Understanding Career Progression in Baseball Through Machine Learning*
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Gether, Regardless Also Note That Rule Changes and Equipment Improve- of Type, Rather Than Having Three Or Four Separate AHP Ments Can Impact Records
Journal of Sports Analytics 2 (2016) 1–18 1 DOI 10.3233/JSA-150007 IOS Press Revisiting the ranking of outstanding professional sports records Matthew J. Liberatorea, Bret R. Myersa,∗, Robert L. Nydicka and Howard J. Weissb aVillanova University, Villanova, PA, USA bTemple University Abstract. Twenty-eight years ago Golden and Wasil (1987) presented the use of the Analytic Hierarchy Process (AHP) for ranking outstanding sports records. Since then much has changed with respect to sports and sports records, the application and theory of the AHP, and the availability of the internet for accessing data. In this paper we revisit the ranking of outstanding sports records and build on past work, focusing on a comprehensive set of records from the four major American professional sports. We interviewed and corresponded with two sports experts and applied an AHP-based approach that features both the traditional pairwise comparison and the AHP rating method to elicit the necessary judgments from these experts. The most outstanding sports records are presented, discussed and compared to Golden and Wasil’s results from a quarter century earlier. Keywords: Sports, analytics, Analytic Hierarchy Process, evaluation and ranking, expert opinion 1. Introduction considered, create a single AHP analysis for differ- ent types of records (career, season, consecutive and In 1987, Golden and Wasil (GW) applied the Ana- game), and harness the opinions of sports experts to lytic Hierarchy Process (AHP) to rank what they adjust the set of criteria and their weights and to drive considered to be “some of the greatest active sports the evaluation process. records” (Golden and Wasil, 1987). -
Sabermetrics: the Past, the Present, and the Future
Sabermetrics: The Past, the Present, and the Future Jim Albert February 12, 2010 Abstract This article provides an overview of sabermetrics, the science of learn- ing about baseball through objective evidence. Statistics and baseball have always had a strong kinship, as many famous players are known by their famous statistical accomplishments such as Joe Dimaggio’s 56-game hitting streak and Ted Williams’ .406 batting average in the 1941 baseball season. We give an overview of how one measures performance in batting, pitching, and fielding. In baseball, the traditional measures are batting av- erage, slugging percentage, and on-base percentage, but modern measures such as OPS (on-base percentage plus slugging percentage) are better in predicting the number of runs a team will score in a game. Pitching is a harder aspect of performance to measure, since traditional measures such as winning percentage and earned run average are confounded by the abilities of the pitcher teammates. Modern measures of pitching such as DIPS (defense independent pitching statistics) are helpful in isolating the contributions of a pitcher that do not involve his teammates. It is also challenging to measure the quality of a player’s fielding ability, since the standard measure of fielding, the fielding percentage, is not helpful in understanding the range of a player in moving towards a batted ball. New measures of fielding have been developed that are useful in measuring a player’s fielding range. Major League Baseball is measuring the game in new ways, and sabermetrics is using this new data to find better mea- sures of player performance. -
A Giant Whiff: Why the New CBA Fails Baseball's Smartest Small Market Franchises
DePaul Journal of Sports Law Volume 4 Issue 1 Summer 2007: Symposium - Regulation of Coaches' and Athletes' Behavior and Related Article 3 Contemporary Considerations A Giant Whiff: Why the New CBA Fails Baseball's Smartest Small Market Franchises Jon Berkon Follow this and additional works at: https://via.library.depaul.edu/jslcp Recommended Citation Jon Berkon, A Giant Whiff: Why the New CBA Fails Baseball's Smartest Small Market Franchises, 4 DePaul J. Sports L. & Contemp. Probs. 9 (2007) Available at: https://via.library.depaul.edu/jslcp/vol4/iss1/3 This Notes and Comments is brought to you for free and open access by the College of Law at Via Sapientiae. It has been accepted for inclusion in DePaul Journal of Sports Law by an authorized editor of Via Sapientiae. For more information, please contact [email protected]. A GIANT WHIFF: WHY THE NEW CBA FAILS BASEBALL'S SMARTEST SMALL MARKET FRANCHISES INTRODUCTION Just before Game 3 of the World Series, viewers saw something en- tirely unexpected. No, it wasn't the sight of the Cardinals and Tigers playing baseball in late October. Instead, it was Commissioner Bud Selig and Donald Fehr, the head of Major League Baseball Players' Association (MLBPA), gleefully announcing a new Collective Bar- gaining Agreement (CBA), thereby guaranteeing labor peace through 2011.1 The deal was struck a full two months before the 2002 CBA had expired, an occurrence once thought as likely as George Bush and Nancy Pelosi campaigning for each other in an election year.2 Baseball insiders attributed the deal to the sport's economic health. -
