Examining Baseball’s Most Extreme Environment

“The Coors Effect.”

These three words evoke a strong reaction from most people and are impossible to ignore when discussing the offensive production of a Rockies player. Ask anyone who was around for the Rockies of the ‘90s and they will tell horror stories of games with final scores of 16-14. Ask anyone at FanGraphs and they will laugh and point at the Rockies’ 2015 Park Factor of 118. Heck, ask Dan Haren and see what he has to say:

Suffice it to say that Coors is a hitter’s park. Nobody will argue that. But there have been murmurs recently about another effect of playing 81 games at altitude, an effect that actually decreases offensive production. These murmurs have evolved into a full-blown theory, which has been labeled the “Coors Hangover.”

This theory supposes that a hitter gets used to seeing pitches move (or, more accurately, not move) a certain way while in Denver. When they go on the road, the pitches suddenly have drastically different movement, making it difficult to adjust and find success at lower elevations. In other words, Coors not only boosts offensive numbers at home, it actively suppresses offensive numbers on the road, which can take relatively large home/road splits for Rockies players and make them absolutely obscene.

The concept seems believable, but thus far we have no conclusive evidence of its merit. FanGraphs’ Jeff Sullivan recently tested this theory, as did Matt Gross from Purple Row. Although neither article revealed anything promising, Jeff is still a believer, as he recently shared his personal opinion that the Coors Hangover might simply last longer than any 10-day road trip. With this is mind, I decided to approach the problem by examining the park factors themselves.

If you haven’t read the article about how FanGraphs calculates its park factors, I highly recommend you do so before continuing. The basic approach detailed in that article is the same approach that I use here. As a quick example, the park factor for the Rockies is calculated by taking the number of runs scored in Rockies games at Coors (both by the Rockies and the opposing team) and comparing that to the number of runs scored in Rockies games away from Coors. Add in some regression and a few other tricks, and we have our final park factors.

This method makes a number of assumptions, most of which are perfectly reasonable, but I was interested in taking a closer look at one critical assumption. By combining the runs scored by the Rockies with the runs scored by their opponents, we are assuming that any park effect is having an equal (or at least, an indistinguishable) impact on both teams. This seems like an obvious assumption, but it becomes invalid when the Rockies play on the road. According to the Coors Hangover, Rockies hitters experience a lingering negative park effect after leaving Coors which the opposing team is not experiencing.

In other words, we expect a gap to exist between a hitter’s performance at Coors and his performance at an average park. If the Coors Hangover is true, this gap would be larger for Rockies hitters than anyone else.

Let’s start by taking a look at the park factors we have now. The following tables only contain data from NL teams for simplicity sake.

Park Factors, 5-year Regressed (2011-2015)
Team Total Runs (team + opponent) Park Factor
Home Away
Rockies 4572 3205 1.18
D-backs 3657 3328 1.04
Brewers 3588 3306 1.04
Reds 3385 3215 1.02
Phillies 3365 3341 1.00
Nationals 3240 3213 1.00
Cubs 3346 3345 1.00
Marlins 3200 3229 1.00
Braves 3086 3199 0.99
Cardinals 3243 3397 0.98
Pirates 3070 3394 0.96
Dodgers 2995 3323 0.96
Mets 3109 3556 0.95
Padres 2936 3440 0.94
Giants 2900 3537 0.92

No surprises. Teams score a ton of runs at Coors and hardly ever score at AT&T Park in San Francisco. Now let’s split up those middle columns to get a closer look at who is scoring these runs.

Runs Scored, 2011-2015
Team Home Stats Away Stats
Team Opponent Team Opponent
Rockies 2308 2264 1383 1822
D-backs 1844 1813 1641 1687
Brewers 1823 1765 1619 1687
Reds 1731 1654 1606 1609
Phillies 1676 1689 1576 1765
Nationals 1749 1491 1651 1562
Cubs 1625 1721 1547 1798
Marlins 1541 1659 1464 1765
Braves 1606 1480 1569 1630
Cardinals 1779 1464 1797 1600
Pirates 1586 1484 1688 1706
Padres 1443 1493 1604 1836
Dodgers 1557 1438 1758 1565
Giants 1481 1419 1797 1740
Mets 1482 1627 1817 1739

These are the two pieces of run differential — runs scored and runs allowed — and we generally see agreement between the home and away stats. If a team out-scores their opponents at home, they can be expected to do the same on the road. Good teams are better than bad teams, regardless of where they play. Although, if you subtract a team’s run differential on the road from their run differential at home, the difference will actually be around 100 runs due to home-field advantage. Doing this for all 30 teams yields a mean difference of 83 runs with a standard deviation of 122.

Where do the Rockies fall in this data set? Not only have they scored over 400 more runs at home than the next-best NL team — they have also scored almost 200 runs less on the road than the next-worst NL team. Comparing their home and road run differentials, we see a difference of 483 runs (+44 at home, -439 on the road), or 3.3 standard deviations above the mean. To put it plainly: that’s massive. This is a discrepancy in run differentials that cannot be explained by simple home-field advantage.

Furthermore, I followed the same process of calculating park factors for each team explained above, but I split up the data to calculate a park factor once using the runs scored by each team (tPF), and again using the runs scored by each team’s opponents (oPF). Generally, these new park factors are closely aligned with the park factors from before…except for, of course, the Rockies.

