Archive for Hitting
Thanks to Bryan Donovan and the guys at The Hardball Times, you can now get player PrOPS which are updated daily. And, just like the other stats at THT, you and filter the data in many different ways. Bryan has really done an amazing job with all of the stats.
I had hoped to write a PrOPS article this week, but I’ve had a bit more to do than I anticipated. So, I’ll quickly mention one minor change. This version of PrOPS is based on data from the 2002-2005 seasons. Unlike previous versions, this PrOPS is park-neutral, instead of showing what a player ought to do because of his home park. This makes comparisons across teams a little easier.
And if you’re wondering, “how accurate is PrOPS?” you need to purchase a copy of The Hardball Times Annual 2006.
I thought I’d check in on some offensive stats for the Braves. Here are some stats for players ranked by linear weights.
Player AVG OBP SLG OPS LWTS Andruw Jones 0.294 0.373 0.538 0.912 12.75 Brian McCann 0.349 0.393 0.569 0.962 11.09 Edgar Renteria 0.336 0.397 0.445 0.842 8.32 Chipper Jones 0.276 0.393 0.398 0.791 5.46 Adam LaRoche 0.226 0.341 0.461 0.802 4.49 Matt Diaz 0.365 0.364 0.538 0.902 3.86 Wilson Betemit 0.268 0.325 0.493 0.818 2.54 Brian Jordan 0.288 0.333 0.500 0.833 2.47 Ryan Langerhans 0.269 0.352 0.389 0.741 1.75 Horacio Ramirez 1.000 1.000 1.000 2.000 0.92 Jorge Sosa 0.167 0.375 0.667 1.042 0.81 Martin Prado 0.200 0.429 0.600 1.029 0.68 John Thomson 0.313 0.313 0.438 0.750 0.23 Chad Paronto 0.000 0.000 0.000 0.000 -0.25 Todd Pratt 0.194 0.306 0.323 0.628 -0.26 Tony Pena 0.111 0.200 0.111 0.311 -1.21 John Smoltz 0.133 0.235 0.200 0.435 -1.33 Marcus Giles 0.229 0.327 0.326 0.654 -1.38 Jeff Francoeur 0.259 0.271 0.452 0.722 -2.38 Tim Hudson 0.125 0.125 0.125 0.250 -2.58 Pete Orr 0.213 0.229 0.298 0.527 -2.90 Kyle Davies 0.000 0.000 0.000 0.000 -3.75
I received a lot of feedback on my Jeff Francoeur post from the other day. Most recently, Jacob Luft of Sports Illustrated picked up on it (thanks for the mention and kind words, Jacob), so I thought I’d add one other quick note on Frenchy.
I’m in the process of generating the initial 2006 PrOPS numbers for all players in the league. It’s going to take me a few days to make sure everything is working properly, but I thought I’d throw out Francoeur’s numbers now. I’ll post all the numbers over at THT as soon as I get them ready. If you’re not familiar with PrOPS, check out my initial post at The Hardball Times or see my article in the 2006 THT Annual. PrOPS gives players credit for how they hit the ball rather than on the outcome of the hit balls.
Jeff Francoeur AVE OBP SLG OPS Actual: .210 .222 .352 .575 Predicted: .269 .282 .441 .723 Difference: -.059 -.060 -.089 -.148
He’s been hitting the ball better than his numbers indicate, but an OPS of .723 is still not very productive.
I’ve been wanting to post some these thoughts for some time, even before the season started. But, I kept putting it off, thinking that The Natural would prove me wrong. And I was hopeful that the kid had something to teach me. I’ve hinted at my thoughts on Francoeur publicly, and discussed them more in private, but I guess I should go ahead an put my thoughts in a single post. Jeff Francoeur’s 2005 was a fluke. And it was flukey for more than one reason. That doesn’t mean he won’t be a very good baseball player one day, but his current performance in 2006 should have been expected. I don’t care how much “make-up” you have, if you can’t lay off bad pitches you’re not going to excel as a hitter.
