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Post by Ian Noble on Mar 9, 2018 9:49:19 GMT
I hate to be that guy... but this sample size is honestly too small to draw any sort of conclusions. You have Phoenix winning 7 games one season and 14 games the next. Denver wins 55 one season and 67 the next. with these huge variations, a sample of 5 doesn't actually give us enough data. How do we know which of these are outliers and which of these are normal? I don't want to create more work to figure this out, but I do think we shouldn't jump to conclusions. True, though in every single case, the maximum win total from the high strength tests is lower than the minimum win total from the low strength tests. The sample size is definitely small, but it's looking pretty good like something is going on here, even if we can't say for sure how large the effect is. Ian Noble how much work is it for you to post team stats along with this? That might give us some clues. Like, maybe strength is correlated with fouls, so 99 strength teams send their opponent to the line 50 times per game while 1 strength teams never send their opponent to the line. It would be interesting to see if we could find any sort of relationships like that. Yea I was thinking of doing just that - the team stats.  |
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Post by Ian Noble on Mar 10, 2018 14:23:06 GMT
Completed 34 seasons of testing Denver and Phoenix's Strengths swapped. The conclusions are a bit more encouraging. ResultsOnly a 3 win difference for Denver. 2.6 win difference for Phoenix. It still baffles me how every single team stats improves but the teams win slightly less games though. |
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Post by Andrei Kirilenko on Mar 10, 2018 14:32:12 GMT
Completed 34 seasons of testing Denver and Phoenix's Strengths swapped. The conclusions are a bit more encouraging. ResultsOnly a 3 win difference for Denver. 2.6 win difference for Phoenix. It still baffles me how every single team stats improves but the teams win slightly less games though. It appears Strength leads to committing a lot more fouls. Maybe opponents are getting more FTs and thus winning games? |
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Post by Andrei Kirilenko on Mar 10, 2018 14:33:27 GMT
And strength doesn’t seem to matter for how many free throws your own team gets. So the foul disparity could be leading to a lot more opponent FTs but not having any benefit on your own FTs.
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Post by Andrei Kirilenko on Mar 10, 2018 14:47:15 GMT
Denver with Denver strength averaged 20 less FTs per season and gave up 165 more fouls per season.
Let’s say each foul averages to 1.5 points... that’s 240 points more for your opponent, plus 15ish points less for yourself. So 255 point swing.
Over 82 games is roughly 3 ppg average swing per game. Seems reasonable that you would pick up 3 more losses, at least.
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Post by Ian Noble on Mar 10, 2018 15:04:20 GMT
Phoenix nevertheless leads the league in fouls
(Current D5 stats)
Team Fouls
Phoenix 1270
Dallas 1214
Detroit 1177
San Antonio 1124
Utah 1110
New Orleans 1087
Indiana 1079
Washington 1040
Boston 1039
Philadelphia 1038
Brooklyn 1020
LA 1004
Houston 975
Portland 959
Memphis 955
Denver 952
Miami 950
Atlanta 937
Orlando 933
New York 926
Cleveland 922
Chicago 896
LA 889
Oklahoma City 873
Charlotte 866
Milwaukee 860
Minnesota 834
Toronto 814
Golden State 780
Sacramento 722
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Post by Alex English on Mar 10, 2018 16:09:13 GMT
Yea strength seems to lead to less turnovers, but more fouls. Turnovers doesn't directly lead to points though, while more fouls does directly lead to more points for your opponent.
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Post by Ian Noble on Mar 11, 2018 11:23:19 GMT
It seems to me that a big issue with rectifying this 'Strength' rating issue is that, when Walt Frazier sets Strength ratings, the rating is based off subjective decision making - it can't be formulaic like 3PT%. So if the Strength Rating is going to be off-set by a small amount to account for the Win/Loss problem, it's going to be off-set compared to an amount that's plucked out of thin air anyway. |
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Post by Ian Noble on Mar 12, 2018 11:26:55 GMT
Looking in the Sim Engine file there is a FOUL hash table that might be worth editing.
Notice the key of the last rating jumps from 68 to 99. It might be worth decreasing just the last 99 value, or it might be better to scale back all the highest values.
RATING_FOUL{{39, 0.20f}, {40, 0.23f}, {41, 0.25f}, {42, 0.28f}, {43, 0.3f}, {44, 0.32f}, {45, 0.33f}, {46, 0.35f}, {47, 0.40f}, {48, 0.41f}, {49, 0.41f}, {50, 0.43f}, {51, 0.43f}, {52, 0.45f}, {53, 0.45f}, {54, 0.48f}, {55, 0.48f}, {56, 0.5f}, {57, 0.53f}, {58, 0.55f}, {59, 0.56f}, {60, 0.58f}, {61, 0.58f}, {62, 0.58f}, {68, 0.60f} {99, 0.69f}}
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