Archive for Hitting
Jason Heyward has just played his 30th game in the big leagues, and oh what a start it has been. A local kid rising to meet exceptional expectations; it kind of reminds me of another young phenom.
Despite Heyward’s hot start, Francoeur’s beginning was arguably hotter. Francoeur had more homers, a higher average, a higher slugging percentage, and a higher OPS. Does this foretell a similar demise for Heyward (Francoeur currently has a .705 OPS for the Mets)? While I won’t be surprised if Heyward’s numbers fall some, there are some distinct differences between the two players.
The first difference is obvious: walks. At the same point in their major league careers, Heyward has 20 walks; Francoeur wouldn’t get his first walk until four games later, and it was intentional. Heyward has the plate discipline that Francoeur still lacks.
And more important are their minor-league performances. Francoeur had decent, but unimpressive, minor-league numbers. Heyward had a better minor-league career, absolutely destroying the Double-A. Analyzing minor-league stats is tricky, so below I use the markers I employ for predicting major-league success from minor-league performance (see my upcoming book for justification): walk rate, strikeout rate, and isolated power (age is also important). These stats are for their High-A and Double-A performances before they joined the big league team. (Stats below High-A do not predict success well. Heyward barely played in Triple-A, and I excluded Francoeur’s 2008 demotion.).
So, despite their similar hot starts, Braves fans shouldn’t worry about Heyward becoming Francoeur. On the surface, the players’ hot starts may appear similar, but their skill sets are quite different. Heyward is already better than Francoeur will ever be, and his future looks very bright.
I’ve been getting a few hits for the term “productive outs” lately. I blame TBS (so does Steve Goldman). When the stat came into being five years ago, I did a little study of its impact, and I thought I’d repost my findings.
If there is anything of use in POP it must be in addition to the impact of OBP and SLG, not an alternative measure. Olney’s argument ought to be: all else being equal, teams that have a higher percentage of productive outs will score more runs than those that do not. This means that when two teams have identical OPSs the one with a higher POP will score more runs. So, what happens when I run a regression including both OPS and POP, which allows me to control for the run-scoring abilities of teams due to OBP and SLG, to capture any additional POP effect? Well, not much. Using the 2004 team data provided by ESPN.com I find that POP has no effect on run-scoring. Though the coefficient is negative it is not statistically significant.
So, why doesn’t it have an effect? I mean, clearly logic dictates that productive outs are preferred to non-productive outs. The problems lies in the fact that productive out situations are also productive at-bat situations. While productive outs are preferred to non-productive outs, non-outs are even better. A team that is producing productive outs is still producing outs.
Hitting coach Rudy Jaramillo is what makes the Rangers attractive.
“These guys have the system,” Jones said. “The hitting coach they’ve got, they work on the things they want to. We’ll see what happens.”
Third baseman Michael Young still expects Jones to have a good season, no matter where he ends up playing.
“He and Rudy have worked hard together,” Young said. “He’s not going to get a hold of Rudy’s system overnight, but he’s definitely got the ability, the experience and the know-how to master the system.”
During a three-day November tutorial with Rangers hitting coach Rudy Jaramillo in Texas, Francoeur changed the position of his hands, opened his stance a bit and widened his feet. The changes were to simplify his approach, improve his balance and help him see the ball better.
Andre Ethier recently said that he felt he was seeing better pitches with Manny Ramirez batting behind him….To test this, I looked at the Pitch F/X data for Ethier from 3/31 to 8/27, when he was not hitting ahead of Manny, and compared it to the data from 8/28 until the end of the season, when Manny was protecting him….He saw virtually the same amount of fastballs and same percentage of pitches in a pretty generous strike zone before hitting in front of Manny and after. It might seem like he is seeing better pitches but it could be some type of placebo effect.
Congratulations to Dave B. for correctly predicting that Jeff Francoeur would walk 39 times this season. The early-season part of The French God of Walks contest was won by the first entrant, and David B. was the second entrant. Also interesting is that the first entrant, Jack, would have won if Francoeur had taken the same number of plate appearances as he had in 2007. Basically, Francouer’s walk total would have been identical to his 2008 total of 42. The lessons here are that Francoeur’s walking eye didn’t change a bit and that winning Sabernomics contests requires entering quickly.
