The Next Jose Bautista

This article was originally posted at WahooBlues.com.

Jose Bautista took the baseball world by storm in 2010 when, after six MLB seasons of doing nothing in particular, he emerged as a candidate for AL MVP. Compare his 54 homers, 124 RBI, and .995 OPS in 161 games last year to the 59 homers, 211 RBI, and .729 OPS he posted in nearly 600 games from 2004-09. Using WAR/PA, Bautista was more than 11 times better in 2010 than he’d been for the rest of his career.

Interestingly, Bautista’s breakout came just a year after Ben Zobrist came out of nowhere to become the second-most valuable player in baseball. After hitting .222/.279/.370 with just 15 homers, 57 RBI and -0.5 WAR in roughly a full season’s worth of games from 2006-08, Zobrist went bananas in 2009, hitting .297/.405/.543 with 27 taters, 91 knocked in, and 8.4 WAR.

Besides the fact that no one expected monster breakouts from either of them, 2009 Zobrist and 2010 Bautista had some interesting things in common. Both had extensive experience in the big leagues but neither had done anything particularly impressive. Both entered their seasons with at some questions about what their roles would be. And both had enjoyed out-of-nowhere power surges during their respective previous Septembers.

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Another Look at Arod’s 2010 Peformance Against Lefties

This post originally appeared on The Captain’s Blog and is a followup to one published at both the Yankeeist and Fangraphs’ Community Forum.

Over at the Yankeeist, Larry Koestler took a look at one of 2010’s most curious mysteries: Alex Rodriguez’ shockingly poor performance against left handed pitchers. Using pitchFX data, Koestler concludes that the pitch selection of opposing southpaws (i.e., fewer four seamers and more cutters, two seamers and sinkers) contributed to Arod’s struggles (while also conceding the limited sample size), but could the answer be much more benign?

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A PitchFX Look at A-Rod’s Bizarre Reverse Platoon Split

This post originally appeared on Yankeeist.

It’s no secret that Alex Rodriguez produced the lowest full-season wOBA of his career in 2010 — his .363 mark was fueled by career-lows in batting average (.270), on-base percentage (.341) and the second-lowest full-season SLG of his career (.506). That these numbers were not only dramatically off from his superb 2009 (.286/.402/.532; .405 wOBA) but his majestic career triple slash (.303/.387/.571) suggests to me that he should be due for a reasonable bounceback. While it’s not impossible Alex has reached an irreversible decline, he’s been too historically good for me to be willing to write him off just yet. I won’t go so far as to proclaim that the Yankees are going to be getting .400-plus-wOBA A-Rod back, but as I’ve noted on at least one occasion this offseason, all A-Rod needs to do is exercise just a tad more patience and a wOBA in the .380s should be more than doable.

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Hall of Shame: Why BBWAA’s Secret Ballots Matter

This was originally posted on WahooBlues.com

When the Baseball Writers Association of America announced Wednesday that Roberto Alomar and Bert Blyleven had been elected to the Baseball Hall of Fame, two worthy inductees who had waited too long were granted entrance to Cooperstown. But to judge the voting process solely by the selections of two worthy candidates would be to ignore the massive problems with the way the BBWAA does business.

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Heyward, Stanton, and 20 year-old studs

Eno Saris’s recent article on Jason Heyward comps got me thinking about comps. It also happens to coincide with the day that I got my Baseball-reference subscription. That I would start looking at seasons from 20 year-olds was inevitable.

It was maybe the third or fourth thing I noticed: 2010 featured another remarkable season from a 20 year-old hitter: Mike Stanton. Here’s a fun fact about Heyward: among 20 year-olds, only two guys walked in more plate appearances than the Braves’ young stud. (Ted Williams and Mel Ott.) Here’s a fun fact about Stanton: the guy closest to him in batted balls for home runs, among 20 year-olds, is Mel Ott, but Mike Staton sent a greater percentage of batted balls over the fence than any age 20 hitter in the retro-sheet era. (Perhaps less fun: he has the highest K% among 20 year-olds too.)

But who are the players most comparable to Stanton and Heyward? To answer this question, I started focusing on three true outcome rate stats (since those are more stable in small samples than ball-in-play stats) in seasons from 20 year-old hitters (regardless of experience). While it’s tempting to focus on rookies, there are just 102 seasons with 200+ PA from a 20 year-old since 1920, so focusing on similarly young rookies just shrinks an already small group. To expand the group a little, I added 21 year-old in their first season (also cut off at 200 PA).

To compare these players, I developed z-scores for players BB/PA, K/AB, and HR/batted ball (AB-K). (See a technical section below on these scores.) Then, treating each 20 year-olds 3 z-scores as a vector, I found the distance of their vector from Heyward’s and Stanton’s vectors. The smaller this distance from their vector, the more comparable they are.

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Visualizing Major League Baseball During the Aughts

2010 marks the end of the “aught” decade for Major League Baseball.  I thought I would take the opportunity to analyze the last 10 years by visualizing team data.  I used Tableau Public to create the visualization and pulled team data from ESPN.com (on-field statistics) and USA Today (team payroll).