Second, I believe the evidence indicates that part of Francoeur’s fast start was the result of poor scouting. In Mississippi, Francoeur posted a line of .275/.322/.487/.809 against double-A pitching. The funny thing is that his performance in the minors was slightly worse than is PrOPS numbers in the majors. Less capable minor league pitchers knew something that major league pitchers didn’t, or the Braves had Jeff on some bizarre hitting program. The way Jeff tailed way off over the rest of the 2005 season is consistent with major leaguers getting good scouting reports on the guy.
This leads to another interesting question: why did it take so long for major league teams to figure him out? There were certainly scouts watching him in double-A, why didn’t they pass along what the minor league pitchers were doing? My guess is that Francoeur’s jump surprised everyone, and that scouts were not scouting him like advance scouts typically do. Instead, they focused on his raw ability and promise. Scouts saw his poor plate discipline and just reported, “he’s not ready yet, fire it in there.” And well, that was very bad advice. And because Francoeur is blessed with amazing power, when he got pitches he could hit he hit them along way. He didn’t fluke his way to 14 home runs, you have to be gifted to hit home runs. But I think with good advance scouting reports he would not have been nearly as successful—maybe half of those homers go away. In fact, one thing teams may have learned from this experience is that unexpectedly pulling up kids from the minors can yield benefits, because other teams lack the information to get these guys out. Instead of contenders looking to get Joe Randa through a waiver-wire deal for the playoff push, maybe teams should pick up a talented prospect whom no one expected to see.
And why is it that minor league pitchers figured him out? Well, look at the incentives for the pitchers in double-A versus those in the majors. If a double-A pitcher wants to move up, he has to get outs. The best way to do that is to prepare for the guys you’re going to face, especially the best players on the team. These pitchers saw he liked to swing at everything—a friend of mine who watched him in high school said this was no secret then—and they stayed away from the zone without fearing the free pass. But for major league pitchers, Francoeur was just another rookie. Why worry about him when you’ve got to face the Jones boys? And that’s when Frenchy’s window for success opened.
The problem is that now that the window has closed, what are the Braves to do? He’s nearing the 100 PA mark, without having walked even once. And he’s leading the league in swinging at first pitches, so his pledge to work on plate discipline is not going so well. Also, he’s only had five extra-base hits, so he’s not hitting for power when he does hit the ball. This isn’t a bad-luck, small-sample-size slump. There is a real problem.
So, what should the Braves do? Some people think he should be sent down. I don’t think you can do that now. He’s been in the big leagues too long. If he goes to Richmond, all he’ll be thinking about is how to get back. I think the mental fatigue would be too much. The Braves are just going to have to gut this one out, and let him learn on the job. But, it is time to stop pretending he’s already an All-Star. Moving him down in the batting order might reduce some of the pressure, and he could split some time with Diaz and (gulp) Jordan. He’s still an excellent defender and baserunner, too. There are plenty of players in the league who are no worse. Most of them don’t get to play as much, though.
UPDATE: This post is old, and uses a fairly weak method for measuring peak age. I have conducted a thorough analysis published in Journal of Sports Sciences that finds peak age occurs around 29–30.
— — —
Judging the peak age of baseball players is an interesting problem. Over the course of a player’s career, many factors may affect his numbers that have little to do with age: injuries, differing park factors, changes to the run environment of the league, long-run contract incentives, etc. I have looked at the peak ages of pitchers and hitters before (see the right sidebar for links), and I’m happy with the results of found, despite the potential problems. But, I’ve thought about another way to find peak age. Instead of looking at the changing performance of players with long careers, I wanted to look at those with short careers.
Players with short careers typically play only during their peak years. Only when they are at their best are these players providing “major league” level of talent. Both before and after, their skills are not good enough to keep them in the league. Therefore, I’m going to put all of the stats aside and only look at the average age of players with three years or less of major league experience. The average of these short-timers should tell us something about when players peak. I used a recent sample of players from 1980-2002. By excluding 2003-2005 I exclude young players with three year careers who may have much longer careers.
For both hitters and pitchers, the median age of players with careers of three years or less is 26. The mean age for hitters is 26.02 with a standard deviation of 2.37 years. The mean age for pitchers is 26.33 with a standard deviation of 2.82 years. Interesting. I haven’t though much about this other than I thought it would be a neat study to do. Comments, as always, are welcome.
