Navigation: Jump to content areas:


Pro Quality. Fan Perspective.
Login-facebook
Around SBN: The End Of Sabanball: Details, Barbarians, And Precision

Plate Discipline Meltdown: A better way to project walk rate?

ST. PETERSBURG - JULY 27:  Designated hitter Willy Aybar #16 of the Tampa Bay Rays gets out of the way of this pitch against the Detroit Tigers during the game at Tropicana Field on July 27 2010 in St. Petersburg Florida.  (Photo by J. Meric/Getty Images)

The importance of walking has finally become widely accepted. Given the obvious benefits of a walk (more baserunners means more runs) it's surprising that it took so long, but now even Jeff Francoeur has changed his stance from the infamous "If OBP is important, then why don't they put it up on the scoreboard?" to a much less mock-worthy "If I can mix in 50-60 walks, I become a totally different guy".

The Rays are, somewhat surprisingly, the current league leaders in BB% at 10.6%, fueled by otherworldly walk rates from our catchers (15.5% for Jaso and 14.6% for Shoppach) and by Carlos Pena's and Ben Zobrist's strong walk propensities. We can, however, get a better idea of what's to come in terms of future walk rates if we dig a little deeper into the underlying stats.

Star-divide

It's no surprise that plate discipline statistics correlate well with a player's walk rate. It's logical: the less you chase pitches, the less strikes you see, and the better you are at making contact, the more you're going to walk. A multi-variable regression gives a somewhat messy looking formula, but also gives us a player's expected walk rate:

xuBB%*=0.5439-0.378*OSwing-0.034*Zswing-0.009*Ocontact-0.13*Zcontact-0.441*Zone

*We're looking at uBB% (unintentional walk rate) for this article. Intentional walks, while a repeatable skill, aren't telling of a player's plate discipline.

The correlation between this and uBB% is .81 for this year's hitters so far.

Xubb_vs_ubb_medium

A few things jump out from this equation. First is the low value of the O-contact's coefficient. This makes sense, as making contact on pitches outside the zone prevents a strikeout, but doesn't help you on the way to a walk. Similarly, the fairly low value of the Z-swing coefficient also makes sense, as swinging at pitches inside the zone is more likely to lead to a hit than a walk.

The two biggest coefficients are also expected relationships. Ever wonder how Carlos Pena gets so many walks even though he swings (and misses) at so many pitches that other players get hits on? It's because of his tiny Zone% (percentage of pitches received in the zone). How about John Jaso's god-like walk numbers? A result of him getting less pitches in the zone than Evan Longoria. Getting pitches outside of the zone and not chasing those pitches is a recipe for success both in terms of walking and just pure hitting.

Name O-Swing%Z-SWing%O-Contact%Z-Contact%Zone%2010 xuBB2009 uBB2010 uBBxuBB-uBB
Carl Crawford 34.50% 69.70% 74.80% 87.20% 44.40% 7.42 7.44 7.28 0.14
Gabe Kapler 27.80% 61.90% 78.10% 91.60% 48.60% 7.76 11.76 8.10 -0.34
Willy Aybar 27.80% 60.30% 73.80% 89.50% 45.90% 9.32 9.52 7.20 2.12
Dioner Navarro 32.20% 60.60% 70.80% 95.00% 49.50% 5.37 4.15 9.10 -3.73
B.J. Upton 24.80% 67.80% 54.90% 79.50% 50.30% 9.73 9.10% 11.10 -1.37
Ben Zobrist 24.90% 51.90% 71.80% 91.40% 44.70% 11 14.52 13.40 -2.4
Jason Bartlett 22.30% 61.00% 63.40% 90.50% 48.00% 10.41 9.17 9.54 0.87
Reid Brignac 42.10% 67.90% 75.60% 85.20% 43.90% 5.08 3.20% 5.58 -0.5
Carlos Pena 28.80% 71.50% 51.00% 81.00% 42.00% 11.59 13.33 14 -2.41
Evan Longoria 25.10% 63.50% 64.00% 86.60% 48.10% 9.72 9.09 10.02 -0.3
John Jaso 17.50% 54.90% 73.00% 93.00% 45.00% 13.34 N/A 15.13 -1.79
Sean Rodriguez 32.00% 63.50% 59.70% 78.90% 52.30% 6.31 N/A 2.80 3.51
Matt Joyce 19.90% 63.70% 73.00% 76.70% 42.10% 15.53 N/A 17.60 -2.07

This table has all of the players who have 100+ PA this year (and Matt Joyce). The correlation between '09 and '10 for the guys who had a reasonable number of plate appearances both years is .51 (R^2=25.8%). That signifies a moderately strong relationship. Using the component-based plate discipline stats to compare this year's numbers with the expected numbers gives a correlation of .77 (R^2=59.7%). This means there's a fairly strong relationship between a player's expected uBB% and their actual uBB%, and certainly a stronger one than with 2009's numbers. While the xuBB%s are hardly perfect, they're more revealing about what we can expect than previous years.

