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Pitching above and below expectations: ERA-FIP after the first half

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A look at the ERA-FIP differential for starting pitchers after the first half of the 2014 MLB season.

Greg M. Cooper-USA TODAY Sports

The All-Star game is almost here. I am not overly interested in looking too deeply at the perceived snubs. There are a few guys every year who likely should be at the game but do not get selected. To many, the All-Star selection system is flawed and until it is changed we will continue to have the same discussion every year. Rather at this arbitrary half-way point in the season (roughly 90 games in), I am interested in looking at how players have performed and what might be expected for the rest of the season. There must be players who are exceeding expectations, and also some who are underwhelming us with their performance. Let's have a look.

For this article I am going to focus on starting pitchers. Future work could look at relief pitchers and batters using different metrics. When considering how starting pitchers have performed a good number to look at is ERA-FIP differential. FIP (Fielding Independent Pitching) provides us with an index of what a player's ERA should have been over their innings pitched, assuming that the results of balls in play were average. As many of you know, pitchers have little control over where a ball goes once it is put in play. They have more control over strikeouts, walks, hit by pitches and home runs. FIP is calculated using these components and then presented on the same scale as ERA. Critically, FIP has been shown to be more effective in predicting future performance than ERA.

The approach here is to look at the 92 qualified starting pitchers' ERA-FIP differential to find players that have performed better (or worse) than their ERA indicates. For a variety of reasons these players have been somewhat fortunate (or unfortunate) so far this season and could be in for some ERA regression the rest of the way. Looking at things from this perspective can provide us with an idea of what to expect for the rest of the season.

First, here are the pitchers whose ERA has outperformed their FIP. Below is a table of the 15 pitchers with the largest negative differential between ERA and FIP, presented with some other relevant statistics for their season so far:

Player Team HR/9 K% BB% BABIP ERA FIP E-F
1 Chris Young SEA 1.28 13.8 9.1 0.203 3.11 5.00 -1.89
2 Josh Beckett LAD 1.04 23.1 7.8 0.235 2.26 3.82 -1.57
3 Alfredo Simon CIN 1.06 15.1 5.9 0.233 2.78 4.36 -1.57
4 Mark Buehrle TOR 0.67 13.9 6.2 0.285 2.60 3.74 -1.14
5 Julio Teheran ATL 0.79 22.0 5.3 0.242 2.29 3.22 -0.94
6 Johnny Cueto CIN 0.62 25.6 6.3 0.221 1.99 2.89 -0.90
7 Henderson Alvarez MIA 0.39 14.7 4.6 0.311 2.27 3.16 -0.89
8 Tommy Milone OAK 1.12 15.1 6.4 0.262 3.55 4.40 -0.85
9 Marco Estrada MIL 2.29 20.5 7.8 0.249 4.94 5.75 -0.81
10 Jason Vargas KCR 1.06 16.0 5.5 0.284 3.32 4.12 -0.80
11 Wily Peralta MIL 1.17 17.7 6.2 0.295 3.35 4.15 -0.80
12 Scott Kazmir OAK 0.82 22.8 6.0 0.253 2.53 3.31 -0.78
13 Jered Weaver LAA 1.24 19.4 7.0 0.261 3.56 4.27 -0.71
14 Jeremy Guthrie KCR 1.32 14.8 5.9 0.283 4.02 4.71 -0.69
15 Jon Niese NYM 0.70 17.3 6.5 0.283 2.96 3.61 -0.65

The average ERA-FIP difference for these players is about 1 run (-0.99). You can see that in almost all cases these pitchers have BABIPs lower than expected (~0.300). This means more balls in play are being turned into outs, which has contributed to ERAs lower than would be expected from their pitching. The news is not all bad for this group. There are a few pitchers where even if they pitched to their FIP level in the second half it would be a valuable performance (e.g., Cueto, Teheran, Alvarez).

Fans of the Brewers, Royals and Athletics might want to take notice of this table, as each of these teams has multiple representatives. While the Athletics have addressed issues in their rotation with the blockbuster trade for Samardzija and Hammel, the Brewers and Royals both have 2 starters in their rotation that may see some slip in their ERA in the second half; not something they want in a battle for playoff spots. Although it should be noted that the Royals have a strong defense (22 defensive runs saved; 2nd in the American League) that may actually sustain the lower BABIP of their pitchers.

Now we should not get too carried away with first half stats as the ultimate predictors for second half performance. As Mitchel Lichtman recently demonstrated, an up-to-date projection system is much better for predicting future performance than a portion of a season's statistics. Projection systems take into account players' performance across multiple seasons (where applicable) in order to provide a more accurate estimate of their true talent level and likely future performance. With that in mind let's look at a projection system's report. Here is the Steamer Rest-of-Season (RoS) FIP projections for the 15 pitchers above (presented with their first half FIP):

Player Team First half FIP RoS FIP
1 Chris Young SEA 5.00 5.96
2 Josh Beckett LAD 3.82 3.83
3 Alfredo Simon CIN 4.36 4.46
4 Mark Buehrle TOR 3.74 4.52
5 Julio Teheran ATL 3.22 4.02
6 Johnny Cueto CIN 2.89 3.41
7 Henderson Alvarez MIA 3.16 3.68
8 Tommy Milone OAK 4.40 4.30
9 Marco Estrada MIL 5.75 4.38
10 Jason Vargas KCR 4.12 4.46
11 Wily Peralta MIL 4.15 4.10
12 Scott Kazmir OAK 3.31 3.56
13 Jered Weaver LAA 4.27 4.42
14 Jeremy Guthrie KCR 4.71 4.75
15 Jon Niese NYM 3.61 3.87

Now we can see that for many of these players even their first half FIP performance was better than what should be expected from their track record. So even more backslide in ERA may be expected. For example, each of the pitchers mentioned above whose FIP would still be acceptable (i.e., Cueto, Teheran, Alvarez) are projected (based on track record) to have a higher FIP in the second half than they have posted in the first half. An increase in FIP in the second half is also expected for crafty lefty Mark Buehrle, which is bad news for a Blue Jays team that is already slipping in the standings.

