dSCORE: Pitcher Evaluation by Stuff by Snerd February 9, 2017 Confession: fantasy baseball is life. Second confession: the chance that I actually turn out to be a sabermetrician is <1%. That being said, driven purely by competition and a need to have a leg up on the established vets in a 20-team, hyper-deep fantasy league, I had an idea to see if I could build a set of formulas that attempted to quantify a pitcher’s “true-talent level” by the performance of each pitch in his arsenal. Along with one of my buddies in the league who happens to be (much) better at numbers than yours truly, dSCORE was born. dSCORE (“Dominance Score”) is designed as a luck-independent analysis (similar to FIP) — showing a pitcher might be overperforming/underperforming based on the quality of the pitches he throws. It analyzes each pitch at a pitcher’s disposal using outcome metrics (K-BB%, Hard/Soft%, contact metrics, swinging strikes, weighted pitch values), with each metric weighted by importance to success. For relievers, missing bats, limiting hard contact, and one to two premium pitches are better indicators of success; starting pitchers with a better overall arsenal plus contact and baserunner management tend to have more success. We designed dSCORE as a way to make early identification of possible high-leverage relievers or closers, as well as stripping out as much luck as possible to view a pitcher from as pure a talent point of view as possible. We’ve finalized our evaluations of MLB relievers, so I’ll be going over those below. I’ll post our findings on starting pitchers as soon as we finish up that part — but you’ll be able to see the work in process in this Google Sheets link that also shows the finalized rankings for relievers. Top Performing RP by Arsenal, 2016 Rank Name Team dSCORE 1 Aroldis Chapman Yankees 87 2 Andrew Miller Indians 86 3 Edwin Diaz Mariners 82 4 Carl Edwards Jr. Cubs 78 5 Dellin Betances Yankees 63 6 Ken Giles Astros 63 7 Zach Britton Orioles 61 8 Danny Duffy Royals 61 9 Kenley Jansen Dodgers 61 10 Seung Hwan Oh Cardinals 58 11 Luis Avilan Dodgers 57 12 Kelvin Herrera Royals 57 13 Pedro Strop Cubs 57 14 Grant Dayton Dodgers 52 15 Kyle Barraclough Marlins 50 16 Hector Neris Phillies 49 17 Christopher Devenski Astros 48 18 Boone Logan White Sox 46 19 Matt Bush Rangers 46 20 Luke Gregerson Astros 45 21 Roberto Osuna Blue Jays 44 22 Shawn Kelley Mariners 44 22 Alex Colome Rays 44 24 Bruce Rondon Tigers 43 25 Nate Jones White Sox 43 Any reliever list that’s headed up by Chapman and Miller should be on the right track. Danny Duffy shows up, even though he spent most of the summer in the starting rotation. I guess that shows just how good he was even in a starting role! We had built the alpha version of this algorithm right as guys like Edwin Diaz and Carl Edwards Jr. were starting to get national helium as breakout talents. Even in our alpha version, they made the top 10, which was about as much of a proof-of-concept as could be asked for. Other possible impact guys identified include Grant Dayton (#14), Matt Bush (#19), Josh Smoker (#26), Dario Alvarez (#28), Michael Feliz (#29) and Pedro Baez (#30). Since I led with the results, here’s how we got them. For relievers, we took these stats: Set 1: K-BB% Set 2: Hard%, Soft% Set 3: Contact%, O-Contact%, Z-Contact%, SwStk% Set 4: vPitch, Set 5: wPitch Set 6: Pitch-X and Pitch-Z (where “Pitch” includes FA, FT, SL, CU, CH, FS for all of the above) …and threw them in a weighting blender. I’ve already touched on the fact that relievers operate on a different set of ideal success indicators than starters, so for relievers we resolved on weights of 25% for Set 1, 10% for Set 2, 25% for Set 3, 10% for Set 4, 20% for set 5 and 10% for Set 6. Sum up the final weighted values, and you get each pitcher’s dSCORE. Before we weighted each arsenal, though, we compared each metric to the league mean, and gave it a numerical value based on how it stacked up to that mean. The higher the value, the better that pitch performed. What the algorithm rolls out is an interesting, somewhat top-heavy curve that would be nice to paste in here if I could get media to upload, but I seem to be rather poor at life, so that didn’t happen — BUT it’s on the Sum tab in the link above. Adjusting the weightings obviously skews the results and therefore introduces a touch of bias, but it also has some interesting side effects when searching for players that are heavily affected by certain outcomes (e.g. someone that misses bats but the rest of the package is iffy). One last oddity/weakness we noticed was that pitchers with multiple plus-to-elite pitches got a boost in our rating system. The reason that could be an issue is guys like Kenley Jansen, who rely on a single dominant pitch, can get buried more than they deserve.