Derby Curse? Nah
Another reader requested piece today: testing the myth (or is it) of homerun derby participants changing their approach and suffering second half regresses.
Taking the combatants from 1998 through 2007 (84 total) I looked up their first half and second half OPS (with help from user SaberToothedPie) to see if the players really did suffer a let down post derby. Why not homeruns? Because for one the games are disproportioned and 15 homers in the second half is actually more impressive than 15 in the first half on a rate scale. Hitters also can have their ratios like HR/FB% regress or progress, meaning homeruns just even out over the 162 game season. Instead we're looking at an outline of their entire offensive performance, or at least a summed up version.
| Year | Player | PreASBOPS | PostASBOPS | NET | W |
| 2007 | Morneau | 0.944 | 0.702 | -0.242 | |
| 2007 | Ordonez | 1.05 | 1.004 | -0.046 | |
| 2007 | Rios | 0.87 | 0.831 | -0.039 | |
| 2007 | Guerrero | 0.962 | 0.935 | -0.027 | W |
| 2007 | Fielder | 0.996 | 1.034 | 0.038 | |
| 2007 | Howard | 0.933 | 1.016 | 0.083 | |
| 2007 | Holliday | 0.964 | 1.073 | 0.109 | |
| 2007 | Pujols | 0.886 | 1.097 | 0.211 | |
| 2006 | Wright | 0.961 | 0.844 | -0.117 | |
| 2006 | Dye | 1.043 | 0.965 | -0.078 | |
| 2006 | Cabrera | 0.998 | 0.998 | 0 | |
| 2006 | Tejada | 0.871 | 0.886 | 0.015 | |
| 2006 | Glaus | 0.859 | 0.879 | 0.02 | |
| 2006 | Berkman | 1.011 | 1.078 | 0.067 | |
| 2006 | Ortiz | 0.996 | 1.121 | 0.125 | |
| 2006 | Howard | 0.932 | 1.259 | 0.327 | W |
| 2005 | Abreu | 0.955 | 0.787 | -0.168 | W |
| 2005 | C. Lee | 0.864 | 0.747 | -0.117 | |
| 2005 | I. Rodriguez | 0.761 | 0.697 | -0.064 | |
| 2005 | A. Jones | 0.93 | 0.911 | -0.019 | |
| 2005 | Choi | 0.777 | 0.814 | 0.037 | |
| 2005 | Ortiz | 0.982 | 1.024 | 0.042 | |
| 2005 | Teixeira | 0.93 | 0.982 | 0.052 | |
| 2005 | Bay | 0.93 | 0.998 | 0.068 | |
| 2004 | Blalock | 0.941 | 0.743 | -0.198 | |
| 2004 | Thome | 1.059 | 0.868 | -0.191 | |
| 2004 | Sosa | 0.939 | 0.777 | -0.162 | |
| 2004 | Bonds | 1.421 | 1.421 | 0 | |
| 2004 | Tejada | 0.887 | 0.902 | 0.015 | W |
| 2004 | Berkman | 1.008 | 1.024 | 0.016 | |
| 2004 | Palmeiro | 0.771 | 0.825 | 0.054 | |
| 2004 | Ortiz | 0.954 | 1.021 | 0.067 | |
| 2003 | Edmonds | 1.066 | 0.864 | -0.202 | |
| 2003 | Boone | 0.963 | 0.815 | -0.148 | |
| 2003 | Anderson | 0.943 | 0.807 | -0.136 | W |
| 2003 | Delgado | 1.053 | 0.965 | -0.088 | |
| 2003 | Giambi | 0.966 | 0.898 | -0.068 | |
| 2003 | Pujols | 1.121 | 1.084 | -0.037 | |
| 2003 | Sheffield | 1.019 | 1.028 | 0.009 | |
| 2003 | Sexson | 0.889 | 0.98 | 0.091 | |
| 2002 | Konerko | 0.949 | 0.743 | -0.206 | |
| 2002 | Berkman | 1.053 | 0.901 | -0.152 | |
