Clutch Hitters Revisited Pete Palmer and Dick Cramer National SABR Convention June 30, 2008

Similar documents
Do Clutch Hitters Exist?

Should pitchers bat 9th?

Figure 1. Winning percentage when leading by indicated margin after each inning,

Table 1. Average runs in each inning for home and road teams,

Effects of Incentives: Evidence from Major League Baseball. Guy Stevens April 27, 2013

Draft - 4/17/2004. A Batting Average: Does It Represent Ability or Luck?

It s conventional sabermetric wisdom that players

Hitting with Runners in Scoring Position

Looking at Spacings to Assess Streakiness

Analyses of the Scoring of Writing Essays For the Pennsylvania System of Student Assessment

Additional On-base Worth 3x Additional Slugging?

One of the most-celebrated feats

Regression to the Mean at The Masters Golf Tournament A comparative analysis of regression to the mean on the PGA tour and at the Masters Tournament

Mapping the Fog Bill James, July, 2005

Simulating Major League Baseball Games

When Should Bonds be Walked Intentionally?

Major League Baseball Offensive Production in the Designated Hitter Era (1973 Present)

How to Make, Interpret and Use a Simple Plot

POWER Quantifying Correction Curve Uncertainty Through Empirical Methods

2014 NATIONAL BASEBALL ARBITRATION COMPETITION ERIC HOSMER V. KANSAS CITY ROYALS (MLB) SUBMISSION ON BEHALF OF THE CLUB KANSAS CITY ROYALS

save percentages? (Name) (University)

Beyond Central Tendency: Helping Students Understand the Concept of Variation

Why We Should Use the Bullpen Differently

BABE: THE SULTAN OF PITCHING STATS? by. August 2010 MIDDLEBURY COLLEGE ECONOMICS DISCUSSION PAPER NO

Matt Halper 12/10/14 Stats 50. The Batting Pitcher:

Rating Player Performance - The Old Argument of Who is Bes

Competitive Performance of Elite Olympic-Distance Triathletes: Reliability and Smallest Worthwhile Enhancement

September 29, New type of file on Retrosheet website. Overview by Dave Smith

PLATE MECHANICS SET POSITION

Percentage. Year. The Myth of the Closer. By David W. Smith Presented July 29, 2016 SABR46, Miami, Florida

The Cold Facts About the "Hot Hand" in Basketball

PGA Tour Scores as a Gaussian Random Variable

Taking Your Class for a Walk, Randomly

WORKING GROUP ON STOCK ASSESSMENTS 5 TH MEETING DOCUMENT SAR-5-08 TARGET SIZE FOR THE TUNA FLEET IN THE EASTERN PACIFIC OCEAN

Chapter 2 - Displaying and Describing Categorical Data

Chapter 3 - Displaying and Describing Categorical Data

1. OVERVIEW OF METHOD

Average Runs per inning,

a) List and define all assumptions for multiple OLS regression. These are all listed in section 6.5

CORESTA RECOMMENDED METHOD N 6

THE NUMBER OF COLONIES ALLOWABLE ON SATISFACTORY AGAR PLATES. counts is the limit in the number of colonies that may be allowed

Department of Economics Working Paper Series

Lorenzo Cain v. Kansas City Royals. Submission on Behalf of the Kansas City Royals. Team 14

Snell Certification and Enforcement Testing EBB 8/28/2011

TPM TIP. Oil Viscosity

Averages. October 19, Discussion item: When we talk about an average, what exactly do we mean? When are they useful?

THE BOOK--Playing The Percentages In Baseball

THE MENTAL GAME OF BASEBALL: A GUIDE TO PEAK PERFORMANCE H.A. DORFMAN AND KARL KUEHL

Pitching Performance and Age

The Rise in Infield Hits

JEFF SAMARDZIJA CHICAGO CUBS BRIEF FOR THE CHICAGO CUBS TEAM 4

Chapter. 1 Who s the Best Hitter? Averages

Which On-Base Percentage Shows. the Highest True Ability of a. Baseball Player?

