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The Mad Professor’s Mid-May Musings on Pitching Prowess and Proficiency

StrasburgThis week I continue with pitching analysis.  I’m inspired in part by a discussion I heard about Stephen Strasburg’s new contract.  It is pretty amazing and so is he.  But, he has cracked 200 IP only once.  Jake Arrieta has cracked 200 IP only once as well.  But, he does not have the history of gimpiness that Strasburg does.  Makes you wonder what Arrieta will command come negotiation time.
Anyway, we know who the stud pitchers are and no one is going to sniff aArrietat Arrieta or Strasburg on draft day.  But, how can we look more closely at pitching performance?  Last week, we picked apart the idea of luck among starters to see that “bad luck” is bad pitching.  It ties into a measure I read about but need to look at more closely:  the 1-2-3 inning. At the time of the article, Taijuan Walker was cast as a strong buy because he had a disproportionate number of 1-2-3 innings.

That would seem to be a good measure of dominance.  But, as we saw with the K:BB rate, not all aspects of pitching are equal.  When David Price and Chris Archer are not striking you out, they are pitching batting practice.  We might find similar Jekyll and Hyde stuff amidst the 1-2-3 innings data.  If those 1-2-3 innings are also high pitch count innings, your SP is not exactly dominating.  As well, he might be pitching BP in innings that aren’t 1-2-3.

Today I’m looking at measures of strength and efficiency.  What do we expect out of our stud SP?  We want them to go reasonably deep into games (at least 6 innings so they can get that QS trophy for participation).So we want high IP (OK.  At least 6) and high GS.  We want them to face few batters per inning (even though they should face a relatively high number of net batters because they are going deep into games).  And, we’d like them not to waste pitches.  There was never anything like a few 13 pitch rounds with the likes of Manny Ramirez in his heyday to get opposing SP deep into their pitch counts while your first beer was still cold. So we want them to have low pitches/batters faced (pibf) counts and low pitches per IP counts (pip).

I looked at the top 103 SP from Fangraphs as of Sunday, 15 May at 4 PM.  Here are their summary data:

Measure Mean Q1 Median Q3
BABIP 0.289 0.260 0.288 0.318
Starts (season) 7.3 7.0 7.0 8.0
IP (season) 44.3 40.1 43.2 48.1
TBF (season) 186.0 173.0 181.0 202.0
Pitches (season) 715.5 662.0 712.0 776.0
IP/Start 6.0 5.6 6.0 6.4
Batters faced/start 25.3 24.4 25.4 26.3
Pitches/start 97.3 93.5 97.1 101.1
Batters faced/ip (bfip) 4.2 4.0 4.2 4.4
Pitches/IP (pip) 16.2 15.2 16.3 17.1
Pitches/batters faced (pibf) 3.9 3.7 3.8 4.0

Q1 and Q3 are the interquartile ranges along with the Median.  We use the Median and the Mean to look at what constitutes “average” from two perspectives.  The mean is the mathematical average:  add the stats up and divide them by their number.  The mean is a great measure. But it can be skewed by outliers.  Q1, the median and Q3 refer to the points at which 25%, 50% and 75% of the values for a particular measure occur.

Ideally, the mean and the median will be equal.  If the mean is higher than the median, it indicates that there are some extremely high values. If it is lower, there are extremely low ones.

So, for example, BABIP is evenly balanced.  The mean and the median are essentially the same (0.288).  Starts (GS) is skewed a bit.  While we have 103 pitchers in the dataset, most pitchers have started 7 games.  Half of the SP in the dataset have 7 starts or fewer and half have 7 or more. So, the median is 7 GS.  But, those 42 pitchers with 8 starts artificially inflate the “average” number of starts to 7.3.


Starts Count
5 1
6 4
7 56
8 42
N= 103

OK. Enough Stats 101. Who are the most dominant, efficient pitchers in terms of high IP/Start, high GS, low batters faced per inning and low pitches per batter. If we look at the top 15 pitchers in terms of Innings Pitched Per Start (IPS), we see the following:

