Tuesday, March 5, 2024
2023 AnalysisAnalysisMLB

Rerevising my Predictive Metrics

Seven weeks ago ago, I published an update to expected swing and miss%+. Today, I will give a necessary update on my predictive metrics, which I revised in early April of last season. Honestly, I should have written and posted such an article prior to the start of the season, like I previously did, but I was not very motivated to. At the bottom of the last predictive metrics piece, I stated my intention to refine them subsequent to the 2023 campaign. Yet, in this most recent off-season, I felt the urge to make changes — sooner. It took plenty of time and effort, but I was able to sucessfully adjust a number of things. Overall, I am confident that the new versions of the statistics are improvements upon the old versions.

As a reminder, the main appeal of these single-season metrics is their predictive value. For instance, predictive weighted on-base average (pwOBA) communicates what one would predict a player’s wOBA to be in the following season, serving as a better estimate of that player’s true talent level.

pwOBA is appropriately built out of predictive metrics: predictive walk percent (pBB%), predictive weighted on-base average on contact (pwOBAcon), and predictive strikeout percent (pK%) (for pitchers).

Its calculation for batters…

pwOBA = HBP% regressed * wHBP (HBP weight for wOBA) + pBB% * wBB + pwOBAcon * (1 – K% regressed – pBB% – HBP% regressed)

For pitchers…

pwOBA = HBP% regressed * wHBP + pBB% * wBB + pwOBAcon * (1 – pK% – pBB% – HBP% regressed)

In the last rendition of my predictive metrics, data as far back as 2008 was utilized when possible. Dwelling on it at a later point, however, I decided that I should focus on just the Statcast era (2015 to the present). Presently, the training data for all of the models consists of consecutive qualified player-seasons from 2015 to 2020.

To start off, K% regressed values now adjust for home/away, home team (park), and the opposing batters/pitchers faced. From the perspective of a pitcher, striking out Luis Arraez is indisputably a greater accomplishment than striking out Mike Zunino. That strikeout would be even more impressive if it came as the road pitcher against the Rockies, whose home park is the hitter-friendly Coors Field.

The new K% regressed(+) for batters appears to be more stable from one season to the next than the old one was. When it comes to predicting future strikeout rates, they are about equal.

It is worth mentioning that for the old metrics yoy (year-over-year), the 2022 data is through late August, while for the new metrics it is complete. This is not ideal and may give the new ones an advantage. Luckily, the predictive part is unaffected because it is 2021 predicting an actual rate (or number) in 2022.

Here is the out-of-sample graph…

Here are the batter-seasons with the lowest K%+ regressed from 2015 to 2022…

  1. 2022 Luis Arraez (47)
  2. 2018 Andrelton Simmons (48)
  3. 2021 Kevin Newman (49)
  4. 2015 Daniel Murphy (50)
  5. 2021 David Fletcher (52)
  6. 2015 Norichika Aioki (53)
  7. 2018 Joe Panik (54)
  8. 2015 Buster Posey (54)
  9. 2019 David Fletcher (55)
  10. 2016 Andrelton Simmons (55)

Highest…

  1. 2016 Dan Straily (158)
  2. 2019 Keon Broxton (156)
  3. 2019 Sandy Alcantara (156)
  4. 2021 Sandy Alcantara (155)
  5. 2017 Chris Davis (155)
  6. 2015 Joey Gallo (154)
  7. 2017 Joey Gallo (153)
  8. 2016 Miguel Sanó (153)
  9. 2017 Miguel Sanó (153)
  10. 2019 Noah Syndergaard (153)

Not shocking to see a few pitchers in the top ten…

The training graph for hit-by-pitches is weird. Contrary to what one would anticipate, the old hit-by-pitch values are more reliable and predictive.

To my relief, the out-of-sample data is more encouraging. Hopefully, it is more representative too.

Highest HBP%+ regressed…

  1. 2016 Brandon Guyer (302)
  2. 2016 Derek Dietrich (232)
  3. 2015 Brandon Guyer (229)
  4. 2019 Tim Locastro (226)
  5. 2015 Anthony Rizzo (225)
  6. 2019 Derek Dietrich (223)
  7. 2019 Anthony Rizzo (201)
  8. 2017 Tyler Flowers (201)
  9. 2017 Josh Harrison (199)
  10. 2022 Mark Canha (196)

The lowest are boring, ten batter-seasons with around 600 plate appearances and zero hit-by-pitches.