2014 National Baseball Arbitration Competition

A Remark on Baserunning risk: Waiting Can Cost you the Game

The Influence of Free-Agent Filing on MLB Player Performance. Evan C. Holden Paul M. Sommers. June 2005

A Monte Carlo Approach to Joe DiMaggio and Streaks in Baseball 1

UnOPS (OPS w/o E minus OPS w/ E)

Chapter 3 Displaying and Describing Categorical Data

Running head: DATA ANALYSIS AND INTERPRETATION 1

When you think of baseball, you think of a game that never changes, right? The

Lab Report Outline the Bones of the Story

An Analysis of the Effects of Long-Term Contracts on Performance in Major League Baseball

Pitching Performance and Age

A Hare-Lynx Simulation Model

Jenrry Mejia v. New York Mets Submission on Behalf of the New York Mets Midpoint: $2.6M Submission by Team 32

ROUNDABOUT CAPACITY: THE UK EMPIRICAL METHODOLOGY

Reduction of Speed Limit at Approaches to Railway Level Crossings in WA. Main Roads WA. Presenter - Brian Kidd

Machine Learning an American Pastime

The Upper Charles Summer Baseball League Rules and Regulations Modified

Revisiting the Hot Hand Theory with Free Throw Data in a Multivariate Framework

DO YOU KNOW WHO THE BEST BASEBALL HITTER OF ALL TIMES IS?...YOUR JOB IS TO FIND OUT.

Journal of Emerging Trends in Computing and Information Sciences

The LEAGUE THAT MATTERS Rules effective January 2018 Page 1 of 5. League Rules effective as of 20 January 2018

Money Lost or Won -$5 +$3 +$7

STANDARD SCORES AND THE NORMAL DISTRIBUTION

IHS AP Statistics Chapter 2 Modeling Distributions of Data MP1

Kelsey Schroeder and Roberto Argüello June 3, 2016 MCS 100 Final Project Paper Predicting the Winner of The Masters Abstract This paper presents a

DECISION MODELING AND APPLICATIONS TO MAJOR LEAGUE BASEBALL PITCHER SUBSTITUTION

2015 NATIONAL BASEBALL ARBITRATION COMPETITION. Mark Trumbo v. Arizona Diamondbacks. Submission on Behalf of Mark Trumbo. Midpoint: $5,900,000

An Analysis of Factors Contributing to Wins in the National Hockey League

Compression Study: City, State. City Convention & Visitors Bureau. Prepared for

Bragan s 1956 Pirates Unconventional Lineups

2014 Tulane Baseball Arbitration Competition Josh Reddick v. Oakland Athletics (MLB)

Greatest Show on the Diamond. As April rolls in, the majority of us are thinking some of the same things; finals and

Predicting the Total Number of Points Scored in NFL Games

Lesson 2 Pre-Visit Slugging Percentage

Tech Suit Survey (Virginia LMSC)

WHAT CAN WE LEARN FROM COMPETITION ANALYSIS AT THE 1999 PAN PACIFIC SWIMMING CHAMPIONSHIPS?

ANALYSIS OF A BASEBALL SIMULATION GAME USING MARKOV CHAINS

Lecture 22: Multiple Regression (Ordinary Least Squares -- OLS)

Bhagwant N. Persaud* Richard A. Retting Craig Lyon* Anne T. McCartt. May *Consultant to the Insurance Institute for Highway Safety

Expansion: does it add muscle or fat? by June 26, 1999

Internet Technology Fundamentals. To use a passing score at the percentiles listed below:

Validation of Measurements from a ZephIR Lidar

Analysis of Shear Lag in Steel Angle Connectors

THERE S NO I IN TEAM

Examining NBA Crunch Time: The Four Point Problem. Abstract. 1. Introduction

Computationally Efficient Determination of Long Term Extreme Out-of-Plane Loads for Offshore Turbines

ESTIMATION OF THE DESIGN WIND SPEED BASED ON

Transcription:

