March 8, 2012 at 12:33 pm by David Lee under Atlanta Braves, Player Analysis, Statistical Analysis
Kris Medlen threw a few curveballs in his start Tuesday against the Nationals. While a third offering isn’t a huge deal for Medlen while he’s in the bullpen, it will be important if he gets back into a rotation some day, which I’m sure will happen at some point. His curve has never been above average, according to run values, but he has shown flashes.
In 2009, he threw it 19% of the time with a whiff rate of 12%, according to Brooks Baseball. However, he nearly abandoned it in 2010 when he made 14 starts for the Braves, throwing it just 9% of the time with a whiff rate of 7%. Compare that to Tommy Hanson’s curve, which he has thrown just 13% of the time over his career, but it breaks harder and results in a 14% whiff rate, as well as a 3% drop in line drive percentage from Medlen’s.
Medlen had potential with it in 2009 when he threw it at a decent rate. His home run rate was solid, he induced a ground ball here and there, he picked up a 24.5 K%, and he put up a 3.35 FIP as a rookie.
When he almost trashed it in 2010, he had similar independent numbers, just the opposite way. His FIP went up to 3.78, but his xFIP went down from 3.65 to 3.49. This was due to an increase in home runs to more than one per nine innings. You could say an innings increase had some effect, but leaning much more heavily toward a two-pitch repertoire likely had some say in the matter.
His swing and contact numbers also prove the change to fewer curves and more changeups. His swinging strike rate saw a slight decrease and he had fewer strikeouts in 2010, and he saw an increase in swinging strike percentage outside the zone by nearly 10%, and greater outside contact that year by 5%. So while he traded strikeouts by curves for contact on the changeup, he got weak contact on many of those pitches. It’s basically a different way to achieve a similar result (note: similar, not the same).
But perhaps the biggest change from Medlen’s 2009 to 2010 is something I haven’t mentioned yet: walks. Medlen is known as a tremendous control pitcher, posting just 27 walks in 120 innings at Double-A in 2008, and performing other similar feats during his minor league career. However, his walk rate jumped to 10.2% in 2009. Whether some of it had to do with nerves is not known. But it’s worth noting that after nearly ditching the curve in 2010, his walk rate dropped to 4.8%. I can’t help but feel there is a connection.
Basically, I waffled throughout this, but the point is to show Medlen went about his business in a different way between 2009 and 2010, and both ways were successful. One way – establishing a curveball as a reliable third offering – potentially leads to more strikeouts and walks (as it should). The other way – relying heavily on the changeup and essentially being a two-pitch pitcher – potentially leads to fewer strikeouts but weaker contact and fewer walks (as it should).
As I said in the opening, if and when Medlen becomes a starter again, I feel he should at least attempt to maintain his curve as a third offering, because while his changeup is a plus pitch, his stuff is not overwhelming three times through a big league lineup. Based on the numbers, I think it will be there when he needs it.
March 7, 2012 at 12:45 pm by Ben Duronio under Atlanta Braves, Statistical Analysis
Mike Minor’s peripherals are a big reason for being so high on him. His current MLB ERA is 4.74, which will certainly alarm the average fan, but his FIP of 3.51 and xFIP of 3.63 are both better than league average over the past two years.
Minor has shown a solid ability post above average strikeout-to-walk ratios and a slightly better than average home run rate over his 24 Major League appearances. Those factors, the controllable ones, lead me and other saber-inclined baseball fans to expect Minor to begin to receive above average results to match the above average performance.
One thing I have noticed, however, is that his line drive rate over the past two years is concerning. His ERA is so high mainly due to high batting averages on balls in play. Over the past two years, his BABIP has sat at .379 and .350, respectively. The league average rate over the past two years has been .293 each season. While it is easy to point out that his BABIP should regress closer to the league average rate, the amount of line drives he has allowed may keep that number high.
The below charts use data taken from Brooks Baseball player cards, with the final five categories being Pitch IQ scores – greater than 100 is above average and under 100 is below average. For line drives and fly balls, the lower the rate the better.
