For an explanation of the methodology for these rankings go to the inaugural post of the Player Performance Rankings. Also for pitchers check out this post.
I didn't get any complaints last week about the images so I will be using them again. One change is that I made Meltdowns a negative number to better identify why a Regulators net SD/MD is negative.
My question this week is: Should I add a WAR ranking board?
Regulators and Fielders after the jump.
One of the most appealing features of sabermetrics is when it tells you that something that you believed really isn't true. Sabermetrics became popular in the Bill James era because it challenged certain "truths" about baseball.
Suppose sabermetrics told you that J.A. Happ may turn out to be a pretty good starting pitcher this year?
Based on comments in the game threads, I think it's fair to say that many Astros' fans don't think that J.A. Happ is a good pitcher---or at the least, they don't trust his pitching. I admit that I probably shared those views. His ERA is almost 5, which means that his results have been bad. But, when I began looking at the Astros' pitchers whose performance is better than his results, I was surprised to find that J.A. Happ fits that description. And it's no contest. He is pitching a LOT better than his results.
Besides the results, I think Happ has some aesthetic reasons for fans' negative opinions. He can slow down to a snail's pace when he gets in a jam. Sometimes he doesn't throw enough strikes. He sometimes accumulates high pitch counts. He is prone to walks. And, well, yes, the walks are more than an aesthetic issue. But aesthetics don't win games, and they can make a pitcher look worse than he is.
Sabermetric Pitching Stats
FIP, x-FIP, and SIERA are pitching stats which attempt focus on what the pitcher controls, filtering out "luck" or random variation in batted balls to varying degrees.
HAPP 2012 PITCHING STATS
4.96 ERA 4.59 FIP 3.91 x-FIP 3.87 SIERA
Let's start with the fact that Happ's ERA is much higher than all of the sabermetric stats. This tell us that Happ's results probably aren't reflective of his pitching. But I will focus on the two predictive stats, x-FIP and SIERA. SIERA is a complex statistic that takes into account a number of factors, including batted ball type, but is similar in objective to x-FIP. x-FIP is a defense independent pitching stat that normalizes HR rate at the league average.
Despite its complexity, I like the SIERA statistic, which is more predictive of a player's future performance than ERA, FIP, x-FIP, and even some projection systems. SIERA indicates that Happ has been pitching quite well. Happ's SIERA is virtually the same as Wandy's SIERA (3.87 vs. 3.85). Yet Wandy's ERA is much lower than Happ's ERA (2.24 vs. 4.96). Again, Happ's earned run results may not indicate how well he has been pitching this year.
Some people don't like SIERA, given its complexity. So we check it with x-FIP, which is intended to be more predictive than FIP and ERA. And x-FIP gives us a similar result to SIERA. Happ's x-FIP is based on the assumption that his HR per fly ball rate (15.1%) will regress toward league average (10.5%). And Happ's HR/ fly ball rate isn't an artifact of the Crawford Boxes. Happ's HR/fly rate actually is league average at MMP. The liklihood is that Happ's HR/fly rate is a product of luck.
In the third installment of this random series, we're going to look at an interesting moment, this time from the pitching side.
Let's set up the situation. It's the top of the third in a scoreless game for the Houston Astros. Left-handed starter and staff ace Wandy Rodriguez is on the mound. He had given up a leadoff double to Ian Kinsler, but got Elvis Andrus to ground into a double play on a comebacker.
That brings up Josh Hamilton, one of the hottest hitters in the game in a pretty critical situation. What is Wandy to do? The crafty lefty had already done a pretty good job of inducing ground balls to that point and the Astros clearly wanted Hamilton to do the same.
That explains the pretty dramatic shift they gave to him, moving shortstop Jed Lowrie over to the first base-side of second. It was pretty much the opposite of what they'd done successfully to Corey Hart two nights previously, as Jose Altuve had made the shift to the other side of the keystone and Hart had grounded out to Lowrie in the hole.
What was Houston expecting in this situation? What was Hamilton expecting to see from Wandy? How was it all supposed to play out and did it work that way? Let's answer some of those questions after the jump...
For an explanation of the methodology for these rankings go to the inaugural post of the Player Performance Rankings. Also for pitchers check out last week's post where we change it up a bit.