Clutch Hitters Revisited Pete Palmer and Dick Cramer National SABR Convention June 30, 2008 Do clutch hitters exist? More precisely, are there any batters whose performance in critical game situations consistently exceeds expectations, as established both by that batter s performance in less critical situation and also by the relative performance of average batters in critical game situations? Thirty years ago one of us published a first investigation of clutch hitting (1), using 1969 and 1970 data (2) that at the time seemed the only play-by-play information that might ever become available. Its conclusions, that any clutch abilities were too small to be either detectable or meaningful, have been confirmed repeatedly (3) as much more data have emerged. However skepticism remains. The occasional stresses that all of us experience in our daily lives are certainly felt as negative influences on our own clutch performances, and professional athletes in particular often talk about the challenge of contending with the pressures of critical game situations. Thus clutch hitting exemplifies the puzzling and fascinating conflicts that occasionally arise between human perceptions and the results of objective investigation. For example, recently Bill James (4) has proposed that the existence of clutch hitters, as exemplified by David Ortiz s recent heroics, is obscured by fog, that is, the unavoidable random variation in the performances of all players and game situations that underlie those objective investigations. Perhaps, he says, clutch hitting is a strong, and so more consistent and detectable, ability only for certain classes of players, identifiable by their personality type or overall hitting style. Our response has been to perform several new studies, taking fullest advantage of the last fifty years of play-by-play that Retrosheet (5) now provides, that attempt objective answers to the following questions about clutch hitting 1) Do batting performances actually decline in critical game situations, in general? 2) How thick is that fog that Bill reminds us about? 3) Over the last fifty years, what are the largest clutch or non-clutch career performances? 4) With respect to Bill s proposed player classes, how many players would need to be members in order to be persuasive about clutch hitting? 5) Would a clutch hitting skill reflect well on the players who possessed it? For those readers who prefer conclusions without statistical equations or argumentative logic, here are the objective answers to those questions. 1) The average batting production by major league players with runners in scoring position, as measured by OPS from 1957 to 2007, is indistinguishable (if anything very

slightly higher) for the 15% of plate appearances when the game is late and close (as defined by Elias), once appropriate corrections are made for the substantial superiority of the pitchers offsetting the greater frequency of intentional walks and the modest superiority of the batters. 2) The fog of random statistical variation is much greater than most baseball fans realize, even those with an analytical bent. Indeed, that random variability has about the same effect on season outcomes such as batting titles and pennant winners as do differences in player skills. Considering also this lack of effect by game situation on overall batting and the small number of high pressure game situations that any individual batter encounters, objective evidence that some particular hitter s superior record in clutch situation is a skill rather than a chance result is very unlikely ever to appear. To that extent, we agree with Bill James. 3) On a career basis, David Ortiz and a different clutch hitter nominee (5), Mark Grace, are both around a third of the way down a ranked list of clutch performances, among all players with 3000 plate appearances from 1957 to 2007. Positive but hardly to any notable extent. The highest career clutch performance was by Scott Fletcher, who on average contributed about ten more runs -worth per year (or one game per year in the standings) to his teams than his season statistics imply. At the bottom of the ranked list is Richard Hidalgo, who contributed ten fewer runs -worth. The overall distribution of the 897 career clutch performances is entirely attributable to chance deviations around our first result, that batters in general perform no differently in clutch situations. 4) The considerable thickness of the fog also makes identifying any class of players likely to possess a clutch ability into a considerable challenge. Inspection of the ranked list does suggest a tendency for power hitters to have experienced lower clutch performances. However this tendency may instead reflect slight weaknesses in the metrics we have used. 5) To repeat the concluding suggestion in the original study, but also now knowing that batters in general perform no differently in clutch situations -- if a batter s performance in clutch situations truly exceeded that in other situations, might that not indicate that he was putting forward a less than maximal effort in non-clutch situations? Why would that be a desirable player characteristic? We now describe, in general terms, the studies that lead to these conclusions. (methodological details of course being available from the authors.) First, perhaps the most important new finding. We compare the general performances of batters in tense game situations with performance in all situations, for two groups, one based on the Elias definition of late and close and considering all major league plate appearances from 1957 to 1979, and the other based on the Mills brothers model (see below) and considering only the previously mentioned group of 897 players who clearly had more successful major league careers. For this purpose we use the widely accepted OPS metric, originally proposed by one of us (6). Here are the results.