Last year, line drives were hit on all of his pitches at a worse than average rate. This is somewhat of a worry, as line drives are generally the worst type of contact a pitcher can allow. It does strike me as somewhat odd that he is able to strike out so many batters while allowing such a large amount of line drives. And 24 appearances is hardly a large enough sample to say that these rates will remain constant throughout a career.
What is even more worrisome is that his xBABIP last year was .342. That type of expected BABIP could lead to Minor being the type of pitcher that annually under-performs in terms of ERA relative to DIPS. But again, he has just 24 appearances under his belt and these rates are not certain to repeat.
As an optimist and as someone who likes what Minor offers on the mound, I think the line drive rates are likely to decline. Either that, or his strikeout rates will drop. I do not see the latter happening, as he has posted stellar strikeout rates everywhere he has pitched as a professional. As high as I am on Minor — I made a bold prediction on RotoGraphs that he will be the team’s best pitcher this year — we all must use caution when projecting his future performance by simply regressing his BABIP. The line drives have been a concern, but I expect him to get that aspect of his game under control during his first full season as a Major League starter.
March 4, 2012 at 6:00 pm by Franklin Rabon under Atlanta Braves, Player Analysis, Statistical Analysis
Over the last few years, me and Peter would occasionally make jokes about Prado giving pitchers a free strike one, as he just patiently watched a perfect meat ball get rolled down the middle of the zone. Then Prado would get lauded for his approach by casual fans. Somehow Prado’s counterintuitive approach made announcers gush, as he managed to work the count and be aggressive. So let’s look at Martin’s approach since 2009. (all of the graphs and stats in this post are compiled using all available data from 2009-2011, courtesy of ESPN Stats & Info)
First, let’s get a sense of where Martin likes the ball, or at least should like the ball, by looking at his slugging percentage by area:
As we can see, power wise, Prado is an extreme inside ball hitter. This shouldn’t surprise anybody, as Prado has among the quickest hands in the game and can turn on virtually any fastball. He has an uncanny ability to get the head of the bat on anything inside and hit it hard. On pitches inside, Martin Prado has an astounding 1.044 OPS since 2009. 31 of his 39 homeruns have come on pitches on the inner half of the plate during that time span. By contrast, Prado has just a 0.613 OPS on pitches on the outer half of the plate and only a .642 OPS on pitches over the middle third of the plate. Basically the difference between Martin on the inside of the plate and Martin everywhere else is something like the difference between Barry Bonds and David Eckstein. This tells us that Prado should be picking and choosing his pitches as much as possible and waiting for any inner half pitches he can get and crushing them. Is this what happens? Let’s see:
Wait, what? From this graph it appears that Prado swings at most everything at roughly the same rate as long as it’s in the strike zone. He’s not picking and choosing his pitches by location, like his extreme splits on inside/outside perhaps indicate he should. he’s just swinging at everything in the zone about half the time. It’s not the extreme free swinging graph we saw from Freddie Freeman the other day, it’s just sort of bizarre.
The weirdness of this approach is most evident when looking at how he does on the first pitch. Saying he’s selective on first pitches would indicate he had some sort of plan as to what pitches he was going after on first pitches. He simply doesn’t swing at them, as we can see:
Contrast that with the three graphs of his swing percentages on 1-0, 2-0 and 3-1 counts, where a batter probably should be very selective:
How backwards are these graphs to the left? Why in the world would a hitter swing more in 1-0, 2-0 and 3-1 counts than in 0-0 counts? Prado swung at 16.9% of 0-0 pitches in the strike zone, compared to the league average of ~43%. Even in Martin’s ‘happy zone’, the inner third of the plate in the strike zone, he only swung at 21.6% of pitches thrown in 0-0 counts. On 2-0 counts, Prado swung at 41.1% of pitches overall, including swinging at 34.5% on the outside of the plate in the strike zone. Think about that for a second. Martin Prado is almost twice as likely to swing at a ball on the outside, where he’s a poor hitter, in a 2-0 count than he his over the inside, where he’s extremely dangerous, on a 0-0 count. It’s mind boggling. But the most truly mind boggling stat of all? Prado swings at 16.9% of strikes on 0-0 counts, as we’ve noted. Yet he swings at 21.5% of balls outside the strike zone on 2-0. That may be one of the most bizarre trends that has endured over a three year period I’ve ever seen. In a count where a hitter should chose their spots, he swings more often at balls than he swings at pitches in the strike zone in 0-0 counts. I had to type that again just to deal with the reality of it.
