Effect of the Home Run Derby on Second Half Performance (Pt.2)

In part 1, I looked at whether significant experience as an all-star or in HRD contributed to second half drops in performance.  Although it does, it's more likely that the inexperienced players are regressing to the mean after flukey first halves.

Here I want to look at whether the number of swings taken affects the second half drop off, to the extent there is one.  The swing counts are approximate, based on 10 outs per round and some info I found about "swing offs" and abbreviations (like when Josh Hamilton in 2008 quit swinging in the second round after 4 outs, because he had already advanced to the finals).

Of the 79 participants in the set, 39 took fewer than 20 swings.  These are pretty much the folks who bow out after the first round.  So that's one "tier".  There are no obvious breaks in the number of swings among the remaining 40 players, so I set the second tier at 21-41 swings, and the third tier at more than 41.  That also happens to give me 20 players in each of the final two tiers.

First tier (0-20 swings):


This group had a higher K% in the second half by 1.5%, lost 44 points of OPS, lost 34 points of ISO and had a reduced HR/Contact% by 1.1%.  BABIPs rose by only 6 points.

Second tier (21-41 swings):


This group had a higher K% in the second half by 0.6%, lost 21 points of OPS, lost 16 points of ISO and had a reduced HR/Contact% by 1.0%.  BABIPs rose by only 4 points.


Third tier (42+ swings):

This group had a higher K% in the second half by 0.9%, lost 25 points of OPS, lost 12 points of ISO and had a reduced HR/Contact% by 0.2%.  BABIPs fell by 4 points.


Conclusions:


Well I know what it doesn't mean.  The HRD does not wear out players.  The guys who took the most swings have negligible reductions in their stats that are consistent with what we found "experienced" players experienced in the second half.  And in many cases, the guys with more swings have less of a drop in the second half; and as explained below, some of them get significantly better.

Moreover, the middle group feels the impact in the second half less than those who take fewer swings in Tier 1.  Swinging more in the HRD is not adversely affecting second half performance.

What's most interesting is that the Tier 1 players have stat reductions in the second half that look almost identical to the stat reductions for the significantly inexperienced all-stars discussed in my first post!  Yet of the 39 players in Tier 1, only 21 fall into the inexperienced category.  It's almost an even split in Tier 1 among experienced and inexperienced players.  (For comparison, 60% of the players in Tier 2 are experienced by my filter, and 50% in Tier 3).  Moreover, the second half differentials for the experienced group in Tier 1 and the inexperienced group in Tier 1 are pretty much the same:  OPS, ISO and BABIP changes are within 1 or two points for both.

Does it get into the Tier 1 group's head that they didn't do so hot in the HRD?  If that's the explanation, you would think the experienced Tier 1 players would shake it off better; but that's not what the numbers say.

Or is it physical/mechanical:  that is, taking fewer hacks trying to hit homers is more likely to mess up your swing than taking more. Maybe taking more swings makes it more likely that your altered mechanics at the beginning of the HRD resolve to your natural rhythm by the time you've taken at least 20 hacks.  And maybe only taking 15 home run swings is just enough to throw you off, but not enough to get you back in rhythm.

The impact is still pretty small, but it seems likely that those who don't make the semis will be more affected than those who do.

Despite all that Tier 1 talk, the worst subset to be in is the inexperienced player taking more than 41 swings (Tier 3).  Those players had their K% jump 2.9% in the second half, lost 32 points of OPS, 37 points of ISO and 1.4% shaved off their HR/Contact%, and those numbers are with a boost in BABIP of 18 points!

By contrast, the experienced players in Tier 3 are the most stable.  They shave off 2% points from their K%, increase OPS by 177, increase ISO by 104 and increase HR/Contact% by 4.3%!  Some of that is because of a BABIP boost of 14 points (and a small sample size...there are only 10 of them).

If you play fantasy baseball, odds are that you won't dump any experienced player just because of HRD.  But if you have an inexperienced player who had a hot first half, made the All-Star team and is participating in HRD, you might be a little worried.  Based on these numbers, ideally those guys (Hart, Swisher and Young) make it past the first round and lose in the semis.  The worst thing that can happen is for those guys to make the finals and take a bunch of swings (think Bobby Abreu and Garret Anderson).

For the experienced players, the further they go in the HRD, the better off you'll be.  :)

Effect of the Home Run Derby on Second Half Performance (Pt.1)

There's a lot on the Web today about whether participation in the All-Star Home Run Derby (HRD) affects second half performance (theoretically, by messing up the player's swing).  Many have commented that the second half performances are just regression to the mean, because players who make the all-star team are often already playing over their heads.

