“[J.P.] Ricciardi also had the best line of the day when asked about clutch hitting. He talked about how there are players who don’t panic in certain situations, who can ‘slow the game down.’ He mentioned how David Ortiz and Manny Ramirez were like that and added, ‘I’ve known Manny since he was 15, and I don’t think he knows the game is on the line.’ The Boston crowd loved it.”
—David Pinto of Baseball Musings on the Blue Jays GM and his comments at the MIT Sloan Sports Business Conference in early February.
Clutch hitting is one of those issues that just won’t go away. Ever since Dick Cramer‘s famous study titled “Do Clutch Hitters Exist?” was published in the 1977 Baseball Research Journal there has been no end to the discussion of just what is and what isn’t clutch hitting, and how it can or can’t be measured.
The controversy was never more in evidence than in the spring and summer of 2005 when, in the wake of the Bill James piece “Underestimating the Fog” (warning: pdf) published in Volume 33 of the Baseball Research Journal, there was plenty of point-counterpoint in the analysis community.
BP’s own James Click got in on the act with two interesting articles in the fall of 2005, where he used Keith Woolner‘s Win Expectancy (WX) framework combined with first VORP and then Marginal Lineup Value (MLV) to generate measures he termed PrjWINS and Clutch. He concluded that the correlation for Clutch from year to year, and even over halves of a career, indicated that the measure was “nearly completely random.”
The issue was again resurrected after the publication of Tom M. Tango, Mitchel Lichtman, and Andrew Dolphin’s The Book in early 2006, wherein the authors noted that there is indeed a small player-to-player variation in clutch skill, and measured that one in six players increase–and a comparable number of players decrease–their on base percentage by eight points or more when faced with pressure situations (defined as any situation in which the batter’s team is trailing by one, two, or three runs in the eighth inning or later). The spread decreases to six points when using their weighted on base average (wOBA) metric, and when regressed to the mean the wOBA skill maxes out at around two points.
Around the same time Nate Silver (with his chapter “Is David Ortiz a Clutch Hitter?” in Baseball Between the Numbers, get your copy in paperback today) used a similar approach to Click with WX and a modified version of MLV, but also included Leverage to create a measure also termed Clutch. After crunching the numbers, he found that players with higher walk and lower strikeout rates do perform slightly better than would otherwise be expected. Overall, he concluded, clutch hitting accounts for something on the order of two percent of what it takes to produce wins at the plate.
That pretty much sums up where we are at this point. While earlier attempts at measuring clutch hitting suffered from various definitions of just what a clutch situation is, versions that use WX can be more fluid since in reality pressure situations probably manifest themselves more as a continuum than as discrete instances. This also then has the effect of allowing a larger sample size, properly weighted, to be included. Even so, it would appear that for the vast majority of players most of the time the effects are so small that perceived clutch hitting ability should generally not drive either strategic or personnel decisions.
So of course that means our topic today is clutch hitting. More precisely, it is a discussion of the best and worst clutch performers of 2006.
Who’s the Clutchest of Them All?
Will Carroll and I had a friendly discussion of WX and clutch hitting in the wake of “the game of the century” which I posted on my blog. In that conversation I largely agreed with Carroll, who compared WX at the level of an individual game to a fancy form of game winning RBI. While I think that’s an apt analogy, since WX at that level is so heavily influenced by the vagaries of opportunity and chance, I do think that WX is valuable at the seasonal level at least in retrospect.
Viewing WX at the level of the game records clutch performances, while at the level of a season, it is simply the total contribution of a player towards winning and losing given the situations they found themselves in. In other words, we can use it to discover who contributed most and least (at least in the realm of pure offensive output) from an aggregate perspective in moving their team towards wins, and as we’ll see, who outperformed or underperformed their 2006 level. What we can’t do–as the previous research has taught us–is use this information as a basis for predicting how they’ll do in the future.
So let’s begin with a look at the leaders and trailers in WX for 2006.