The formula for battter pBB%+ (predictive walk percent plus) contains four variables:

  1. chase region swing percent plus regressed (swing percent in chase attack region, on a scale where 100 is league average, regressed to mean)
  2. walk percent plus regressed
  3. strike percent plus regressed
  4. contact percent plus regressed

Some graphs…

It is reassuring to see that the new pBB%(+) is likely more stable, and that did not seem to come at the expense of the metric’s ability to predict future walk rates.

Highest pBB%+…

  1. 2015 Joey Votto (210)
  2. 2022 Juan Soto (203)
  3. 2021 Juan Soto (200)
  4. 2021 Yasmani Grandal (193)
  5. 2016 Matt Joyce (190)
  6. 2021 Joey Gallo (190)
  7. 2015 Carlos Santana (182)
  8. 2015 Alex Avila (181)
  9. 2019 Alex Bregman (181)
  10. 2018 Joey Votto (180)

Lowest…

  1. 2019 José Iglesias (30)
  2. 2019 Kevin Pillar (31)
  3. 2019 Hanser Alberto (32)
  4. 2020 Hanser Alberto (33)
  5. 2022 Francisco Mejía (36)
  6. 2021 José Iglesias (39)
  7. 2021 Hanser Alberto (39)
  8. 2022 José Iglesias (39)
  9. 2017 Salvador Perez (39)
  10. 2018 Dee Strange-Gordon (40)

The second list feels incomplete without Javier Báez…

Batter pwOBAcon+ (predictive weighted on-base average on contact plus) consists of seven components:

  1. (standard deviation)launch angle plus regressed
  2. under percent plus regressed (percent of tracked batted ball events that are classified by Statcast as “under”, on a scale where 100 is league average, regressed to mean)
  3. barrel percent plus regressed
  4. sprint speed plus regressed
  5. 10th percentile exit velocity plus regressed
  6. 50th percentile exit velocity plus regressed
  7. 90th percentile exit velocity plus regressed

More graphs…

Similar story to the last set of graphs… It is appealing that the new pwOBAcon(+) is not only more stable, but also fared notably better in terms of predicting future wOBAcon, especially out-of-sample. The old pwOBAcon+ model grossly used raw wOBAcon plus, which is influenced by park, as an input, which one could imagine as a leg up as far as making predictions go. Nonetheless, the new version reigns supreme.

Highest pwOBAcon+…

  1. 2017 Aaron Judge (144)
  2. 2015 Giancarlo Stanton (139)
  3. 2022 Aaron Judge (139)
  4. 2015 Mike Trout (138)
  5. 2017 Joey Gallo (135)
  6. 2018 Joey Gallo (131)
  7. 2022 Mike Trout (131)
  8. 2015 J.D. Martinez (130)
  9. 2021 Shohei Ohtani (130)
  10. 2019 Mike Trout (130)

Lowest…

  1. 2021 Andrelton Simmons (74)
  2. 2021 David Fletcher (74)
  3. 2022 David Fletcher (77)
  4. 2022 Michael Papierski (78)
  5. 2016 Billy Burns (78)
  6. 2015 Brayan Peña (78)
  7. 2022 Yadier Molina (78)
  8. 2016 Ender Inciarte (78)
  9. 2022 Tony Kemp (79)
  10. 2015 Billy Burns (79)

K% regressed, HBP% regressed, pBB%, and pwOBAcon can be combined to arrive at pwOBA using the formula I already documented.

Some graphs for pwOBA…

Seemingly, the new pwOBA is more reliable and predictive than the old pwOBA. It is superior to wOBA and Statcast’s expected weighted on-base average (xwOBA), especially when looking at smaller samples, which is not surprising given that wOBA and xwOBA do not regress to the mean. This is not a “bad thing”, as wOBA’s goal is to measure a batter’s actual contributions at the plate, and xwOBA is trying to ballpark what one would expect a player’s wOBA to be given elements like launch angle and exit velocity. On the other hand, pwOBA is predicting how a batter would do next year, basing it on the batter’s performance from the current season. Which batter-seasons most impressively demonstrate “good hitting potential”?

