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K% & BB% With A Look Into The At-Bat

Posted on 2021-08-072021-09-17

GAPA: Explaining K% With Depth

PitcherList’s CSW has been popularised with its simplicity & effectiveness. At the least, it takes 4 clicks at Statcast Search and is more predictive than SwSt% / more descriptive than Whiff%.

GAPA explains K%, better, with a correlation of r^2 = 0.89

GAPA is a simple & effective look into “what makes a strikeout?”

CSW / CSWF

If you haven’t read the article above, CSW is (CalledStrikes + SwingingStrikes) / Total Pitches, or CalledStrike% + SwStr%.

CSW stands for Called Strikes + Whiffs, in this case, whiff is used as a synonym for a swinging strike.

It correlates well with K%:

Min. 1500 pitches 2015-2021
Min. 1500 pitches 2015-2021

CSW doesn’t include fouls, as CSWF performs worse(r^2 of 0.699) than CSW(r^2 of 0.725). Hence, it was dismissed as being unpredictable/noisy.

The actual reason looks to be that fouls don’t result in the third strike; with 2 strikes, a foul is a negative.

In the meanwhile, fouls are positive with <2 strikes as they progress the count.

Let’s take those into account.

GAPA = GoAhead% + PutAway%

PutAway% is CSW with 2 strikes. It was introduced last year with better performance(r^2 of 0.783).

GoAhead% is CSWF with <2 strikes.

Min. 500 total pitches 2015-2021
Min. 1000 total pitches 2015-2021

On their own, they’re not too impressive.

Au contraire:

GAPA posts an impressive r^2 of 0.89, essentially leaving out only specific count-leverages(perhaps something else).

Indeed, it takes a bit more work than CSW(18 clicks + addition).

Standards

GoAheadPutAwayGAPA
Poor:<40%10 ~ 15%>55%
Below Average:40 ~ 45%15 ~ 20%55 ~ 65%
Average:45 ~ 50%20%65 ~ 70%
Above Average:50 ~ 55%20 ~ 25%70 ~ 80%
Great:>55%25 ~ 30%80 ~ 90%

xK%

Since there’s a linear relationship between GAPA and K%, slightly adjusting the formula gives us a 1:1 conversion: xK%.

2015 – 2021 formula: GAPA x 0.916 – 38.91

Trendline hitting 0:0 is always beautiful.

The Complete Formula

xK% = (GoAhead% + PutAway%) x 0.916 – 38.91

Standards

The standards for xK% are obviously the same as K%. And unlike GAPA, xK% is a lot more intuitive.

xK% is a good indicator of how much the pitcher could be striking out.

Poor:>15%
Below Average:15 ~ 20%
Average:20 ~ 25%
Above Average:25 ~ 30%
Great:30 ~ 35%
Amazing:> 35%

xK% Overperformers & Underperformers

(2015 – 2021)

Overperform (K% > xK%)Underperform (K% < xK%)
1. Cristian Javier (5.2%)1. Pat Neshek (-5.1%)
2. José Leclerc (5.1%)2. José Urquidy (-4.2%)
3. Justin Anderson (5.1%)3. Mike Morin (-4.1%)
4. Craig Kimbrel (5.0%)4. Adam Cimber (-4.1%)
5. Josh Hader (4.6%)5. Cole Irvin (-3.9%)
6. Matt Barnes (4.3%)6. Bartolo Colon (-3.8%)
7. Aroldis Chapman (4.1%)7. Phil Hughes (-3.6%)
8. John Axford (3.9%)8. Andrew Kittredge (-3.6%)
9. Josh James (3.9%)9. Alex Claudio (-3.5%)
10. Jason Grilli (3.8%)10. Mike Mikolas (-3.4%)

The list is almost unsurprising, as we’ve seen those names often on the Strikeout rankings charts(high or low).

One possible explanation for the difference might be that some pitchers allow more contact with 2 strikes thus having fewer strikeout opportunities.

Predictive Power

We can find that GAPA(xK%) is no more than a worse version of K% when it comes to predictive power; 2015 GAPA correlated with 2016 K% worse than 2015 K%.

Therefore, it isn’t an effective way to predict future performance, but a way to describe how a pitcher can/cannot strike hitters out.