Alternate Park Factors, 5-year Regressed (2011-2015)
Team tPF (Team Park Factor) oPF (Opponent Park Factor)
Rockies 1.27 1.10
D-backs 1.05 1.03
Brewers 1.05 1.02
Reds 1.03 1.01
Phillies 1.03 0.98
Nationals 1.02 0.98
Cubs 1.02 0.98
Marlins 1.02 0.97
Braves 1.01 0.96
Cardinals 1.00 0.96
Pirates 0.97 0.94
Padres 0.96 0.92
Dodgers 0.95 0.97
Giants 0.93 0.92
Mets 0.92 0.97

On average, a team’s tPF is about two points higher than its oPF — again, this can be attributed to home-field advantage. The Rockies, however, are in an entirely different zip code with a discrepancy of 17 points. We aren’t talking about home-field advantage anymore. We are talking about something deeper, something that should make us stop and think before averaging the two values to get a park factor that we apply to the most important offensive statistics.

We have no reason to believe that any team should have a 17-point difference between their tPF and oPF; the fact that the Rockies are in this situation either means that they are enjoying hidden advantages at home, or they are suffering hidden disadvantages on the road. To date, we don’t have a theory supporting the former, but we do have one supporting the latter. This is the Coors Hangover.

Does this mean that the Rockies’ Park Factor should actually be their oPF of 110? Should it be some weighted average of different values? I don’t know. But I do know these numbers can’t be ignored. Something is going on here, and we need to talk about it.



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Jacob is a mechanical engineer who spends an unhealthy amount of his free time researching baseball.

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Doorknob11
Member
Doorknob11

Looks like their pitchers have it too, except they go from awful at home to bad away.

evo34
Member
evo34

“This is a discrepancy in run differentials that cannot be explained by simple home-field advantage.”

Yes, it can. There is no law that says HFA is constant among teams. Denver teams always have the highest home advantages in their respective leagues — and the Rockies are no exception. Their HFA is generally about 3.5 STDevs above average.

BTW, to do park factors correctly, you need to look at how many half-innings were actually played, which account for winning home teams not batting in the 9th and extra-inning games.

ap0001
Member
ap0001

I’ve looked at this on occasion on my own time, and while giving the Rockies hitters a little more creidt doesn’t change single-season numbers a whole bunch, I’m thinking Todd Helton might be a little undersold on FG with his 55 WAR.

Not entirely sure how much, but considering he might get borderline HOF support with that number it might end up being crazy important for future voters. Tulowitzki, Gonzalez and Holliday probably see a little change too, while Rockies pitchers are technically worse than you think (Boo! Halloween comes early)!

AC_Butcha_AC
Member

I think part of the discrepancy can be explained by the fact that besides Arizona, all other Ballparks in the NL West are graveyards.

I took a quick look at their schedule this year and they had to play 44 games in ballpark that surpress run scoring by your defintion compared to just 12 which increase run scoring on the road. The rest was neutral.
To make it even more extreme, 34 of the 44 road games in ballparks that surpress run scoring came against the 4 most extreme run surpressing ballparks (10@SF, 10@SD, 4@NYM, 10@ LAD)

GG_huson
Member
GG_huson

The way I understand it, that shouldn’t really change the discrepancy. The fact that the Rockies play in pitcher-friendly away stadiums means the gap between their runs scored at home vs on the road will be larger than it should, which means their “tPF” should actually be a bit smaller. But the same should theoretically happen to their pitchers, meaning the “oPF” should actually be a bit smaller too.

If both go down a few points, it doesn’t make the discrepancy any smaller, it just means that we’re overcompensating for Coors in a completely different way as well.

WARrior
Member
Member

I know you referred readers to the FG explanation of park factors, but it would have been helpful if you had explained in slightly more detail how you came up with yours. In the first table, if you divide the total runs scored by the Rockies and their opponents at Coors by the total runs scored in road games, you get 1.42. How does one get a park factor of 1.18 from this?

First, you have to cut the portion > 1 by 50%, because the 1.42 would apply if all games were played at Coors, whereas of course players play half their games on the road, where the park factor is assumed to average out to close to 1.0. But second, there is apparently a regression factor of about .84, at least that is what one needs to multiply the ratios in the first table by to get the park factors you actually come up with. And the regression factor for the second table is different, though apparently not by very much.

Now on to the actual analysis. You note the large discrepancy between the factors of 1.27 and 1.10 in the second table, where one considers just the runs scored by the Rockies at home or on the road. More precisely, 1.27 is the ratio of the runs scored by the Rockies at home vs. on the road, while 1.10 is the ratio of runs scored by their opponents at Coors vs. on the road. You argue that either the Rockies have some benefit from playing at Coors not available to their opponents, or that there is a hangover effect on the road, so that they play worse than other teams on the road (thus inflating their apparent home benefit).

Couldn’t both factors be in play? I take it that the Coors factor is partly because the low density air results in less movement on pitches, and partly because batted balls carry further. The second factor obviously will be the same for both home and visitors, but the first does not have to be. In the first place, Rockies pitchers may adjust to the different conditions by throwing fewer breaking balls, or different kinds of breaking balls. Second, whether they do or don’t, visiting players, not used to the different movement, may not be able to take as much advantage of it as the home players. It could be a matter of expecting more break, or even if they go in to Coors expecting less break, simply not able to adjust as well as the home players.

mtsw
Member
Member

I wonder how much of this is the Rockies’ front office prioritizing players that will succeed in Coors’ extreme environment. It makes sense that contact-oriented guys who can put the ball in play and run well will do much better at Coors than a standard hitter will, given the enormous dimensions and high BABIP of the park. Players who can hit fastballs well but struggle vs breaking pitches would also presumably have big home/away splits at Coors.