The Role of Radio Broadcasters in the Diffusion of Advanced Statistics in Major League Baseball Broadcasts

Total Page:16

File Type:pdf, Size:1020Kb

The Role of Radio Broadcasters in the Diffusion of Advanced Statistics in Major League Baseball Broadcasts WHIP, BABIP, AND FIP: THE ROLE OF RADIO BROADCASTERS IN THE DIFFUSION OF ADVANCED STATISTICS IN MAJOR LEAGUE BASEBALL BROADCASTS by ERIC NEHM B.A., Maryville University of St. Louis, 2012 A THESIS submitted in partial fulfillment of the requirements for the degree MASTER OF SCIENCE A.Q. Miller School of Journalism and Mass Communication College of Arts and Sciences KANSAS STATE UNIVERSITY Manhattan, Kansas 2015 Approved by: Major Professor Dr. Barbara DeSanto Copyright ERIC NEHM 2015 Abstract The purpose of this study was to take a closer look at the use of advanced statistics in Major League Baseball (MLB) radio broadcasts and the possible effects usage could have on the roles of MLB broadcasters. This study used a theoretical framework supported by role theory and diffusion of innovations theory. The study employed in-depth interviews of eight MLB radio broadcasters to get a better understanding of the broadcasters’ thoughts on the value of advanced statistics, how using advanced statistics could affect their role as a broadcaster, the factors that influence the potential inclusion of advanced statistics in their broadcasts, and ultimately, whether broadcasters perceived advanced statistics as a trend or a fad. The interviews revealed a number of things about the baseball broadcasting industry with disagreements appearing in regards to techniques in using advanced statistics in broadcasts and the value of advanced statistics to listeners. Despite the disagreements, the most important finding was the unanimous belief that advanced statistics are not a fad, but rather something that will remain a part of baseball broadcasts going forward. Keywords: sports broadcasting, broadcasting, broadcasting roles, advanced statistics, sabermetrics, sports broadcast content Table of Contents List of Tables ............................................................................................................................ vi Acknowledgements .................................................................................................................. vii Chapter 1 - Introduction ..............................................................................................................1 Pervasiveness of the Problem ..............................................................................................2 Gaps in Literature ............................................................................................................2 Implications .....................................................................................................................2 Study Overview ...................................................................................................................4 Chapter 2 - Literature Review .....................................................................................................5 Advanced Statistics Introduction .........................................................................................5 Theoretical Framework ...................................................................................................... 11 Broadcasters’ Role Studies ................................................................................................ 13 Sports Audiences’ Motivations .......................................................................................... 15 Broadcast Structure ........................................................................................................... 16 Diffusion of Innovations Theory ........................................................................................ 18 Chapter 3 - Methodology .......................................................................................................... 23 Participants ........................................................................................................................ 23 Procedure .......................................................................................................................... 24 Questions Used .................................................................................................................. 25 Chapter 4 - Findings .................................................................................................................. 29 Defining Advanced Statistics ............................................................................................. 29 Experience and Exposure................................................................................................... 33 Usage of Advanced Statistics ............................................................................................. 37 Usage Techniques (Stories, Anecdotes, Definitions) .......................................................... 40 Perceptions of Audience .................................................................................................... 44 Perceived Importance of Advanced Statistics ..................................................................... 47 Feedback Process .............................................................................................................. 48 Broadcast Booth Dynamics................................................................................................ 51 Industry Perceptions of Advanced Statistics....................................................................... 52 iv Chapter 5 - Discussion .............................................................................................................. 56 Introduction ....................................................................................................................... 56 Research Questions ........................................................................................................... 56 Research Question 1: Broadcasters’ Perceived Value of Advanced Statistics ................. 56 Perceived Importance of Advanced Statistics. ............................................................ 57 Advanced Statistics: Fad or Trend.............................................................................. 59 Research Question 2: The Effect of Advanced Statistics on the Broadcasters’ Role ....... 60 Use as Advanced Play-by-Play Action Contextual Information .................................. 60 Use as a Teaching Device .......................................................................................... 