| 2002 | Sosa | 1.059 | 0.911 | -0.148 | |
| 2002 | Hunter | 0.911 | 0.78 | -0.131 | |
| 2002 | Sexson | 0.882 | 0.847 | -0.035 | |
| 2002 | Giambi | 1.032 | 1.035 | 0.003 | W |
| 2002 | A. Rodriguez | 1.008 | 1.023 | 0.015 | |
| 2002 | Bonds | 1.342 | 1.432 | 0.09 | |
| 2001 | L. Gonzalez | 1.189 | 1.032 | -0.157 | W |
| 2001 | Boone | 0.945 | 0.956 | 0.011 | |
| 2001 | Glaus | 0.877 | 0.922 | 0.045 | |
| 2001 | Helton | 1.09 | 1.148 | 0.058 | |
| 2001 | A. Rodriguez | 0.993 | 1.052 | 0.059 | |
| 2001 | Sosa | 1.126 | 1.225 | 0.099 | |
| 2001 | Giambi | 1.082 | 1.202 | 0.12 | |
| 2001 | Bonds | 1.314 | 1.455 | 0.141 | |
| 2000 | E. Martinez | 1.114 | 0.883 | -0.231 | |
| 2000 | Everett | 1.05 | 0.831 | -0.219 | |
| 2000 | Guerrero | 1.131 | 1.004 | -0.127 | |
| 2000 | Delgado | 1.185 | 1.069 | -0.116 | |
| 2000 | C. Jones | 1.023 | 0.913 | -0.11 | |
| 2000 | Griffey | 0.935 | 0.952 | 0.017 | |
| 2000 | Sosa | 0.962 | 1.138 | 0.176 | W |
| 1999 | Surhoff | 0.923 | 0.737 | -0.186 | |
| 1999 | S. Green | 1.047 | 0.889 | -0.158 | |
| 1999 | Griffey | 1.024 | 0.882 | -0.142 | W |
| 1999 | Bagwell | 1.109 | 0.968 | -0.141 | |
| 1999 | Burnitz | 0.998 | 0.886 | -0.112 | |
| 1999 | Garciparra | 1.054 | 0.988 | -0.066 | |
| 1999 | Walker | 1.188 | 1.135 | -0.053 | |
| 1999 | Jaha | 0.981 | 0.956 | -0.025 | |
| 1999 | Sosa | 0.972 | 1.036 | 0.064 | |
| 1999 | McGwire | 1.027 | 1.236 | 0.209 | |
| 1998 | Thome | 1.09 | 0.792 | -0.298 | |
| 1998 | Griffey | 1.061 | 0.876 | -0.185 | W |
| 1998 | Lopez | 0.937 | 0.789 | -0.148 | |
| 1998 | Easley | 0.876 | 0.731 | -0.145 | |
| 1998 | McGwire | 1.252 | 1.189 | -0.063 | |
| 1998 | A. Rodriguez | 0.94 | 0.894 | -0.046 | |
| 1998 | Palmeiro | 0.959 | 0.928 | -0.031 | |
| 1998 | C. Jones | 0.955 | 0.946 | -0.009 | |
| 1998 | Alou | 0.975 | 0.988 | 0.013 | |
| 1998 | Castilla | 0.926 | 0.98 | 0.054 |
Above you see the 843 players, their first and second half OPS, a "net" column (second half OPS - first half OPS) and a "W" column - only the players who won that derby have a W listed. 50 of the 84 players either saw no post-derby gain or suffered an OPS drop, meaning only 34 had positive post-derby experiences.It's important to note that Ivan Rodriguez played in all of 10 games following the derby, hence his absence.
So can we predict a fall off for some of the contestants in tomorrow's derby? It seems quite likely that at least a few will have lower second half OPSes, but correlation doesn't always stem from causation, so while people may think the derby affected a player, there's nothing too conclusive to be drawn, despite only a .443 R2 between first half and second half OPSes which I actually figured would be a bit higher.