A few random observations:

  • It looks like Willy would do well with more at bats; his BB% is a full 2 points lower than what we'd expect.
  • Navi's improved plate discipline appears to have been a trick of the light.
  • xuBB says Zobrist can't keep up this rate of walking, but given that last year and his minor league track record strongly disagree, maybe he's good at situational swinging?
  • It's kind of relieving to see that something suggests that Sean's BB% will rise. All the foul bunts might be skewing his xuBB% though.
  • John Jaso's still smelling like roses; even a 13.3 BB% would put him above Joe Mauer.
  • Matt Joyce is a destroyer of worlds.

Comment 24 comments  |  4 recs  | 

Do you like this story?

Comments

Display:

Welcome to the front page.

And interesting read.

As you can always expect come from behind victory is when you least expect it.

by Buc Wild on Jul 30, 2010 12:18 PM EDT reply actions  

Awesome stuff and another excellent edition to the staff

www.draysbay.com, www.bloombergsports.mlblogs.com, Twitter @trancel

by Tommy Rancel on Jul 30, 2010 12:25 PM EDT via mobile reply actions  

edition

As you can always expect come from behind victory is when you least expect it.

by Buc Wild on Jul 30, 2010 12:40 PM EDT up reply actions  

I have an agenda. Deal with it.

www.draysbay.com, www.bloombergsports.mlblogs.com, Twitter @trancel

by Tommy Rancel on Jul 30, 2010 12:57 PM EDT via mobile up reply actions  

Great first post!

Looking forward to many more, Pbender Gbending Prodriguez!

Excuse the ignorance, but what’s “Zone” (the last term in the equation)? Is that related to the size of the player’s strike zone or something?

by mattc286 on Jul 30, 2010 12:48 PM EDT reply actions  

Ah, that makes sense.

So of course more pitches out of the zone would be the biggest factor in xuBB%.
One more question: sometimes a walk can be the result of a pitcher missing what he meant to be strikes, falling behind in the count, and choosing to pitch around him instead. Do these fall into “unintentional” or “intentional”, because they ARE an indicator of plate discipline (at least the first few pitches), but the later pitches are more the pitcher’s “fear” of that hitter. Like if a guy gets a walk on 4 balls, perhaps the first 2 or 3 were unintentional and the last one or two intentional to get to the next batter. So it’s kind of like “semi-intentional”… Is that ignored?

by mattc286 on Jul 30, 2010 1:31 PM EDT up reply actions  

Zone% isn't an exact value

It also varies somewhat from year to year, but it’s more stable than BB%, and it (combined with these other plate discipline stats) are a better predictor of BB% going forward than BB% thus far.

The event you’re mentioning here is something that gets accounted for by large samples (and probably evens out between hitters in the long-run).

by PGP on Jul 30, 2010 1:37 PM EDT up reply actions  

Couple of thoughts/questions

Very interesting analysis.

Can you put up a correlation matrix between the inputs to your regression?

I want to say that Zone% is not really under control of the batter but is really a function of their chase rate (O-Swing%) and contact rate in the zone (Z-Contact%). I figure if a batter makes great contact in the zone, pitchers will be wary of going there, and obviously if you have a chaser you would rather throw them balls than strikes. Since Zone is the largest coefficient, if it is highly correlated with those variables then it may be masking the underlying drivers.

by david_a on Jul 30, 2010 12:54 PM EDT reply actions  

To be honest I have no clue how to make a correlation matrix easily

Here’s a few correlations for you to look at though:
ISO: .47
O-swing: -.253
Z-Swing:
.47
O-contact: .34
Z-contact: .36

It looks like ISO and Z-Swing are the biggest impacts (correlation between things like BA and SLG was weak)

by PGP on Jul 30, 2010 1:05 PM EDT up reply actions  

ISO: -.47
Oswing: -.253
ZSwing: -.47
Ocontact: .34
Zcontact: .36

by PGP on Jul 30, 2010 1:06 PM EDT up reply actions  

Congrats Bender, always enjoyed your insight

Did this come out to be statistically significant? A P-Value or t-statistic would be an easy test. Also, what were your standard errors?

And if one has a problem using stats to prove a point, then use your eyes.

2010 Trade Deadline Primer --> http://dockoftherays.com/2010/07/03/2010-trade-deadline-primer/

by Sandy Kazmir on Jul 30, 2010 1:11 PM EDT reply actions  

P-Value was 2.89*10^-19

I think it’s safe to say it’s statistically significant.

SE=.0206

by PGP on Jul 30, 2010 1:28 PM EDT up reply actions  

Uhh yeah, that worked out nice.

Just to make sure I’m reading that right, then the range of, say, Craw’s xuBB% 5.4% – 9.4% or would it be 7.2% – 7.6% within the first SD?

