A Closer Look at September Numbers
The OP posted by dtoddwin the other day got me thinking about September numbers. How much different from the rest of the season are they? Can we treat them like other number sets, or do we have to adjust them? This is not an exhaustive study, just something to scratch the surface. If there is interest, maybe I can look into this a little deeper, but I think that what I found is at least interesting. I realize that his comes with small sample size issues.
My first thought was to look at the monthly OPS numbers for Pujols. I figured, if anyone can take advantage of AAAA pitching, it would have to be Pujols. Over the past 3 years, his OPS has actually dipped in the last month of the season, with August showing the largest spike and July showing the biggest drops.
It looks like, if there is a September boost, Pujols is not a beneficiary. Maybe, to him, all pitchers are AAAA, so there is not much of a difference. So, what about hitters that profile generally like Pedro. I took corner infielders with high K tendencies who have most of their value from power, not average. I also wanted to keep it in the NL. I came up with 5 names: Ryan Howard, Prince Fielder, Marc Reynolds, Aramis Ramirez, and Adam LaRoche. I include LaRoche especially because of his reputation for early season struggles and late season success. If anyone would feast on the lesser competition of September call-ups, I figured it would be LaRoche.
|
Year |
Season |
Sept/ Oct |
Dif |
Year |
Season |
Sept/ Oct |
Dif. |
|||
|
Ryan Howard |
2010 |
0.859 |
0.939 |
0.08 |
Aramis Ramirez |
2010 |
0.745 |
0.794 |
0.049 |
|
|
2009 |
0.931 |
0.972 |
0.041 |
2009 |
0.905 |
0.871 |
-0.034 |
|||
|
2008 |
0.881 |
0.852 |
-0.029 |
2008 |
0.898 |
0.951 |
0.053 |
|||
|
Prince Fielder |
2010 |
0.871 |
0.763 |
-0.108 |
Adam LaRoche |
2010 |
0.788 |
0.595 |
-0.193 |
|
|
2009 |
1.014 |
1.045 |
0.031 |
2009 |
0.843 |
0.844 |
0.001 |
|||
|
2008 |
0.879 |
0.998 |
0.119 |
2008 |
0.841 |
1.065 |
0.224 |
|||
|
Marc Reynolds |
2010 |
0.753 |
0.291 |
-0.462 |
||||||
|
2009 |
0.892 |
0.61 |
-0.282 |
|||||||
|
2008 |
0.779 |
0.681 |
-0.098 |
|||||||
So what is the average change of OPS from the season average for these three?
|
Howard |
0.031 |
|
Fielder |
0.014 |
|
Reynolds |
-0.281 |
|
Ramirez |
0.023 |
|
LaRoche |
0.011 |
Again, not conclusive. Reynolds does worse, and everyone else gets slightly better, but nothing siginificant. Definitely not the difference I expected from September call-up.
There is one more thing I thougth to check. Last year, Pedro was a mid-year call up. What about the Septembers of some similar guys who were called up mid-year? Again I drew from the above criteria of corner infield and National League. Howard and LaRoche were both called up mid year. Fielder, Reynolds and Rameriz were not. I added GFJ to the mix. We are all familiar with his late season heriocs in his rookie year.
This looks more like what we expected. I don't know if there is something really here or not. It looks like some rookies do better in that last month. Maybe they are seeing some pitchers that they saw in AAA, so there is some familiarity. Maybe it is nothing. More work to be done on this. I hope this adds to the debate.
Go Bucs.
This is a FanPost and does not necessarily reflect the views of the managing editor (Charlie) or SB Nation. FanPosts are written by Bucs Dugout readers.
17 comments
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Without doing too much research
My impression is that the issue is overblown because 1) Most September callup pitchers don’t actually get all that many innings. 2) September callups generally aren’t taking innings away from elite pitchers, they’re taking innings away from guys who are marginally better than they are.
For instance, last year the Pirates promoted 4 pitchers after the rosters expanded on 1 Sept: Brad Lincoln, Steven Jackson, Brian Bass and Justin Thomas. Here’s what they did:
Lincoln: 2 IP, 9.00 ERA
Bass: 1 IP, 9.00 ERA
Jackson: 4.1 IP, 4.15 ERA
Thomas: 2.1 IP, 3.86 ERA
So on the 2010 Pirates, a team out of contention, September callups accounted for a little less than 3% of the teams’s innings pitched in Sep/Oct. Less than one complete game’s worth. Some other teams might use their callups a bit more, but I doubt that anyone is using September callups for more than 10% of the team’s innings. And again, a callup reliever like Steven Jackson isn’t going to take inings away from a really good reliever like Hanrahan or Meek, he’s most likely going to take innings away a guy who’s just a bit better than he is, like Karstens or someone like that.
There’s a probably an exhaustive study on the “September effect” in the THT archives or someplace like that if anyone is inclined to look.
A-HA!
Less than one complete game’s worth.
2 + 1 + 4.1 + 2.1 = 9.2! More than one game!
Therefore, your entire post and theory is negated.