How about the other side of things? Which pitchers have posted a first half ERA that is worse than would be expected from their FIP? Similar to the table above, below is a table of the 15 pitchers with the largest positive differential between ERA and FIP, presented with some other relevant statistics for their performance:

Player Team HR/9 K% BB% BABIP ERA FIP E-F
1 Ricky Nolasco MIN 1.39 15.7 6.1 0.362 5.90 4.54 1.37
2 Brandon McCarthy ARI 1.23 20.0 4.3 0.345 5.01 3.79 1.21
3 Justin Masterson CLE 0.56 21.0 12.1 0.339 5.16 3.97 1.18
4 Phil Hughes MIN 0.74 21.0 2.5 0.328 3.95 2.79 1.16
5 Edwin Jackson CHC 0.85 21.1 10.3 0.342 4.99 3.94 1.05
6 Ian Kennedy SDP 0.74 25.4 6.1 0.326 3.87 2.88 0.99
7 Kevin Correia MIN 0.84 11.4 5.2 0.317 4.95 4.11 0.85
8 Ervin Santana ATL 0.70 21.8 6.9 0.321 3.93 3.18 0.75
9 Stephen Strasburg WAS 0.88 27.8 5.1 0.348 3.53 2.80 0.73
10 Justin Verlander DET 0.85 17.3 8.3 0.325 4.71 4.02 0.69
11 Zack Wheeler NYM 0.62 22.9 10.2 0.320 4.07 3.47 0.60
12 Max Scherzer DET 0.83 28.3 6.7 0.321 3.47 2.88 0.59
13 John Lackey BOS 1.00 21.6 4.7 0.316 3.84 3.33 0.50
14 Ryan Vogelsong SFG 0.64 20.9 7.3 0.318 3.86 3.35 0.50
15 Travis Wood CHC 0.82 18.1 9.7 0.306 4.62 4.16 0.46

The average ERA-FIP difference for these pitchers is 0.84. You can see that, contrary to the pitchers presented previously, these pitchers' BABIP are higher than expected, which has likely contributed to their higher ERA. The biggest ERA-FIP differential belongs to Ricky Nolasco, but even his FIP level of performance is not something to be desired. Nolasco's difficulty may also be related to his apparent elbow injury. Two of Nolasco's rotation-mates also make this list (Phil Hughes, Kevin Correia) but much like Nolasco, Correia's FIP level performance is not really desirable. Recent Yankee addition Brandon McCarthy is near the top of the list. McCarthy has pitched well this season according to his FIP, posting career-best numbers in many categories. But his ERA has not followed suit. Perhaps getting out of gritty Chase Field will help him a little bit, but the ugly Yankee defense will likely counteract any benefit.

Detroit Tigers fans may be happy to see two of their aces on the list. Unfortunately, Justin Verlander appears to be more in the Nolasco-Correia category with a FIP that is not overly desirable. Scherzer on the other hand has pitched better than his ERA indicates and has posted a FIP that is quite impressive. Stephen Strasburg is in a similar situation to Scherzer.

As with the previous group, we should have a look at an up-to-date projection system's outlook for these players. Here is the Steamer Rest-of-Season (RoS) FIP projections for this second group of 15 pitchers (presented with their first half FIP):

Player Team First half FIP RoS FIP
1 Ricky Nolasco MIN 4.54 4.23
2 Brandon McCarthy ARI 3.79 4.04
3 Justin Masterson CLE 3.97 3.69
4 Phil Hughes MIN 2.79 4.09
5 Edwin Jackson CHC 3.94 3.94
6 Ian Kennedy SDP 2.88 3.89
7 Kevin Correia MIN 4.11 4.65
8 Ervin Santana ATL 3.18 3.65
9 Stephen Strasburg WAS 2.80 2.92
10 Justin Verlander DET 4.02 3.99
11 Zack Wheeler NYM 3.47 3.90
12 Max Scherzer DET 2.88 3.39
13 John Lackey BOS 3.33 3.65
14 Ryan Vogelsong SFG 3.35 4.06
15 Travis Wood CHC 4.16 4.78

Again we see that many players' first half FIP performance was actually even better than what should be expected from their track record. Yet, note that in many cases (11/15), the FIP projection is still better than the observed first half ERA (average difference of 0.47). So some of these pitchers even have a decent track record of pitching better than their current ERAs are demonstrating; it is not limited to the first half of this season. This could be good news for their second half.

All in all, this article was intended to identify a group of players whose performance may change a fair amount in the second half of the season. However, none of this means that it is guaranteed to change. While our best bet for how these pitchers will pitch in the second half is their FIP projection (from one or more of the projection systems; not necessarily just Steamer), players perform differently from their projections and peripherals all the time. That is part of what makes baseball interesting. As such it will be worth following how these pitchers perform the rest of the way to see where their numbers are at the end of the season.


All data through July 6th, 2014.

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All statistics courtesy of FanGraphs.

Chris Teeter is a Featured Writer at Beyond the Box Score. You can follow him on Twitter at @c_mcgeets.