The bloggers at Pinstripe Alley, a Yankee fan blog, looked at the first and second half OPS of all HRD participants since 2000 (except IRod in 2000 because he barely played in the second half).  Their conclusion was that the OPS dropped .042 points, which they described as "not huge".

I wanted to slice the numbers a little differently, using essentially the same data set that Pinstripe Alley used.

I wondered whether HRD participants with significant all-star game or HRD experience were affected differently than inexperienced players.  I categorized experienced players as those who, at the time of the HRD appearance in question, had made the all-star team at least twice before or had participated in an official HRD before.  Of the 79 players in the data set, 40 were experienced using that filter, and 39 were not.  That worked out pretty nicely.  :)

I used 5 stats:

Strikeout percentage (SO/AB):


Experienced players had their K% increase from 19.2% to 19.9% in the second half, for a 0.7% increase.  A difference not worth commenting on further.

Inexperienced players had their K% increase from 20.3% to 21.8% in the second half, for a 1.5% increase.  It's not a huge difference from first half to second half, but the difference is twice as large as for experienced players.

OPS (OBP+SLG):

Experienced players had their OPS decrease from 1.011 to .987 in the second half, for a .024 decrease.  That's not a big difference.

Inexperienced players had their OPS decrease from .956 to .913 in the second half, for a .043% decrease.  Again, not a huge difference from first half to second half, but the difference is almost twice as large as for experienced players.

I also wondered how much OPS was affected by high first half BABIPs and regression to the mean in the second half.  As an average, neither group had a significant BABIP change from first half to second half.

Nine (9) of the experienced players had their OPS drop 100 points or more, and five (5) of those had their BABIPs drop 25 points or more.  By contrast, fifteen (15) of the inexperienced players had their OPS drop 100 points or more, and nine (9) had their BABIPs drop 25 points or more.  So inexperienced players were hit more dramatically, but essentially the same percentage had significant BABIP adjustments as a contributor.

Five (5) of the experienced players had their OPS rise 100 points or more, and three (3) of those had their BABIPs rise 25 points or more (and the other two had rises of 14 and 19 points).  Only three (3) of the inexperienced players had their OPS rise 100 points or more, and all of them had a rise in BABIP of 25 points or more.

BABIP seems to be a partial explanation for significant drops in OPS in the second half, but seems to be a more significant factor to significant OPS gains in the second half.

ISO (SLG-AVG):

Experienced players had their ISO decrease from .293 to .279 in the second half, for a 14 point decrease. No big deal.

Inexperienced players had their ISO decrease from .277 to .243 in the second half, for a 34 point decrease.  More significant, but again, the difference is two and a half times as large as it is for experienced players.

BABIP:

Neither group experienced a significant change in BABIP.  The inexperienced players actually got a little 5 point BABIP bump in the second half.  Both groups started with substantially equivalent BABIPs.  See note above under OPS.

HR/Contact Percentage (HR/(AB-SO)...essentially, how many balls contacted flew out of the park):

Experienced players had their HR/Contact% decrease from 9.3% to 9.0% in the second half, for a .3% decrease. No significance at all.

Inexperienced players had their

HR/Contact% decrease from 8.7% to 7.2% in the second half, for a 1.5% point decrease.  That strikes me as more notable, but again the most glaring difference is that the change is five times bigger than for experienced players.  

Conclusion

One could conclude from the numbers above that the effect on second half performance is not tremendously significant for any HRD participant, and is basically non-existent for the players I've named as "experienced."

On the other hand, the difference between "experience" and "inexperience" is probably just regression at work.  Consider that everyone in the experienced data set was appearing in at least their third all-star game, with one exception of a player who participated in HRD twice before ever making his third all-star appearance.  So for the most part, these guys are true all-stars and less likely to be in the game because of a statistical fluke.  

The so-called inexperienced players have more trouble in the second half because their first half performances were surprises.  Brandon Inge in 2009's HRD was the best example.  He went from having the best first half of his life, to being literally one of the worst hitters in MLB during the second half (how do you like a OPS of 541?).

It's not that all-star game or HRD experience makes a player seasoned enough to not let his swing get screwed up by HRD. It just means those are the really good players -- the perennial all-stars -- who naturally have more consistency.  After all, the first half numbers of experienced players are better than the inexperienced players across the board...lower K%, a full 60 points better on OPS, 16 points better on ISO and a higher HR/Contact %.

I have a quick part 2 to post, because I also sliced the data by the number of swings the player took in the HRD.  To come...