October, 1998
By the Numbers Volume 8, Number 1 The Newsletter of the SABR Statistical Analysis Committee October, 1998 RSVP Phil Birnbaum, Editor Well, here we go again: if you want to continue to receive By the If you already replied to my September e-mail, you don’t need to Numbers, you’ll have to drop me a line to let me know. We’ve reply again. If you didn’t receive my September e-mail, it means asked this before, and I apologize if you’re getting tired of it, but that the committee has no e-mail address for you. If you do have there’s a good reason for it: our committee budget. an e-mail address but we don’t know about it, please let Neal Traven (our committee chair – see his remarks later this issue) Our budget is $500 per year. know, so that we can communicate with you more easily. Giving us your e-mail address does not register you to receive BTN by e- Our current committee member list numbers about 200. Of the mail. Unless you explicitly request that, I’ll continue to send 200 of us, 50 have agreed to accept delivery of this newsletter by BTN by regular mail. e-mail. That leaves 150 readers who need physical copies of BTN. At four issues a year, that’s 600 mailings, and there’s no As our 1998 budget has not been touched until now, we have way to do 600 photocopyings and mailings for $500. sufficient funds left over for one more full issue this year. -
Openwar: an Open Source System for Overall Player Performance in MLB
OpenWAR: An Open Source System for Overall Player Performance in MLB Ben Baumer1 Shane Jensen2 Gregory Matthews3 1 Smith College 2 The Wharton School University of Pennsylvania 3 University of Massachusetts Joint Mathematical Meetings Baltimore, MD January 17th, 2014 Baumer (Smith) openWAR JMM 1 / 21 Introduction Motivation WAR - What is it good for? WinsAboveReplacement Question: How large is the contribution that each player makes towards winning? Four Components: 1 Batting 2 Baserunning 3 Fielding 4 Pitching Replacement Player: Hypothetical 4A journeyman I Much worse than an average player Baumer (Smith) openWAR JMM 2 / 21 Introduction Motivation Units and Scaling In terms of absolute runs: Me Replacement Average Miguel Cabrera 10 40 90 140 In terms of Runs Above Replacement( RAR): Me Replacement Average Miguel Cabrera −30 0 50 100 In terms of Wins Above Replacement( WAR): Me Replacement Average Miguel Cabrera −3 0 5 10 Baumer (Smith) openWAR JMM 3 / 21 Introduction Motivation Example: 2012 WAR leaders FanGraphs fWAR BB-Ref rWAR Mike Trout 10.0 Mike Trout 10.9 Robinson Cano 7.8 Robinson Cano 8.5 Buster Posey 7.7 Buster Posey 7.4 Ryan Braun 7.6 Miguel Cabrera 7.3 David Wright 7.4 Andrew McCutchen 7.2 Chase Headley 7.2 Adrian Beltre 7.0 Miguel Cabrera 6.8 Ryan Braun 7.0 Andrew McCutchen 6.8 Yadier Molina 6.9 Table : 2012 WAR Leaders Baseball Prospectus also publishes WARP There is no ONE formula for WAR! Baumer (Smith) openWAR JMM 4 / 21 Introduction Motivation WAR is the Answer Baumer (Smith) openWAR JMM 5 / 21 Introduction Related -
PFF WAR: Modeling Player Value in American Football
PFF WAR: Modeling Player Value in American Football Submission ID: 1548728 Track: Other Sports Player valuation is one of the most important problems in all of team sports. In this paper we use Pro Football Focus (PFF) player grades and participation data to develop a wins above replacement (WAR) model for the National Football League. We find that PFF WAR at the player level is more stable than traditional, or even advanced, measures of performance, and yields dramatic insiGhts into the value of different positions. The number of wins a team accrues throuGh its players’ WAR is more stable than other means of measurinG team success, such as PythaGorean win totals. We finish the paper with a discussion of the value of each position in the NFL draft and add nuance to the research suggesting that tradinG up in the draft is a negative-expected-value move. 1. Introduction Player valuation is one of the most important problems in all of team sports. While this problem has been addressed at various levels of satisfaction in baseball [1], [23], basketball [2] and hockey [24], [6], [13], it has larGely been unsolved in football, due to unavailable data for positions like offensive line and substantial variations in the relative values of different positions. Yurko et al. [25] used publicly available play-by-play data to estimate wins above replacement (WAR) values for quarterbacks, receivers and running backs. Estimates for punters [4] have also been computed, and the most-recent work of ESPN Sports Analytics [9] has modified the +/- approach in basketball to college football beginning in the fall of 2019. -
Determining the Value of a Baseball Player