Name Team BABIP GS IPS bfip pip pibf
Clayton Kershaw Dodgers 0.271 8 7.75 3.63 13.48 3.72
Chris Sale White Sox 0.204 8 7.39 3.76 14.48 3.86
Dan Straily Reds 0.202 5 7.22 4.13 16.90 4.09
Johnny Cueto Giants 0.335 8 7.15 4.02 14.70 3.66
Jeff Samardzija Giants 0.288 8 7.01 3.99 15.42 3.86
Marcus Stroman Blue Jays 0.256 8 7.00 4.02 14.36 3.57
Jake Arrieta Cubs 0.203 8 7.00 3.73 14.39 3.86
Stephen Strasburg Nationals 0.301 8 6.88 3.96 14.84 3.74
J.A. Happ Blue Jays 0.277 7 6.87 3.97 14.18 3.57
John Lackey Cubs 0.260 7 6.87 3.87 14.18 3.67
Jordan Zimmermann Tigers 0.260 7 6.86 4.00 15.23 3.81
Matt Wisler Braves 0.197 6 6.85 4.04 14.04 3.48
Aaron Nola Phillies 0.248 8 6.63 3.83 14.26 3.72
Masahiro Tanaka Yankees 0.240 7 6.59 3.93 14.08 3.59
Noah Syndergaard Mets 0.316 7 6.59 3.95 14.79 3.75
Average of 103 SP   0.289 7.3 6 4.2 16.2 3.9

The numbers highlighted in bold indicate that a pitcher falls in the top 15 of each category.  Not one SP falls in the top 15 in all, though several make it in four of the five categories.  In general, we see that the SP going deepest into games generally are the most efficient in terms of batters faced per inning (see the following graph). This should come as no surprise.  If you are getting people out, you are doing well and you do not get pulled any earlier than necessary.

Scatterplot of bfip vs IPS

The relationship between IPS and PIP is similar, though not as tight.  In both graphs, the two points in the lower right hand corner are Kershaw and Sale.  Both go deep into games and see the fewest batters per inning and waste the fewest pitches.  They are models of efficiency.  But, based on these data. Folks like Matt Wisler of the Braves and Marcus Stroman of the Blue Jays are worth noting.  They waste very few pitches per batter or inning pitched.  Wisler’s BABIP of 0.197 is otherworldly.  (He is owned in only 11% of Yahoo! leagues, by the way.)

In the graph below, though, we begin to see outliers.  Dan Straily sits high above the rest of the group.  He is not efficient.  Despite going deep into games, he throws a lot of pitches (16.9).


Scatterplot of pip vs IPS


What is interesting is that among the top 100 SP, there is not all that much of a difference in terms of BFIP and PIP.  Kershaw has the fewest BFIP with 3.62.  Wily Peralta has the most with 4.85.  That’s 33% more.  But, it does translate in more than one additional batter per inning. Kershaw throws 13.4 PIP and his fellow Angeleno Nick Tropeano leads with 18.8 (more than 5 additional pitches per IP).  In terms of net pitches, 5 may not seem to be a lot.  But it translates into more than 33% more than Kershaw and means that you will hit your 100 pitch threshold in 5 IP while Kershaw will last almost 8 IP.

Sometimes data surprise us.  Sometimes they do not.  The measures of pitching prowess show us little that we do not expect.  No secrets here:  the best pitchers are dominant because they are efficient.


(Click the RED link below to listen)

Major League Fantasy Baseball Radio Show: Join Corey D Roberts on Sunday May 15th, 2016 from 7-9pm EST for this week’s episode of the Major League Fantasy Baseball Radio Show. We are a live call in radio show so we encourage callers at 323-870-4395. Press 1 to speak with the host. Every week we will do a quick recap of Fr-Sat games, and a forecast of Monday through Thursday’s games.

Our guests this week are Marc Foster and Phil Weiss. Marc is a former writer with MLFS, a two-time MLFB champ, and frequent guest on the shows this year. Phil Weiss. Phil Weiss’s resume includes working as a CPA with a large public accounting firm as well as private industry (Fortune 500), specializing in international corporate tax planning. Chief Financial Analyst for Independent RIA.

Media Experience: Frequent guest on CNBC and Bloomberg television. Multiple appearances on Bloomberg radio, local and national radio. Regularly quoted in Wall Street Journal, Reuters, New York Times, AP,, local news, Financial Times

“You can find our shows on I-Tunes. Just search for Major League Fantasy Sports in the podcasts section. For Android users go to “Podcast Republic,” then download that app, and search for “Major League Fantasy Sports Show”

Unrepentant Red Sox fan and all things Boston. Deflategate was a joke. Boston Latin School is awesome. Harvard and Johns Hopkins alma maters... Besides that... Stanley D. and Nikki Waxberg Professor of Politics and Law at Washington and Lee University. Wrote for Ron Shandler's Shandler Park for two summers and have been on board with MLFS since 2011. Been at Washington and Lee since 1990 with a brief hiatus (2010-2013) in the Middle East. Currently developing that last word in Fantasy Baseball analysis. Married to Flor, Dad to William and Alex, and adopted daughter Reem. Soon to be father and law to Meaghann. Alpha male to the world's super-pup, Humphrey. Life is not bad.

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  1. Pingback: Moonlighting: Reflections on 2016 Baseball Analysis « Mark Rush

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