The season was a disaster for Francoeur; not because of his overall poor performance, but because he didn’t improve where he needs improvement. In fact, I think much of Francoeur’s 2008 struggles can be attributed to bad luck, and then adjusting for bad luck in a way that made things worse. At season’s end, Francoeur’s PrOPS was .726, which isn’t too far off from his career OPS of .746. I agree with most people that Francoeur will bounce back to the player he was. The problem is that a mid-.700s OPS from a corner outfielder isn’t good.
Francoeur’s walks, strikeouts, and hitting power were quite similar to his 2007 performances. His strikeout rate was a little lower (17% versus 18.5%) and his isolated power was down a bit (120 versus 151). His base-stealing remains abysmal. He attempted one steal and was caught. How is it possible that a man recruited to play safety for several major college football programs is unable to steal a single base in a season? Brian McCann, who runs like turkey flies, stole five bases without getting caught.
On top of this, his defense—the area where he had been good—declined significantly. After winning in a Gold Glove in 2007, Francoeur was an absolute disaster in the field in 2008. According to John Dewan’s Plus/Minus ($) Francoeur was the sixth-best right fielder in 2007, making 10 plays more than the average right fielder. In 2008, he ranked 28th among right fielders, making 17 fewer plays than the average right fielder.
Many commentators have blamed Francouer’s 2008 on a weight-training program designed to increase his hitting power. This, they say, accounts for his decline in the field and the bat. While I might be willing to buy the explanation for the fielding—though he didn’t appear to get any better after shedding the weight—I think it had no impact on his hitting. If anything, he should have increased his power as he expected. One thing we have learned in recent history is that increasing muscle mass does not hurt bat-speed. That myth went out the window with late-80s Oakland A’s. And furthermore, Francoeur’s fundamental holes are the same ones he has always had. The reason his power didn’t improve is that you can’t hit the pitches he’s hitting (non-strikes), or not hitting, any harder.
I expect Francoeur will improve until his late-twenties before plateauing and declining in his early-thirties like most players. At his peak, I expect he will be an .800 OPS hitter, which is about average for the position. That is, at his best, he will be average for his position. And the peak will occur after he is no longer controlled by the Braves. 2005 was a fluke, and people just need to accept that.
From David Pinto.
One thing that amazed me during the writing was how much Jeff Francoeur hurt the Braves this season. The Braves have only been outscored 612-590; they should be around a .500 team, not a .435 team. With any kind of decent power from Francoeur, the Braves likely add 30 runs. With all the one-run losses, those 30 runs could be huge. Instead of looking to build a team for next year, they’d likely be in the Marlins spot, on the edge of the playoff race.
Here is a link to his article in Sporting News. Thanks to Tom for the pointer.
Here are the top-three performers in terms of PrOPS by position and league (via THT).
If you are unfamiliar with PrOPS, it is a metric that estimates how players typically perform in terms of OPS based on how they hit the ball, along with a few other characteristics. You can read the primer here.