  1. 2019 Mike Trout (130 pwOBA+)
  2. 2022 Aaron Judge (130)
  3. 2015 Mike Trout (129)
  4. 2017 Aaron Judge (128)
  5. 2018 Mike Trout (128)
  6. 2022 Yordan Alvarez (127)
  7. 2021 Vladimir Guerrero Jr. (126)
  8. 2017 Mike Trout (126)
  9. 2016 Mike Trout (125)
  10. 2021 Juan Soto (124)

Least impressively…

  1. 2022 Michael Papierski (80)
  2. 2019 Jeff Mathis (82)
  3. 2022 Yadier Molina (82)
  4. 2017 Juan Graterol (82)
  5. 2018 Billy Hamilton (83)
  6. 2022 Jose Herrera (83)
  7. 2018 Francisco Peña (83)
  8. 2016 Bobby Wilson (83)
  9. 2015 Billy Burns (83)
  10. 2017 Darwin Barney (83)

Mostly catchers on the bottom list…

Of course, striking out is not good; walking is good. With that said, even players that strike out a ton or walk a lot put the ball in play a fair amount. In 2021, Alex Jackson had 150 plate appearances (not ending in an intentional walk). He struck out almost 49% of the time, walked 8% of the time, and got hit by a pitch nearly 5% of the time. Still, he put the ball in play more than one-third of the time. That batter-season had the lowest percent of “plate appearances” ending in a ball-in-play. The highest pwOBAcon+ for the lowest ten pwOBA+ batter-seasons is 89, which is eleven percent below average. Really, it is okay to strike out often if it means better results on contact. Ask Aaron Judge… Undoubtedly, it is challenging for a batter to supply premium production if that batter does not hit the ball well. Now on to pitchers…

Pitcher pwOBA has the same formula, aside from the fact that a predictive strikeout percent is used instead of a regressed strikeout percent.

pK%+ has five inputs:

  1. shadow region swing percent plus regressed
  2. waste region swing percent plus regressed
  3. heart region whiff percent plus regressed
  4. average fastball velocity plus regressed
  5. strikeout percent plus regressed

Graphs…

All the lines look somewhat similar in the out-of-sample graph, but in the training one, the new pK%+ is more consistent season-to-season. So far, it feels as though all of the graph pairs tell a similar promising story: the new metrics are more reliable and at least as predictive as the old metrics.

Here are the top pK%+ seasons…

  1. 2017 Craig Kimbrel (192)
  2. 2016 Dellin Betances (191)
  3. 2019 Josh Hader (190)
  4. 2015 Dellin Betances (188)
  5. 2018 Josh Hader (186)
  6. 2022 Edwin Díaz (184)
  7. 2015 Aroldis Chapman (181)
  8. 2016 Andrew Miller (180)
  9. 2015 Carter Capps (178)
  10. 2018 Edwin Díaz (175)

Bottom…

  1. 2022 Hanser Alberto (48)
  2. 2022 Brett Phillips (52)
  3. 2015 Mark Buehrle (53)
  4. 2022 Carson Kelly (59)
  5. 2021 Dallas Keuchel (60)
  6. 2019 John Ryan Murphy (61)
  7. 2016 Justin Nicolino (65)
  8. 2019 Brett Anderson (65)
  9. 2022 Marco Gonzales (65)
  10. 2022 Josh Harrison (65)

Half of the bottom ten are position players. They are the ones used to striking out.

Pitcher pBB%+ has three variables:

  1. ahead in count swing percent plus regressed (swing percent when pitcher is ahead in count, on a scale where 100 is league average, regressed to mean)
  2. wOBAcon denominator percent plus regressed (percent of pitches that constitute wOBAcon denominator)
  3. strike percent plus regressed

Graphs…

The new pBB%+ is more stable, but possibly not as predictive. Interestingly, in the training graph, when the minimum wOBA denominator for each season in the pair is about 550 or more, actual walk percent is more predictive of next-season walk rate than the two predictive walk rates.

