RADIO
In 2019, I introduced a new (yet simple) index statistic for pitchers – mPDI, which was inspired by a famous quote by Hall of Fame pitcher, Greg Maddux:
“The key to pitching is to have the ability to throw a strike when they’re taking and throw a ball when the hitter is swinging.”
Maddux’s simplistic way of depicting [good] pitching inspired me to come up with a statistic that looked at three basic binary events:
Featured Promo: For this week only, take 50% off any full-season or yearly Premium Pass on the site! Just enter discount code THANKS when checking out. Thanks for being a reader, and Happy Holidays! Sign Up Now!- Was the ball thrown in the zone?
- Was the ball swung on?
- Did the batter make contact with the ball?
That is all. Just three simple queries.
wPDI Matrix
By answering the three binary questions above, each and every pitch can be classified into one of the following tracked six outcomes:
| Outcome A |
Outcome B |
Outcome C |
Outcome D |
Outcome E |
Outcome F |
|
| Zone? | Out of Zone | Out of Zone | Out of Zone | In Zone | In Zone | In Zone |
| Swing? | Swung On | Swung On | No Swing | Swung On | Swung On | No Swing |
| Contact? | No Contact | Contact Made | No Swing | No Contact | Contact Made | No Swing |
Each plate discipline outcome can be enumerated, and subsequently expressed as a percentage of all pitches thrown. Next, we can index each outcome appropriately, and aggregate it in a linear equation. The general family of formulae generated by this approach I refer to as wPDI (Weighted Plate Discipline Index). wPDI can be used as an accurate representation of many other statistics such as called strikes, whiffs, strikeouts, walks, etc.
For example, the strikeout rate can be estimated by the six plate discipline outcomes using the following linear indexes:
| Outcome | Description | Index |
| A | Out of Zone / Swung On / No Contact | 150% |
| B | Out of Zone / Swung On / Contact Made | -20% |
| C | Out of Zone / No Swing | 0% |
| D | In Zone / Swung On / No Contact | 225% |
| E | In Zone / Swung On / Contact Made | -20% |
| F | In Zone / No Swing | 75% |
The wPDI linear equation for strikeouts is represented by:
wPDIK = 150% * A% – 25% * B% + 225% * D% – 20% * E% + 75% * F%
Though this equation only asks three binary questions (was the ball thrown in the zone, was the ball swung on, did the batter make contact), the equation yields an excellent 84% correlation coefficient.
The strength of representing strikeout rate in terms of its wPDI components is the fact that a “pitch” is the smallest base event in baseball. You cannot break down the game of baseball into any smaller pieces than pure pitches. Since a pitcher could throw 100+ pitches per game, wPDI converges a lot faster than many other standard sabermetric statistics.
Similarly, the PitcherList metric CSW enumerates called strikes and whiffs as a percentage of total pitches. CSW rates become meaningful after just a handful of outings for starting pitchers.
mPDI for Hitters
The Maddux Plate Discipline Index (mPDI) is a special case of wPDI. For pitchers, this is represented by the following quantity:
Outcome A + Outcome B + Outcome F
Total Pitches
Using linear indexes per outcome, this corresponds to:
| Outcome | Description | Index |
| A | Out of Zone / Swung On / No Contact | 100% |
| B | Out of Zone / Swung On / Contact Made | 100% |
| C | Out of Zone / No Swing | 0% |
| D | In Zone / Swung On / No Contact | 0% |
| E | In Zone / Swung On / Contact Made | 0% |
| F | In Zone / No Swing | 100% |
mPDI for pitchers represents the outcomes where batters swing at out-of-zone pitches, plus the outcomes where batters do not swing at in-zone pitches.
However, today’s article will focus on the corresponding hitter metric. For batters, we would need to consider the exact inverse of Maddux’s quote for a hitter version of mPDI.
The key to hitting (according to the inverse of Maddux) would be to swing when the ball is in the zone and to lay off when the ball is out of the zone.
The Maddux Plate Discipline Index (mPDI) for hitters would capture all of the other plate discipline scenarios. In terms of the six defined outcomes above, mPDI for hitters is then defined as:
Outcome C + Outcome D + Outcome E
Total Pitches
| Outcome | Description | Index |
| A | Out of Zone / Swung On / No Contact | 0% |
| B | Out of Zone / Swung On / Contact Made | 0% |
| C | Out of Zone / No Swing | 100% |
| D | In Zone / Swung On / No Contact | 100% |
| E | In Zone / Swung On / Contact Made | 100% |
| F | In Zone / No Swing | 0% |
For the first six weeks of 2022, an awful mPDI would be close to .600s, while an elite one would approach .775. An average mPDI in 2022 would be roughly .685.
mPDI Leaders
Let’s now go look at a few early Maddux Plate Discipline Index studs. We will dive into some of their underlying metrics in the early going of the season, as well as their specific plate discipline component outcomes.