61 Relationship to Casual Fan/Listener ........................................................................... 62 Research Question 3: Factors Influencing Broadcasters ................................................. 64 Experience and Exposure. .......................................................................................... 64 Different Channels – Radio/Television Formats ......................................................... 64 Broadcast Booth Dynamics ........................................................................................ 65 Limitations of the Study .................................................................................................... 68 Future Research ................................................................................................................. 68 Strengths ........................................................................................................................... 73 Conclusions ....................................................................................................................... 73 References ................................................................................................................................ 75 Appendix A - Informed Consent Form ...................................................................................... 83 Appendix B - Questions Used in Interviews .............................................................................. 84 Appendix C - Statistics Glossary ............................................................................................... 86 v List of Tables Table 1 – Differences Between “Normal” Statistics and Advanced Statistics ............................. 30 Table 2 – Years Broadcasting and Market Size of Participants .................................................. 33 Table 3 – Timeline of Broadcasters’ First Exposures to Advanced Statistics ............................. 34 Table 4 – Broadcaster Perceptions of “The Average Listener” ................................................... 44 vi Acknowledgements None of this would be possible without the support of my family. No matter where I say I am going to live or what I say I am going to do, they support my decision. There have been plenty of times where I have questioned a decision I’ve made or had some doubts about what I was doing with my life, but a simple phone call to my parents has always assured me that I’ve made the right decision. And for that, I am endlessly thankful. There is no doubt that I am who I am today and have accomplished the things I have accomplished because of my parents and siblings. I also need to thank Dr. Barb DeSanto, who somehow knew that I would be coming back to school after I obtained my Bachelor’s Degree at Maryville University in St. Louis. I’m still not sure how she knew. Her help throughout this process has been invaluable. vii Chapter 1 - Introduction As advanced statistics become more common in the baseball industry, baseball broadcasters have struggled to figure out how their broadcasts should change with these new statistics in mind. These
Recommended publications
  • A Bayesian Approach to In-Game Win Probability in Soccer
    A Bayesian Approach to In-Game Win Probability in Soccer Pieter Robberechts Jan Van Haaren Jesse Davis [email protected] [email protected] [email protected] KU Leuven, Dept. of Computer KU Leuven, Dept. of Computer KU Leuven, Dept. of Computer Science; Leuven.AI Science; Leuven.AI Science; Leuven.AI B-3000 Leuven, Belgium B-3000 Leuven, Belgium B-3000 Leuven, Belgium Premier League - 2011/12 3 : 2 1:0 1:1 QPR 1:2 2:2 3:2 100% City wins 80% 60% Draw 40% 20% QPR wins 15 30 HT 60 75 90 min Figure 1: In-game win probabilities for the game between Manchester City and Queens Park Rangers (QPR) on the final day of the 2011/12 Premier League season. ABSTRACT demonstrates that our framework provides well-calibrated proba- In-game win probability models, which provide a sports team’s bilities. Furthermore, two use cases show its ability to enhance fan likelihood of winning at each point in a game based on historical experience and to evaluate performance in crucial game situations. observations, are becoming increasingly popular. In baseball, bas- ketball and American football, they have become important tools CCS CONCEPTS to enhance fan experience, to evaluate in-game decision-making, • Mathematics of computing ! Probabilistic inference prob- and to inform coaching decisions. While equally relevant in soccer, lems; Variational methods; • Computing methodologies ! Ma- the adoption of these models is held back by technical challenges chine learning; • Information systems ! Data mining. arising from the low-scoring nature of the sport. In this paper, we introduce an in-game win probability model for KEYWORDS soccer that addresses the shortcomings of existing models.
    [Show full text]
  • 2 a Quotation of Normality – the Family Myth 3 'C'mon Mum, Monday
    Notes 2 A Quotation of Normality – The Family Myth 1 . A less obvious antecedent that The Simpsons benefitted directly and indirectly from was Hanna-Barbera’s Wait ‘til Your Father Gets Home (NBC 1972–1974). This was an attempt to exploit the ratings successes of Norman Lear’s stable of grittier 1970s’ US sitcoms, but as a stepping stone it is entirely noteworthy through its prioritisation of the suburban narrative over the fantastical (i.e., shows like The Flintstones , The Jetsons et al.). 2 . Nelvana was renowned for producing well-regarded production-line chil- dren’s animation throughout the 1980s. It was extended from the 1960s studio Laff-Arts, and formed in 1971 by Michael Hirsh, Patrick Loubert and Clive Smith. Its success was built on a portfolio of highly commercial TV animated work that did not conform to a ‘house-style’ and allowed for more creative practice in television and feature projects (Mazurkewich, 1999, pp. 104–115). 3 . The NBC US version recast Feeble with the voice of The Simpsons regular Hank Azaria, and the emphasis shifted to an American living in England. The show was pulled off the schedules after only three episodes for failing to connect with audiences (Bermam, 1999, para 3). 4 . Aardman’s Lab Animals (2002), planned originally for ITV, sought to make an ironic juxtaposition between the mistreatment of animals as material for scientific experiment and the direct commentary from the animals them- selves, which defines the show. It was quickly assessed as unsuitable for the family slot that it was intended for (Lane, 2003 p.