Furthermore, even in 1-0 counts, where Prado is reasonably appropriately selective, he’s selective in a weird and counterproductive way. As we will go into greater detail with below, in a 1-0 count he should be looking for a pitch he can hit hard and drive. Instead it seems like in 1-0 counts he’s looking for pitches he can dink into right field.
As Prado has gained in reputation, pitchers have really honed in on Martin’s habit of taking the first pitch no matter what and are increasingly using this habit to get a free strike. More often than not Prado only really makes use of 2 of his 3 strikes, basically giving one away. After getting Prado in a 0-1 hole, an intelligent pitcher can use Prado’s aggressiveness in later counts against him and then get him to chase poor pitches off the plate on the outside.
Something you will hear quite often is that “Martin’s game is going the opposite way, tagging those pitches on the outer half to right field, he gets himself in trouble when he gets pull happy and yanks too much to left field.” That was a direct quote from Braves announcer Jim Powell during today’s thrashing against the Tigers. While this may be the conventional wisdom, it simply couldn’t be more wrong. When Martin Prado pulls pitches on the inner half of the plate, his batting average is .498 with a .996 slugging percentage. This leads to a stupefying .616 wOBA when he pulls pitches on the inner half of the plate. Contrast that with his line of .324 BA, with a .429 slugging percentage and a .324 wOBA when he hits pitches on the outer half to the opposite field. Obviously both of those lines are pretty good, because a player is going to do well when they pull inside pitches or hit outside pitches the opposite way, but one is stupefyingly good and one is average. Martin’s game should be looking for pitches to pull in favorable counts, and then when he’s behind in the count going the opposite way with pitches on the outer half.
The graph to the left is a graph of expected wOBA Delta by location on swings. Which sounds complicated, but really isn’t. The graph takes wOBA, perhaps one of the better single composite measures of a player’s offensive ability, then graphs it out by location. The expected delta part means that this particular graph then measures it against what should be expected given the current count. So, for instance, if a player’s wOBA on 3-1 counts is .367, and a player gets a double it compares the weighted value of this double and subtracts .367, which is what would be expected for any pitch given that count. Furthermore, for this graph I only used times when Martin swung, to get an idea of where he hits best.
So, to make all that a little more easily understandable, that graph simply shows the locations that a hitter does relatively best when he swings, ie his personal hot zones. And as we can see, Martin is very clear as to what his hot zone is when he swings. The red parts indicate areas where him swinging produces better results than would be expected for an average pitch, while the blue areas indicate locations where him swinging produces worse results than would be expected. So, no Jim Powell, Martin’s game should not be hitting outside pitches the opposite way. In an ideal world, in hitters counts, a players swing rate graph should closely match his expected wOBA delta on swings graph.
Now, I don’t want to get too down on Prado’s plate approach, as it may simply be the case that he has a hard time differentiating strikes from balls, inside from out, and there’s not much he can do about it. I doubt that is the case, but it’s at least a plausible explanation. However, if it’s possible for him to do so, Prado could definitely see a large spike in his productivity if he was more intelligently selective. He gets himself into far too may 0-1 counts by taking pitches he could rake and then he swings at far too many poor pitches in hitters counts where he should be selective and wait for a pitch. Even putting aside the holes he gets himself in, Prado should be looking for inside pitches to drive in favorable and early counts much more. When he’s ahead in the count he should lay off outside pitches, and then only leverage his ability to slap the ball into right field when he gets behind in the count, not when he’s ahead in the count.
