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jaa36 · 04-17-2025, 10:31 AM

Thanks for publishing all this.

For defensive ratings, it's worthwhile to look at ratings below 50 (or 55) as well just to see the full spread of how many runs you lose by running out a terrible defender. In looking at this in OOTP 25, there were definitely some lower and upper bounds where it really didn't matter much if you were a 20 vs 30 range defender, or a 70 vs 80 range defender. This reddit post comments on this phenomenon as well: https://www.reddit.com/r/OOTP/commen...ue_in_ootp_25/

From my defensive testing (which was done similarly, creating an "average" defensive team and then adjusting one variable and running 16200 games in the simulation module) I found the following spread from worst-to-best (e.g. how many runs different from a 20 to an 80) for these variables, measured in runs per season for a starter:
C Framing 30
C Arm 30
2B Range 45 (with essentially no benefit beyond 65 range)
2B Arm 15
2B DP 35
3B Range 20
3B Arm 15
SS Range 50 (no benefit beyond 70)
SS Error 10
SS DP 15
LF Range 40 (no benefit beyond 65)
LF Arm 10
CF Range 60 (no benefit beyond 65)
CF Arm 25
RF Range 30 (no benefit beyond 55)
RF Arm 15

I also found that these were cumulative, so if you stacked a good range and a good arm that it would lead to even better results for that player. I would also emphasize that these findings are all in a very artificial testing environment.

HOWEVER- in practice, I also found that it was extremely difficult to use these numbers, because "real life" OOTP teams have such varied defenses and you aren't comparing to 50 or 55. Not to mention that for many players in practice, they might have 70 range but not be maxed out on experience at the position, which impairs their performance. So in modeling defense for my projection system, I actually found it considerably simpler (and reasonably accurate) to just base it on the position ratings rather than the individual component ratings. This was all calculated in OOTP 25 in a "real life" league, essentially figuring out how many runs per game a 25 SS vs a 55 SS would end up with in ZR (and incorporating arm and benefit to runs allowed for catchers). The position ratings are heavily driven by range anyway, which is the most important component. I found that from a 20 to 80 defender you would end up with the following ranges of values, in terms of runs per inning, from worst to best:

C .039 (53 per 150 games/1350 innings)
1B .009 (12)
2B .033 (45)
3B .025 (34)
SS .045 (61)
LF .024 (32)
CF .040 (54)
RF .028 (38)

In most cases, the "cut point" for where a player is accruing positive defensive value is around 55- so a player less than 55 at that position will end up with negative defensive value, while a player above that will end up with positive value. Of note, this is likely not true in an online league where savvy players are not running out 40 center fielders and are prioritizing good defensive players- in that setting, you probably need at least 60-65 at a position to end up with positive defensive value.

04-17-2025, 10:31 AM	#31
jaa36 Hall Of Famer Join Date: May 2011 Posts: 3,106	Thanks for publishing all this. For defensive ratings, it's worthwhile to look at ratings below 50 (or 55) as well just to see the full spread of how many runs you lose by running out a terrible defender. In looking at this in OOTP 25, there were definitely some lower and upper bounds where it really didn't matter much if you were a 20 vs 30 range defender, or a 70 vs 80 range defender. This reddit post comments on this phenomenon as well: https://www.reddit.com/r/OOTP/commen...ue_in_ootp_25/ From my defensive testing (which was done similarly, creating an "average" defensive team and then adjusting one variable and running 16200 games in the simulation module) I found the following spread from worst-to-best (e.g. how many runs different from a 20 to an 80) for these variables, measured in runs per season for a starter: C Framing 30 C Arm 30 2B Range 45 (with essentially no benefit beyond 65 range) 2B Arm 15 2B DP 35 3B Range 20 3B Arm 15 SS Range 50 (no benefit beyond 70) SS Error 10 SS DP 15 LF Range 40 (no benefit beyond 65) LF Arm 10 CF Range 60 (no benefit beyond 65) CF Arm 25 RF Range 30 (no benefit beyond 55) RF Arm 15 I also found that these were cumulative, so if you stacked a good range and a good arm that it would lead to even better results for that player. I would also emphasize that these findings are all in a very artificial testing environment. HOWEVER- in practice, I also found that it was extremely difficult to use these numbers, because "real life" OOTP teams have such varied defenses and you aren't comparing to 50 or 55. Not to mention that for many players in practice, they might have 70 range but not be maxed out on experience at the position, which impairs their performance. So in modeling defense for my projection system, I actually found it considerably simpler (and reasonably accurate) to just base it on the position ratings rather than the individual component ratings. This was all calculated in OOTP 25 in a "real life" league, essentially figuring out how many runs per game a 25 SS vs a 55 SS would end up with in ZR (and incorporating arm and benefit to runs allowed for catchers). The position ratings are heavily driven by range anyway, which is the most important component. I found that from a 20 to 80 defender you would end up with the following ranges of values, in terms of runs per inning, from worst to best: C .039 (53 per 150 games/1350 innings) 1B .009 (12) 2B .033 (45) 3B .025 (34) SS .045 (61) LF .024 (32) CF .040 (54) RF .028 (38) In most cases, the "cut point" for where a player is accruing positive defensive value is around 55- so a player less than 55 at that position will end up with negative defensive value, while a player above that will end up with positive value. Of note, this is likely not true in an online league where savvy players are not running out 40 center fielders and are prioritizing good defensive players- in that setting, you probably need at least 60-65 at a position to end up with positive defensive value.