National League American League C Year Last First Tm PrOPS Year Last First Tm PrOPS 2008 McCann Brian M ATL 0.900 2008 Mauer Joe MIN 0.841 2008 Soto Geovany CHN 0.868 2008 Hernandez Ramon BAL 0.793 2008 Martin Russell LAN 0.861 2008 Rodriguez Ivan DET 0.727 1B Year Last First Tm PrOPS Year Last First Tm PrOPS 2008 Pujols Albert STL 1.054 2008 Giambi Jason NYA 1.017 2008 Berkman Lance HOU 0.961 2008 Youkilis Kevin BOS 0.853 2008 Howard Ryan J PHI 0.940 2008 Morneau Justin MIN 0.838 2B Year Last First Tm PrOPS Year Last First Tm PrOPS 2008 Utley Chase PHI 1.001 2008 Kinsler Ian M TEX 0.834 2008 Uggla Dan C FLA 0.894 2008 Ellis Mark OAK 0.803 2008 DeRosa Mark CHN 0.849 2008 Roberts Brian BAL 0.792 3B Year Last First Tm PrOPS Year Last First Tm PrOPS 2008 Jones Chipper ATL 1.030 2008 Rodriguez Alex NYA 0.946 2008 Ramirez Aramis CHN 0.922 2008 Lowell Mike BOS 0.870 2008 Wright David A NYN 0.910 2008 Longoria Evan TB 0.867 SS Year Last First Tm PrOPS Year Last First Tm PrOPS 2008 Ramirez Hanley FLA 0.921 2008 Peralta Jhonny CLE 0.797 2008 Reyes Jose NYN 0.820 2008 Scutaro Marco TOR 0.775 2008 Rollins Jimmy PHI 0.808 2008 Renteria Edgar DET 0.751 LF Year Last First Tm PrOPS Year Last First Tm PrOPS 2008 Dunn Adam CIN 1.057 2008 Cust Jack OAK 0.956 2008 Burrell Pat PHI 1.025 2008 Quentin Carlos CHA 0.926 2008 Lee Carlos HOU 0.912 2008 Ramirez Manny BOS 0.882 CF Year Last First Tm PrOPS Year Last First Tm PrOPS 2008 Ankiel Rick STL 0.898 2008 Sizemore Grady CLE 0.932 2008 Beltran Carlos NYN 0.878 2008 Hamilton Josh TEX 0.926 2008 McLouth Nate PIT 0.877 2008 Swisher Nick CHA 0.879 RF Year Last First Tm PrOPS Year Last First Tm PrOPS 2008 Ludwick Ryan STL 0.992 2008 Drew J.D. BOS 0.954 2008 Hawpe Brad COL 0.896 2008 Dye JermaineCHA 0.908 2008 Nady Xavier PIT 0.872 2008 Markakis Nick BAL 0.883 DH Year Last First Tm PrOPS 2008 Bradley Milton TEX 1.045 2008 Thome Jim CHA 0.941 2008 Huff Aubrey BAL 0.865
Also here is a list of the top-25 overperformers, which means their OPS exceed their PrOPS. I expect these players’ performances to decline.
Last First Tm PrOPS OPS OPS-PrOPS Berkman Lance HOU 0.961 1.096 0.135 Kinsler Ian TEX 0.834 0.945 0.111 Lewis Fred SF 0.701 0.798 0.097 Uggla Dan FLA 0.894 0.978 0.084 Damon Johnny NYA 0.774 0.856 0.082 Youkilis Kevin BOS 0.853 0.933 0.080 Holliday Matt COL 0.896 0.975 0.079 Jones Adam BAL 0.658 0.732 0.074 Roberts Brian BAL 0.792 0.864 0.072 Morneau Justin MIN 0.838 0.903 0.065 Granderson Curtis DET 0.782 0.838 0.056 Jones Chipper ATL 1.030 1.086 0.056 Rios Alex TOR 0.691 0.737 0.046 Durham Ray SF 0.754 0.799 0.045 Loney James LAN 0.752 0.796 0.045 Gomez Carlos MIN 0.594 0.638 0.044 Hudson Orlando ARI 0.773 0.816 0.044 Guzman CristianWAS 0.721 0.765 0.044 Rowand Aaron SF 0.764 0.804 0.041 McCann Brian ATL 0.900 0.940 0.040 Young Delmon MIN 0.677 0.716 0.039 Ramirez Hanley FLA 0.921 0.957 0.036 Reyes Jose NYN 0.820 0.854 0.035 Young Michael TEX 0.743 0.777 0.034 Hart Corey MIL 0.799 0.831 0.033
And here are the top-25 underperformers. I expect these players to improve.
