With the All-Star Break rapidly approaching, it’s time to take a look at the biggest overachievers and underachievers over the first three months of the season. Sample sizes are getting bigger, so pitchers that had tough starts to the season or had a couple of really bad starts to skew their ERAs have been able to recover. Some have not recovered because of a prolonged stretch of bad pitching.
There was a fascinating article a couple of weeks ago at MGL on Baseball about how pitchers that have a bad month or a good month early in the season are extremely likely to pitch to their projections the rest of the way, regardless of what happened in that one month. Of course there are going to be outliers or guys that improve or decline, but the vast majority of pitchers, according to the article, are going to perform to expectations the rest of the way. The article also found that pitchers perform close to their mid-season expectations in the second half after a good or bad first half.
The baseline that’s being used to collect the five pitchers for each of these sections is a statistic labeled E – F, or ERA minus FIP. FIP is a metric that calculates runs allowed per nine innings using the outcomes a pitcher can control – home runs, strikeouts, walks, and hit by pitches. ERA, as everybody knows, is simply runs allowed per nine innings pitched, found by multiplying the pitcher’s earned runs by nine and dividing by innings pitched.
With that in mind, here’s a look at the top three overachievers and underachievers in the first three months of the MLB season.
1. Chris Young (Mariners) – Chris Young is probably the most interesting case on this list. He has a 3.15 ERA and a 4.99 FIP, for the largest discrepancy in all of MLB at -1.84. Nobody else comes particularly close. Young is a fly ball artist that works up in the zone with the fastball with his 6’10” frame and pitches to contact. Young has the third-lowest K% among qualified pitchers at just 12.6 percent. The unfortunate thing for Young is that he’s also tied for 11th for the highest BB% at 9.4 percent. With 12 home runs allowed in 91.1 innings, it’s easy to see how Young makes this list, considering that he’s well below average in three of the four categories that determine FIP.
Is this sustainable? The short answer, from a sabermetric standpoint, is no. The long answer shows the fascinating dynamic between projection and reality. Most sabermetric stats serve as predictors of future performance with varying degrees of significance. All of the sabermetric run allowance stats suggest that Young is due for some substantial regression. However, his home park at Safeco Field, very conducive to his style of pitching, and he makes road starts in Oakland and Anaheim a fair amount of the time. Also, he does provide a much different arm angle for hitters because of his height.
Young has always been a guy that has outpitched his advanced metrics. This season, however, represents a career-low strikeout rate, which makes it harder to strand runners on base. This is also Young’s worst year by SIERA, one of the strongest predictors of future performance, so, the expectation should be that Young will regress in the second half of the season. That’s far from a guarantee, though.
2. Alfredo Simon (Reds) – With an ERA-FIP discrepancy of 1.47, Simon is the second-biggest overachiever on the season. He has been one of the league’s most profitable pitchers to back with a 10-3 record and a 2.88 ERA in 16 starts. Despite a strikeout rate that is well below average, Simon has stranded over 85 percent of baserunners and has held opponents to a .219 batting average.
Simon has a lot of signs of regression. For starters, nearly 79 percent of his plate appearances end with a ball in play and his batting average against on balls in play is just .235. Only rotation mate Johnny Cueto and the aforementioned Chris Young are better in that category. Simon is another guy that has outpitched his advanced metrics, but it’s different for relievers than it is for starters. This is the second time Simon has been used as a starter, the first in 2011 when he made 16 starts out of 23 appearances and posted a 4.96 ERA.
Simon has benefited from a good walk rate and his SIERA of 4.08 is pretty close to his career average of 3.96. With four different varieties of fastballs and a couple breaking balls mixed in, Simon could continue this pace because his raw stuff is above average. However, bettors should be concerned as Simon reaches new inning thresholds. He’s thrown 102.2 innings this season after topping out at 87.2 last season. Durability and health could be in question in the second half.
3. Josh Beckett (Dodgers) – This one may come as a little bit of a surprise, but Beckett’s ERA-FIP discrepancy of 1.33 manages to be higher than Mark Buehrle and Jeremy Guthrie, so he’s in this list. How much of an overachiever Beckett has been is definitely a matter of conjecture. Unlike the other pitchers that occupy the top spots in the E-F list, Beckett has a well above average strikeout rate and an above average walk rate. What Beckett does have in common with the others is a high home run rate.
Batted ball luck has played a big role in Beckett’s season so far. He has a 2.46 ERA and a 3.80 FIP. In all actuality, Beckett really doesn’t belong on this list, but using the baseline above, he’s in it. There are some concerns about regression for Beckett, though, so it’s not a bad place to talk about him. Beckett’s xFIP and SIERA are nearly a full run above his ERA and his BABIP against is .237. His career BABIP against is .289. Of course the Fenway Park factor has to be considered, but Beckett has enjoyed the pitcher-friendly NL West parks (minus Chase Field) and his left on base rate of 85 percent is among the league’s best.