Lowest pBB%+…

  1. 2015 Bartolo Colon (34)
  2. 2015 Phil Hughes (36)
  3. 2021 Richard Bleier (37)
  4. 2018 Miles Mikolas (40)
  5. 2019 Mike Leake (42)
  6. 2016 Bartolo Colon (42)
  7. 2016 Josh Tomlin (43)
  8. 2017 Bartolo Colon (44)
  9. 2021 Julio Urías (46)
  10. 2017 Clayton Kershaw (49)

Highest…

  1. 2018 Tyler Chatwood (162)
  2. 2019 Jace Fry (153)
  3. 2019 Trevor Rosenthal (150)
  4. 2017 Adam Ottavino (147)
  5. 2017 José Leclerc (147)
  6. 2017 Dellin Betances (147)
  7. 2018 Justin Anderson (146)
  8. 2019 Tanner Rainey (145)
  9. 2022 Zach Jackson (144)
  10. 2021 Austin Adams (144)

Hit-by-pitch graphs…

Highest HBP%+ regressed…

  1. 2021 Austin Adams (210)
  2. 2022 Nick Lodolo (157)
  3. 2017 Dellin Betances (156)
  4. 2021 Alek Manoah (150)
  5. 2016 Jimmy Nelson (149)
  6. 2022 Steve Cishek (149)
  7. 2015 Justin Masterson (148)
  8. 2019 Spencer Turnbull (146)
  9. 2015 Nick Martinez (144)
  10. 2019 Jake Diekman (144)

Lowest aren’t noteworthy enough.

Pitcher pwOBAcon+ has a couple of pieces:

  1. topped percent plus regressed (percent of tracked batted ball events that are classified by Statcast as “topped”, on a scale where 100 is league average, regressed to mean)
  2. hard hit percent plus regressed (percent of tracked batted ball events that have an exit velocity of at least 95 mph)

Graphs…

This might be the most disappointing graph yet. The old pwOBAcon was more predictive of the following season’s wOBAcon than the new pwOBAcon is. I cannot explain precisely why this is the case, as I experimented with identical inputs.

Out-of-sample graph…

Fortunately, that trend is not as magnified in this graph. One might suggest that I use the old pwOBAcon+ instead, but I cannot be fully certain that the old is better than the new. Also, I like for all the models to be constructed in the “same manner”.

Here are the pitcher-seasons with the lowest pwOBAcon+…

  1. 2016 Zack Britton (83)
  2. 2019 Zack Britton (84)
  3. 2022 Clay Holmes (85)
  4. 2015 Brett Anderson (87)
  5. 2015 Zack Britton (88)
  6. 2021 Framber Valdez (88)
  7. 2017 Scott Alexander (88)
  8. 2022 Framber Valdez (88)
  9. 2018 Scott Alexander (88)
  10. 2019 Aaron Bummer (89)

It is not a coincidence that the six pitchers making up the top ten are all ground ball guys.

Highest…

  1. 2019 Dan Straily (108)
  2. 2019 David Hess (108)
  3. 2019 Adrian Sampson (108)
  4. 2018 Dan Straily (107)
  5. 2022 Logan Gilbert (107)
  6. 2015 Phil Hughes (107)
  7. 2017 Andrew Moore (107)
  8. 2016 Ian Kennedy (107)
  9. 2015 Ian Kennedy (107)
  10. 2016 A.J. Griffin (107)

The opposite… Pitchers that do not get very many ground balls…

pwOBA graphs…

Virtually a neck-and-neck matchup for the old pwOBA and the new pwOBA… It’s disheartening that 2021 pwOBA was not more predictive of 2022 wOBA than 2021 wOBA. I can only hope that this trend is not a sticky one.

Here is a graph that evaluates different stats’ abilities to predict future ERA…

pwOBA leads the pack at the extremes (low minimum wOBA denominator and high minimum wOBA denominator), but it is practically tied in the middle.

pwOBA dropped the ball in the out-of-sample-test, as I already admitted. At least it did pretty well at the extremes again…

Here are some graphs that compare the reliabilities of the same statistics…

Because kwERA solely incorporates strikeouts and walks, it makes sense that it ranks first in a stability meaasure. pwOBA does well in the training but poorly out-of-sample, which we saw before.