And if one has a problem using stats to prove a point, then use your eyes.

2010 Trade Deadline Primer --> http://dockoftherays.com/2010/07/03/2010-trade-deadline-primer/

by Sandy Kazmir on Jul 30, 2010 1:47 PM EDT up reply actions  

"Please welcome our another new writer"

If John Jaso somehow strikes out, it means you didn’t do your job right as an umpire.
by raysrule44 on Jul 9, 2010 8:37 PM CDT

by Vin on Jul 30, 2010 1:26 PM EDT reply actions  

Got it.

I love Casey Fossum. Now try and take me seriously.

by Steve Slowinski on Jul 30, 2010 1:35 PM EDT up reply actions  

Also, I look forward to seeing more of your work.

It’s good stuff.

If John Jaso somehow strikes out, it means you didn’t do your job right as an umpire.
by raysrule44 on Jul 9, 2010 8:37 PM CDT

by Vin on Jul 30, 2010 1:28 PM EDT reply actions  

Good work, Pretty much the exact same thing I did last year for pitchers and their strikeout and walk rates

What data did you use to get your formula? (pardon me if I missed this)

Did you test this on out of sample data?

Go Gators!!

by matthan on Jul 30, 2010 2:03 PM EDT reply actions  

I'm pretty sure I used 09s information

I tested it on this year’s numbers for the rays hitters I guess

by benderbrodriguez on Jul 30, 2010 2:48 PM EDT via mobile up reply actions  

Just what we need, another MVB apologist on the staff

nice analyses :)

Longo! (Ah-a-ah!) Fighter of the Upton! (Ah-a-ah!) Champion of the Rays! He's the master of batting and defense for everyone!

by pudieron89 on Jul 30, 2010 2:43 PM EDT reply actions  

Cool stuff

Also, I agree that its encouraging to see that there’s reason to hope that Sean’s walk rate will improve, as he’s got to figure that out if he wants to ever become an above-average hitter.

by Matt Slowinski on Jul 30, 2010 2:50 PM EDT reply actions  

Well it can't get any worse. I'm fine with it, he struggled early when he was taking tons of pitches

The aggressiveness helped him during his hot streak (or was it all the lefties). Now he needs to find the middle ground.

And if one has a problem using stats to prove a point, then use your eyes.

2010 Trade Deadline Primer --> http://dockoftherays.com/2010/07/03/2010-trade-deadline-primer/

by Sandy Kazmir on Jul 30, 2010 3:25 PM EDT up reply actions  

Comments For This Post Are Closed


User Tools

Founded in 2005, DRaysBay is home to, "Progressive statistical analysis and reasoned argument."

Please read our Community Guidelines.

FanPosts

Community blog posts and discussion.

Recommended FanPosts

Small
Zobrist vs Pedroia vs Cano
Scaled_php_small
Rays Community Prospect #31 Runoff

Recent FanPosts

Small
Joe Maddon Town Hall meeting on the Ron and Ian show. Any ideas for questions I should ask?
Scaled_php_small
Rays Community Prospect #37
Scaled_php_small
Rays Community Prospect #35
Scaled_php_small
Rays Community Prospect #34
Scaled_php_small
Rays Community Prospect #33
Scaled_php_small
Rays Community Prospect #32
Scaled_php_small
Rays Community Prospect #31
Scaled_php_small
Rays Community Prospect #30 (Again)

+ New FanPost All FanPosts >

FanShots

Quick hits of video, photos, quotes, chats, links and lists that you find around the web.

Recent FanShots

Jeff Bagwell, Fred McGriff, The Hall of Fame, and 400 Home Runs
ESPN Chat with Matt Moore
Danny Clyburn: 1974-2012
Joe Maddon Town Hall Contest
Hickey said as of now all of the starters -- Wade Davis, Jeff Niemann,...
White Sox sign Dan Johnson
Indians acquire Canzler
Justin Ruggiano to Elect Free Agency
Dougdirt over at MinorLeagueBall compiled John Sickels' rankings with WAR values from Victor Wang's research.

Thread here.
The increasingly desperate search for offense has caused some teams to...

+ New FanShot All FanShots >

DRB Fantasy Baseball

Friends of the Site

DRB Suggestion Box

Drb4_medium


Managers

Slowsky__1__small Steve Slowinski

Dad_small Jason Collette

Brad_small BWoodrum

Price_small Erik Hahmann

Analysts

Lob-city_design_small rglass44

Untitled_small EminenceFront

Small Mulva

Rutg_uakjmedjwh9ndzd4lkll_small Imperialism32

100_1952_small MrNegative1

Steak-with-crown_small CBJones

Whelk_small Whelk

Small PGP

Scaled_php_small mr. maniac

Tampa_theatre_small jcmitchell

Me_small John Gregg