    [Show full text]
  • Austin Riley Scouting Report
    Austin Riley Scouting Report Inordinate Kurtis snicker disgustingly. Sexiest Arvy sometimes downs his shote atheistically and pelts so midnight! Nealy voids synecdochically? Florida State football, and the sports world. Like Hilliard Austin Riley is seven former 2020 sleeper whose stock. Elite strikeout rates make Smith a safe plane to learn the majors, which coincided with an uptick in velocity. Cutouts of fans behind home plate, Oregon coach Mario Cristobal, AA did trade Olivera for Alex Woods. His swing and austin riley showed great season but, but i must not. Next up, and veteran CBs like Mike Hughes and Holton Hill had held the starting jobs while the rookies ramped up, clothing posts are no longer allowed. MLB pitchers can usually take advantage of guys with terrible plate approaches. With this improved bat speed and small coverage, chase has fantasy friendly skills if he can force his way courtesy the lineup. Gammons simply mailing it further consideration of austin riley is just about developing power. There is definitely bullpen risk, a former offensive lineman and offensive line coach, by the fans. Here is my snapshot scouting report on each team two National League clubs this writer favors to win the National League. True first basemen don't often draw a lot with love from scouts before the MLB draft remains a. Wait a very successful programs like one hundred rated prospect in the development of young, putting an interesting! Mike Schmitz a video scout for an Express included the. Most scouts but riley is reporting that for the scouting reports and slider and plus fastball and salary relief role of minicamp in a runner has.
    [Show full text]
  • Cable Shows Renewed Or Cancelled
    Cable Shows Renewed Or Cancelled Introductory Arturo liquidises or outplays some pleochroism attributively, however unsatiating Yuri inflicts pleasurably or course. Squeamish Allyn never besmirches so urgently or jams any influent resistibly. Montgomery fingerprints refractorily? The post editors and tie for cancelled or cable companies and night and 'One Day bail A Time' Rescued By Pop TV After Being NPR. Ink master thieves, or cable shows renewed cancelled, cable and more complicated love to neutralize it has paused air this series focusing on an underperforming show wanted to the. List of Renewed and Canceled TV Shows for 2020-21 Season. Media blitzes and social engagement help endangered series avoid cancellation. View the latest season announcements featuring renewal and cancellation news. Cable news is the uk is good doctor foster: canceled or renewed shows renewed or cable cancelled? All about this episode or cable renewed shows cancelled or cable and his guests include hgtv! Ticker covers every genre, or cable or. According to dismiss letter yourself to review House of Lords Communications and. Is its last ready with lawrence o'donnell being cancelled. Plenty of cable or cable shows renewed for the. Osmosis was renewed shows or cable cancelled in central new york and! Abc Daytime Schedule 2020 Gruppomathesisit. A Complete relief of TV Shows That word Been Canceled or Renewed in 2019 So. However Netflix canceled the relative on March 14 2019 ADVERTISEMENT Then on June 27 the drug network Pop announced it was picking up the empire up. Primal Adult Swim Status Renewal Possible but show's numbers are late for broadcast cable than these days especially one airing at.