Top pwOBA+…

  1. 2016 Andrew Miller (79)
  2. 2018 Chris Sale (82)
  3. 2015 Zack Britton (82)
  4. 2022 Edwin Díaz (82)
  5. 2021 Jacob deGrom (82)
  6. 2016 Zack Britton (82)
  7. 2015 Clayton Kershaw (82)
  8. 2016 Clayton Kershaw (83)
  9. 2022 Emmanuel Clase (83)
  10. 2019 Gerrit Cole (83)

Bottom…

  1. 2017 Chris Tillman (113)
  2. 2019 Dan Straily (113)
  3. 2022 Jonathan Heasley (111)
  4. 2022 Adam Oller (111)
  5. 2020 Ryan Castellani (110)
  6. 2019 Eric Skoglund (110)
  7. 2018 Chris Tillman (110)
  8. 2018 Jacob Nix (110)
  9. 2017 Derek Holland (110)
  10. 2018 Bryan Mitchell (110)

None of the bottom pitchers are in the majors right now.

Here is a graph that plots the new pwOBA+ versus the old pwOBA+ for batter-seasons from 2015 to 2021…

Expectedly, the two are strongly related.

The biggest single-season gainers (minimum wOBA denominator of 600)…

  1. 2021 Manny Machado (112 –> 117)
  2. 2015 Curtis Granderson (108 –> 112)
  3. 2021 Freddie Freeman (111 –> 114)
  4. 2016 Christian Yelich (113 –> 116)
  5. 2015 Mookie Betts (109 –> 112)
  6. 2016 Carlos Correa (109 –> 111)
  7. 2015 Kyle Seager (106 –> 108)
  8. 2021 Bo Bichette (102 –> 104)
  9. 2021 DJ LeMahieu (100 –> 102)
  10. 2019 Eric Hosmer (96 –> 98)

Losers…

  1. 2016 Jean Segura (111 –> 104)
  2. 2015 Bryce Harper (128 –> 121)
  3. 2019 Rafael Devers (116 –> 110)
  4. 2016 Carlos González (113 –> 108)
  5. 2015 Paul Goldschmidt (121 –> 116)
  6. 2016 Brian Dozier (107 –> 102)
  7. 2019 Nolan Arenado (109 –> 104)
  8. 2017 Brian Dozier (106 –> 101)
  9. 2018 José Ramírez (121 –> 116)
  10. 2017 Dee Strange-Gordon (89 –> 84)

Graph for pitchers…

Strongly related again, but there seem to be more deviations…

Biggest single-season gainers (minimum wOBA denominator of 600)…

  1. 2019 Stephen Strasburg (92 –> 87)
  2. 2017 Justin Verlander (100 –> 95)
  3. 2015 Masahiro Tanaka (100 –> 95)
  4. 2018 Rick Porcello (101 –> 96)
  5. 2019 Patrick Corbin (97 –> 92)
  6. 2016 Rick Porcello (101 –> 96)
  7. 2018 Jack Flaherty (98 –> 93)
  8. 2018 Corey Kluber (95 –> 91)
  9. 2015 Félix Hernández (98 –> 94)
  10. 2016 Drew Pomeranz (99 –> 95)

Losers…

  1. 2021 Ryan Yarbrough (98 –> 102)
  2. 2016 Kenta Maeda (91 –> 94)
  3. 2018 Reynaldo López (105 –> 108)
  4. 2021 Cal Quantrill (97 –> 100)
  5. 2019 Reynaldo López (102 –> 105)
  6. 2017 Zack Godley (94 –> 97)
  7. 2015 Chris Sale (85 –> 88)
  8. 2019 Zack Wheeler (92 –> 95)
  9. 2015 Jered Weaver (104 –> 107)
  10. 2016 Steven Wright (97 –> 100)

Although pwOBA is not a “projection”, it is a predictive metric. I was curious to see how it’s doing this year, as in how well my 2022 numbers predicted this season’s numbers.