Name PA WX Albert Pujols 634 9.30 Ryan Howard 704 8.17 David Ortiz 686 7.98 Lance Berkman 646 5.66 Derek Jeter 715 5.42 Carlos Beltran 617 5.25 Miguel Cabrera 676 5.15 Jermaine Dye 611 4.61 Travis Hafner 563 4.58 Jason Giambi 579 4.55 Barry Bonds 493 4.36 David Wright 661 4.33 Chase Utley 739 4.30 Ryan Zimmerman 682 4.19 Andruw Jones 669 3.97 Justin Morneau 661 3.93 Bobby Abreu 686 3.81 Todd Helton 649 3.71 Garrett Atkins 695 3.54 Jim Thome 610 3.51 -------------------------------- Ronny Cedeno 572 -4.53 Angel Berroa 503 -4.28 Adam Everett 566 -3.31 Jose Castillo 562 -2.97 Brad Ausmus 502 -2.59 Clint Barmes 535 -2.49 Cory Sullivan 443 -2.48 Javy Lopez 364 -2.48 Shea Hillenbrand 566 -2.44 Royce Clayton 502 -2.42 Craig Biggio 607 -2.39 Neifi Perez 316 -2.36 Alex Gonzalez 429 -2.36 Coco Crisp 452 -2.34 Yuniesky Betancourt 584 -2.33 Jose Lopez 655 -2.33 Ron Belliard 590 -2.23 Jorge Cantu 448 -2.22 Abraham Nunez 369 -2.18 Brian N. Anderson 405 -2.15
From an overall perspective Albert Pujols comes out on top at +9.30 wins, followed by Ryan Howard (+8.17) and David Ortiz (+7.98), while Ronny Cedeno brings up the rear at -4.53 with Angel Berroa (-4.28) close behind. While it is not surprising that most of the MVP candidates made their way onto the top 20 with AL MVP Justin Morneau coming in 16th overall and sixth in his league, both Bobby Abreu (+3.81) and Todd Helton (+3.71), both of whom hit just 15 home runs and turned in remarkably similar seasons, made the list.
Rookie
These lists largely reflect what we know already: Albert Pujols is good, and Neifi Perez isn’t. To level the playing field, we can use a technique I discussed in a column almost a year ago titled “Wins and the Quantum.” There, we used the formula Woolner provided in an article in the 2006 Baseball Prospectus to estimate the WX value of various offensive events by run environment, and then applied them to the entire history of baseball. Using that same approach, we can apply the formula to the 2006 season and produce a table which shows us the players who would be expected to contribute the most in terms of WX under a measure called WX
Name PA WX1 Albert Pujols 634 5.73 Ryan Howard 704 5.04 Travis Hafner 563 4.59 Lance Berkman 646 4.33 Miguel Cabrera 676 4.32 Carlos Beltran 617 4.18 David Ortiz 686 4.14 Manny Ramirez 558 3.79 Chipper Jones 477 3.48 Garrett Atkins 695 3.24 Derek Jeter 715 3.21 Nick Johnson 628 3.19 Jim Thome 610 3.18 Jermaine Dye 611 3.10 David Wright 661 3.07 Jason Bay 689 3.00 Jason Giambi 579 2.90 Bobby Abreu 686 2.86 Vladimir Guerrero 665 2.86 Brian McCann 492 2.82 -------------------------------- Angel Berroa 503 -3.59 Clint Barmes 535 -3.59 Ronny Cedeno 572 -3.51 Yadier Molina 461 -2.71 Brad Ausmus 502 -2.71 Adam Everett 566 -2.68 Joey Gathright 445 -2.40 Brian N. Anderson 405 -2.29 Tomas Perez 254 -2.26 Abraham Nunez 369 -2.23 Neifi Perez 316 -2.12 Scott Podsednik 592 -2.03 Royce Clayton 502 -2.01 Juan Uribe 495 -2.00 Jose Castillo 562 -1.94 John McDonald 286 -1.88 Mark Loretta 703 -1.87 John Buck 409 -1.80 Rondell White 355 -1.79 Willy Taveras 587 -1.76