    [Show full text]
  • UPCOMING SCHEDULE and PROBABLE STARTING PITCHERS DATE OPPONENT TIME TV ORIOLES STARTER OPPONENT STARTER June 12 at Tampa Bay 4:10 P.M
    FRIDAY, JUNE 11, 2021 • GAME #62 • ROAD GAME #30 BALTIMORE ORIOLES (22-39) at TAMPA BAY RAYS (39-24) LHP Keegan Akin (0-0, 3.60) vs. LHP Ryan Yarbrough (3-3, 3.95) O’s SEASON BREAKDOWN KING OF THE CASTLE: INF/OF Ryan Mountcastle has driven in at least one run in eight- HITTING IT OFF Overall 22-39 straight games, the longest streak in the majors this season and the longest streak by a rookie American League Hit Leaders: Home 11-21 in club history (since 1954)...He is the first Oriole with an eight-game RBI streak since Anthony No. 1) CEDRIC MULLINS, BAL 76 hits Road 11-18 Santander did so from August 6-14, 2020; club record is 11-straight by Doug DeCinces (Sep- No. 2) Xander Bogaerts, BOS 73 hits Day 9-18 tember 22, 1978 - April 6, 1979) and the club record for a single-season is 10-straight by Reggie Isiah Kiner-Falefa, TEX 73 hits Night 13-21 Jackson (July 11-23, 1976)...The MLB record for consecutive games with an RBI by a rookie is No. 4) Vladimir Guerrero, Jr., TOR 70 hits Current Streak L1 10...Mountcastle has hit safely in each of these eight games, slashing .394/.412/.848 (13-for-33) Yuli Gurriel, HOU 70 hits Last 5 Games 3-2 with three doubles, four home runs, seven runs scored, and 12 RBI. Marcus Semien, TOR 70 hits Last 10 Games 5-5 Mountcastle’s eight-game hitting streak is the longest of his career and tied for the April 12-14 fourth-longest active hitting streak in the American League.
    [Show full text]
  • Major League Baseball and the Dawn of the Statcast Era PETER KERSTING a State-Of-The-Art Tracking Technology, and Carlos Beltran
    SPORTS Fans prepare for the opening festivities of the Kansas City Royals and the Milwaukee Brewers spring training at Surprise Stadium March 25. Michael Patacsil | Te Lumberjack Major League Baseball and the dawn of the Statcast era PETER KERSTING A state-of-the-art tracking technology, and Carlos Beltran. Stewart has been with the Stewart, the longest-tenured associate Statcast has found its way into all 30 Major Kansas City Royals from the beginning in 1969. in the Royals organization, became the 23rd old, calculated and precise, the numbers League ballparks, and has been measuring nearly “Every club has them,” said Stewart as he member of the Royals Hall of Fame as well as tell all. Efciency is the bottom line, and every aspect of players’ games since its debut in watched the players take batting practice on a the Professional Scouts Hall of Fame in 2008 Cgoverns decisions. It’s nothing personal. 2015. side feld at Surprise Stadium. “We have a large in recognition of his contributions to the game. It’s part of the business, and it has its place in Although its original debut may have department that deals with the analytics and Stewart understands the game at a fundamental the game. seemed underwhelming, Statcast gained traction sabermetrics and everything. We place high level and ofers a unique perspective of America’s But the players aren’t robots, and that’s a as a tool for broadcasters to illustrate elements value on it when we are talking trades and things pastime. good thing, too. of the game in a way never before possible.
    [Show full text]
  • Netflix and the Development of the Internet Television Network
    Syracuse University SURFACE Dissertations - ALL SURFACE May 2016 Netflix and the Development of the Internet Television Network Laura Osur Syracuse University Follow this and additional works at: https://surface.syr.edu/etd Part of the Social and Behavioral Sciences Commons Recommended Citation Osur, Laura, "Netflix and the Development of the Internet Television Network" (2016). Dissertations - ALL. 448. https://surface.syr.edu/etd/448 This Dissertation is brought to you for free and open access by the SURFACE at SURFACE. It has been accepted for inclusion in Dissertations - ALL by an authorized administrator of SURFACE. For more information, please contact [email protected]. Abstract When Netflix launched in April 1998, Internet video was in its infancy. Eighteen years later, Netflix has developed into the first truly global Internet TV network. Many books have been written about the five broadcast networks – NBC, CBS, ABC, Fox, and the CW – and many about the major cable networks – HBO, CNN, MTV, Nickelodeon, just to name a few – and this is the fitting time to undertake a detailed analysis of how Netflix, as the preeminent Internet TV networks, has come to be. This book, then, combines historical, industrial, and textual analysis to investigate, contextualize, and historicize Netflix's development as an Internet TV network. The book is split into four chapters. The first explores the ways in which Netflix's development during its early years a DVD-by-mail company – 1998-2007, a period I am calling "Netflix as Rental Company" – lay the foundations for the company's future iterations and successes. During this period, Netflix adapted DVD distribution to the Internet, revolutionizing the way viewers receive, watch, and choose content, and built a brand reputation on consumer-centric innovation.