the Valu a Samuel Kaufman and Matthew Tennenhouse Samuel Kaufman Matthew Tennenhouse lllinois Mathematics and Science Academy: lllinois Mathematics and Science Academy: Junior (11) Junior (11) 61112012 Samuel Kaufman and Matthew Tennenhouse June 1,2012 Baseball is a game of numbers, and there are many factors that impact how much an individual player contributes to his team's success. Using various statistical databases such as Lahman's Baseball Database (Lahman, 2011) and FanGraphs' publicly available resources, we compiled data and manipulated it to form an overall formula to determine the value of a player for his individual team. To analyze the data, we researched formulas to determine an individual player's hitting, fielding, and pitching production during games. We examined statistics such as hits, walks, and innings played to establish how many runs each player added to their teams' total runs scored, and then used that value to figure how they performed relative to other players. Using these values, we utilized the Pythagorean Expected Wins formula to calculate a coefficient reflecting the number of runs each team in the Major Leagues scored per win. Using our statistic, baseball teams would be able to compare the impact of their players on the team when evaluating talent and determining salary. Our investigation's original focusing question was "How much is an individual player worth to his team?" Over the course of the year, we modified our focusing question to: "What impact does each individual player have on his team's performance over the course of a season?" Though both ask very similar questions, there are significant differences between them. -
Baseball Prospectus, 1997, 1997, Gary Huckabay, Clay Davenport, Joe Sheehan, Chris Kahrl, 0965567400, 9780965567404, Ravenlock Media, 1997
Baseball Prospectus, 1997, 1997, Gary Huckabay, Clay Davenport, Joe Sheehan, Chris Kahrl, 0965567400, 9780965567404, Ravenlock Media, 1997 DOWNLOAD http://bit.ly/1oCjD77 http://en.wikipedia.org/wiki/Baseball_Prospectus_1997 DOWNLOAD http://fb.me/23h0t0pz6 http://avaxsearch.com/?q=Baseball+Prospectus%2C+1997 http://bit.ly/1oRwfu3 Hockey Prospectus 2010-11 The Essential Guide to the 2010-11 Hockey Season, Hockey Prospectus, Tom Awad, Will Carroll, Lain Fyffe, Philip Myrland, Richard Pollack, Sep 15, 2010, Sports & Recreation, 370 pages. In the winning tradition of the New York Times bestselling Baseball Prospectus comes the world's greatest guide to the NHL. The authors of Hockey Prospectus combine cutting. There's a God on the Mic The True 50 Greatest Mcs, Kool Moe Dee, Oct 4, 2008, Music, 224 pages. Rates fifty of the greatest rap emcees, scoring them in seventeen categories, including lyricism, originality, vocal presence, poetic value, body of work, social impact, and. The Hardball Times Baseball Annual , Dave Studenmund, Greg Tamer, Nov 1, 2004, Sports & Recreation, 298 pages. A complete review of the 2004 baseball season, as seen through the eyes of an online baseball magazine called The Hardball Times (www.hardballtimes.com). The Hardball Times. Baseball Prospectus 2005 Statistics, Analysis, and Insight for the Information Age, David Cameron, Baseball Prospectus Team of Experts, Feb 18, 2005, Sports & Recreation, 576 pages. Provides profiles of major league players with information on statistics for the past five seasons and projections for the 2005 baseball season.. Vibration spectrum analysis a practical approach, Steve Goldman, 1991, Science, 223 pages. Vibration Spectrum Analysis helps teach the maintenance mechanic or engineer how to identify problem areas before extensive damage occurs. -
Twar: Introducing a Method to Actually Calculate Wins Above Replacement
tWAR: introducing a method to actually calculate wins above replacement Daniel J. Eck March 21, 2019 1 Introduction Wins above replacement (WAR) is meant to be a one-number summary of the total contribution made by a player for his team in any particular season. As stated by Steve Slowinski of Fangraphs, WAR offers an estimate to answer the question, \If this player got injured and their team had to replace them with a freely available player of lower quality from their bench, how much value would the team be losing," where this value is expressed in number of wins [Slowinski, 2010]. That being said, nobody actually calculates WAR in a manner that properly answers the above question as posed. This is not by any explicit fault of the metric and those who calculate it. One problem is that it is impossible to simultaneously quantify the value of a player when the player is available and the value of a replacement to that player when the player is unavailable. The player in question is either available to play or unavailable to play, never both. Instead of confronting the problems raised in this factual-counterfactual world, people have attempted to calculate a hypothetical replacement player to implicitly compare every player with using the machinery of a proprietary black box [Baumer et al., 2015]. Three widely used versions of WAR that are calculated in this manner are Baseball Reference's bWAR [Reference, 2010], Fangraphs's fWAR [Slowinski, 2010], and Baseball Prospectus's bWARP [Prospectus, 2019]. Through the incorporation of ideas from causal inference, we propose methodolody to directly estimate wins above replacement. -
Pine Tar and the Infield Fly Rule: an Umpire’S Perspective on the Hart-Dworkin Jurisprudential Debate