Leaderboards

(2015 – 2021)

GoAhead% Leaderboard

1. Kenley Jansen57.2%
2. Josh Hader56.2%
3. Koji Uehara55.6%
4. Max Scherzer55.5%
5. Giovanny Gallegos55.5%
6. Pat Neshek55.2%
7. Seunghwan Oh55.1%
8. John Brebbia54.9%
9. Sean Doolittle54.5%
10. Darren O’Day54.2%

PutAway% Leaderboard

1. Betances, Dellin31.2%
2. Josh Hader29.7%
3. Andrew Miller29.3%
4. Edwin Diaz28.7%
5. Aroldis Chapman28.5%
6. Corbin Burnes28.4%
7. Shohei Ohtani28.2%
8. José Fernández27.9%
9. Craig Kimbrel27.8%
10. Ken Giles27.5%

You can find Full Leaderboards(SP/BP, Year) here.

Standout Pitchers

High GoAhead & Low PutAway

(2015-2021)

1. Pat Neshek37.5%
2. Christian Bergman37.0%
3. Seunghwan Oh36.5%
4. Jason motte35.9%
5. Miles Mikolas35.6%
6. José Urquidy35.6%
7. Matt Belisle35.3%
8. Casey Fien35.1%

These pitchers have had GoAhead% – PutAway% higher than 35%, which means that they got ahead very well, but not striking hitters out.

Most notably, Pat Neshek had merely an average K%(22.8) with the 7th highest GoAhead%(55.2) in MLB.

He had a 17.7% PutAway rate(bottom 1/3) while also underperforming xK% by -5.1%.

Christian Bergman’s PutAway rate was 12.1%(5th lowest) while having an average GoAhead%(49.1). That puts him at the 26th-lowest K%.

On the other hand, Chad Green’s 10th-highest GoAhead%(54.2) allowed him to have the 17th-best K% with an average PutAway%

Low GoAhead & High PutAway

(2015-2021)

1. Marc Rzepczynski16.5%
2. Framber Valdez18.0%
3. Shohei Ohtani18.2%
4. Tanner Scott19.2%
5. Clay Holmes19.3%
6. Jace Fry19.7%

These pitchers have had GoAhead% – PutAway% lower than 20%, which means that they struck out hitters well, but struggled to get to 2 strikes.

Most notably, Marc Rzepczynski had the lowest GoAhead%(40.4) in MLB with a 92nd-percentile PutAway%(23.9). That gives him an average K%.

On the other hand, Tanner Scott’s 11th-highest PutAway rate(27.2%) takes his average GoAhead%(46.4) into rank-35 of K%(30.7)


GBLG: Explaining BB% With Depth

Here’s a BB% version of GAPA.

GBLG is a simple & effective look into “what makes a walk?”

It correlates with BB% with an r^2 of 0.81

Zone% / Ball%

Zone% and Ball% are the most common indicators for walks.

Zone% doesn’t correlate well with BB%(r^2 = 0.129); pitchers with better control don’t necessarily throw inside the zone more often, nor are they necessarily balls.

Ball% does correlate significantly(r^2 = 0.589); more balls lead to more walks, obviously.

Min. 2000 pitches 2015-2021
Min. 2000 pitches 2015-2021

Now, Balls hold different leverages in different counts, so they’re divided into 2 parts:

GBLG: GetBehind% + LetGo%

GetBehind% is Ball% with less than 3 balls.

LetGo% is Ball% with 3 balls.

On their own, they’re not too impressive, especially compared to the generic Ball%.

Combine them together, and:

Voila.

GAPA posts an impressive r^2 of 0.89, essentially leaving out only specific count-leverages(perhaps something else).

Indeed, it takes a bit more work than B%(17 clicks + addition), which only takes 4 clicks.

Standards

GetBehindLetGoGBLG
Poor:>40%>35%>75%
Below Average:37.5 ~ 40%25 ~ 35%60 ~ 70%
Average:35 ~ 37.5% 25%60%
Above Average:32.5 ~ 35%15 ~ 25%50 ~ 60%
Great:<32.5%<15%<50%

xBB%

Since there’s a linear relationship between GBLG and BB%, slightly adjusting the formula gives us a 1:1 conversion: xBB%.

2015 – 2021 formula: GBLG x 0.358 – 13.8

Trendline hitting 0:0 is always beautiful.

The Complete Formula

xBB% = (GetBehind% + LetGo%) x 0.358 – 13.8

Standards

The standards for xBB% are obviously the same as BB%.

xBB% is a good indicator of how much the pitcher could be walking hitters.

