# Cole vs. Wacha by Pitch Repertoire – on the ‘Sabermetric Outcome’ Level:

Cole or Wacha? According to MockDraftCentral (only 18 qualifying drafts since 1/4/2014), they’re only 9 slots apart (Cole at 168 and Wacha at 177). NFBC has them 9 slots apart as well except swapped (80^{th} and 89^{th} respectively).I can tell you even I would have dwelled in the moment if I was into round 8+ and they were both still available. So let’s look at their projections, command ratio, balls in play mix and most importantly here, their repertoire:

**2014 Projections: **

You can see where I have them in my Top 100 SP Rankings. I have the following 5×5 projections for them:

Wacha: 13W 3.32ERA 1.17WHIP 174k

Cole: 13W 3.51ERA 1.24WHIP 167k

As an FYI, I use Stephen Staude’s new expected ERA called BERA and then incorporate Park Factors, SwStr% and LOB% so that we can hit their surface ERA a bit better. Let’s take a look at what’s in BERA and their weights to see what variables are a bit more significant:

**11.4***BB% – **7.9***K% + 5*LD% + FB%*(1 – 4.4*IFFB%) + **32.6***(HR/TBF) + 2.2*ZC% + 0.22*SIP% + 0.51.

In my projections, I have additional tabs dedicated to their Command ratios (BB & K-related data) and Balls in Play mix (GB/FB/LD). Again, here’s what I have for Wacha & Cole:

Rnk |
Player |
K/BB |
K% |
BB% |
SwStr% |

14 |
Michael Wacha |
3 |
0.222 |
0.074 |
0.104 |

26 |
Gerrit Cole |
2.99 |
0.215 |
0.072 |
0.092 |

Rnk |
Player |
GB/FB |
GB% |
FB% |
LD% |
IFFB% |
HR/FB% |
HR/9 |
WHIP |
BABIP |

14 |
Michael Wacha |
1.27 |
0.459 |
0.361 |
0.18 |
0.011 |
0.085 |
0.77 |
1.17 |
0.293 |

26 |
Gerrit Cole |
1.81 |
0.49 |
0.27 |
0.24 |
0.07 |
0.083 |
0.59 |
1.24 |
0.31 |

While Cole has the slight edge in the most significant factors (HR/TBF and BB%), Wacha beat him out in my projections because he had the slightly better IFFB%, Z-Ct%, park factors and SwStr%.

This is why FIP (and xFIP for that matter) isn’t nearly enough to look at Wacha and Cole in relation to each other. For reference, *FIP = ((13*HR)+(3*(BB+HBP))-(2*K))/IP + constant. You can also check out what their xERA, xFIP and SIERA’s would be for 2014 in the last tab of my embedded *projections*. *Per my projections, they’re within .2% of each other from a BB-perspective and .2% away as it relates to HR per FB’s – Cole leading slightly in both of these categories, but again Wacha makes up for it other command and BIP related aspects (SwStr and K%; IFFB% & LD%).

**No expected ERA formula is perfect…some work better for different pitchers – especially when we’re working with a smaller sample size. So instead of looking at their potential ERA outputs, let’s look at their 2013 Repertoires **(all data from Brooks Baseball and Baseball Prospectus’ Pitch F/X Leaderboard):

In the very near future, Dan Brooks of Brooks Baseball will be updating his sabermetric outcome levels of pitch f/x data where you can manipulate the percentages into z-scores (categorical outcome value in relation to the same category for all other pitchers with that same pitch), which is what I did for each pitch in Cole and Wacha’s repertoire (and Sonny Gray for the heck of it, since I thought he would be comparable).

**First, another (more descriptive/contextual) Approach:**

Let me be clear in that one other obviously potent way to understand a pitcher’s pitch value is by looking at their pitch type linear weights on FanGraphs. The issue, which they point out is that the results are extremely descriptive (vs. predictive) because they value pitches based on each specific count and the run prevention…probably the best way to understand anything in baseball (how does this stat prevent a run and on what level), but I want to look at a pitch’s value from a different (possibly more predictive level). I won’t focus on how predictive or reliable my custom scores will be because we’re still missing some z-scores (PU/BIP and HR/(FB+LD)), which will be available once Brooks Baseball installs the z-scores into his matrices.

**What If Approach:**

I also wanted to reference a fun conversation I heard from the Baseball Prospectus, Effectively Wild podcast last week. A reader asked them if they can instill one thing in all of baseball that no one could argue – what would it be? Ben Lindbergh I believe it was, sent the question to Dan Brooks who said this: All hitters would know what pitch was coming, but the pitcher wouldn’t know that the hitters knew. This would really help us understand the true value (or at least dominance) of a pitch…if a hitter knew what was coming but potentially still couldn’t do something with it?