First, below is the current mPDI leaderboard for players with at least 30 plate appearances:
| Player | mPDI |
| Kyle Tucker | .772 |
| Chris Taylor | .764 |
| Jed Lowrie | .763 |
| Will Smith | .760 |
| Andy Ibanez | .760 |
| Anthony Rendon | .758 |
| Ji-Man Choi | .755 |
| Victor Caratini | .754 |
| Yandy Diaz | .751 |
| Curt Casali | .751 |
| Jeff McNeil | .751 |
| Andrew Benintendi | .748 |
| Max Kepler | .747 |
| J.D. Davis | .745 |
| Jesse Winker | .744 |
| Franchy Cordero | .743 |
| Brandon Belt | .742 |
| Matt Olson | .740 |
| Taylor Ward | .738 |
| Jonah Heim | .738 |
| Sam Hilliard | .737 |
| George Springer | .737 |
| Shohei Ohtani | .736 |
| Alex Bregman | .734 |
| Michael A. Taylor | .734 |
| Willie Calhoun | .732 |
| Corey Seager | .732 |
| Andrew Knapp | .732 |
| Tyler Wade | .731 |
| Christian Walker | .729 |
| Brandon Crawford | .729 |
| Carlos Santana | .729 |
| Jon Berti | .727 |
| Dom Nunez | .727 |
| Gilberto Celestino | .727 |
| Zack Collins | .726 |
| Matt Duffy | .726 |
| Aaron Hicks | .726 |
| Jose Miranda | .725 |
| Taylor Walls | .724 |
| Mike Brosseau | .723 |
| Josh Lowe | .723 |
| Kurt Suzuki | .723 |
| Akil Baddoo | .723 |
| Ryan O'Hearn | .722 |
| Mike Yastrzemski | .722 |
| Gavin Lux | .722 |
| Alec Bohm | .722 |
| Josh Harrison | .722 |
| Jo Adell | .721 |
| Robbie Grossman | .721 |
| Josh Rojas | .721 |
| Freddie Freeman | .720 |
Kyle Tucker, Houston Astros
The Astros' Kyle Tucker currently leads all of baseball in mPDI for the new year. Despite just a .254 batting average, Tucker has five HRs, eight stolen bases, and a .360 OBP. He has hit for a 142 wRC+ and has accumulated 1.4 fWAR – a top-20 batter in the majors.
But what jumps out in the early part of the season is Tucker’s rise in plate discipline. Kyle finished 2021 with a .748 mPDI, which has now risen to .772 – the highest in the majors. Following suit is his walk rate, which is now at a career-high 14.4% - which is the 14th highest in the majors among qualified hitters in 2022!
| Player | mPDI | Outcome C Percentile | Outcome D Percentile | Outcome E Percentile |
| Kyle Tucker | .772 | 87% | 76% | 95% |
Looking at the breakdown of his mPDI discipline outcomes (Outcomes C, D & E) - we can see that his Outcome E is super elite [Outcome E is in-zone contact] and Outcome C is elite [Outcome C is no swing out of zone]. Tucker is above the 87th percentile for C and above the 95th for E.
While his walk rate has been near the top of the MLB leaderboards, his 20.1% strikeout rate is merely just above league average (22.6%). I am hoping that his elite mPDI indicates that his K% rate will lower from here on out – hopefully to the 16% level that we saw in 2021.
As far as fantasy baseball, Tucker had been drafted within the first two rounds of 2022 drafts. mPDI confirms that you can simply roll with the Astros' plate discipline stud all season long.
Jesse Winker, Seattle Mariners
I currently play in the USA Today/League of Alternative Baseball Reality (LABR) mixed auction expert league. I had drafted Jesse Winker for $10 in the 12-team mixed 5x5 rotisserie contest. Last week, my patience ran out with the Seattle outfielder – and I traded him away for struggling pitcher Eduardo Rodriguez.
Sure, part of the reason for the trade was that I needed some extra pitching help. After a rash of injuries, assistance in the strikeouts category would benefit me greatly - and I had an extra outfielder on my roster.
Perhaps, I should have given Winker a longer look.
| Player | mPDI | Outcome C Percentile | Outcome D Percentile | Outcome E Percentile |
| Jesse Winker | .744 | 75% | 67% | 94% |
Component-wise, Winker has a similar plate discipline makeup to Tucker. He is also sporting an excellent 13.7% walk rate to go with his superb 13.7% strikeout rate. A zero K-BB% is phenomenal!
Winker has been the product of some bad luck in the early going. He has a .250 BABIP and just a 5.4% HR/FB ratio. His career figures are .307 and 18.8%, respectively. At 28-years-old now, Winker still has the 3+ WAR upside that he flashed last season when he batted .305 with 24 HRs.
