Daily Notes: How Last Spring’s Pitching Laggards Fared

Table of Contents
Here’s the table of contents for today’s edition of the Daily Notes.

1. How Last Spring’s Pitching Leaders Fared (Amended)
2. How Last Spring’s Pitcher Laggards Fared

How Last Spring’s Pitching Leaders Fared (Amended)
In yesterday’s edition of the Notes, we considered how the top-10 pitchers from last spring — according to the SCOUT leaderboards, that is — how those pitchers ended up faring during the 2012 regular season.

While it’s manifestly the case that the author has little idea what he’s doing, it’s also the case that he knew even less of what he was doing when he published the final spring-training SCOUT pitching leaderboards last April, or whenever. In the meantime, I’ve made some slight changes to SCOUT that correlate directly to my increased understanding of how to use certain functions in Excel.

Recalculating pitching SCOUT from last spring, then, using the benefit of More Knowledge, here are the top-10 pitchers by that measure:


Name Team SCOUT- —— G GS IP TBF K% BB% GB% ERA- FIP- xFIP- WAR
Zack Greinke - – - 74 —— 34 34 212.1 868 23.0% 6.2% 49.2% 88 79 80 5.1
Francisco Liriano - – - 74 —— 34 28 156.2 693 24.1% 12.6% 43.8% 128 103 100 1.8
Roy Halladay Phillies 80 —— 25 25 156.1 646 20.4% 5.6% 44.7% 114 94 92 2.5
Cory Luebke Padres 84 —— 5 5 31 130.0 17.7% 6.2% 47.9% 72 78 100 0.7
Matt Cain Giants 84 —— 32 32 219.1 876 22.0% 5.8% 37.4% 74 91 98 3.8
Chris Sale White Sox 84 —— 30 29 192.0 772 24.9% 6.6% 44.9% 71 75 78 4.9
Felix Hernandez Mariners 84 —— 33 33 232.0 939 23.8% 6.0% 48.9% 80 73 77 6.1
Madison Bumgarner Giants 84 —— 32 32 208.1 849 22.5% 5.8% 47.9% 89 94 88 3.4
Yu Darvish Rangers 84 —— 29 29 191.1 816 27.1% 10.9% 46.2% 89 74 85 5.1
Andrew Cashner Padres 84 —— 33 5 46.1 196 26.5% 9.7% 53.3% 117 99 79 0.3
Average   82 —— 29 25 165 679 23.2% 7.5% 46.4% 92 86 88 3.4

Some different names populate this version of top-10 list than yesterday’s, but the idea is roughly the same: these pitchers were better than other pitchers last spring, for the most part, at striking batters out. They were also pretty good at striking batters out during the regular season, too. Because recording strikeouts also correlate rather highly to run prevention, these pitchers were also pretty good at doing that, too.

How Last Spring’s Pitcher Laggards Fared
Below are the 10 pitchers from the bottom of last spring’s SCOUT pitching leaderboard. SCOUT- combines regressed strikeout and walk rates in a kwERA-like equation to produce a number not unlike ERA-, where 100 is league average (in this case, for all spring pitchers) and below 100 is better than average. xK% and xBB% stand for expected strikeout and walk rate, respectively.


Name Team SCOUT- —— G GS IP TBF K% BB% GB% ERA- FIP- xFIP- WAR
Josh Collmenter Diamondbacks 118 —— 28 11 90.1 375 21.3% 5.9% 37.4% 88 95 100 1.0
J.A. Happ - – - 117 —— 28 24 144.2 627 23.0% 8.9% 44.0% 121 102 99 1.8
Chris Narveson Brewers 117 —— 2 2 9.0 41 12.2% 9.8% 38.7% 177 158 130 -0.1
Kevin Correia Pirates 116 —— 32 28 171.0 728 12.2% 6.3% 51.2% 110 117 111 0.9
Jhoulys Chacin Rockies 116 —— 14 14 69.0 314 14.3% 10.2% 38.5% 99 116 130 0.5
Jeremy Guthrie - – - 115 —— 33 29 181.2 788 12.8% 6.4% 40.8% 109 118 118 1.0
Wandy Rodriguez - – - 114 —— 34 33 205.2 875 15.9% 6.4% 48.0% 97 103 105 2.5
Jason Marquis - – - 114 —— 22 22 127.2 561 16.2% 7.5% 52.5% 137 135 101 -0.2
Tim Stauffer Padres 114 —— 1 1 5.0 24 20.8% 12.5% 53.3% 148 152 104 0.0
Average   116 —— 22 18 112 481 16.5% 8.2% 44.9% 121 122 111 0.8

Notes
• It’s important to begin by recognizing that, because SCOUT- features regressed strikeout and walk rates, this is not merely a list of the 10 worst performances from last spring (or nine, technically, because other laggard Mark Hamburger made zero major-league appearances), but rather the 10 worst performances by pitchers who were permitted to throw a relatively substantial numbers of innings. None of the pitchers here threw fewer than 10 innings, or faced fewer than 44 batters.

• While the top-10 pitchers by SCOUT from last spring went on to post a collective regular-season park-adjusted ERA about 8% lower than league average, this group posted one about 21% higher than league average during the regular season.

• Also of note: while this group of laggards did not feature a regular-season walk rate much worse than the leading group, their collective strikeout rate was ca. 7 percentage points worse. This make sense: because strikeout rate becomes reliable in smaller samples than walk rate, it more greatly informs SCOUT-. That the group of leaders would go on to outproduce the laggards by strikeout rate in the regular season, too, is perhaps not surprising.




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Carson Cistulli occasionally publishes spirited ejaculations at The New Enthusiast.


4 Responses to “Daily Notes: How Last Spring’s Pitching Laggards Fared”

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  1. dbake005 says:

    I think I’m having a hamburger and a good laggard for lunch

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  2. Price enforcer says:

    Could you, would you post this springs laggards with a goat?

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  3. RL says:

    The real question isn’t how well or badly the top-10 and bottom-10 spring training pitchers do in the regular season–we could pick any similarly small sample during the regular season and the top-10 performers from that sample would be much better than the bottom-10 performers.

    To get any useful information out of this kind of analysis, I think you would have to do one of two things:
    1. You could compare the predictive power of spring training stats with similarly small sample sizes during the regular season.
    2. You could look at the poor performers from spring training that performed very well the previous regular season and the top performers in the spring that were very poor in the previous regular season. If these pitchers’ spring stats were predictive of a decline or improvement, then spring training stats mean something. If not, not.

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  4. Jaker says:

    Great stuff. I’ve been waiting to see someone analyze spring SCOUT for its predictive ability. I suspect it will be able to better predict pitching performance than hitting. Would be nice if someone could run a correlation with spring SCOUT and season ERA-, FIP-, WAR, etc.

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