I included this as a link in a recent post on whether park sizes matter, but felt it deserved it's own post. I pulled something like 500 - 600 seasons worth of data utilizing a python script I wrote and calculated some updated park factors for how different parks actually perform in game. The results can be found here. These aren't window dressing numbers like the ones listed by WiS in the select city screen. The fact still remains that cities like Burlington and Tacoma (-4 across the board) play essentially the same as parks like Seattle, and Colorado produces 11 percent more offense than a place like Santa Fe, despite comparable + ratings.

During the process of trying to create a park factors, I remembered how inconsistent WiS is in their stats and what they show. Runs are shown on the home/away splits for batting, but only unearned runs are shown for home/away splits for pitching. It makes no sense. Anyway, I estimated home/away wOBA utilizing the formula from this website. It is definitely not perfect, but it's close to the factors I generated in the past that can be found at this post.

Interesting. Which NY is Yankee Stadium?

Posted by opie100 on 1/24/2018 8:55:00 PM (view original):
Interesting. Which NY is Yankee Stadium?

NY1 is AL
NY2 is NL

CH1 is NL
CH2 is AL

Thank you. Shouldn't Iowa City be more of a pitcher's park than STL?

Posted by opie100 on 1/24/2018 9:07:00 PM (view original):
Thank you. Shouldn't Iowa City be more of a pitcher's park than STL?

You would think. Ask WiS.

Nice

Posted by chimaera on 1/24/2018 9:16:00 PM (view original):

Posted by opie100 on 1/24/2018 9:07:00 PM (view original):
Thank you. Shouldn't Iowa City be more of a pitcher's park than STL?

You would think. Ask WiS.

I know the -4 to +4 ratings are aesthetic, but perhaps Iowa City is more like -1.7, -1.7, -1.7, -1.7, -1.7 (-8.5) and STL is -2.3, -2.3, -1.4, -1.3, -1.3 (-8.6). I know each value doesn't affect the total the same, but that's all I can figure.

WiS doesn't keep track of 2B and 3B for pitchers for home/away splits, but it does track hits and HRs. I could pull out hits minus home runs and calculate that, and also calculate just home runs.

If I wanted to be less precise, I could just calculate 1B, 2B, 3B, and HRs using just batting splits for home/away, but that doesn't account for away teams performance in a stadium, so it would be skewed towards the makeup of the home team's batters.

Thus, can we assume that different stadiums with the same +/- ballpark effects impact player ratings exactly the same in either park (and regardless of PF factor differences, published or calculated)?

I also don't know why the sim can't negotiate a hitter with modified ratings that become decimals. It's all just math, right?

Not to poop on parades but there is a problem with data-collecting actual results from all worlds. There are more bad worlds than good. A good world will see total runs allowed around 700, a WHIP under 1.35 and an ERA under 4.10. What happens in a world with 800 RA, WHIP of 1.45 and ERA over 4.50 will skew the results. Those worlds are A) using terrible fielders because the dude can hit, B) using AAA-type pitchers because they don't know any better or C) both because there's no penalty for giving up 5+ runs a game and winning 48 times.

And, in all fairness, it's more fun to win 10-8 games.

If it's not too much of a pain in the ***, run the data on all of Coop and MG, 90 something seasons, and 3 random worlds(30 someodd seasons each to equal Coop+MG total seasons). The 30 someodd season worlds would have slower rolls and, I'm willing to bet, much worse pitching data.

Posted by pjfoster13 on 1/25/2018 1:45:00 PM (view original):

Posted by opie100 on 1/25/2018 12:03:00 PM (view original):
Thus, can we assume that different stadiums with the same +/- ballpark effects impact player ratings exactly the same in either park (and regardless of PF factor differences, published or calculated)?

I also don't know why the sim can't negotiate a hitter with modified ratings that become decimals. It's all just math, right?

I also don't know why the sim can't negotiate a hitter with modified ratings that become decimals.

Probably just to save on computing bandwidth, math is math but less math is always better amirite

I suppose that each batter-pitcher interaction could simply just be using the decimal multiplier rather than the +4-4, but the reason I believe it's the latter is because you have to account for really odd patterns like AT&T Park +1+0+3-3-3 where HRs are nerfed due to temperature, air pressure, and wind (and not allowing Barry Bonds to single-handedly skew the HR-RF data), and juicing triples because everything that hits their weird RF brick wall takes a crazy bounce into that little RCF alcove. Or Toronto's Rogers Centre -2+2+0+1+1 where doubles are juiced because tons of fly balls that land on their outfield turf rocket into the stands as ground-rule doubles that would not otherwise occur in grass outfields, but singles are negative because Rogers has extra foul territory square metre-age which accumulates in the data record as extra "free outs" for the pitcher that reduce overall batting average.

So that's why you can't just multiply every interaction with the same overall decimal, because each ballpark truly does affect singles doubles triples and HRs differently on their own

Yes. It would be incorrect to take these park rating ratios and try to say they impact each outcome the same. As I mentioned earlier, it would be difficult to extract 1B, 2B, 3B totals from the data that WiS gives us. Total hits minus HRs and HRs would be relatively easy to do though.The park factors are simply an expression of how each park impacts overall offensive output during games played there.

Posted by MikeT23 on 1/25/2018 12:20:00 PM (view original):
Not to poop on parades but there is a problem with data-collecting actual results from all worlds. There are more bad worlds than good. A good world will see total runs allowed around 700, a WHIP under 1.35 and an ERA under 4.10. What happens in a world with 800 RA, WHIP of 1.45 and ERA over 4.50 will skew the results. Those worlds are A) using terrible fielders because the dude can hit, B) using AAA-type pitchers because they don't know any better or C) both because there's no penalty for giving up 5+ runs a game and winning 48 times.

And, in all fairness, it's more fun to win 10-8 games.

If it's not too much of a pain in the ***, run the data on all of Coop and MG, 90 something seasons, and 3 random worlds(30 someodd seasons each to equal Coop+MG total seasons). The 30 someodd season worlds would have slower rolls and, I'm willing to bet, much worse pitching data.

That is not how park factors work. A bad team at home is going to be a bad team away from home. This isn't measuring average runs per game. It's simply measuring the ratio of offensive production for games played at a park and games played elsewhere. A bad team that plays at a park with a park factor of 1.000 that sees a total of 10 runs a game between runs they score and give up would be expected to see 10 runs per game at games away from home. Bad teams, or badly run worlds are not likely to skew the data.

However, a source of possible skewness would be if a city like Seattle was in a world where the other 31 ballparks were super hitter friendly. The data would possibly say that Seattle depresses offensive production more in that world compared to other worlds. The way to get around potential outliers like that would be to just get more data.

I could run the script on Coop, MG, BBWAA, Capra and one other world tonight when I get home, but my hypothesis is the final numbers from those worlds would be relatively close to the list in the original post.

I'll disagree but it's your program.

We had the "Too many homers" debate years ago. It wasn't that there was too much power in the game, there were simply good hitters facing minor league quality pitchers in unbalanced worlds.