Balls finding holes will change both the ERA and LOB% in a hurry. Only Masahiro Tanaka has a higher LOB% than Beckett, and he’s got an elite strikeout rate. Beckett’s health has to be a question in the second half, now in his mid-30s with declining velocity and an injury-riddled 2013 season. Approach Beckett with caution going forward.
1. Brandon McCarthy (Diamondbacks) – In terms of the outcomes that determine FIP, McCarthy has been solid in all but one of them. Through 104 innings, McCarthy has struck out 19.7 percent of batters, which is about a full percent below National League average. His walk rate is outstanding at 4.1 percent. He has only hit two of the 442 batters he has faced. The problem for McCarthy is that he has allowed 15 home runs in 104 innings and six of the 15 have come with runners on base, including two three-run homers and a grand slam.
McCarthy is just 2-10 with a 5.11 ERA, but the quality K% and BB% numbers equate to a 3.88 FIP. As a ground ball pitcher, McCarthy’s giving up an inordinate amount of home runs per fly ball, with the league’s highest percentage at over 20 percent. His xFIP is 2.91 and his SIERA is 3.01. It has to be frustrating for McCarthy, one of the league’s biggest supporters of the sabermetric movement, to see sparkling advanced metrics and have no results to show for it.
Unfortunately, things might not get a whole lot better for McCarthy. Being a ground ball pitcher with a home run problem is a tough way to make a living. Opposing hitters are batting .297 against him, even though the Diamondbacks rate above average in fielding. McCarthy added velocity in this offseason, a case study in why velocity is important, but not everything.
McCarthy is a free agent after this season and a team that believes in analytics could take a chance on him, so keep an eye out for where he might land. A team with a good infield defense and a home park that suppresses home runs would be a great fit.
2. Justin Masterson (Indians) – It came to light over the last week that Masterson has been dealing with a knee injury all season long. The drop in velocity and the lack of control have been side effects of Masterson’s attempt to find mechanics that are pain-free for his knee. With an E-F of 1.19, Masterson’s 5.16 ERA is significantly higher than his 3.96 FIP (numbers rounded to nearest hundredth).
This one has a lot to do with the Indians defense and how downright awful it is. The Indians are -50 in defensive runs saved and Masterson’s ground ball stylings don’t play well with the horrendous infield defense. Masterson’s ability to limit home runs is the reason why his FIP is below 4.00. He has allowed 63 baserunners via walk or hit by pitch and a .339 BABIP against has exacerbated the free passes.
There’s no end in sight for Masterson’s struggles, so don’t trust the advanced metrics in this one. As a sabermetrician (and an Indians fan), that’s hard to say, but unless the knee gets fixed via rest or surgery and Masterson’s velocity returns, lefties are going to continue to destroy him and the control won’t get any better. Most of all, the Indians defense won’t magically get better, though a Francisco Lindor appearance after the All-Star Break would be a monumental upgrade at shortstop.
3. Ricky Nolasco (Twins) – The Twins thought they were getting a bargain when the signed Nolasco early in the free agency period. The Twins are also a poor defensive team and the shift to the American League has taken a bite out of Nolasco’s strikeout rate. Nolasco has also been destroyed on the road to the tune of a 7.32 ERA in 55.1 innings.
Nolasco got paid off of one good season, his 2013 campaign, when he posted a 3.70 ERA and a 3.34 FIP. For his career, Nolasco has had ERAs above 4.00 in all but two seasons and has been a guy that has constantly posted a higher ERA than his advanced metrics would suggest.
One of the biggest flaws of FIP is that it accurately depicts control, with strikeouts and walks comprising a huge portion of the stat’s value, but it only considers command in the form of home runs. Not every pitch over the middle of the plate gets hit for a home run, but doubles and triples aren’t considered by FIP.
Nolasco has the opportunity to improve because a .355 BABIP is unsustainably high. He’s around league average with stranding runners, so fewer runners will help him immensely. The Twins may not improve much defensively, but Nolasco is due for some batted ball luck because he’s near his career averages in those categories.
Sabermetrics have a lot of predictive value and are the best way to analyze a player. In some cases, no matter how extreme the differences are, regression is simply not going to happen because of certain variables. Overall, sabermetrics have proven to be a valuable, effective way to project future performance and a lot of sabermetric stats have better correlations than the traditional metrics. They are not infallible, however, and anybody that wants to use them to handicap baseball needs to understand how they work.