How a Starting Pitcher Performs When Immediately Facing the Same Lineup

Today’s article has been a couple of weeks in the making. I know it came up when one of my co-managers, Fred Zinkie, asked how much a pitcher’s performance changes if they immediately reface the same team. I don’t remember the pitcher or team involved but I didn’t know the answer so I’d find it out. The obvious answer is sure, a pitcher will be worse. It makes sense that the team that just faced him will have some familiarity. Two questions do come up though. First, how much does the pitcher’s performance degrade in the second matchup? Next, if there is a familiarity factor, how long does it take to go away? After examining the data, a small factor exists and quickly disappears.

Simply, this is one of the noisiest, possibly biased studies I’ve ever worked on. First, a starter usually doesn’t see a team right away since schedules have quite a bit of variation in them. This limits the sample size. Second, the data is clumped at five-day multiples because the starters need rest. I begged for a possible solution on Twitter but no solution was found. Even with the limitations, I forged ahead with some workable results.

To get the data, I paired up starters who had one start against a team and then X days later made another against the same team. Since 2010, I collected the difference in several rate stats and length of start (innings and pitches). With such short time frames, an ERA over 100 could completely throw off an average so I found the median values. Using those settings, here are the results:

Median Change in Results Since the Last Start
Days Since Facing the Team ERA K/9 BB/9 H/9 Pitches IP Win% Count
5 0.45 0.00 0.00 0.09 0.0 0.0 -2% 543
6 0.00 -0.02 0.00 0.08 1.0 0.0 -1% 709
7 0.80 0.03 0.00 0.08 -2.0 0.0 2% 165
8 0.00 -0.21 0.07 -0.08 0.0 0.0 4% 45
9 0.14 0.00 0.14 0.00 2.0 -0.3 -9% 45
10 0.28 0.00 0.01 0.07 0.0 0.0 -4% 499
11 0.00 0.00 0.00 -0.03 0.0 0.0 -2% 803
12 0.00 0.00 0.02 0.02 -1.0 0.0 -1% 268
13 -1.31 -0.03 -0.11 -0.13 -0.5 0.3 6% 82
14 0.55 -0.01 0.00 0.25 -8.5 -0.3 -23% 22
15 0.08 -0.11 -0.05 0.01 3.5 1.0 -3% 40
16 -1.04 0.04 0.00 -0.07 2.0 0.3 8% 133
17 0.16 0.16 0.00 0.11 0.0 0.0 -8% 120
18 -0.67 0.06 0.03 -0.10 1.0 0.0 0% 63
19 -0.68 -0.01 -0.10 -0.20 -1.0 0.7 13% 39
20 -0.11 0.02 -0.11 -0.03 2.0 0.0 11% 62
21 0.00 0.04 0.00 0.13 0.0 0.0 -1% 164
22 0.00 -0.11 -0.04 0.00 1.0 0.0 0% 189
23 0.36 -0.02 -0.08 0.09 0.0 0.0 5% 122
24 0.21 -0.10 0.04 0.06 1.0 0.0 -3% 87
25 0.62 0.00 0.00 -0.10 -4.0 0.0 11% 45

What a mess to dechyper. Here is a visual of just the median difference in ERA with the circle size being the number of samples.

The clustering of samples can be seen with this image. Instead of grouping by individual days, I decided to create three groups and here are those results.

Median Change in Results Since Last Start
Days Since Facing the Team ERA K/9 BB/9 H/9 Pitches IP Win%
5 to 9 0.25 -0.01 0.01 0.07 0.31 -0.01 -0.93%
10 to 14 0.03 0.00 0.00 0.01 -0.30 0.01 -2.09%
15 to 25 0.08 -0.02 -0.02 0.03 0.21 0.00 1.32%

The second table is a little easier to consume. A quarter-point jump in ERA is expected with the cause being from several other categories. After that first start, the ERA’s are just barely higher. The length the pitcher throws is unchanged with the pitches thrown being plus or minus a third of a pitch. Not an actionable change. The Win% does drop a bit but rebounds.

The results would support the narrative that the hitter would remember the pitcher if they recently faced them. Similar to times-through-order penalty. After 10 days or so, the hitter has faced enough other pitchers, the familiarity advantage disappears.

As for being an actionable occurrence, facing a recent repeat opponent seems to just be a tie-breaker to use when starting similarly valued pitchers. And after just one start between occurrences, any negative reputcutions effectively disappear.





Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won three FSWA Awards including on for his MASH series. In his first two seasons in Tout Wars, he's won the H2H league and mixed auction league. Follow him on Twitter @jeffwzimmerman.

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ClevelandBob
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ClevelandBob

Eyes on Skubal v. CWS tonight

Sean
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Sean

I feel like I’ve had bad results on my sit/start decisions all season. CWS mash lefties (125 wRC+, .269/.345/.459), so I’m sitting him, which means he’ll probably get 10 k’s and a W.

Stock
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Stock

This is an excellent example. Skubal is a different pitcher than he was in April. The Sox struggled to figure him out last week. Right now it looks as though Skubal figured something out. However, if the Sox light him up maybe the success he has obtained because of his adjustments are just short lived and easy to adjust to. But if he dominates again it may time to trade for him in your fantasy league before he becomes too expensive.