Group OPS: Tense Situations OPS: All Situations All players, Elias late and close (15% of appearances).704.715 891 players, tensest 10% of plate appearances (Mills).779.771 Certainly factors other than tension affect the average outcome of late and close plate appearancesl. The best available pitchers will be used (depressing OPS in tense situations), but pinch hitters are used more and intentional walks occur twice as often (raising OPS in tense situations). However, we estimate that these factors roughly cancel one another, so that, as the tabulated OPS values themselves suggest, major league hitters is little if at all affected by game situation tension. Further investigations require a working definition of pure clutch performance, and we follow other analysts in taking the approach that the Mills brothers (2) pioneered. The probable outcome of any game fluctuates at-bat by at-bat until the game ends, and this probability fluctuation constitutes a win value, a positive or negative contribution that a batter makes to his team s chance of winning, as the outcome of each and every plate appearance. The sum of these win values over every appearance in a particular batter s career becomes a direct measurement of that batter s total win value. Division of that total performance by the number of plate appearances yields the batter s average win performance. However there is a general propensity for superior hitters to have superior win performances in any game situation. To isolate clutchness, a possible tendency for a hitter to be more effective in critical game situations than otherwise, this general propensity must be removed from that hitter s total win value. Linear weights (also introduced by one of us) provide a thoroughly tested measure of situation-independent hitting skill. We can then compare these two measurements, win performances depending only on how the probability of victory changed after each plate performance, and linear weights depending only on the fundamental counting statistics. Correlation of the 897 players seasonal win performances now available with their corresponding linear weight totals yields this general propensity, as depicted by the diagonal line in Figure 1. The clutchness or non-clutchness of a player in a particular season then becomes the distance by which his total win performance in that season lies above or below the particular position on that diagonal determined by his linear weight total. Figure 1 also shows these clutchness results for each season of David Ortiz s career. His reputation for clutchness was built in 2005 and 2006. His hitting in 2007 was even slightly better overall (the 2007 point is farther to the right of the graph) but less timely (the 2007 point is also lower), yielding a lower-than-average clutchness result.

However, no one doubts that baseball is a percentage game, that because of unavoidable and therefore random variations such as bad bounces, good performances can produce bad results and vice versa. To what extent might David Ortiz s historically superior clutch performances in 2005 and 2006 be matters of good fortune? This type of question motivated us to estimate the general magnitudes of these inherent and inevitable random variations in both win value and linear weight performances, using a variety of computer modeling approaches. Another way of expressing this central concern is shown in Figure 2, which compares the clutch performance results we have just defined (at the bottom) with a curve representing our various estimates (which all agree within 10% or so) of these random variations in clutch performance (or, in Bill James language, the density of the fog ). As the graph suggests and as probability theory confirms, there is nothing in the overall distribution of clutch performance results for the 897 most active batters over the last fifty years that proposes anything other than random fluctuations as their cause.

Because of both the importance of the result and also the uncertainties of the result from any individual computer model, the largest component of this study involved devising and applying several independent computational approaches. The agreement among their results is encouraging. Here are brief descriptions of these approaches: Direct simulation, or actual play of 1220 games with 18 similar batters and using the same outcome probabilities regardless of game situation. Comparing actual clutchness distributions with a performance distribution that is undoubtedly random, in this case the remainder from dividing the day of the month of the game by 10. actual seasonal win-performance-to-linear-weight comparisons by clutchness Considering that Ortiz s two greatest clutch seasons were consecutive, perhaps suggesting that clutch ability is real but fleeting, and recapitulating a key component of the original study, we calculated the correlation coefficient between clutch performance results in all consecutive seasons of at least 250 BFP s each for every one of those 895 most successful batters. The resulting r 2 value of.002 is as inconsequential as it looks. For comparison, the r 2 value for OPS itself is 0.43. Presumably batters feel pressure most strongly at the unproven starts of their major league careers. However the batting average of these 895 batters in their first hundred BFP,.260, is not very different from their collective career batting average.

Thus the results of the original study (1) are yet again confirmed, this time by every analysis we can devise and based mostly on fifty seasons of major league play. Over this period there is no convincing evidence that any fluctuation of any batter s performance in tense situations had any cause beyond random variation. Furthermore, because batting performance is unaffected by game situation overall, there would be no honor in being identified as a clutch hitter. Why shouldn t a major league batter give his best effort regardless of the game situation? The conflict continues between the feeling of tension in critical game situations, expressed even by many of the most experienced and successful major league batters, and the actual outcomes. References: 1) Do Clutch Hitters Exist? By Richard D. Cramer (SABR Baseball Research Journal 1977) 2) Mills, E. G.; Mills, H. D. Player Win Averages, A.S. Barnes, Cranbury, NJ (1970). (1970 data provided by Pete Palmer.) 3) http://www.geocities.com/cyrilmorong@sbcglobal.net/clutchlinks2.htm 4) Mr. Clutch Big Papi, Chipper, Pujols come through when it counts by Bill James. Underestimating the Fog by Bill James 5) Tango, T. M.; Lichtman, M. G.; Dolphin, A. E. The Book: Playing the Percentages. TMA Press (2006). 6) Thorn, J.; Palmer, P. Total Baseball (1989).