I’ve been really busy lately—I know who hasn’t?—which has significantly postponed some things I wanted to do. For example, I have been wanting to post the SSPS Projections for 2006 for a month. I’m only going do so for hitters this year. If you want to know what’s in SSPS (Sabernomics Simple Projection System) see the introductory post from last season.
I’m not going to defend it against other systems, it’s just more information. Use it as you wish. I don’t predict playing time or make projections for new teams. The projections assume that hitters play in the same home park as they did in 2005. For players who played on more than one team, the projections assume the player played for the team on which he played the most.
Here’s a list of the top-20 projected hitters (by OPS) by league. Enjoy!
Addendum: Something is screwed up with my projections for the Nationals. I’ve removed them, and I will add them when I get a chance. Sorry.
NL Rank Player Team05 AVG OBP SLG OPS 1 Adam Dunn CIN 0.282 0.412 0.583 0.995 2 Todd Helton COL 0.321 0.425 0.552 0.977 3 Chipper Jones ATL 0.300 0.411 0.560 0.972 4 Albert Pujols SLN 0.315 0.411 0.560 0.971 5 Derrek Lee CHN 0.299 0.384 0.572 0.956 6 Andruw Jones ATL 0.287 0.371 0.577 0.948 7 Jim Edmonds SLN 0.276 0.390 0.551 0.940 8 Lance Berkman HOU 0.294 0.400 0.519 0.919 9 J.D. Drew LAN 0.289 0.397 0.518 0.916 10 Morgan Ensberg HOU 0.281 0.381 0.534 0.915 11 Ken Griffey CIN 0.288 0.389 0.525 0.914 12 Tony Clark ARI 0.276 0.358 0.555 0.913 13 Jose Cruz ARI 0.269 0.380 0.533 0.912 14 Javier Valentin CIN 0.293 0.396 0.516 0.912 15 Russell Branyan MIL 0.265 0.381 0.527 0.908 16 Troy Glaus ARI 0.272 0.366 0.538 0.904 17 Jason Bay PIT 0.288 0.387 0.508 0.896 18 Dustan Mohr COL 0.269 0.342 0.551 0.892 19 Preston Wilson COL 0.284 0.357 0.535 0.891 20 Carlos Delgado FLO 0.284 0.373 0.517 0.890 AL Rank Player Team05 AVG OBP SLG OPS 1 Mark Teixeira TEX 0.316 0.393 0.588 0.981 2 David Dellucci TEX 0.294 0.397 0.578 0.976 3 Jason Giambi NYA 0.281 0.414 0.545 0.959 4 Travis Hafner CLE 0.293 0.398 0.559 0.956 5 Alex Rodriguez NYA 0.295 0.397 0.557 0.954 6 David Ortiz BOS 0.293 0.396 0.555 0.950 7 Manny Ramirez BOS 0.285 0.380 0.546 0.926 8 Mark DeRosa TEX 0.295 0.372 0.548 0.921 9 Kevin Mench TEX 0.314 0.377 0.533 0.910 10 Alfonso Soriano TEX 0.302 0.359 0.549 0.907 11 Richie Sexson SEA 0.275 0.380 0.526 0.906 12 Michael Young TEX 0.317 0.380 0.521 0.902 13 Richard Hidalgo TEX 0.289 0.358 0.538 0.896 14 Rod Barajas TEX 0.302 0.360 0.535 0.895 15 Hank Blalock TEX 0.302 0.363 0.526 0.889 16 Jhonny Peralta CLE 0.286 0.370 0.517 0.887 17 Paul Konerko CHA 0.270 0.361 0.520 0.881 18 Gary Matthews TEX 0.298 0.368 0.510 0.879 19 Adrian Gonzalez TEX 0.290 0.348 0.524 0.872 20 Jonny Gomes TBA 0.273 0.353 0.515 0.868
OK, this is really cool. Cyril Morong analyzes run-maximizing lineups based off player OBP and SLG. Ken Arneson “perls it up” for the A’s and posts the script. Then Dave Pinto writes a program that allows you to enter in player stats to generate an optimum lineup for any team of real or hypothetical players. The results are fully linkable, and with the help of tinyurl.com, you can e-mail and post on the web these lineups with ease.