R-squared to 2023 wOBA for batters with at least 100 “plate appearances” in 2022 and 2023…

  1. pwOBA and FanGraphs’ Depth Charts projection wOBA (.2388)
  2. FanGraphs’ Depth Charts projection wOBA (.2297)
  3. pwOBA (.2016)
  4. wOBA (.1196)

R-squared to 2023 ERA (for pitchers)…

  1. pwOBA and FanGraphs’ Depth Charts projection ERA (.1729)
  2. FanGraphs’ Depth Charts projection ERA (.1603)
  3. pwOBA (.1559)
  4. ERA (.08936)

I am super pleased with these results. pwOBA looks useful, appearing to complement the Depth Charts projection system and performing similarly well on its own, in spite of not directly knowing the player’s team, park, and role, and only evaluating stats from a single MLB season.

Here are the batting leaders for 2023…

Lowest K%+ regressed…

  1. Luis Arraez (50)
  2. Keibert Ruiz (60)
  3. José Ramírez (61)
  4. Nico Hoerner (66)
  5. Jeff McNeil (67)
  6. Masataka Yoshida (68)
  7. Alex Bregman (69)
  8. Tony Kemp (70)
  9. Wander Franco (70)
  10. Ronald Acuña Jr. (70)

Highest…

  1. Mike Zunino (143)
  2. Patrick Wisdom (139)
  3. Joey Gallo (139)
  4. Brandon Belt (135)
  5. Nick Pratto (134)
  6. James Outman (133)
  7. Brenton Doyle (130)
  8. Trayce Thompson (130)
  9. Jake Rogers (129)
  10. Seby Zavala (128)

Highest HBP%+ regressed…

  1. Andrés Giménez (153)
  2. Zach Neto (153)
  3. Ty France (151)
  4. Jonathan India (147)
  5. Esteury Ruiz (146)
  6. Luke Raley (145)
  7. Isaac Paredes (145)
  8. Miguel Amaya (144)
  9. Josh H. Smith (144)
  10. Anthony Rizzo (141)

Highest pBB%+…

  1. Juan Soto (180)
  2. Ryan Noda (162)
  3. LaMonte Wade Jr. (159)
  4. Jack Suwinski (152)
  5. Andrew McCutchen (150)
  6. Kyle Schwarber (148)
  7. Aaron Judge (148)
  8. Ian Happ (147)
  9. Max Muncy (144)
  10. Mike Trout (143)

Lowest…

  1. Javier Báez (45)
  2. Salvador Perez (46)
  3. Mauricio Dubón (53)
  4. Will Brennan (57)
  5. Francisco Mejía (58)
  6. Yainer Diaz (59)
  7. Edmundo Sosa (60)
  8. Josh Naylor (61)
  9. Bo Bichette (62)
  10. Harold Castro (63)

There’s Javier Báez…

Highest pwOBAcon+…

  1. Aaron Judge (125)
  2. Mike Trout (119)
  3. Matt Chapman (117)
  4. Shohei Ohtani (117)
  5. Ronald Acuña Jr. (117)
  6. Luke Raley (116)
  7. Matt Olson (116)
  8. Jack Suwinski (115)
  9. Joey Gallo (115)
  10. Patrick Wisdom (114)

Lowest…

  1. Alejandro Kirk (80)
  2. Tony Kemp (83)
  3. Steven Kwan (84)
  4. Esteury Ruiz (85)
  5. Jose Trevino (85)
  6. Luis Arraez (85)
  7. Nicky Lopez (85)
  8. Austin Hedges (86)
  9. Yasmani Grandal (86)
  10. Elvis Andrus (86)

Highest pwOBA+…

  1. Ronald Acuña Jr. (125)
  2. Aaron Judge (117)
  3. Shohei Ohtani (115)
  4. Vladimir Guerrero Jr. (115)
  5. Corey Seager (115)
  6. Yandy Díaz (114)
  7. Mike Trout (114)
  8. Juan Soto (114)
  9. Yordan Alvarez (113)
  10. José Ramírez (113)

Lowest…

  1. Reese McGuire (85)
  2. Tucker Barnhart (86)
  3. Tomás Nido (87)
  4. Jesús Aguilar (88)
  5. Austin Wynns (88)
  6. Sandy León (88)
  7. Cam Gallagher (88)
  8. Seby Zavala (88)
  9. Martín Maldonado (88)
  10. Alan Trejo (88)