**My (Z-Score without Linear Weights) Approach:**

Again, there’s limited value in what I am about to present (haven’t incorporated the Pop-up and HR-related z-scores) and other than in the final “Repertoire Score” matrix I will furnish, I did not weigh any of the z-scores by their pitch quantity/usage which is important. In any case, here is my approach:

For each pitch, I found the z-score for the following categories: **Velocity and Movement** (summed both vertical and horizontal movement z-scores and then found the z-score for the summed movement z-scores). I then summed the combined movement z-score and the velocity z-score which is my first pitch value we’ll simply call **V+M Score**. The other pitch value is each pitch’s combined **Whiff/Swing** z-score and combined **Balls in Play** z-score (similar to what I did for movement above, I did the same for LD/BIP and GB/FB). This is our **Wh+BIP Score**. Finally, I combine these two scores into our **VMWB Value** (again for each pitch). After all of these shenanigans, I added all the pitch VMWB scores together which is depicted in the last ‘totuwVMWB’ and ‘totVMWB’ full repertoire score columns below.

Here’s Cole’s, Wacha’s and Gray’s un-weighted and (weighted by usage) Repertoire Scores:

Cole has one devastating curveball. In fact, according to this approach, there were only 6 better pitches in baseball last year. In order: Brad Peacock’s Slider (6.65), AJ Burnett’s Changeup (6.23), Johnny Cueto’s Sinker (6.02), Tyson Ross’ Slider (5.72), Stephen Strasburg’s Changeup (5.27) and Yusmeiro Petit’s Curveball (5.21).

*****If you want to look at each categorical z-score or full pitch VMWB value per the BP Pitch F/X Leaderboard, then go into the different sheets in the embedded file above. Each pitch has its own tab with all the individual z-scores, V+M score, Wh+BIP Score and their final VMWB Values…in review, the Velocity, Movement, Whiff/Swing rate as well as their GB/FB and LD/BIP relative significance.*****

As I mentioned earlier, PU/BIP and HR/(FB+LD) weren’t included so scroll down in the first tab for their PU & HR/BIP results.

**Results** (and other important factors):

I didn’t talk about Gray much because he doesn’t have as significant of a pitch score relative to Cole and Wacha on the factors I looked at, but he still dominates with his release point. Per Jeffrey Long on Beyond the Boxscore:

Gray throws pitches in the strikezone 2.8% more often than the average MLB pitcher but batters swing at pitches in the strikezone 9.7% less than they do compared to the league average. It’s interesting that Gray throws more pitches in the zone than the average pitcher, but batters swing at them significantly less than they do versus the MLB average. One possible explanation for this is that hitters have a difficult time picking up pitches out of Gray’s hand, which makes it more difficult for them to decide to swing or not. The chart below suggests that this might be a big part of it, as Gray’s release point for all of his pitches is remarkably consistent.

His repertoire is one that drives an elite GB/FB ratio and a K/BB ratio approaching 3.00. Value him near Cole and Wacha above where I have him in my rankings (again, I will be incorporating pitch f/x a bit more into my projections next year).

From a pitch-repertoire perspective, I have to go with Gerrit Cole… a deep 5 pitch repertoire and a bigger sample size, I think Cole can exceed my expectations more than anyone else in my rankings. Next year I’ll be instilling much more of a Pitch F/X effect on my projections, and I believe Cole will be a borderline top 10 SP (possibly this year). Dynasty-wise, I’d rank Cole borderline top 5.

But I might like Danny Salazar even more!

**For other important factors (release point and velocity differential as it relates to off-speed pitches relative to fastballs) and outcomes (wOBA and averages against), ensure you read Stuart Wallace’s (@TClippardsSpecs on Twitter) series on ****‘First and Worst’ Pitches of 2013****.**

I really appreciate the depth of analysis on this site, and this Cole/Wacha matchup article is one of my favorites of the winter. Well done.

In an effort to go “all in” for a 2014 championship, I just traded Wheeler and Gausman in a keeper league for Anibal Sanchez and Brian McCann. I think Gausman will be the arm I miss the most long term, but I’d love to see this comparison of “stuff” between Wheeler and Gausman, both of which could be great in 2014.

I’m always for the win-now approach and that’s the obvious (& right) direction here. Anibal may be their #3 but he’s an ace…a better bb% away from being a top 5 w/ health