Readjusting Batted Ball Input for pERA

A few years back, I created pERA (pitch ERA) to help give each pitch a grade based on its results. For each grade, I never included any kind of walk rate until the final value when I added it in BB/9. It was never included in the individual pitches. A few months back, I looked into Ball% and immediately knew I needed to add it to the pERA formula. On top of that, I added a weak contact element. After a new finding, I needed to go back and tweak the batted ball numbers.

I thought that Baseball Savant would incorporate just Launch Angle (LA) when it comes to batted ball types but I found out there was an Exit Velocity (EV) component.

So I went back to the drawing board.

Previously I used <-5 degrees (groundballs) and >40 degrees (pop-ups) as my cutoffs. I threw out those numbers and started over. For groundballs, the angle found that the majority (83%) of all batted balls between 5 and 6 degrees were still groundballs but the groundball rate started dropping, so 6 degrees is now the cutoff.

From that point on, groundballs have a combination of each Launch Angle and Exit Velocity. I found the equation works out to:

EV <112.8 – (3.1 * LA)

Here are the Exit Velocity and Launch Angle cutoffs to have a batted ball grouped in with groundballs.

Launch Angle & EV Pairing for a Goundball
LA <EV
7 91.1
8 88.0
9 84.9
10 81.8
11 78.7
12 75.6
13 72.5
14 69.4
15 66.3
16 63.2
17 60.1
18 57.0
19 53.9
20 50.8

As for pop-ups, they have their own grouping of Launch Angle and Exit Velocity. The deal is that hitters start doing similar damage when a batted ball has a launch angle between 22 and 38 degrees if the batted ball has an Exit Velocity over 95 mph. Over 38 degrees, the batted ball is an out. Under 22 degrees, a line drive.

Note: From now on, I’m making a designation going forward that the batted ball rate with NO hard hit component will be called Fieldable% and the one with a hard hit batted ball component Weak%.

So there is a Fieldable% formula (<6 deg and >38 deg) and a more complex formula (Weak%) where the groundball equation and 95+ mph over 22 degrees. I next wanted to see how the values correlate between seasons.

Since 2015, I matched up starters (GS/G >= .5) who made at least 10 starts. Then I matched up back-t0-back seasons and found the correlation between values. Here are the results.

Season-to-Season Correlations for Weak Contact
Year-to-Year Correlation r-squared
Fieldable% y1 to Fieldable% y2 0.14
Weak% y1 to Weak% y2 0.08
Fieldable% y1 to Weak% y2 0.09
Fieldable% y1 to Weak% y1 0.71
Fieldable% y2 to Weak% y2 0.69

First, there isn’t a ton of correlation for the simple reason, batters, not pitchers, control most of where and how hard the ball is hit. The big conclusion is on line three. The value that best predicts next season’s Weak% is the previous season’s Fieldable%. The Fieldable% is a superior value.

Moving on to adjusting the equation. At a 57.8% Fieldable%, there is no ERA adjustment. For each percentage point over that amount, the average pitcher’s ERA should drop by about 0.10 (0.094 exactly).

ERA Adjustment =Fieldable%*(-9.49)+5.66

For reference, here are the adjustments for different Fieldable% rates.

Fieldable% ERA Adjustments
Fieldable% ERA Adjustment
45% 1.39
46% 1.29
47% 1.20
48% 1.10
49% 1.01
50% 0.92
51% 0.82
52% 0.73
53% 0.63
54% 0.54
55% 0.44
56% 0.35
57% 0.25
58% 0.16
59% 0.06
60% -0.03
61% -0.13
62% -0.22
63% -0.32
64% -0.41
65% -0.51
66% -0.60
67% -0.70
68% -0.79
69% -0.89
70% -0.98
71% -1.08
72% -1.17

 

Also, here are the top and bottom 10 starters from this past season ranked by Fieldable%.

Top & Bottom-10 2023 Starters by Fieldable%
Pitcher ERA pERA Fieldable% ERA Adjustment Adjusted pERA
Ty Blach 5.54 4.67 46.0% 1.30 5.97
Noah Syndergaard 6.50 4.48 48.0% 1.10 5.58
Spencer Strider 3.86 1.95 48.7% 1.04 2.99
Jack Flaherty 4.99 4.24 49.0% 1.01 5.24
Adam Wainwright 7.40 5.56 49.9% 0.93 6.49
Jose Quintana 3.57 4.57 50.0% 0.92 5.49
Luke Weaver 6.40 4.46 50.0% 0.92 5.38
Johnny Cueto 6.02 4.32 50.0% 0.92 5.24
Dylan Cease 4.58 3.57 50.1% 0.90 4.48
Nick Pivetta 4.04 3.46 51.0% 0.82 4.27
Wade Miley 3.14 4.79 61.9% -0.21 4.58
Tanner Houck 5.01 3.63 62.8% -0.30 3.33
Cole Ragans 3.47 3.32 62.8% -0.30 3.02
Marcus Stroman 3.95 4.54 63.2% -0.34 4.20
Brayan Bello 4.24 4.11 64.2% -0.43 3.68
Edward Cabrera 4.24 4.08 65.9% -0.59 3.49
Logan Webb 3.25 4.17 65.9% -0.59 3.57
Tarik Skubal 2.80 2.73 66.5% -0.65 2.08
Brandon Bielak 3.83 4.65 66.9% -0.69 3.96
Max Fried 2.55 3.90 67.3% -0.73 3.17
Min 10 GS

Hopefully, that’s for working with pERA for a season or two. I need to move on to clean up loose ends with my hitter evaluations before I move on to player previews.





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 four FSWA Awards including on for his Mining the News series. He's won Tout Wars three times, LABR twice, and got his first NFBC Main Event win in 2021. Follow him on Twitter @jeffwzimmerman.

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nuxieMember since 2020
1 year ago

wondering if this study takes into account bunts and what effect that would be,if any