NERD Game Scores for July 17, 2017

Devised originally in response to a challenge issued by sabermetric forefather Rob Neyer, and expanded at the request of nobody, NERD scores represent an attempt to summarize in one number (and on a scale of 0-10) the likely aesthetic appeal or watchability, for the learned fan, of a player or team or game.

How are they calculated? Haphazardly, is how. An explanation of the components and formulae which produce these NERD scores is available here. All objections to the numbers here are probably justified, on account of how this entire endeavor is absurd.

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Most Highly Rated Game
Milwaukee at Pittsburgh | 19:05 ET
Suter (27.1 IP, 94 xFIP-) vs. Kuhl (85.1 IP, 110 xFIP-)
The author’s haphazardly calculated algorithm has identified today’s Brewers-Pirates game as the day’s most compelling due partly to Milwaukee’s chances of winning the division (about 64% accrording to the coin-flip method) and also to Brent Suter’s surprising competence as a member of the Brewers’ rotation (he’s recorded an 83 xFIP- over three starts). Why else that algorithm has identified this game as the day’s most compelling, though, is due to the pace at which Suter works.

Consider the following table, which includes the top pace marks by starting pitchers (minimum 10 innings):

Pace Among Starters, 2017
Name Team IP Pace zPace
1 Brent Suter Brewers 17.0 17.2 3.2
2 Madison Bumgarner Giants 34.0 18.3 2.7
3 Amir Garrett Reds 58.1 18.9 2.4
4 Tommy Milone – – – 26.0 19.0 2.3
5 Kyle Hendricks Cubs 61.2 19.1 2.3
6 Adam Conley Marlins 27.2 19.3 2.2
7 Jason Vargas Royals 106.1 19.8 1.9
8 Andrew Moore Mariners 24.0 19.9 1.8
9 Brett Anderson Cubs 22.0 19.9 1.8
10 Dallas Keuchel Astros 75.2 20.0 1.8
11 Michael Wacha Cardinals 85.2 20.0 1.8
zPace denotes standard deviations better than league average.
Min 10 IP.
Numbers as starter only.

What one finds here is that Suter works a second faster per pitch than the next resident on this list, Madison Bumgarner, and that he works two seconds more quickly per pitch than the sixth-fastest-working pitcher. League average among starters is 23.6 seconds between pitches, or roughly six seconds slower than Suter. Over the course of a 100 pitches, in other words, Brent Suter saves 10 minutes of everyone’s life — time which one can then dedicate to the consumption of a long Russian novel or other improving book.

Readers’ Preferred Broadcast: Milwaukee Radio.

Another Brief Note
Today’s Free Game
Today’s free game features Washington at Cincinnati, starts at 12:35 ET, and can be accessed by means of this hyperlinked text.

Complete Schedule
Here’s the complete and also sortable table for all of today’s games. Pitching probables and game times aggregated from MLB.com and the rest of the internet. Note that calculations both for team and game NERD scores feature adjustment for postseason odds that increases as season progresses. Read more about those adjustments here and here.

NERD Scores for July 17, 2017
Away SP TM GM TM SP Home Time
Stephen Strasburg WAS 9 5 6 5 5 CIN Scott Feldman 12:35
Brent Suter MIL 10 7 7 3 7 PIT Chad Kuhl 19:05
Andrew Cashner TEX 1 6 3 4 0 BAL Chris Tillman 19:05
Jerad Eickhoff PHI 4 3 4 4 3 MIA Tom Koehler 19:10
Adam Wainwright STL 6 5 5 4 7 NYN Zack Wheeler 19:10
Marcus Stroman TOR 8 4 6 7 6 BOS Eduardo Rodriguez 19:10
Jon Lester CHN 7 7 5 3 2 ATL Julio Teheran 19:35
Bryan Mitchell* NYA 6 8 6 6 3 MIN Adalberto Mejia 20:10
Ariel Miranda SEA 2 4 5 5 10 HOU Lance McCullers 20:10
Jordan Zimmermann DET 2 4 4 5 5 KC Jason Vargas 20:15
Luis Perdomo SD 9 5 6 5 7 COL German Marquez 20:40
Jake Odorizzi TB 3 8 6 4 7 OAK Daniel Gossett 22:05
Josh Tomlin CLE 6 7 5 3 3 SF Matt Moore 22:15
SP denotes pitcher NERD score.
TM denotes team score.
GM denotes overall game score.
Highlighted portion denotes game of the day.

* = Fewer than 10 IP, NERD at discretion of doomed author.





Carson Cistulli has published a book of aphorisms called Spirited Ejaculations of a New Enthusiast.

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JMason15
5 years ago

Seven of the 10 fastest working pitchers are left-handed. Does this trend hold when extrapolating the data?

And if so, is there any explanation for this? Possibly some level of correlation with holding base runners?