Prado has obviously been a great player during his tenure for the Braves. I’m simply saying that given his talent level, he could actually be an even better hitter.
edit: Here is a great video showing why Martin is so deadly on inside pitches. Look at how fast he clears the head of the bat. He doesn’t even really start his swing until the ball is around 15 feet away, but still gets the head of the bat all the way around on a fastball and pulls it.
edit2: There has been some wondering if Martin just doesn’t get a whole lot of inside pitches to hit, and thus that shapes his outlook, ie because pitchers throw him pitch after pitch outside, he starts looking that way, and is thus surprised when he does get one in his wheelhouse inside and is frozen. Reasonable quandary, but numbers just don’t bear it out. Here is a graph of where he gets pitched:
As we can see, pitchers shy away from the inside part of the plate a tiny bit, but that’s a pretty normal amount for any hitter, and it indicates that Prado is being thrown a pretty fair amount of pitches inside.
February 29, 2012 at 12:15 pm by Ben Duronio under Atlanta Braves, Statistical Analysis
Here is a summary on xBABIP from The Hardball Times.
Below is each players BABIP and xBABIP, followed by their actual slash lines against their expected slash lines
Most of the players received less luck than expected. The only players who actually had a BABIP higher than their expected mark were Freeman and Bourn, and most of Bourn’s plate appearances were in Houston (both he and Schafer’s above marks are overall totals, not just with Atlanta). While lack of patience was a big part of the Braves’ offensive issues last year, poor luck on balls in play was also a problem.
That is not a very impressive list of slash lines. Only three players have a combination of an on base percentage above .340 and a slugging percentage over .400. For a borderline playoff team, it is astonishing that the Braves had so much success without much offense. Consider the fact that two of the three players who qualified for the above benchmarks missed several games, and it becomes even more astonishing that the Braves won 89 games.
That group of lines would cause one to believe that the offense should be upgraded. The below chart shows why Frank Wren and the Braves’ front office were wise to keep this offense in tact.
Now this is an offense that should be in the upper echelon of the National League. Prado and Chipper should have been .300 hitters according to xBABIP, and Jason Heyward would have had a solid sophomore campaign. Nate McLouth and Jordan Schafer actually look like better players too, but as we stated here many times during Schafer’s hot streak, McLouth is the better hitter– this shows that as well. Uggla’s expected line actually has the biggest change from his actual line. Those numbers are in line with his career rates, more or less. A year like that out of Uggla this year would be huge, to say the least.
While the offense’s BABIPs are not expected to match their xBABIPs perfectly, having so many under-perform is simply bad luck. A few recording marks lower than expected is understandable, but basically the whole offense hitting worse than they should have is an anomaly. Expect the Braves to hit much better this year, specifically Prado, Heyward, and Uggla.
February 13, 2012 at 12:27 pm by Ben Duronio under Atlanta Braves, Statistical Analysis
The steady argument between sabermetricians and old school types in regards to Jair Jurrjens has been alive since his second season. Jair posted a 2.60 ERA in ’09, leading many to believe that he is one of the best young starters in the game. His FIP that season was a much higher 3.68, which put his -1.08 ERA-FIP spread the third biggest in the league. Many saber types predicted a regression to the mean, while others expected him to build off of that performance into a perennial Cy Young candidate. To date, neither have been quite right.
Last year, Jurrjens did it again. His ERA sat at another incredible mark of 2.96 while his FIP of 3.99 did not quite agree with the results. Again, his ERA-FIP spread was one of the largest in baseball, ranking fifth in the league, at -1.03. Since the start of his Braves’ tenure, he maintains a spread of -0.48, 16th over that time period.