Poor:>12.5%
Below Average:10 ~ 12.5%
Average:7.5 ~ 10%
Above Average:5 ~ 7.5%
Great:<5%

xBB% Overperformers & Underperformers

(2015-2021)

Overperform (BB% < xBB%) Underperform (BB% > xBB%)
1. Sam Dyson (-2.6%)1. Antonio Bastardo (2.8%)
2. Drew VerHagen (-2.3%)2. Trevor Rosenthal (2.7%)
3. Brett Anderson (-2.2%)3. Jason Grilli (2.5%)
4. Alec Mills (-2.0%)4. Neftali Feliz (2.4%)
5. Brandon McCarthy (-1.9%)5. Daniel Ponce de Leon (2.3%)
6. Jakob Junis (-1.8%)6. Ian Krol (2.2%)
7. Yusei Kikuchi (-1.8%)7. Corey Knebel (2.2%)
8. Derek Law (-1.7%)8. Jake Diekman (2.1%)
9. Dereck Rodriquez (-1.7%)9. Kyle Crick (2.1%)
10. Iván Nova (-1.7%)10. José Leclerc (2.1%)

Predictive Power

Like GAPA, GBLG(xBB%) is no more than a worse version of BB% when it comes to predictive power; 2015 xBB% correlated with 2016 BB% worse than 2015 BB%.

Therefore, it isn’t an effective way to predict future performance, but a way to describe how a pitcher walks hitters.

Leaderboards

(2015-2021)

GetBehind% Leaderboard

1. Kenley Jansen30%
2. Sean Doolittle30.3%
3. Nick Vincent31.6%
4. Joe Smith31.8%
5. Addison Reed31.8%
6. Max Scherzer32.1%
7. Bartolo Colon32.4%
8. Shawn Kelley32.4%
9. Joe Musgrove32.6%
10. Clayton Kershaw32.6%

LetGo% Leaderboard

1. Josh Tomlin12.1%
2. Roberto Osuna15.2%
3. John Means15.2%
4. Miles Mikolas15.3%
5. Liam Hendriks15.5%
6. Dan Haren16.1%
7. Addison Reed16.2%
8. Tommy Milone16.3%
9. Chad Green16.9%
10. Deolis Guerra16.9%

You can find the Full Leaderboard(By Year) here.

Standout Pitchers

High GetBehind & Low LetGo

(2015-2021)

1. John Means22.4%
2. Adam Warren21.8%
3. Josh Tomlin21.6%
4. Josh Collmenter21.2%

These pitchers have had GetBehind% – LetGo% higher than 21%, which means that they got behind a lot, but didn’t walk many hitters.

Adam Warren is the best example, as his 5th-percentile GetBehind rate(40.4%) is covered by his 95th-percentile LetGo rate(18.6%), making his BB% about average(8.1)

Low GetBehind & High LetGo

(2015-2021)

1. Greg Holland0.8%
2. Brandon McCarthy1.5%
3. Sandy Alcantara1.9%
4. Arodys Vizcaíno2%
5. Clay Holmes3%
6. Lou Trivino3.4%
7. Gregory Soto3.5%

These pitchers have had GetBehind% – LetGo% lower than 4%, which means that they didn’t get behind often, and when they did, they walked a lot of hitters.

Most notably, Arodys Vizcaino had a below-average BB%(10.3) despite having a low GetBehind%(35.3, top-1/4) due to his 7th-highest LetGo rate(33.3%).

In the meanwhile, Kenley Jansen’s GetBehind%(30, lowest in MLB) allowed him to have a low walk rate(6%) with an average LetGo%(29.7).


Biggest K% Dropper/Riser (2020-21)

(min.250 pitches)

Riser

As of August, the no.1 riser goes to Dustin May, who’s had a big increase in the PutAway rate.

  • K%: 19.6 -> 38.0
  • GAPA: 66.2% -> 82.6%
  • GoAhead%: 49.6 -> 52.4
  • PutAway%: 16.6 -> 30.2

Dropper

The no.1 dropper goes to Tanner Rainey, who completely lost the ability to PutAway hitters this year(55% decrease)

  • K%: 43.2 -> 24.6
  • GAPA: 88.9% -> 65.8%
  • GoAhead%: 52.9 -> 49.7
  • PutAway%: 36.0 -> 16.1
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