;-)
Free your ass and your mind will follow.
by cocktailsfor2 on Apr 11, 2011 3:15 PM EDT up reply actions
Free your ass and your mind will follow.
by cocktailsfor2 on Apr 11, 2011 3:26 PM EDT up reply actions
Imma repost this
I think I added this to the other thread at about the time Woz put this up. May as well include it in this part of the discussion:
Look at all Qualified hitters, look at their September numbers.
I don’t have time to do any spreadsheetery, but here are the wOBA for each quartile, full season first:
Full Season September
99 %ile .447 .468
75 %ile .366 .375
50 %ile .340 .332
25 %ile .316 .293
1 %ile .248° .214°°
So what do you see? Exactly what you’d expect between any larger and smaller sample size – with a larger n, you get regression towards the mean, such that 50% of qualifying MLB hitters hit between .316 and .366 for the season, while the middle 50% in September ranged from .293 to .375 – an extra .033 of spread. But, if anything, the hitters were worse in September as a group. Maybe that’s fatigue, maybe that’s because I only looked at one year, but it’s really, really hard to argue that MLB regulars see a reliable and significant bump to their hitting numbers from facing AAAA pitching in September.
[Note: the samples are not identical; there are 11 more qualifying hitters for Sept than for the season as a whole, which reflects injuries, rested vets, and mid- and late-season callups. But we’re talking 149 guys in the full-season sample, the vast majority of whom would have had to qualify in Sept. to qualify for 2010 as a whole. I’m confident that these are largely the same players]
° Iszturis, worst in the league by .020
°° there’s actually a guy at .165, but he’s a really big outlier in a SSS, so hell with him°°°
°°° Aha! I’ve finally figured out a method for using asterisked notes that the software doesn’t translate into bullets.
by JRoth95 on Apr 11, 2011 4:23 PM EDT reply actions 3 recs
holy crap
Amazing work, JRoth! This a very simple, straightforward, and powerful example of regression to the mean. Very nice.
I think the OP’s conclusion (that there is no conclusion to be drawn) hits the nail on the head. You just don’t get any meaningful information from small sample sizes, and you don’t get any meaningful information from selectively excluding samples from your data set.
Good stuff
Another instance of selective memory supplemented by something that seems like it would make sense.
I think that if fatigue is a big issue, it may explain the younger guys with a bigger upswing. I wonder if we grouped by age, if there would be a noticeable difference. Even if there was, I can’t imagine that it would be significant. If it was significant, it may indicate that teams should rest vets more often. That’s getting the cart before the horse.
Again, good stuff.
by Wizard of Woz on Apr 11, 2011 4:36 PM EDT up reply actions
Another thing not mentioned yet
about just being the end of the season in general. I don’t think teams way out of it have much to play for. I don’t know how this changes things since there is no way to prove it even does but I’d have to say it affects the mental/psychological approaches of players/managers.
Nice work Woz.
Good post. I think the what I take from this is that September stats should be taken in contect when that is all you have to go on. For instance, they need to be contexualized when you are looking at a player called up in September when there is no other track record to go on. Since Pedro was not a Sept call up looking at just his Sept stats is less meaningful since there is a larger body of work to analyze.
I think this is the right conclusion
Perhaps if a guy’s only good month was Sept., but even then: if a guy has 3 dismal months then one good one, his overall numbers will probably look the same as what you get if you try to discount September. Not very good.
Since we don’t know how much to discount Sept., and whatever the correct discount is is evidently small, I don’t see any reason to do anything more than say, “X’s September numbers may be slightly inflated,” but otherwise take them at face value.
Yeah...
I guess I was trying to say that when a guy like Tike Redman gets called up for the first time in September and goes on tear it’s more important to contextualize his performance given their is nothing else to go on. In other words, don’t pencil him in as your everyday leadoff hitter for the following season and call him the most important player in the organization given he has only been in the league a short time and there really wasn’t a “book” on him for opposing pitchers to use.
BTW
If there’s a rigorous analysis out there, I’m certainly open to changing my conclusions. But this smells to me like a nugget of old-fashioned baseball wisdom that has somehow slipped into sabermetric convention without close examination. It makes intuitive sense, but that should really be a red flag for the statistically-minded, not a recommendation.
I haven’t found anything, though my search hasn’t been thorough. If I don’t find something, I am going to try to put together some data and see what come of it. With FanGraphs providing monthly splits, it shouldn’t be too difficult.
by Wizard of Woz on Apr 11, 2011 10:23 PM EDT up reply actions
Yeah
If I had time to extend the analysis I did, I’d do just 2 things: filter the lists to make sure we’re looking at the exact same players, and stretch the analysis over multiple years. I’d probably like to see the last 5 years, then a few other samples deeper into the past. Rosters are managed differently than they used to be, and it’s entirely possible that the CW used to be true, even if it isn’t now.
Thanks for clearly stating my feelings on the issue!
Everyone can be snookered by received wisdom occasionally. People need to remember that statistical analysis can be tricky.

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