So I'm trying something new yet again, but this time it's visual instead of me putting a table on the board I've decided to make charts. With this I've included some other information, for example, hitters now show their BABIP numbers, regulators and fielders show the components for their net numbers. Let me know what you think of the images.
Today I find myself in the passenger seat of a vehicle headed southbound through the hills of Kentucky, en route to a family vacation in Nashville. This leads me into the topic of this article: Chris Johnson, the Third Baseman of the Houston Astros. Several things relate Johnson to the beautiful state of Kentucky, including:
Now that I’ve established the relevance of my current location with the topic of the day, I shall proceed.
Thus far in his career, Johnson has followed a path that is common among young major leaguers. He began in 2010 with a performance worthy of Rookie of the Year consideration (.308, 40 Runs, 11 HR, 52 RBI, .818 OPS in 341 AB). Astros fans immediately proclaimed Johnson as the Third Baseman of the Future—a paragon of greatness destined for hot corner glory. But the sabermetricians cried to the heavens, "Wait, ye plebes of uninformed old-school-itude! Johnson’s BABIP is a veritably unsustainable .381! Regression is in order to restore balance to the universe!" History proved the database junkies correct, as Johnson’s comet crashed to earth in a messy splat in 2011, prompting a demotion to Triple-A ( .251, 32 Runs, 7 HR, 42 RBI, .670 OPS in 378 AB). The once-adoring fans grabbed their torches and pitchforks, ready to run their former hero out of Houston on a rail. Going into 2012, Johnson was public enemy number one on the Astros and SB Nation message boards. The armchair experts bemoaned his appointment as the opening-day third sacker. Women tore out their hair and the men gnashed their teeth.
Then, Johnson opened the season hitting .300, with an .800 OPS in 120 AB. During the month of April, he performed like one of the top Third Baseman in the majors. Thus screams the sabermetrician: "He has a BABIP of .381 again!"--only this time, they seem more hesitant. How did Johnson return to a high BABIP after dropping to only .317 in 2011, when league average is .300? Their universe is rocked.
After the jump, I’ll try to determine what’s changed from 2011 and explain Johnson’s return to success.
For an explanation of the methodology for these rankings go to the inaugural post of the Player Performance Rankings.
The rankings are being tweaked yet again. I'm hoping this will be our final iteration and going forward this will be the standard format. The pitching staff will be split up into starters and relievers. The starters will be ranked by average Game Score (GSC) on the season. If you want to learn more about Game Score I just did a post about the statistic Tuesday.
Relievers will be ranked by subtracting Meltdowns (MD) from Shutdowns (SD). Meltdowns and Shutdowns are a relief statistic meant to be an alternative to the Saves statistic. Here's the breakdown on how Meltdowns and Shutdowns are handed out, via FanGraphs:
Using Win Probability Added (WPA), it’s easy to tell exactly how much a specific player contributed to their team’s odds of winning on a game-by-game basis. In short, if a player increased his team’s win probability by 6% (0.06 WPA), then they get a Shutdown. If a player made his team 6% more likely to lose (-0.06), they get a Meltdown.
For the full article on Metldowns/Shutdowns check out the FanGraphs Library.
Now that we've got that out of the way lets move onto the rankings, and lets go ahead and look at the SD/MD rankings first considering that statistic is the freshest on our minds:
| Regulators | SD/MD |
| 1) Brett Myers | 7 |
| 2) Wilton Lopez | 3 |
| 3) Rhiner Cruz | 0 |
| 4) Brandon Lyon | 0 |
| 5) Wesley Wright | -1 |
| 6) Fernando Rodriguez | -1 |
| 7) Fernando Abad | -1 |
| 8) David Carpenter | -2 |
| Starters | GSC |
| 1) Wandy Rodriguez | 59.14 |
| 2) Bud Norris | 49.67 |
| 3) J.A. Happ | 47.17 |
| 4) Lucas Harrell | 46.14 |
Hitting and fielding after the jump:
If you're a regular reader of our site you may have noticed me starting to use the statistic Game Score to evaluate pitching performances, more and more
Game Score is a Bill James created statistic that takes a pitchers final pitching line and turn it into a single number. Introduced in 1988, Game Score uses a 0-114 scale to rate a pitcher. To get a score of 114 a pitcher would have to nine innings and strikeout every batter he faces. Most pitching performance fall in the 0-100 range, although there are cases of a pitcher having a Game Score above 100. To get a pitchers Game Score do the following:
Screenshot taken from Baseball Reference
Eight easy steps and you're done. If you can fill out a scorecard you can figure out a pitchers Game Score. At the very least, It would give you something to do during the later innings.
