Does defense matter in OOTP6?

[khucke]

I tried to find an answer to this question by setting up a test league. I created an 8-team league in replay mode with injuries, trades and financials turned off. The players were fictional and there was an initial draft.
I then picked one team randomly, in this case the Baltimore club, and changed the fielding ratings of the shortstop players, there were 3 with a SS rating, to 50. I simulated 10 seasons. Then I put the ratings of these players at 100 and then at 1 , simulating 10 seasons with each setting.
Here are the results:
average team wins standard deviation
SS at 100 : 79.1 4.1
SS at 50 : 81.9 5.7
SS at 1 : 78.6 7.9


I have to conclude that defense at the SS position, generally regarded as the most crucial, does not have a recognizable effect on winning games in an OOTP baseball season, espcially if you take the high value in the standard deviation into consideration.
One might argue that the sample of 10 seasons is too small, I plan to expand that sample sample to 20 seasons and will post the results then.

[Fool Inc.]

That rating is just for range. What were each of the guy's fielding percentage?

[khucke]

You`re right to suggest that fielding percentage and range combine to determine the overall defense ability of a fielder. But my intention was to isolate the effects of range, therefore I kept the fielding percentage of the players involved unchanged in all test runs.

[khucke]

I carried my test runs a little further:

The league`s setup is explained in my initial post. After 15 seasons the reselts are:

SSs at 100 range : average team wins 80.4
SSs at 50 range : average team wins 79.2
SSs at 1 range : average team wins 79.6

While the difference berween a 50-range SS and a 100-range SS seems reasonable (about 1 win per season , I find the lack of a differnce to the 1-range SS disturbing.

I ran another 10 seasons with a different setup. My Baltimore team has all fielders at 100 range (except the pitchers):

All fielders at 100-range: average team wins 84.3

This translates roughly to a gain of 4-5 wins over the established team results of 79-80. It means an average gain of 0.5 to 0.6 team wins per position over an average team. next I might take a look at runs and hits given up relative to differing range values.

[akw4572]

Originally posted by khucke
I tried to find an answer to this question by setting up a test league. I created an 8-team league in replay mode with injuries, trades and financials turned off. The players were fictional and there was an initial draft.
I then picked one team randomly, in this case the Baltimore club, and changed the fielding ratings of the shortstop players, there were 3 with a SS rating, to 50. I simulated 10 seasons. Then I put the ratings of these players at 100 and then at 1 , simulating 10 seasons with each setting.
Here are the results:
average team wins standard deviation
SS at 100 : 79.1 4.1
SS at 50 : 81.9 5.7
SS at 1 : 78.6 7.9


I have to conclude that defense at the SS position, generally regarded as the most crucial, does not have a recognizable effect on winning games in an OOTP baseball season, espcially if you take the high value in the standard deviation into consideration.
One might argue that the sample of 10 seasons is too small, I plan to expand that sample sample to 20 seasons and will post the results then.

There are so many different factors that can happen, it's just about impossible to say "defense doesn't matter" by looking at one position. Try doing this will ALL positions at the same time, going 1, 50, 100 and see how that comes out.

[dougaiton]

Try looking at BABIP rates rather than wins, or even just runs. With a SS's defensive ability probably measuring in at around a 30th maximum of a team's total output (this is all off the top of my head) then its fair to say that there are too many variable in the wins to justify this.

There was another study for OOTP5 that showed that an A graded SS was disproportionately effective compared with RL. Obviously, different game, but still...

Good stuff, though. Keep trying stuff out!

[Joshv02]

Great stuff!. I love reading these studies. Thanks for doing this.

It may be a good idea to do three things to control the variables in your study:

have all defensive ratings = 50.
have all pitching ratings = 50.
have all gb percentages = 50.

Defense is synergistic. It is important to isolate the variable you are looking to study. (I assume you made this a replay league and turned off injuries and fatigue, btw ).

Looking forward to seeing more over time!

[IatricSB]

Originally posted by Joshv02
(I assume you made this a replay league and turned off injuries and fatigue, btw ).