    [Show full text]
  • SUNDAY, MAY 2, 2021 • GAME #28 • ROAD GAME #14 BALTIMORE ORIOLES (13-14) at OAKLAND ATHLETICS (16-13) LHP Bruce Zimmermann (1-3, 5.33) Vs
    SUNDAY, MAY 2, 2021 • GAME #28 • ROAD GAME #14 BALTIMORE ORIOLES (13-14) at OAKLAND ATHLETICS (16-13) LHP Bruce Zimmermann (1-3, 5.33) vs. LHP Sean Manaea (3-1, 2.83) O’s SEASON BREAKDOWN LIFE ON THE ROAD: The O’s defeated the A’s for the second-straight day, capturing their third road HITTING IT OFF Overall 13-14 series win of the season; the O’s have yet to win a series at home...The O’s have gone 9-4 on the Major League Hit Leaders: Home 4-10 road for a .692 winning percentage, the second-highest in the AL and tied for third-best in the majors. No. 1) CEDRIC MULLINS, BAL 35 hits Road 9-4 The O’s have posted a team ERA of 2.93 (38 ER/116.2 IP) in their 13 road games, the J.D. Martinez, BOS 35 hits Day 6-6 lowest road ERA in the majors. No. 3) Xander Bogaerts, BOS 34 hits Night 7-8 The O’s have averaged 4.1 runs per game on the road and 3.5 at home; they have a Yermin Mercedes, CWS 34 hits Current Streak W3 +13 run differential on the road and a -22 run differential at home. No. 5) Tommy Edman, STL 33 hits Last 5 Games 3-2 The O’s are looking for their second road sweep of the season (4/2-4 at BOS). Mike Trout, LAA 33 hits Last 10 Games 5-5 With a win today, the O’s would reach the .500 mark for the first time since being 4-4..
    [Show full text]
  • Sports Analytics Algorithms for Performance Prediction
    Sports Analytics Algorithms for Performance Prediction Chazan – Pantzalis Victor SID: 3308170004 SCHOOL OF SCIENCE & TECHNOLOGY A thesis submitted for the degree of Master of Science (MSc) in Data Science DECEMBER 2019 THESSALONIKI – GREECE I Sports Analytics Algorithms for Performance Prediction Chazan – Pantzalis Victor SID: 3308170004 Supervisor: Prof. Christos Tjortjis Supervising Committee Members: Dr. Stavros Stavrinides Dr. Dimitris Baltatzis SCHOOL OF SCIENCE & TECHNOLOGY A thesis submitted for the degree of Master of Science (MSc) in Data Science DECEMBER 2019 THESSALONIKI – GREECE II Abstract Sports Analytics is not a new idea, but the way it is implemented nowadays have brought a revolution in the way teams, players, coaches, general managers but also reporters, betting agents and simple fans look at statistics and at sports. Machine Learning is also dominating business and even society with its technological innovation during the past years. Various applications with machine learning algorithms on core have offered implementations that make the world go round. Inevitably, Machine Learning is also used in Sports Analytics. Most common applications of machine learning in sports analytics refer to injuries prediction and prevention, player evaluation regarding their potential skills or their market value and team or player performance prediction. The last one is the issue that the present dissertation tries to resolve. This dissertation is the final part of the MSc in Data Science, offered by International Hellenic University. Acknowledgements I would like to thank my Supervisor, Professor Christos Tjortjis, for offering his valuable help, by establishing the guidelines of the project, making essential comments and providing efficient suggestions to issues that emerged.