Perhaps give Winker a second look before you decide to trade him away in your league …
Jeff McNeil, New York Mets
I first discovered the greatness of Jeff McNeil a few years ago while looking at league mPDIs. It seems that McNeil is back to his old tricks once again!
| Player | mPDI | Outcome C Percentile | Outcome D Percentile | Outcome E Percentile |
| Jeff McNeil | .751 | 63% | 59% | 99% |
Wow, McNeil is in the 99th percentile for Outcome E! That means that as a percentage of pitches seen, he both swings and makes contact with the ball more than almost any other player. The only players who have a higher Outcome E thus far are Mauricio Dubon (.689 mPDI), Nick Gordon (.701), Didi Gregorius (.660), and Tim Anderson (.640).
McNeil’s 2022 strikeout rate of 11.5% is now amazingly under his career average of 12.4%, and his walk rate this year (8.5%) is over his career average (6.9%). These component figures are back in the neighborhood of where he was in the 2020 season, showing that he has fully rebounded from last year’s woes where he batted an abysmal .251.
I don’t believe that Jeff’s 2019 power figures will return … or at least not this season. His power metrics are still down. The 23-round trippers in ’19 might have been the product of the juiced ball that season – and 2019 looks to be an outlier. But so does 2021 now.
Expectations for McNeil were greatly lowered coming into 2022, but we can quickly see that should not have been. McNeil will flirt with a .300 batting average all season long. Hopefully, the Mets will move him a bit higher up in the order soon.
Ji-Man Choi, Tampa Bay Rays
Ji-Man Choi is quite the opposite player of Jeff McNeil in approach. However, he still ranks highly in plate discipline. His skill set consists of recognizing out-of-zone pitches rather than making contact with in-zone ones. Let’s dig in a bit into his makeup.
| Player | mPDI | Outcome C Percentile | Outcome D Percentile | Outcome E Percentile |
| Ji-Man Choi | .755 | 100% | 74% | 38% |
Thus far in 2022, Choi is batting .262 with two HRs and 12 RBI. Tampa Bay does not play him every day, but these are fairly good numbers on a per plate appearance basis. He has walked 15.3% of the time, which is amongst the league leaders for players with at least 70 PAs. He is also sporting a 17.1% barrel rate with a 94 MPH average exit velocity – both figures are amongst the league leaders.
Choi has plenty of flaws in his game. He has struck out 36% of the time this season and has been somewhat lucky as seen in his fortunate .424 BABIP.
I wouldn’t consider rostering Choi on your squad unless there is a week where he has an excellent upcoming schedule (facing plenty of righties), you are in a deep league, or you play in a walk-heavy category format. Keep tabs on him though in case the strikeout rate comes down, as he does have 15-20 HR upside even in limited playing time.
Anthony Rendon, Los Angeles Angels
Did you check out Anthony Rendon’s lefty-righty splits this season? Rendon has a 5.000 OPS, a 1404 wRC+ and a 2.129 wOBA as a lefty! Well, this all was the result of Rendon’s left-handed at-bat against Brett Phillips the other day. A rate lefty at-bat for Rendon led to a home run in a runaway game!
Aside from all the hijinks, Anthony Rendon has returned to prestige with a glorious .758 mPDI.
| Player | mPDI | Outcome C Percentile | Outcome D Percentile | Outcome E Percentile |
| Anthony Rendon | .758 | 98% | 47% | 80% |
Through 139 plate appearances, Rendon only has a .227 batting average – but he has swatted four HRs and has knocked in 18 runs. He is sporting an 81% contact rate and a 12% walk rate, and his average exit velocity has ticked up to the highest levels of his career. The batting average should pick up; Rendon’s GB/FB ratios are thus far close to his norm, and he has an unfortunate .253 BABIP.
On a rotisserie valuation basis – Rendon is just an $8 hitter in a 15-team 5x5 format. However, with his elite mPDI and the excellent supporting metrics described above, I would venture that his value will be on the rise. Old veterans sometimes bring great value in the second half of the season.
Chris Taylor, Los Angeles Dodgers
Finally, we have a repeat mPDI stud from last year! Chris Taylor finished 2021 with a wonderful .741 mPDI, and he is right back at it to start 2022. Currently, he has the second-highest Maddux plate discipline index at .764 – second only to Kyle Tucker.
| Player | mPDI | Outcome C Percentile | Outcome D Percentile | Outcome E Percentile |
| Chris Taylor | .766 | 84% | 99% | 63% |
A bit of caution though with Taylor - it is the 99th percentile Outcome D which is propelling his lofty mPDI. Ideally, we would like to see some of the D category pitches shifting into the Outcome E category [Remember, the difference between Outcome D and E is that E is contact, whereas D is not]. To further cast doubt on his success – his strikeout rate has risen this year to 35.0%, the highest of his career.
On the plus side, Taylor’s walk rate has also gone up to a career level as well, at 12.5%. Chris seems to be inching towards three true outcome territories.
mPDI is about zone recognition at the purest, and Taylor is certainly one of the best in baseball at recognizing balls and strikes. On a rotisserie valuation basis, it helps that Chris has moderate power and the ability to steal bases. He scored 92 runs for the Dodgers last season and should continue to get opportunities to compile ample run production stats again this season. Taylor should once again be undervalued in most fantasy formats (as he is every single year).
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