These lists are very similar to the previous ones, primarily being just a reshuffling of the same guys, since good players tend to get hits in all situations, while bad players do not. The correlation in 2006 between WX and WX
Where it gets more interesting is to subtract WX from WX
Name PA WX1 WX WXC Leverage David Ortiz 686 4.14 7.98 3.84 1.02 Albert Pujols 634 5.73 9.30 3.57 1.07 Ryan Zimmerman 682 0.90 4.19 3.28 1.07 Geoff Jenkins 555 -0.03 3.22 3.25 1.06 Ryan Howard 704 5.04 8.17 3.13 1.05 Melvin Mora 705 -1.07 1.90 2.97 1.00 Marcus Giles 626 -0.63 2.34 2.96 1.08 Mark Loretta 703 -1.87 0.79 2.66 1.02 Ken Griffey 472 -0.37 1.93 2.31 1.10 Todd Helton 649 1.41 3.71 2.30 1.05 Derek Jeter 715 3.21 5.42 2.21 0.99 Brian Schneider 455 -1.68 0.43 2.11 1.08 Jay Payton 588 -0.69 1.39 2.08 1.00 Jeff Francoeur 686 -1.32 0.64 1.97 0.99 Chase Utley 739 2.42 4.30 1.88 1.07 Andruw Jones 669 2.17 3.97 1.80 1.00 Barry Bonds 493 2.62 4.36 1.74 1.03 Frank Catalanotto 499 0.17 1.89 1.72 1.01 Jacque Jones 577 0.47 2.14 1.66 1.01 Jason Giambi 579 2.90 4.55 1.65 1.01 -------------------------------------------------------- Chipper Jones 477 3.48 0.98 -2.50 1.01 Dave Roberts 566 1.01 -1.18 -2.19 1.04 Troy Glaus 634 0.81 -1.35 -2.16 0.96 Alex Rodriguez 674 2.77 0.85 -1.92 0.97 Jason Bay 689 3.00 1.11 -1.88 1.12 Victor Martinez 652 1.60 -0.26 -1.86 0.93 Juan Rivera 494 1.41 -0.23 -1.64 0.97 Tim Salmon 244 0.17 -1.37 -1.53 1.03 Marco Scutaro 423 -0.13 -1.65 -1.53 0.96 Shea Hillenbrand 566 -0.93 -2.44 -1.51 0.99 Scott Rolen 594 1.79 0.36 -1.43 1.00 Chone Figgins 683 -0.66 -2.03 -1.38 1.00 Scott Hatteberg 539 0.53 -0.84 -1.37 1.02 Casey Blake 456 0.70 -0.66 -1.37 0.92 Andre Ethier 441 0.56 -0.81 -1.37 1.00 Cory Sullivan 443 -1.19 -2.48 -1.29 1.13 Adam Melhuse 139 -0.68 -1.97 -1.29 1.00 Hideki Matsui 201 0.78 -0.48 -1.26 0.84 Henry Blanco 261 -0.58 -1.83 -1.25 0.94 Carl Crawford 652 0.98 -0.26 -1.23 1.05
The players in the first group can truly be called the best clutch performers of 2006, while those in the latter group you can use for scapegoating if they happen to have played for your favorite team. David Ortiz (+3.84) comes out on top essentially repeating his performance of 2005 while Geoff Jenkins (+3.25) and Marcus Giles (+2.96), look good despite otherwise poor seasons, as does Jeff Francoeur (+1.97). Chipper Jones (-2.50) lead the trailers, and while not wanting to add any fuel to the fire for patrons of Yankee Stadium, I couldn’t in all honesty omit Alex Rodriguez (-1.92) even though both his teammates Derek Jeter (+2.21) and Jason Giambi (+1.65) make the top 20.
You’ll notice that the Leverage scores–the ratio of the impact of one additional run at a point in time to the impact of one additional run at the beginning of the game, and averaged over all plate appearances–don’t vary much, since the situations that players who garner this many plate appearances find themselves in tend to even out. This is illustrated by the graph below, which shows the distribution of Leverage scores for hitters with 150 plate appearances or more. You’ll notice that the scores have a fairly compact distribution centered in the 1.00 to 1.05 range.
