Every park is different. That's one of the unique subtleties of baseball that is different from the other majors sports (besides golf, if you consider it a major sport...which I personally do not). The outfield fences are at different depths, designs, and height. Foul ball territory is different from park to park. The field's location and it's environment make each park different. There's just so much variance in the playing field from park to park.
Now, parks aren't as varying in the minor leagues, but they still have their uniqueness. With uniqueness, you have changes in how the park plays in respect to it's run environments. It's an often over-looked aspect in prospect analysis. The parks have significant impacts on each prospects results. We all know about Lancaster, but there's so much more to look at.
I'm going to take the park factors published by Baseball America which is an average over the last three years (2010-2012). To use a park factor, you take the number and divide it into whatever stat you want to create a rough park-adjusted stat. It's more accurate for stats like runs created and such, but we'll be using OPS and similar stats.
Oklahoma City RedHawks
We always talk about the California League as the offensive environment of the minors. We talk about the Pacific Coast League as being more offensive than the International League, but really it's factors for home runs and hits are more extreme. The Cal League does win out in runs per game though.
Specifically speaking for OkC, it plays very neutrally. It has a park factor of .990, which means that hitters have about a 1% reduction in their home stats while pitchers receive that same 1% bump in their stats, but in a good way.
Out of 120 minor league parks, it has the 56th highest rate of HR's per game, a 1.52 HR/G. That actually makes it the most home run unfriendly park in the PCL. But, it's right in the middle for the minors and fairly neutral.
The league as a standard deviation in runs/game that is 1.88 which is high. That means there's a large variability between parks. That makes for large statistical variations. Using home park data and adjusting it makes for potentially more reliable data.
What this means is that we can take a lot of confidence in OkC's home stats. Overall, their stats are likely very inflated, but the home stats should be a good start in analyzing prospects.
Spotlight: Marc Krauss started the season off very well but cooled off in May. But, take a look at his home stats. He has batting line of .347/.446/.632 which is just crazy. Considering what was just covered, that's very encouraging, but his BABIP at home is .380. But, the six home runs at home compared to three on the road with roughly the same amount of plate appearances is encouraging. You're essentially seeing the same situation with Jonathan Villar. He rakes at home, but has the most absurd BABIP of .416 at home.
On the pitching side, Jarred Cosart is pitching better at home. He boasts a 2.70 ERA in 30 innings. His strikeout rate is definitely lower at home though with his walk rate about the same. Asher Wojciechowski has a 1.65 ERA at home, but is being upheld by a .222 BABIP. On the depressing side, Brett Oberholtzer has a 5.78 ERA with a .286 BABIP at home. A 1% aid there doesn't make it look attractive still.
Corpus Christ Hooks
The Texas League is close to the middle but leans a little to the offensive side in terms of leagues. Overall, the numbers for the league are fairly accurate and reliable. When looking at Corpus' stats, they are pretty neutral. The park factor is just 1.023 so hitters numbers are inflated by approximately just 2.3%. The HR/G is higher than OkC at 1.76.
The standard deviation for the league is 1.04. The overall stats are moderately reliable for the league.
Spotlight: George Springer is a monster at home...but then again, he's a monster everywhere. Here's an encouraging one. Jonathan Meyer's home splits are .292/.357/.460. His OPS at home is .817 and if you reduces that to .797. His BABIP is .312, so that's pretty accurate. Good to see him hitting well and have good markers for confidence in his stats. Domingo Santana has a .919 OPS at home but has a .393 BABIP at home.
Here's a pitching line you'll like. Nick Tropeano has a 2.84 ERA at home and adjusts to 2.78. He has a high .324 BABIP, so I'm very encouraged by Trope's season so far. Bobby Doran also has some strong home statistics.
Ahhh, the Cal League. We already brought up their rankings of the park factors in respect to other leagues. It's an offensive overall environment. But, there's only four out of ten parks with positive park factors. Lancaster has the second most with a 1.162, which means hitters get a 16% boost in offensive performance. There's also a 1.76 standard deviation, so like the PCL, overall statistics can have variances.
The HR/G for Lancaster is 2.48, making it very friendly for home runs. It's second in the league in R/G, H/G, HR/G, and park factor for runs.
Spotlight: Nolan Fontana has a batting line of .259/.404/.469 at home which makes an .873 OPS with a .316 BABIP. His park adjusted home split is .752 OPS. That's good for a middle infielder, but not as standout as what we all have looking at. But, his old college buddy, Preston Tucker, as an OPS at home of 1.029 with a .369 BABIP. He still has an OPS of .886 which is still really good. M.P. Cokinos has been creating a bit of a buzz this season and has a .850 OPS at home and a park-adjusted home OPS of just .731. Hype is cooling, but his BABIP is a little low at .284.
On the pitching side, Brady Rodgers has an ERA of 4.91 with a good BB/SO ratio. Adjusted, the ERA looks better at 4.22 and he's been unlucky at home with a .380 BABIP. Aaron West fits the same category with good BB/SO numbers and high BABIP. His park adusted ERA is 3.73. But with his injuries, the sample size is even smaller than others with just 18 2/3 innings. David Rollins has been rocked at home and his walk rate is a bit high as well there. His BABIP is where it should be and even after adjusting for the park, his home ERA is still 5.04.
Quad Cities River Bandits
The Midwest league numbers are interesting. Hits per game are typically a strong indicator for runs per game. However, the league is 10th (out of 10) in hits per game and ninth in home runs per game but is actually fifth in runs per game. So, lots of walks turn into runs in the MWL. Also, the the standard deviation in runs per game between parks is the lowest of all leagues at 0.48, making them overall stats pretty reliable.
Quad Cities individual park factor is .993 which makes it almost as neutral as you can get. There are just 1.28 HR/G so it's a little suppressive to home runs compared to the rest of the league but is by no means an extremely suppressive park.
Spotlight: Carlos Correa has a home OPS of .767 so that should be accurate. However, he has a high BABIP at .357. Teoscar Hernandez has a .333 BABIP at home and his OPS of .699. How about an absolute insane one? Ariel Ovando has a .294 OPS at home. His BABIP is horrible there though. It's .156 but even than normalizing wouldn't pull his numbers up enough to be respectable.
On the pitching side, Vincent Velasquez stands out even more. His home ERA is 3.42 and he's been unlucky with a .349 BABIP. Lance McCullers has the exact same home ERA and his BABIP is just one point lower. Crazy. Brian Holmes has a very encouraging split. His home ERA is 2.92 but has been lucky with a .263 BABIP. Jordan Jankowski has a split almost two runs lower at home with a 2.56 ERA and his BABIP is .298 at home too.
This is a rough way of using park factors and would be more appropriate with stats like runs created as I've said before. But, it still works and puts some stats into perspective and a frame of reference for the stats that you look at when evaluating prospects. The sample sizes are still a bit small for home stats for some prospects and we can still see some big swings in them in the coming months, but it's still a good exercise for now.
I purposefully didn't adjust all the players for you and put into a table. It's a fun exercise. So, now you know the park factors how to use them. So, go find the home stats for some of the prospects that you have been wondering about and see how reliable the stats are. Post them in the comments and we'll hash them out.