To see if this is regular or not we took the top 50 homerun hitters from 2007 and compared their first and second half OPSes - since in the end we are talking about some of their power hitting brethren who, again in theory, didn't "mess up their swings" or anything of the sort. The R2 of the first and second half OPSes: .344.
That means your average HRD participant actually has a better chance at maintaining his first half OPS than your top 50 homerun hitters, at least in 2007.
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improvement of graph
Interesting work. Might I suggest to make the graph more readable you scale down both the axes so only numeric coordinates that contain data are shown. Second, if you were to plot a line where the x and y values were exactly equal across the graph it would be easier to visualize the results as one could directly see how many players improved/declines and the rates of those declines.
I assume that you took out individuals who may have gotten injured early in the second half, whereas this could have led to a unrealistic OPS split?
On your last point, yes.
You definitely have a point about the scales, I should’ve done that originally.
by R.J. Anderson on Jul 13, 2008 11:13 PM EDT up reply actions
sorry
about the x=y line suggestion. Now that I think about it that doesn’t make too much sense.
by RaysTheRoof on Jul 13, 2008 11:14 PM EDT up reply actions
It makes sense
I’m just not sure how helpful it would be visually though.
by R.J. Anderson on Jul 13, 2008 11:21 PM EDT up reply actions
database?
Is there a specific database where you get access to the statistics you use? I tried using mlb.com to compile some data and it was brutal.
by RaysTheRoof on Jul 13, 2008 11:44 PM EDT up reply actions
No database
I hand collected it through BR’s splits pages.
by R.J. Anderson on Jul 13, 2008 11:47 PM EDT up reply actions
I have faith
Evan will be just fine after the Derby and ASG. I’d be more worried about the pressure put on him by the offensive struggles of the team in general.
TAMPA BAY RAYS: 2008 CITRUS SERIES CHAMPIONS
Are there any statistics
for rookies in the HRD who also happen to be the most handsome contestant? Because I am predicting that he will get an OPS of 1.500 after the HRD, and then we will elect him president of the world for life.
B Rad the Ray Fan
9 = 8
the jinx is a sampling bias
Which players tend to be picked for derby? It tends to be players having breakthrough power years or breakthrough years in general. Older, established power threats tend not to participate. (I realize this is not a hard and fast rule, just a trend.)
Ok, so if we’re selective players who have had breakout seasons in the first half, what can we expect from them, whether or not they participate in the derby? We would expect that part of their breakout is due to luck. Which is more likely, that someone who hit 25 homeruns actually has 20 homerun talent but got lucky or that they actually have 30 homerun talent and got unlucky? The first one, obviously. That’s the whole point of regression. Performances far away from the mean most likely include random variation.
Therefore, since breakout performances should have future expectations regressed, it’s not the derby’s fault for bringing their stats down.
It’s like the SI cover jinx. They only put people on the cover who do awesome shit. People who do awesome shit have nowhere to go but down.
by Sky Kalkman on Jul 14, 2008 11:54 AM EDT reply actions 1 recs
IIRC your coefficient of .9076
would indicate an overall difference of .0924 between a perfectly, positive correlated sample. Would this indicate a roughly 9% decrease in first half to second half OPS across the board?
Be who you are and say what you feel, because those who mind don't matter, and those who matter don't mind.
Yeah, I can make up statistical sounding stough too!
The problem is that the leading coefficient of the reverse normalizer is well over 1.034, the mean that we rely on for most normalized calibrations with sample sizes over 15. The truthometer also has a suspiciously low standard deviation, which is liable to discount the overall contingency barometer to -0.502 or lower.
Is it fun to read things that don’t make sense!? That’s what I thought.
B Rad the Ray Fan
9 = 8
Truthometer
That’s funny right there I don’t care who you are.
Be who you are and say what you feel, because those who mind don't matter, and those who matter don't mind.
by Sandy Kazmir on Jul 14, 2008 3:18 PM EDT up reply actions

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