Last First Tm PrOPS OPS OPS-PrOPS Sanchez Freddy PIT 0.721 0.556 -0.165 Cust Jack OAK 0.956 0.815 -0.140 Dunn Adam CIN 1.057 0.918 -0.138 Hernandez Ramon BAL 0.793 0.664 -0.128 Renteria Edgar DET 0.751 0.627 -0.124 Swisher Nick CHA 0.879 0.754 -0.124 Mora Melvin BAL 0.802 0.688 -0.114 Howard Ryan PHI 0.940 0.832 -0.108 Greene Khalil SD 0.701 0.593 -0.107 Cabrera Melky NYA 0.751 0.648 -0.103 Giambi Jason NYA 1.017 0.915 -0.103 Millar Kevin BAL 0.828 0.730 -0.098 Garko Ryan CLE 0.765 0.668 -0.098 Griffey, Jr. Ken CIN 0.843 0.748 -0.096 Scutaro Marco TOR 0.775 0.680 -0.095 Cano RobinsonNYA 0.737 0.643 -0.094 Beltre Adrian SEA 0.863 0.769 -0.094 Delgado Carlos NYN 0.876 0.784 -0.092 Kent Jeff LAN 0.801 0.711 -0.090 Francoeur Jeff ATL 0.746 0.659 -0.087 Ellis Mark OAK 0.803 0.716 -0.087 Helton Todd COL 0.866 0.783 -0.083 Barton Daric OAK 0.718 0.639 -0.080 Pierre Juan LAN 0.716 0.644 -0.072
Playing for the first time since being sent to Double-A Mississippi to get his head and swing right this past weekend, Jeff Francoeur looked good in three of his five at-bats.
His only hit was a fifth-inning single through the left side of the infield. But he grounded sharply to the right side during his first plate appearance and didn’t look pull-happy in the fourth inning when he hit a sharp fly ball to right field.
Putting aside the sample size issue, I am tired of hearing people (I’m talking directly to you Joe Simpson) praise the virtue of hitting to the opposite field. While the ability to hit to all fields is a nice skill, not everyone has it. Take Jeff Francoeur, for example. Thanks to Baseball-Reference’s splits we can see how he performs when he hits the ball to different parts of the field (career numbers below).
Field PA AVG OBP SLG OPS BABIP Pulled 441 0.451 0.447 0.815 1.261 0.396 Up Mdle 822 0.297 0.296 0.46 0.756 0.269 Opp FldR 258 0.289 0.283 0.443 0.726 0.275
He is far more successful when he pulls the ball. There is an Braves folk tale that involves Joe Torre telling Dale Murphy “there are a lot of hits out there in right field.” Unfortunately, there are a lot of outs over there too, and Frenchy’s finding plenty of them.
Field PA AVG OBP SLG OPS BABIP Pulled-RHB 286 0.396 0.396 0.714 1.110 0.347 Up Mdle-RHB 553 0.293 0.290 0.357 0.648 0.285 Opp Fld-RHB 254 0.421 0.419 0.556 0.975 0.414 Pulled-LHB 611 0.396 0.393 0.723 1.116 0.336 Up Mdle-LHB 1164 0.305 0.304 0.401 0.705 0.294 Opp Fld-LHB 446 0.370 0.362 0.540 0.902 0.344
It’s easy to see why TP preaches the opposite-field philosophy: it worked for him. However, it doesn’t look like this is the proper approach for Frenchy.
Francoeur’s problem is a simple one: he has no plate discipline. He needs to worry about what he swings at rather than where he hits the ball when he makes contact.
Nate Silver at Baseball Prospectus posts an interesting article on Chipper Jones’s probability of hitting .400 this year. Silver correctly notes that the proper question isn’t whether or not it’s likely that he will hit .400–of course, it’s unlikely, it was unlikely for even Ted Williams to do it. If some of Chipper’s excellent hitting this year is a product of improved talent–hitting over .400 is more than good luck for a career .310 hitter–there is a realistic chance that he may do it.
At this point, however, we have significantly more information about Chipper than we did at the start of the season. Information like the fact that Chipper really, really knows how to hit a baseball. So the idea is to come up with a new estimate of Jones’s talent that incorporates what we’ve learned about him this year.
The process for doing this is a little involved, and requires the use of something called Bayes’ Theorem, but the basic intuition is as follows: sure, it seemed unlikely at the start of the season that Jones was a .360 hitter. But we also know that it’s much, much likelier for a .360 hitter to sustain a .420 batting average over the first ten weeks of the season than it is for a .310 or a .290 hitter. What Bayes’ Theorem gives us is a way to balance these two pieces of information. (I’ve used this process before to evaluate hot and cold starts, and it’s proven to have pretty good predictive power.)
