MLB Park Factors

Our fantasy hamsters are busy spinning their activity wheel to produce a nice MLB Park Factors page, but the real 411 insiders know to get it here on the blog, so 
here it is!

What do these numbers mean, how did we determine them? Glad you asked!

* We added up the batting stats compiled by the home team in all games in their home ballpark over the past three seasons (2006-07 for the new Busch Stadium), PLUS the stats compiled by their opponents in those games;

* Then, we added up the batting stats for each team and their opponents in their road games… that is to say, we took all Diamondbacks home batting stats (plus their opponents in home games) and compared them to their road batting stats (plus their opponents in road games);

* Next, we pro-rated all stats over 1,000 plate appearances so we’d be comparing the frequency of events on a per-plate-appearance basis, rather than simply counting up to see where something happened the most, which could be skewed if hitters had more PA’s in one ballpark than another;

* Then, we divided the prorated home stats by the prorated road stats to determine an index for each stat category. Keep in mind that some ballparks may increase production in one category, but decrease it in others, so providing only a single value isn’t a great way to determine the influence of each park on offensive production.

The numbers provided here are “simple” park factors, meaning that these numbers are not adjust edfor strength of schedule. That is, the Pirates may play the Red Sox in interleague play while the Cardinals play the Orioles, and the relative strength of those opponents will somewhat skew the frequency with which different offensive events occur. Our friends at Baseball Prospectus do this, which results in some slightly different numbers, but for basic fantasy purposes the “simple” method is still very useful and telling.

Here’s a for instance… the Chase Field HR factor is 114, meaning the Diamondbacks and their opponents hit 14% more homers in Chase Field over the past three years than they did on the road. And while Fenway Park is actually not a good homer park (83), it increases doubles (135) more than enough to offset that, making it a good offensive park overall in terms of runs per game (108) and OPS (102).

Another interesting tidbit is the effect of parks on stolen base attempts and success rate… note that many of the parks perceived as bad hitters’ parks have above-average rates of stolen base attempts, perhaps as teams attempt to compensate for the tougher environment by running more. But what’s also interesting is that (with smaller variation than other stats, but still) some parks lead to higher SB success rates that others… for instance, PNC Park saw 3% more SB attempts than road games, but allowed 8% less in terms of success rate. What causes this? Infield types? Different types of materials? Wet track? I wonder how we can find out more about this to figure out where our sleeper basestealers would come from…

OK, that’s it, enjoy. Looking forward to reading questions and comments!



Hey Cory,

I’ve often wondered where to get good statistics on park factors. This is a terrific resource I will definitely use in my pitch or ditching this year.


The biggest question i think of this year is how well dan haren will do in chase field. I haven’t been totally sold on this guy until last year. How well do you guys think dan haren will do this year with the D-backs? From what it seems, with a variety of different sources, people are half and half on this. Let me know what you guys think.

Matt D. Pensy-vania

Matt, I think Haren will be fine. Moving to Chase Field will be a challenge, but the NL is overall the easier league, and he’s right in his prime. He may give up a few more homers than in the AL, but his walk rate should dip a little and his strikeout rate should bump up against the NL’s weaker #8 hitters and pitchers.


Awesome work, really helpful. I’ll also use this for pitch or ditch.

Shane in Seattle

Cory, this is great stuff. I like how you broke it out by batting events rather than just runs. That makes a world of a difference in fantasy.

As long as we’re looking at batting events (and not just runs), it seems to me that the next step into something more granular would be to take these and translate them into lefty/righty splits. For instance, what is the net impact of the short porch in right field at Yankee stadium to a pull hitting lefty? What is the impact of the Green Monster on a right handed batter at Fenway? Or, for pitch or ditch, what do the park factors look like based on the handedness of the pitcher?

Oh man, (and this is wishful thinking), then you could combine the park factors with pitch FX data, to see what parks favor fastball pitchers, or what parks favor pitchers who throw a changeup over 30% of the time…the possibilities are endless.

Not sure if your fantasy “gerbils” (or what have you) are going that in depth for the new landing page, but that would be some incredible data to offer, if it’s available. Complicated, yes, but with a very applicable purpose to fantasy baseball (and maybe even real baseball).

Thinking about this is another reminder that despite the massive amounts of work already done in sabermetrics, there’s always more on the horizon.

Thanks Cory!

WOW, that is a really great point. This is probably something that MLB clubs already figure participate in, and pay someone 6-digit salaries to do, but for people in the fantasy world, we’re all itching for the knowledge I’d say.

Dave, I don’t think it would be too difficult at all to break out the data vs. left/right, but I’m in full NFBC-prep mode right now so don’t expect it right away!

Also keep in mind that this is a case where the various annual changes in OF dimensions could have a big impact, so I’ll see about posting the data on a year-by-year basis (I think that’s what I did here?) as well as a three-season aggregate.


Thanks for the great info. I’m curious to see how the National’s new park will play out.

As for stolen bases, I’d suspect that the opposing battery has much, much more to do with stolen base attempts and percentages than any physical characteristic of the park.

With that being said, some of the numbers in your chart don’t seem to add up. For example, in 861.1 innings caught by Yadier Molina opposing players only attempted to steal 50 times and were caught for the majority of these (27 times). These numbers would lead one to assume that Busch would have significantly lower than average attempts and success rates, but you data seems to indicate otherwise.

Also, the Padres catchers last year were terrible at throwing out runners. Bard and Barret combined to only throw out 12 percent (141SB 17CS), but your data appears to suggest that Petco had fewer than average stolen base attempts and a lower than average success rate.

Am I reading this data wrong?

Andrew, I think you are reading the data wrong. Remember that these nubmers take into account the various stats compiled by BOTH teams in each park, not just the home team. So while the Padres gave up a lot of SB’s last year, they didn’t get that many, so those balance out. And remember that these are three-year averages, so maybe the Padres did a better job of stopping the running game back in ’05 and ’06 than last year?


Would interleague play matter much for park averages with NL & AL averages as a baseline?

Indeed it would, since interleague play will heavily influence “strength of schedule” and skew these results somewhat. For example, if the Pirates play against a good offensive team like the Red Sox in Fenway, that might pump up their “away” numbers and make PNC look like more of a pitchers’ park than it really is. On the other hand, if the Red Sox play at the Astros, that might make Minute Maid Park look like a little bit more of a hitters’ park than it really is.

That said, these are all probably minor effects in the overall scheme of things. As noted in the original post, we didn’t take these strength of schedule issues into account in these numbers, but for “simple park effects”, these values should be valid still. What’s the practical difference between a value of 108 and 109? Not enough to change the overall conclusion.



The link is dead after the migration.

I fixed this, thanks for the heads-up.


I would not know how I am supposed to feel about many stories if not for the fact that the TV news personalities make sad faces for sad stories and happy faces for happy stories. Do you think so?
Air Jordan

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