So, in a matter of moments, I used my 2006 SSPS estimates for the Braves to generate the 2006 Optimal Braves Lineup.
Pitcher (Based on Smoltz’s career OBP and SLG)
Pretty cool! I love the internet.
Update: I made a slight change to the above analysis, by giving half of the pitcher’s plate appearances to Langerhans, but it didn’t change the order. I wonder why it puts the worst hitter in the 8-hole? I’m going to have to review Morong’s post.
The Hall of Fame voting this year reveals some information about the voters. Mainly, they’re not very consistent. For one, Bruce Sutter gets in but Goose Gossage does not. Have any voters posted their reasons for voting for Sutter but not Gossage? Goose received 100% of ESPN writer’s votes, while Sutter only got 80%. Well, enough people have pointed this out, but I want to look at how voters treated the hitters.
Jim Rice and Andre Dawson were the only position players with a majority of the votes. Dale Murphy comes in with a measly 10.8% of the vote. The thing is, all three of these guys are very similar.
Player Career Gold Gloves MVPs OPS+ HOF Votes Jim Rice 16 0 1 128 337 Andre Dawson 21 8 1 119 317 Dale Murphy 19 5 2 121 56
They all played outfield. They had similar offensive numbers. They all had a few spectacular years, each winning an MVP. All had few post-season opportunities. They played in the same era. Both Dawson and Murphy won several gold gloves. So, come on Braves fans, it’s time to start lobbying. Dawson and Rice have Boston and Chicago fans going for them. It’s time to start up the comparisons to guys who are receiving serious HOF consideration. It may be that none of these guys ever make it, but I think they all should be treated the same by the voters.
In today’s St. Louis Post-Dispatch, columnist Bryan Burwell writes the following:
Bill James, baseball’s ultimate seamhead and statistical guru, tried Tuesday to explain to me why Jim Rice should never get into the Hall but Mark McGwire, Sammy Sosa, Barry Bonds and many of their chemically enhanced contemporaries should. It was a dazzling bit of stat geek mumbo-jumbo that basically came down to this:
Stats and baseball’s integrity are very relevant to baseball … unless I don’t want them to be.
This prompted me to write the following to Mr. Burwell in an e-mail:
I believe your assertions about several MLB players using steroids to create a home run chase are misguided. While there is a cloud of suspicion surrounding some players this is hardly evidence that they cheated their way to success. Please read the following paper for a discussion of the statistical variance of home runs (http://www.arthurdevany.com/webstuff/images/HomeRunHitting.pdf). The achieved excellence by the sluggers you mention is all within the natural variance of home run hitting in baseball history.
I don’t expect to hear back, but it bothers me that so many people are willing to convict players of using steroids with evidence that wouldn’t meet the weakest of legal standards. If you have not read De Vany’s paper, which I posted a link to above, you should. Art De Vany is a retired economics professor with an excellent research reputation. I wish more people would take notice of his work. I have yet to see someone successfully refute De Vany’s findings.
With the announcement that Bruce Sutter will be the only inductee into the Hall of Fame in 2006, I thought I’d post my list of hitters still playing or too recently retired to be eligible whom I predict will be in the Hall of Fame. The methodology I use is the same one I used to examine which eligible players who should be in the HOF. Here they are, with their probabilities of getting in. This list is only for hitters.
Player P(in HOF) Barry Bonds 100.00% Rickey Henderson 99.80% Frank Thomas 97.44% Ken Griffey 95.63% Larry Walker 95.03% Cal Ripken 91.22% Roberto Alomar 88.01% Jeff Bagwell 86.85% Rafael Palmeiro 83.96% Barry Larkin 81.51% Alex Rodriguez 74.10% Ivan Rodriguez 66.90% Edgar Martinez 64.03% Tim Raines 63.32% Fred McGriff 62.86% Gary Sheffield 60.90% Tony Gwynn 60.78% Mark McGwire 58.73% Craig Biggio 56.77% Juan Gonzalez 55.64% Sammy Sosa 51.77%
There you have it. I don’t think there are too many surprises here.