The current most popular way to evaluate a pitchers single game performance is the quality start, which has only two qualifications: go at least six innings and allow three runs or less, that's it. That's even simpler than Bill James Game Score, and probably one of the reasons why it's caught on and Game Score has stayed relatively unused, even within the sabermetrics community. Quality start is a very vague statistic though and doesn't tell the entire story of an outing, Game Score does.
A study by Jeff Angus showed that a Game Score of 50 typically means that the pitcher gave their team slightly over a 50% chance to win the game. The numbers don't match up exactly, but they're close enough that you get a good idea of how much a pitching performance contributed to that teams chances of winning based of Game Score.
Last summer, John Dewan suggested anything above a 65 should be considered a gem. I won't go into detail regarding that idea, but I did want to give some idea how to gauge a performance. I've read in another location, and I apologize for not being able to find the source and give proper credit, that anything above 60 is considered a great start. According to Angus' study a 60 Game Score resulted in a 62% winning percentage for teams in 2007.
What I like about Game Score is that it gives you a single number in which to compare starts between the pitcher himself and his rotation mates. I also like that it's an all inclusive stat.
Earned Run Average is just that it averages runs per nine innings, it does not account for hits, walks, unearned runs and strikeouts. You know that already, though, and that's why you use Fielding Independent Pitching and it's variants which only looks at what a pitcher can control, hits walks and strikeouts. It doesn't, however, take into account any runs scored. Game Score accounts for both.
Game Score isn't perfect and has its own flaws, and I'm not suggesting it replace any of the other statistics, but it is a better indicator of a pitching performance than the more popularly used Quality Start statistic.
After the jump we'll look at some observations of Game Score for the Astros 2012 season and some past observations.
For an explanation of the methodology for these rankings go to the inaugural post of the Player Performance Rankings.
I'm changing the format a bit and including every player who has been with the Major League team a majority of the year. This means guys like Brian Bixler, Jordan Lyles and Fernando Abad are not on the board because they've spent most of their times in the minors and have very little data at the Major Leagues.
| Hitters | wOBA |
| 1) Jed Lowrie | .410 |
| 2) Jose Altuve | .405 |
| 3) J.D. Martinez | .364 |
| 4) Travis Buck | .356 |
| 5) Chris Johnson | .353 |
| 6) Jordan Schafer | .331 |
| 7) Brian Bogusevic | .319 |
| 8) Carlos Lee | .269 |
| 9) Matt Downs | .291 |
| 10) Jason Castro | .284 |
| 11) Justin Maxwell | .276 |
| 12) Marwin Gonzalez | .239 |
| 13) Chris Snyder | .210 |
| Pitchers | FIP |
| 1) Wandy Rodriguez | 2.35 |
| 2) Rhiner Cruz | 2.51 |
| 3) Wilton Lopez | 2.90 |
| 4) Wesley Wright | 3.33 |
| 5) Brett Myers | 3.76 |
| 6) J.A. Happ | 3.86 |
| 7) Brandon Lyon | 3.93 |
| 8) David Carpenter | 4.10 |
| 9) Lucas Harrell | 4.20 |
| 10) Bud Norris | 4.35 |
| 11) Fernando Rodriguez | 4.79 |
| Fielder | UZR*DRS |
| 1) Jordan Schafer | 3.75 |
| 2) Jed Lowrie | 2.45 |
| 3) Marwin Gonzalez | 1.6 |
| 4) Travis Buck | .7 |
| 5) Justin Maxwell | .5 |
| 6) Jose Altuve | -.15 |
| 7) Carlos Lee | -.2 |
| 8) Brian Bogusevic | -.7 |
| 9) J.D. Martinez | -1.25 |
| 10) Chris Johnson | -1.3 |
| 11) Matt Downs | -1.7 |
Thoughts after the jump.
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