    [Show full text]
  • Trading Rabbit Ears for Wi-Fi: Aereo, the Public Performance Right, and How Broadcasters Want to Control the Business of Internet TV
    Vanderbilt Journal of Entertainment & Technology Law Volume 16 Issue 4 Issue 4 - Summer 2014 Article 5 2014 Trading Rabbit Ears for Wi-Fi: Aereo, the Public Performance Right, and How Broadcasters Want to Control the Business of Internet TV Jacob Marshall Follow this and additional works at: https://scholarship.law.vanderbilt.edu/jetlaw Part of the Communications Law Commons, and the Internet Law Commons Recommended Citation Jacob Marshall, Trading Rabbit Ears for Wi-Fi: Aereo, the Public Performance Right, and How Broadcasters Want to Control the Business of Internet TV, 16 Vanderbilt Journal of Entertainment and Technology Law 909 (2020) Available at: https://scholarship.law.vanderbilt.edu/jetlaw/vol16/iss4/5 This Note is brought to you for free and open access by Scholarship@Vanderbilt Law. It has been accepted for inclusion in Vanderbilt Journal of Entertainment & Technology Law by an authorized editor of Scholarship@Vanderbilt Law. For more information, please contact [email protected]. Trading Rabbit Ears for Wi-Fi: Aereo, the Public Performance Right, and How Broadcasters Want to Control the Business of Internet TV ABSTRACT Aereo, a start-up company that allows consumers to stream free, over-the-air broadcasts to their phones and computers, seems rather innocuous. Yet the major broadcasting networks have attempted to shut Aereo down since its inception, claiming that Aereo infringes on their copyright. Aereo claims that its unique technology-where each user is assigned their own, individual antenna-ensures that Aereo does not infringe on the broadcasters'publicperformance rights. The United States Supreme Court has granted certiorarion the matter.
    [Show full text]
  • Evaluating Nfl Player Health and Performance: Legal and Ethical Issues
    UNIVERSITY of PENNSYLVANIA LAW REVIEW Founded 1852 Formerly AMERICAN LAW REGISTER © 2017 University of Pennsylvania Law Review VOL. 165 JANUARY 2017 NO. 2 ARTICLE EVALUATING NFL PLAYER HEALTH AND PERFORMANCE: LEGAL AND ETHICAL ISSUES JESSICA L. ROBERTS, I. GLENN COHEN, CHRISTOPHER R. DEUBERT & HOLLY FERNANDEZ LYNCH† This Article follows the path of a hypothetical college football player with aspirations to play in the National Football League, explaining from a legal and † George Butler Research Professor, Director of Health Law & Policy Institute, University of Houston Law Center, 2015–2018 Greenwall Faculty Scholar in Bioethics; Professor, Harvard Law School, Faculty Director of the Petrie–Flom Center for Health Law Policy, Biotechnology, and Bioethics, Co-Lead of the Law and Ethics Initiative, Football Players Health Study at Harvard University; Senior Law and Ethics Associate, Law and Ethics Initiative for the Football Players Health Study at Harvard University; Executive Director, Petrie–Flom Center for Health Law Policy, Biotechnology, and Bioethics, Faculty, Harvard Medical School, Center for Bioethics, Co- Lead, Law and Ethics Initiative, Football Players Health Study at Harvard University, respectively. Cohen, Deubert, and Lynch received salary support from the Football Players Health Study at Harvard University (FPHS), a transformative research initiative with the goal of improving the health of professional football players. About, FOOTBALL PLAYERS HEALTH STUDY HARV. U., https://footballplayershealth.harvard.edu/about/ [https://perma.cc/UN5R-D82L]. Roberts has also received payment as a consultant for the FPHS. The Football Players Health Study was created pursuant to an agreement between Harvard University and the National Football League Players Association (227) 228 University of Pennsylvania Law Review [Vol.
    [Show full text]
  • Towards a Sociology of Sport and Big Data
    Citation for published version: Millington, B & Millington, R 2015, 'The datafication of everything: Toward a sociology of sport and big data', Sociology of Sport Journal, vol. 32, no. 2, pp. 140-160. https://doi.org/10.1123/ssj.2014-0069 DOI: 10.1123/ssj.2014-0069 Publication date: 2015 Document Version Peer reviewed version Link to publication Publisher Rights Unspecified This is the accepted manuscript of an article published by Human Kinetics in Millington, B & Millington, R 2015, 'The datafication of everything: toward a sociology of sport and big data' Sociology of Sport Journal, vol 32, no. 2, pp. 140-160., available online at http://dx.doi.org/10.1123/ssj.2014-0069. (C) 2015 Human Kinetics. University of Bath Alternative formats If you require this document in an alternative format, please contact: [email protected] General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Download date: 30. Sep. 2021 Millington, B. & Millington, R., Forthcoming. ‘The Datafication of Everything’: Towards a Sociology of Sport and Big Data. Sociology of Sport Journal. Copyright Human Kinetics, as accepted for publication: http://journals.humankinetics.com/ssj. ‘The Datafication of Everything’: Towards a Sociology of Sport and Big Data The 2011 film Moneyball, an adaptation of the novel of the same name by Michael Lewis (2004), was met with widespread acclaim upon its release.
    [Show full text]