Sparing everyone some math, our solution from Bayes’ Theorem is that Jones is really and truly about a .350 hitter—specifically, our estimate is that he should hit about .348 the rest of the way out. There is some uncertainty around this estimate, because it’s plausible that Jones has become a .360 or a .370 hitter who has gotten a little lucky, and it’s also very plausible that he’s still more like a .320 or .330 hitter who has gotten a lot lucky. What we can say almost for certain is that Jones isn’t really a .400 hitter, but that he’s also almost certainly better than the .310-.320 range we pegged him at before the season began.
I think it is interesting that Silver’s estimate of Chipper’s 2008 hitting is nearly identical to his predicted estimate according to PrOPS;, which estimates his , based on the way he is hitting the ball this season.
So, if Chipper is a .350 hitter this year, what is the probability that he will break .400?
Overall, out of our 1000 simulations, Jones hit .400 or better and had enough plate appearances to qualify for the batting title 125 times. So this is your answer: I estimate that Jones has about a 12-13 percent chance of finishing with a .400 average.
Good luck, Chipper!
Addendum: Here are a few things that Chipper is doing differently this season. These don’t necessarily mean anything, I am just pointing them out.
P/PA %Strikes put in play Career 3.68 35% 2008 3.48 41%
Bleg: Pre tags don’t seem to be working since I have upgraded to WP 2.5.1. Any suggestions?
For the second year in a row, home runs are down in baseball. It won’t be long until someone attributes this change to improved drug testing and the response to the the Mitchell Report. Here is a graph of March/April home runs (thanks to Baseball-Reference’s league splits).
Now, it is possible that testing might have had an effect, but it is not obvious in the data. MLB began random tests with sanctions for a first offense in 2005. Home runs were down in 2005, but they were not significantly different from prior years; and, in 2006 home runs returned to the 2004 level.
But still, there is no denying that home runs are down from recent historical highs. In fact, the home-run rate this year is the lowest it has been since 1993—the beginning of the modern home-run era. And this continues the decline from last season, when the home-run rate dropped below three percent for the first time since 1997. Are there any factors that could be causing this aside from a decline in drug use or random variation in the data?
It is easy to remember something very unique about last season’s first few weeks: it was unseasonably cool. Off the top of my head, I recall the Indians losing several games to snow and playing a home series with the Angels in Milwaukee. Chris Constancio looked at the impact of temperature on home runs and found strong positive relationship the two.
The average temperature for major league baseball games [in 2007], 58.2 degrees Farenheit, was over four degrees cooler than the average during the early part of the previous two seasons. This relationship seems relevant to understanding why home runs, and consequently run totals, are down this season….
Game-time temperature was a significant predictor (at the p [greater than] .001 level) of whether or not batted balls left the ballpark, but the day of the season was not statistically significant. A batted ball has a 4.0% chance of leaving the park during a game played in 70 degree conditions, but only a 3.5% chance of becoming a home run in a game played in 50 degree conditions. This relationship exists regardless of whether or not the game is being played during the first week of the season or in the middle of May.
In summary, it’s true that hitters gain an advantage in hitting home runs as the season progresses, but this advantage can be explained entirely by accounting for air temperature changes.
This year, I can only recall one snow-out (Braves–Rockies), and the early-season temperature hasn’t gotten as much press as it did last year. I decided to look at how the April temperature this season differs from previous seasons, and compare temperatures to home-run rates.
Over the past decade, early-season home runs and temperature have moved together. April 2008 was actually 0.3 degrees cooler than April 2007—sorry Al Gore*—and 5.12 degrees cooler than April 2006. This doesn’t mean drug testing has not affected hitting power, but we have have a decent alternative explanation for why home runs are down. So, make sure you point this out to the first person who claims drug testing is working.
*It’s a joke, no angry e-mails please.
UPDATE: Upon closer inspection, it appears that temperature changes do not appear to explain much of the decline in home runs. See the following links.