Because of the two big seasons and the current high spread, many conclude that this is just something Jurrjens can do regularly. It is believed by some that he has the ability to outpitch his peripherals. Often, ground ball pitchers and weak contact pitchers do have this ability. To the extent that they have said ability is unknown. For example, Tim Hudson and Derek Lowe both have ground ball rates at 59% or higher, with Lowe actually having the higher rate. Hudson has a -0.38 spread while Lowe’s is +0.15. Obviously, the conclusion that all ground ball pitchers are misjudged by FIP is not valid, though it is often the case.
Now is that the case with Jurrjens? Of the 173 qualified pitchers since ’08, Jurrjens ranks 78 in ground ball percentage. He is not exactly a ground ball wizard, though that misconception is one that is often assumed. His infield fly rate, a number also often associated with weak contact, ranks 136. Jair’s GB/FB rate also sits in the middle of the pack at 78. Lastly, his line drive rate ranks 53, closer to the top of the league than his ground ball or infield fly rates. Batted ball numbers are still statistics to look at with caution, but over the relatively large sample size of four seasons the bias in their ratings gets at least somewhat mitigated.
So what exactly has Jair done that enabled him to record two seasons with a BABIP south of .270 and spreads better than -1.00? The only conclusion I can wrap my finger around is plain good fortune. In both of Jair’s seasons where he outperformed his peripherals, he finished in the top-5 in left on base percentage.
|LOB%||Jair’s||League Avg||E-F Spread|
Is there some uncanny skill that Jair retains that sometimes allows him to leave men on base at a higher rate than almost every pitcher in the league? I doubt it.
One argument commonly heard is to entirely discount his 2010 year due to injuries. On September 14 of that year, Jair tweaked his knee, which actually resulted in a torn meniscus. He did not start a Major League game after the reported tear. Prior to the tweaked knee, Jair made every start from June 30th until that final start in mid-September. He pitched to a 4.02 ERA over that 14 game span, with 68 strikeouts and 30 walks in 87.1 innings. That equates to 7.02 K/9 and 3.10 BB/9 rates, which are similar to his career numbers. To completely discount his entire year, despite having what seemed to be at least 14 healthy starts during the season, is picking and choosing numbers.
During spring training of that year, Jurrjens reported shoulder issues. He made four starts before his hamstring gave him problems in his one-inning outing against the Cardinals. In those four starts, he had two decent appearances and two poor ones. There is a chance that the shoulder problems he had in the early parts of spring affected those starts — the shoulder may have even led to the hamstring injury by nature of altering his mechanics — but he did have a nine strikeout performance before hitting the disabled list. While his start against the Cardinals can obviously be discounted due to the hamstring injury, assuming the previous four should be looked over is a stretch, in my opinion.
So while Jair did have injury issues in 2010, it is hard to say that all 116.1 innings — roughly 17% of his entire career — should not be included when evaluating his career. After all, his strikeout and walk percentages of 17.2% and 8.4% that season matched his rates from the previous season.
Jair basically has two seasons in which he stranded tons of runners, comparable with anyone in the league, and also posted a batting average on balls in play that ranked among the league’s lowest. There simply is not much evidence to support that this is the type of pitcher that Jair is, due to batted ball rates and the other two seasons in which he started. Simply doing this in two seasons does not make it the standard with which to project performance. While 367 innings is a relatively large sample size, Jair’s peripherals and batted ball rates make the notion that FIP does not judge him accurately seem somewhat inaccurate. Maybe there is something to Jair’s style of pitching that allows him to get better than expected results, but that conclusion is not one I am ready to side with just yet.
December 21, 2011 at 5:56 pm by Ben Duronio under Atlanta Braves, Player Analysis, Statistical Analysis
In 2011 the Braves were a game away from making the playoffs despite having no players with a Fangraphs WAR above 3.7. The team was well on pace to make the playoffs before the monumental collapse, as we all know, so expecting this team as currently built to again contend for a playoff spot is certainly plausible.
Not heavily relying on any individual player offensively or on the mound and still being able to win 89 games is very impressive. It is good that the Braves have the depth throughout the roster to be able to compete with the upper echelon of National League teams, but top tier production from a few players could push this team into contention for the NL East and assure them a wild card, barring a rash of injuries.