Ummmm... yes he did and stated so in the 2nd sentence of the first paragraph of his first post.

[Joshv02]

Ugg. Simple reading. That would be nice.

Thanks, Iatric.

[IatricSB]

[khucke]

dougaiton,
I must admit to my ignorance, but what is BABIP?

joshv02,
that`s an excellent idea and I´m still looking for a button to click that sets all values to average, because I`m too lazy to dit it manually.


The more I´m looking into this the more confusing it gets. How about this:

All fielders set at 1 : average wins 76.8 (max 97, min58)
All fielders set at 50: average wins 84.3 (max 95, min 76)
All fielders set at 100: average wins 82.8 (max 91!, min 71)

each of the three setting were run 12 seasons. Hard to understand why the 100-range fielders produce fewer runs than the 50-range guys, or may it still be a case of small sample size?

to be continued....

[IatricSB]

Originally posted by khucke
dougaiton,
I must admit to my ignorance, but what is BABIP?

Batting Average on Balls In Play.... part of the new DIPS system in OOTP6.

[dougaiton]

Sorry BABIP is the rate that balls put into play turn into hits. I believe the formula is BABIP = (H-HR)/(BF-HR-HBP-BB-K)

That looks like quite a bit of work for yourself, but if you just take the team totals at the end of each year and do the sums, then that might show how much hits are dependent on D.

[khucke]

Are the team totals for batters faced or HBP compiled somewhere within OOTP, I think they aren`t.? Would have to go through each pitcher`s stat page and add them up, quite some work ...

[dougaiton]

Yeah - probably too much! Don't worry about it - you never know. I might get bored and try it myself tonight!

[dougaiton]

Well, I thought I'd run 3 quick, controlled sims - 1 8 team league, 1 div, 162 games, and see what it spat out. Not being bothered to calculate stuff correctly, I made up my own shoddy statistics to do it for me. Thanks Knuche for the inspiration and initial research!

BF* = OutsMade (IP*3) + hits +walks (discounting thus DP, basepath outs and HBP)
Sorry, but we’ll have to take them as constants for my own sanity. As none are truly dependent on the SS apart from DP, we’re doubly weighting his performance, and some might see that as a good thing!

Doug’s PoorBABIP = h- hr / BF* - hr - bb – k

100 range = (1374– 160) / (6147- 160 – 453 – 1001)
1214/4553 = .267 (remember, discounting all that jazz)
ERA = 3.79

50 range = (1467– 168) / (6273- 167 – 444 – 1017)
1467/4654 = .315 (remember, discounting all that jazz)
ERA = 4.34

1 range = (1477– 192) / (4464) = 1285/4464 = .287 (remember, discounting all that jazz)
ERA = 4.42 (check the huge increase in homers, though!)

1 range = (1478– 164) / 4696 = 1314/4696 = .279 (remember, discounting all that jazz)
ERA = 4.09 (check the huge increase in homers, though!)

Oddly, all three times I ran the 1 range guy, the team came 1st or 2nd in the division. No either time, the team came higher than 5th. Barmy, but I suppose that's chance!

I'll try a couple more tonight, but it looks a little odd. I would expect the results to be so apparent (1 being the worst SS you could hope to imagine, range-wise) that only one test year would do it.

[dougaiton]

Uhh, moreover (and I should have checked this before): despite having a range of 1, his range factor is 4.79, which makes him the 2nd highest in the league at short. I know, I know, tiny sample size, but any chance it could be a problem with a 1 rating?

[dougaiton]

double dola,

The thing that worries me is that all the other stats stay so sensibly constant that with the only change being the SS's abilities that there isn't a more obvious indicative pattern here. Obviously, the 100 guy is lights out, but still...

[Henry]

Try the same tests using "2" as the lowest value....

[dougaiton]

Will do! I'm thinking a bit more about this as well, and maybe I've been going at it from the wrong tack assuming the '1' is the outlier. It could be that the 50 is the outlier. I'll try again.