual
1. Set up # 1.1. Install Insert the game CD in the CD drive and follow the on-screen instructions in order to install the game. If no dialog box appears after you insert the CD, go to the contents of the CD and double click on “setup.exe”, then follow the instructions. # 1.2. Uninstall If you want to remove the game from your system, click on the “uninstall.exe” in the folder of the installation or use the uninstall option from the start menu. # 1.3. System requirements Minimum: Pentium IV or equivalent, 512MB RAM, Windows XP/ Vista Sp1 or later, 3D card, sound card, 500MB free hard disk space. Recommended: Pentium Core Duo, 1GB RAM, Windows XP. 2. Intro Welcome to “World Basketball Manager” (WBM). In this game, you will be called to fill in the shoes of the manager of a basketball team somewhere in the world and lead it to fame, and simultaneously advance your own career and prestige. You will be faced with all the challenges and difficulties of your real life counterparts, and you will have to make the right decisions at the right moment. Hopefully you will make it through and become a worldwide renowned manager. So read through the following pages to get some help on how to accomplish this. 3. Starting the game # 3.1. Start a new game You can begin a new game by clicking on the “Start a new game” label, which is located on the upper interface bar. You will then be prompted to type in a name for your game (so you can later easily recognize it when you want to load and continue it). -
An Examination of Customer Discrimination in the National Basketball Association
Colby College Digital Commons @ Colby Honors Theses Student Research 2002 Above and Beyond the Rim: An Examination of Customer Discrimination in the National Basketball Association Carl E. Tugberk Colby College Follow this and additional works at: https://digitalcommons.colby.edu/honorstheses Part of the Economics Commons Colby College theses are protected by copyright. They may be viewed or downloaded from this site for the purposes of research and scholarship. Reproduction or distribution for commercial purposes is prohibited without written permission of the author. Recommended Citation Tugberk, Carl E., "Above and Beyond the Rim: An Examination of Customer Discrimination in the National Basketball Association" (2002). Honors Theses. Paper 337. https://digitalcommons.colby.edu/honorstheses/337 This Honors Thesis (Open Access) is brought to you for free and open access by the Student Research at Digital Commons @ Colby. It has been accepted for inclusion in Honors Theses by an authorized administrator of Digital Commons @ Colby. Above and Beyond the Rim: An Examination ofCustomer Discrimination in tbe National BasketbaD Association Carl E. Tugberk Colby College May 2002 Above and Beyond the Rim: An Examination of Customer Discrimination in the National Basketball Association Carl E. Tugberk* Colby College May 2002 Carl E. Tugberk Economics Major Class of 2002 Colby College Waterville, ME 04901 Phone: (207) 859-7039 Email: [email protected] *This paper is submitted in partial fulfillment of the requirements of Honors in Economics. I wish to thank Colby College and Dean Edward H. Yeterian for financing the purchase of several materials necessary to complete this study. Further, I would like to give a special thanks to Professor David W. -
A Stakeholder Assessment of Basketball Player Evaluation Metrics
Original Article A stakeholder assessment of basketball player evaluation metrics JOSE A. MARTÍNEZ 1 , LAURA MARTÍNEZ Departamento de Economía de la Empresa, Universidad Politécnica de Cartagena, Cartagena, Spain ABSTRACT Martínez JA, Martínez L. A stakeholder assessment of basketball player evaluation metrics. J. Hum. Sport Exerc. Vol. 6, No. 1, pp. 153-183, 2011. In this research we examined the opinions of basketball stakeholders regarding several questions of special interests to valuate players. Players, coaches, agents, journalists, editors, bloggers, researchers, analysts, fans and chairs participated in this macro-research. After analysing their opinions using the content analysis methodology, we found that current player evaluation systems are insufficient to fulfill the expectations of stakeholders regarding the definition of value, because they fail to rate intangibles. In addition, the importance of qualitative thinking is prominent and should be considered in valuating such intangibles. The current system of valuation used in Euroleague and Spanish ACB League (Ranking) is acknowledged as deficient, but stakeholders think that other advanced metrics do not significantly outperform Ranking. Implications for management, decision making and marketing in basketball are finally discussed. Key words: PLAYER EVALUATION METRICS, BASKETBALL, STAKEHOLDERS, DECISION MAKING. 1 Corresponding author. Departamento de Economía de la Empresa, Universidad Politécnica de Cartagena, Cartagena, Spain. E-mail: [email protected] Submitted -
RIVERVALLEY BOYS BASKETBALL Individual Records (Through
RIVER VALLEY BOYS BASKETBALL Individual Records (through 2015-16 season) Most field goals made in one game 17 by Max Gundlach vs. Iowa Grant 2/14/69 Most field goals attempted in one game 31 by LeRoy Crook vs. Wis. Heights 11/27/63 31 by LeRoy Crook vs. Poynette 1/7/63 Most field goals made in one season 189 by Jacob Baryenbruch 2004-05 Most field goals attempted in one season 462 by Jacob Baryenbruch 2004-05 Best field goal percentage in one game 93.7% (15/16) by Jim Crook vs. Prairie du Chien 2/6/70 (at least 10 attempts) Best field goal percentage in one season 70.8% (46/65) by Matt Foster 2005-06 (at least 60 attempts) Most three point goals made in one game 10 by Mason Horton vs. Mauston 2/6/16 Most three point goals made in one season 76 by Jacob Baryenbruch 2004-05 Best three point percentage in one season 43.7% (31/71) by Alex Richard 2009-10 (at least 40 attempts) Best three point percentage in one game 86% (6/7) by Josh Baryenbruch 12/13/02 (at least 5 attempts) Most three point goals made in a career 203 by Jacob Baryenbruch 2001-05 Most free throws made in one game 14 by Tim Doyle vs. Richland Center 1/26/63 14 by Mark Richard vs. Boscobel 12/17/82 14 by Josh Baryenbruch vs. Lancaster 3/4/03 14 by Jacob Baryenbruch vs. Richland Center 2/5/04 14 by Brandon Gilbeck vs. Adams-Friendship 12/2/14 Most free throws made in one season 118 by Brandon Gilbeck 2014-15 Most free throws attempted in one game 23 by Tim Doyle vs.