Below are the most likely candidates to have a season worth 4.5 Fangraphs WAR or more, in order of most likely to achieve said status, in my opinion. ZiPS projections for the Braves come out tomorrow, and we will see where they rate each player as well. I will comment on those projections around the same time tomorrow. For the rest of the post, I will simply state WAR when speaking of Fangraphs WAR.
We all know the story behind Heyward, an uber prospect with a sensational rookie season that struggled immensely during his sophomore campaign. Despite the poor offensive year, he was still able to produce a 2.2 WAR playing his entire season in right field, where he receives a -5.1 positional adjustment.
Heyward was still able to be the Braves’ most valuable outfielder and third most valuable position player according to WAR by playing excellent defense and being solid on the base paths. In fact, if you replace UZR with DRS, Heyward becomes a 2.7 win player instead of 2.2, which would make him more valuable than any position player aside from Brian McCann. That is pretty impressive given the fact that he had the least amount of plate appearances of the entire top five.
I expect Heyward to bounce back. He may not perform as well as some imagined in terms of the power numbers, but he is still an excellent player with solid secondary skills that help his overall value.
Three year average ( two seasons): 3.65
Fan projection via Fangraphs: 5.0
My projection: 4.8
Bourn has hovered around this mark for each of the past three seasons, mostly due to his position, base running, and defense. UZR disliked Bourn’s defense in 2011, but I put more of that on the metric’s massive volatility than on Bourn’s skills defensively decreasing. For what it’s worth, DRS had Bourn at -1, so it is possible that he had a poor season in the outfield, but a combined +27 over the past three seasons suggest his true talent level is among the best in the game in center.
He probably will not have as much luck on balls in play as he had last year (.369 BABIP in ’11 compared to .341 for his career), but he has had two seasons with a mark over .366, so it is possible. Bourn should also walk a bit more, which should keep his on base percentage around the same .345-.350 level that it has hovered around throughout most of his career, sans 2008.
Three year WAR average: 4.6
Fans projection via Fangraphs: 4.1
My prediction: 4.5
McCann was in the midst of one of his best seasons ever until he ran into a late season slump. In the season’s final two months, he batted just .180/.292/.346 compared to .306/.374/.514 from April until July 26. That was the last day McCann played before hitting the disabled list, and he returned on August 14 when he put up that awful slash line to end the year. There is legitimate reason to believe the injury hurt his performance, so I do not expect the poor tail end of the season to linger on into 2012.
The rough end of the year left McCann’s WAR at 3.7, the lowest since 2007 and second lowest of his entire career. McCann has a lot of games and innings behind the plate now, so injuries could unfortunately become more prevalent. Hopefully he is able to stay injury free, but at this point I am at least a bit skeptical of whether that will happen.
Three year average: 4.2
Fan projection via Fangraphs: 5.0
My projection: 4.1
Beachy is my pick to provide the most value from the rotation in 2012. His phenomenal rookie year was somewhat quiet on the national scene due to his low win total (he ended the season just 7-3) and the fact that he threw just over 140 innings.
Beachy’s strikeout rate was simply outstanding, and there is little reason to expect that number to drop below one per inning. He led the league among starters who threw over 140 innings, slightly edging out Zack Greinke. Even if Beachy’s strikeout rate regresses, expecting over a 16.2% decrease (the percentage difference between his 10.74 mark and 9.00) in his strikeout per nine rate is being pessimistic. Most signs point to Beachy’s ERA decreasing, as the spread between his ERA and FIP, SIERA, and xFIP is rather vast. If he remains healthy and all things remain equal, Beachy should be the top pitcher on the Braves’ staff next season in terms of WAR.