The highest Leverage score belongs to Ken Griffey Jr. at 1.10, and the lowest is Hideki Matsui at 0.84. The highest score for any player with more than 50 plate appearances went to Reggie Willits of the Angels, who recorded a Leverage of 1.38 in 58 plate appearances. As you can imagine, pitchers more heavily populate the bottom of the Leverage list, although left fielder Josh Rabe of the Twins had a Leverage score of just 0.65 in 51 plate appearances.
It’s also important to keep in mind that a high Leverage score doesn’t necessarily mean a hitter will do better in terms of WX. It does mean that if they take advantage of their opportunities that they will score higher; more risk, more reward. By the same token, they also have the opportunity to score more poorly if they don’t succeed.
Finally, let’s wrap this up by taking the WXC measure and scaling it to 650 plate appearances to see who were the best and worst clutch performers of 2006 on a per-plate-appearance basis (including players with 200 or more plate appearances).
Name PA WXC WXC/650 Leverage Geoff Jenkins 555 3.25 3.80 1.06 Albert Pujols 634 3.57 3.66 1.07 David Ortiz 686 3.84 3.64 1.02 Gabe Gross 252 1.28 3.30 1.09 Mike Sweeney 252 1.27 3.28 1.09 Ken Griffey 472 2.31 3.17 1.10 Ryan Zimmerman 682 3.28 3.13 1.07 Marcus Giles 626 2.96 3.08 1.08 Brian Schneider 455 2.11 3.02 1.08 Ryan Howard 704 3.13 2.89 1.05 Melvin Mora 705 2.97 2.73 1.00 Ryan Shealy 219 0.90 2.67 1.03 Mark Loretta 703 2.66 2.46 1.02 Scott Spiezio 321 1.15 2.33 0.97 Todd Helton 649 2.30 2.31 1.05 Jay Payton 588 2.08 2.30 1.00 Barry Bonds 493 1.74 2.29 1.03 Frank Catalanotto 499 1.72 2.24 1.01 Mark Teahen 439 1.46 2.16 1.02 Jason Tyner 232 0.77 2.14 0.91 ------------------------------------------------ Tim Salmon 244 -1.53 -4.08 1.03 Hideki Matsui 201 -1.26 -4.08 0.84 Chipper Jones 477 -2.50 -3.41 1.01 Henry Blanco 261 -1.25 -3.11 0.94 Kendry Morales 215 -0.91 -2.76 0.97 Jose Cruz 273 -1.13 -2.68 1.02 Omar Infante 245 -0.98 -2.61 0.97 Gerald Laird 260 -1.04 -2.60 0.95 Kazuo Matsui 265 -1.05 -2.57 1.15 Dave Roberts 566 -2.19 -2.51 1.04 Marco Scutaro 423 -1.53 -2.35 0.96 Joe Randa 227 -0.79 -2.25 1.28 Troy Glaus 634 -2.16 -2.22 0.96 Jeremy Reed 229 -0.77 -2.17 1.01 Juan Rivera 494 -1.64 -2.16 0.97 Jason Lane 345 -1.12 -2.11 1.10 Eric Hinske 312 -0.99 -2.06 0.93 Hector Luna 379 -1.20 -2.05 1.01 Javy Lopez 364 -1.13 -2.02 0.99 Andre Ethier 441 -1.37 -2.01 1.00
These lists include many of the same players we’ve seen before, with the addition of some who had fewer plate appearances, such as Mike Sweeney (+3.28) and Gabe Gross (+3.30), while Tim Salmon takes the bottom spot at -4.08.
And the Beat Goes On
The performance analysis community has made a number of strides in developing metrics to quantify clutch hitting, and then using those tools to measure its magnitude and persistence. As evidenced by the question put to Mr. Ricciardi, I’ve no doubt that it will be a topic of discussion for quite some time. For what it’s worth, Manny Ramirez in 2006 recorded a WX of +2.97, although his offensive stats alone should have yielded him a +3.79. That puts him on the negative side of the ledger at -0.81 and -0.95 over 650 plate appearances.
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