Pine Tar and the Infield Fly Rule: An Umpire’s Perspective on the Hart-Dworkin Jurisprudential Debate William D. Blake, Ph.D.1 Assistant Professor Department of Political Science Indiana University, Indianapolis (IUPUI) [email protected] Abstract: What is law? Though on its face this question seems simple, it remains an incredibly controversial one to legal theorists. One prominent jurisprudential debate of late occurred between H.L.A. Hart, a positivist, and Ronald Dworkin, an interpretivist. While positivism, at its core, holds the law is a set of authoritative commands, Dworkin rejects this reflexive approach and instructs judges to incorporate and advance communal norms and morals in their decisions. In baseball, umpires utilize both legal theories, depending on the type of rule they are asked to interpret or enforce. I conclude that, like umpires, most citizens are not dogmatic about either legal theory. 1 I wish to thank Justice George Nicholson of the California Court of Appeal for encouraging my participation at this Symposium. I am eternally grateful to former Major Leaguer Jim Abbott for taking the time to respond to my questions. Finally, to the 13 year-old pitcher whom I discuss in this paper: your courage and enthusiasm are inspiring, but, for Pete's sake, please practice coming set. Electronic copy available at: http://ssrn.com/abstract=2403586 Bill Klem, one of the 2 first umpires inducted into the Baseball Hall of Fame, once wrongly called a runner out at home plate. A lucky newspaper photographer snapped a shot, which demonstrated Klem’s mistake. The next day, reporters demanded to know how the batter could be out in light of the incontrovertible photographic evidence. -
Investigating Major League Baseball Pitchers and Quality of Contact Through Cluster Analysis
Grand Valley State University ScholarWorks@GVSU Honors Projects Undergraduate Research and Creative Practice 4-2020 Investigating Major League Baseball Pitchers and Quality of Contact through Cluster Analysis Charlie Marcou Grand Valley State University Follow this and additional works at: https://scholarworks.gvsu.edu/honorsprojects Part of the Sports Sciences Commons, and the Statistics and Probability Commons ScholarWorks Citation Marcou, Charlie, "Investigating Major League Baseball Pitchers and Quality of Contact through Cluster Analysis" (2020). Honors Projects. 765. https://scholarworks.gvsu.edu/honorsprojects/765 This Open Access is brought to you for free and open access by the Undergraduate Research and Creative Practice at ScholarWorks@GVSU. It has been accepted for inclusion in Honors Projects by an authorized administrator of ScholarWorks@GVSU. For more information, please contact [email protected]. Investigating Major League Baseball Pitchers and Quality of Contact through Cluster Analysis Charlie Marcou Introduction The rise of sabermetrics, the quantitative analysis of baseball, has changed how baseball front offices operate, how prospects are evaluated and developed, and how baseball is played on the field. Stolen bases are on the decline, while strikeouts, walks, and homeruns have steadily increased. Hitters care more and more about their launch angle and pitchers have started using high speed cameras to analyze their movement. Despite these changes, there are still many areas that need investigation. This paper seeks to investigate the quality of contact that a pitcher allows. Not much is currently known about quality of contact, but if factors determining quality of contact could be determined it could assist teams in identifying and developing pitching talent. -
Overlooked Legend Award
! ! ! ! ! ! ! ! !SABR Nineteenth Century Committee Overlooked Legend Award ! 2014 Nominees ! ! Doc Adams Bob Caruthers Jim Creighton Jack Glasscock Paul Hines Dummy Hoy Bobby Mathews Tony Mullane Al Reach George Van Haltren ! ! !Biographies compiled by Adam Darowski and Joe Williams. All references to Wins Above Replacement (WAR) use the version published on Baseball-Reference.com. Doc Adams Born: November 1, 1814, Died: January 3, 1899 Years as Player: 1839–1862 Position: Pioneer ! The title “Father of Baseball” has been bestowed on a handful of gentlemen since the early days of our national pastime. Daniel Lucius Adams is among them. A graduate of both Yale and Harvard, Adams helped shape the game as we know it today. As a young physician in New York City, “Doc” played a form of baseball as early as 1839 and became a member of the famed Knickerbocker Base Ball Club in 1845, about a month after the club was formed. In 1846, Doc was elected vice president of the Knickerbockers and played in the famous “first” game between clubs on June 19 at Elysian Fields in Hoboken, New Jersey. The following year he was elected president of the club, a position he held for the next three years and would serve again from 1856 to 1858. ! In 1848, he headed the committee to revise the rules and by-laws of the Knickerbockers. As a player, Adams is credited as being the first shortstop in 1849 or 1850, first as an intermediary to receive the relay throws of the outfielders, but later moving up to the infield. The lefty batter played regularly and productively into his forties.