Three year average (one season): 2.8
Fan projection via Fangraphs: 3.6
My Projection: 4.0
Hanson suffered a similar fate as McCann. Stellar start to the year followed by an injury, trailed by an attempt to play through the injury which subsequently destroyed his statistics. In his first 17 starts, he had a 2.44 ERA with 109 strikeouts and 35 walks in 103.1 innings. His season at that point was comparable to almost anyone in the league, and there was little reason to expect his performance to drop the way it did, though a slight regression was expected due to the spread between his ERA and FIP.
Three of those 17 starts actually occurred after returning from the disabled list, but the rotator cuff tendinitis began to bother Hanson in mid-July, causing him to throw just 26.2 more innings in the season to the tune of an 8.10 ERA. Hanson’s ERA ballooned up to 3.60 from the aforementioned 2.44, and he missed the remainder of the season due to the complications in his shoulder.
I expect Hanson to return to his ~3.30 FIP performance, but the shoulder issues leave some cause for concern that he will be able to throw 200 innings as he did in 2010. Expecting him to pitch around 180 innings is probably more realistic at this point, which will likely cause him to fall shy of the 4.5 win mark.
Three year average: 2.9
Fan projection via Fangraphs: 3.2
My projection: 3.8
The joke around the Braves blogosphere and on twitter was that Dan Uggla should have won the comeback player of the year due to his performance in the second half of last season compared to his performance to start the year. The oddness of Uggla’s start to his tenure in Atlanta is well documented, and he straightened everything out to put up a rather productive offensive season that was just a tad below what was to be expected based on his career averages.
Uggla’s performance seems to be tied to his BABIP. When he has had a BABIP north of .300, he has put up 4.5, 4.6, and 4.9 win seasons. When his BABIP is below .300, he has had 2.7, 2.7, and 2.5 win seasons. In fact, in the years that his BABIP was below .300, it was never eve above .279. Uggla has only had a BABIP below .279 or above .309, which to me is just incredibly strange. This makes projecting him on a year-to-year basis very difficult, as he has really only had very good or decent seasons, with no solid good years in between.
Three year average: 3.4
Fan projections via Fangraphs: 3.7
My projection: 3.5
Tim Hudson was excluded from this exorcise due to the fact that this version of WAR dislikes him so much. Fangraphs’ WAR uses FIP, which does not account for Hudson’s ground ball tendencies. He has consistently outperformed his FIP over his career, and should be one of the top pitchers on the staff if his back injury does not cause him problems over the course of the season.
If my projections are accurate (far from certain), the Braves will have five players with a WAR higher than 3.7. The outfield would go from being an annual weakness to potentially harnessing the top two most valuable players on the roster. A full season of Bourn and a rebound from Heyward make that rather likely, so the projections do not have a ton of optimism in them.
A newly acquired left fielder could also provide performance north of 4.5, but I doubt this is the type of player the Braves actually do acquire. It seems as though Wren is confidence that his team will be able to rebound, in the depth of the rotation, strength of the bullpen, and anticipated performance of the offense. Make no mistake, the Braves still have a quality roster despite being very quiet this offseason.
November 22, 2011 at 10:52 am by Ben Duronio under Statistical Analysis
Mike Fast of Baseball Prospectus released a report on batted balls, specifically on the speed of balls leaving the bat and how likely each a ball is to land in for a hit.
It’s fascinating research, and as a saber-slanted blog we highly recommend reading it.
Fast does a good job of pointing out that the problems many of us have considered with FIP are real. Pitchers have more than no control over batted balls, so pitchers with bigger ground ball or pop-up splits need to be looked at differently than those with standard batted ball splits.
This does not mean FIP or similar defensive independent pitching stats are useless. Most pitchers don’t have those splits, and the analysis we often use to point to a positive or negative expected regression is often still correct. Even in cases such as Tim Hudson’s 2010, FIP can still be used to determine an expected regression by looking at the spread between ERA and FIP throughout his career.
No stat is perfect, and using a combination of the components of defensive independent pitching stats along with analyzing batted ball rates is the best method to accomplish what FIP attempts to do. Using FIP to glance over pitchers quickly is still a reasonable tool if you understand the pitcher being studied has relatively standard batted ball rates.