The data is visualized through three dashboards.  The first visualizes the relationship between run differential (RunDiff) and OPS differential (OPSDiff) as well as the cost per win for teams.  The second visualization is in table form and can be sorted and filtered along a number of dimensions.  The final visualization looks at expected wins and actual wins.

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Why I Can’t Ignore Stats

If some of you have been active in following your Hall of Fame voters, you probably read this post on Jon Heyman discussing his ballot. He spent the majority of this piece stating why he didn’t vote for Bert Blyleven, and then he explained why he voted for Jack Morris instead. I promise this is not intended to be a “Vote Blyleven, not Morris!” post, because I’m more interested in something else. Heyman claims that Morris had a bigger impact in his games than Blyleven. Well then, what happens if I never experienced this impact?

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A Guaranteed HOF Snub

On January 5, the Hall of Fame class of 2011 will be announced. It appears that Bert Blyleven will finally get the call after 14 years on the ballot. Roberto Alomar is likely to receive the necessary votes as well. There will be a long list of deserving candidates left out this year. After the announcement, there will be no shortage of analysis of the snubbery. But we know for a fact that, even before the votes are tallied, one deserving candidate will not be inducted.

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A Pitch F/X Look at Cliff Lee

Lee has a tremendous variety of movement in his pitches. He has three pitches that tail away from righties (fourseam, twoseam, changeup) and a nasty curveball with a ton of movement. For most pitchers this would be plenty; but Cliff Lee is not like most pitchers. He also packs a cutter with as much horizontal movement as some sliders.

We can see this with the following graph, which is from the catcher’s perspective (same with all following graphs):

CLeepitchmovementandlocation

CU=curveball, FC=cutter, FF=fourseam, FT=twoseam, CH=changeup. The black box represents the strikezone and has the average pitch locations for each pitch.

Looking at a pitcher’s entire repertoire like this is useful, but it can be more interesting to look at pitches individually when it comes to pitchers like Lee.

FFdensRHw_strikezone

FFdensLH_w_strikezone




Against righties his location is pretty varied with the fourseam. He mainly locates the pitch middle-away, but often goes up and in too. Against lefties, he consistently pounds the outer half.

Pitch Type Count Selection% Swing% Swing-Miss% HR% GB% LD% FB%
vs·RHB
FF 352 13.8 50.9 12.3 0.9 28.9 25.0 46.1
vs LHB
FF 305 36.4 47.2 13.2 0.7 45.6 12.3 42.1

FTdensRHw_strikezone FTdensLHw_strikezone


Against righties he primarily throws the twoseam pitch up and away, which explains why he has a high flyball rate on a pitch typically associated with groundballs. Against lefties the pitch is pretty much thrown low and over the middle of the plate.

Pitch Type Count Selection% Swing% Swing-Miss% HR% GB% LD% FB%
vs·RHB
FT 1174 46.2 48.2 14.5 0.5 31.0 21.0 48.1
vs·LHB
FT 241 28.8 46.1 11.7 0.0 59.6 27.7 12.8

FCdensRHw_strike

FCdensLHw_strike


Against righties the pitch is a real weapon; the cutter results in many whiffs and a solid amount of groundballs. Against lefties the pitch isn’t as remarkable, but still solid. His location against lefties with the cutter is very similar to his location with his fourseamer against lefties.

Pitch Type Count Selection% Swing% Swing-Miss% HR% GB% LD% FB%
vs·RHB
FC 510 20.1 54.9 20.4 0.6 47.0 23.0 30.0
vs·LHB
FC 185 22.1 49.7 17.4 1.1 41.9 18.6 39.5

CUdensRHw_strike

CUdensLHw_strike


His location against righties and lefties is pretty much the same, though he does backdoor the pitch occasionally to righties. He pretty much only throws his curve late in counts for strikeouts.

Pitch Type Count Selection% Swing% Swing-Miss% HR% GB% LD% FB%
vs·RHB
CU 170 6.7 44.1 37.3 0.0 76.0 12.0 12.0
vs·LHB
CU 49 5.8 36.7 38.9 0.0 20.0 20.0 60.0

CLeedensCH

Pitch Type Count Selection% Swing% Swing-Miss% HR% GB% LD% FB%
CH 293 11.5 58.7 29.7 0.3 42.5 17.5 40.0

Only one graph here because he only threw 20 changeups to lefties the entire year, so I’m just going to ignore those. According to Fangraphs pitch run values, his changeup was his most effective pitch this year. And you can see why; he was great and locating the pitch down and away.

*all data and tables are from Joe Lefkowitz’ site.

*This article was originally posted on www.pendingpinstripes.net


Graphical wOBA by Count

I am a big fan of graphs and baseball. Fangraphs made me excited because putting complex data into reasonably easy to understand graphs helps open up sabermetrics to more fans. I’m a big fan of statistical analysis, but after a while, a table full of numbers just starts running together and stops making sense. That’s what makes graphs such an effective tool.

I’ve dabbled in graphs myself. When people were creating the WAR graphs to compare hall of famers, I made a sample graph showing cumulative WAR by age on Tom Tango’s Book Blog:

(click for a larger image)

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