1-9 all catchers…

Pitching leaders…

Highest pK%+…

  1. Félix Bautista (170)
  2. Spencer Strider (158)
  3. Aroldis Chapman (157)
  4. Jordan Hicks (143)
  5. Craig Kimbrel (143)
  6. Jhoan Duran (138)
  7. Alexis Díaz (137)
  8. Matt Brash (137)
  9. Jacob deGrom (136)
  10. Bryan Abreu (135)

It is fitting that Félix Bautista, “The Mountain”, is at the peak.

Lowest…

  1. Josh Harrison (63)
  2. Adam Wainwright (65)
  3. Carlos Pérez (73)
  4. Kyle Freeland (73)
  5. Josh Fleming (74)
  6. Hanser Alberto (74)
  7. Kyle Hendricks (75)
  8. Cal Quantrill (76)
  9. Yonny Chirinos (77)
  10. Adam Cimber (77)

Lowest are the slowest.

Lowest pBB%+…

  1. George Kirby (46)
  2. Tyler Alexander (62)
  3. Joe Ryan (62)
  4. Miles Mikolas (65)
  5. Zach Eflin (68)
  6. Zack Greinke (68)
  7. Logan Webb (68)
  8. Garrett Whitlock (69)
  9. Braxton Garrett (69)
  10. Chris Martin (70)

Highest…

  1. Edward Cabrera (140)
  2. Brad Keller (139)
  3. Blake Snell (135)
  4. Alex Lange (133)
  5. Michael Kopech (133)
  6. Chad Kuhl (133)
  7. Jake Diekman (133)
  8. Dinelson Lamet (130)
  9. Shintaro Fujinami (129)
  10. Jack Flaherty (129)

Highest HBP%+ regressed…

  1. Peter Strzelecki (138)
  2. Ryan Yarbrough (129)
  3. Sam Moll (129)
  4. Nick Lodolo (127)
  5. Seth Martinez (126)
  6. Phil Maton (126)
  7. Jason Adam (125)
  8. Kevin Kelly (125)
  9. Yohan Ramirez (124)
  10. Connor Seabold (123)

Lowest pwOBAcon+…

  1. Yennier Cano (91)
  2. Marcus Stroman (93)
  3. Andre Pallante (94)
  4. Brad Keller (94)
  5. Yohan Ramirez (94)
  6. Hunter Brown (94)
  7. Griffin Jax (94)
  8. Ryan Pressly (94)
  9. Gregory Santos (94)
  10. Jhoan Duran (94)

Highest…

  1. Eric Lauer (105)
  2. JP Sears (105)
  3. Nestor Cortes (105)
  4. Phil Bickford (104)
  5. Brandon Pfaadt (104)
  6. Dean Kremer (104)
  7. Dylan Cease (104)
  8. Hunter Greene (104)
  9. Chad Kuhl (104)
  10. Will Smith (104)

Lowest pwOBA+…

  1. Félix Bautista (88)
  2. Spencer Strider (89)
  3. Yennier Cano (90)
  4. Jhoan Duran (90)
  5. Tanner Scott (91)
  6. Mitch Keller (91)
  7. Ryan Pressly (91)
  8. Jacob deGrom (91)
  9. Aroldis Chapman (91)
  10. Logan Webb (91)

Highest…

  1. Chad Kuhl (109)
  2. Alek Manoah (109)
  3. Jared Shuster (108)
  4. Madison Bumgarner (108)
  5. Kyle Muller (108)
  6. Luis Cessa (108)
  7. Adam Wainwright (108)
  8. Brandon Bielak (107)
  9. José Ureña (107)
  10. Adam Oller (107)

A number of the highest are out of the majors.

You can view player-season data from 2015 to 2023 on this this pay-to-access application. You can read more about the app if you want. Click here to read “How to Purchase Access to the Leaderboards”…

If you follow the app’s Twitter account (@pwoba_plus) and DM me, I will set you up for a week of free access.

Thank you for reading!

Featured image- Cleveland.com