SRS, or Simple Rating System, is commonly considered the best box-score stat for measuring team dominance in the regular season. It's basically Margin of Victory, adjusted for the difficulty of opponent. Regular season SRS is more predictive of playoff success than regular season record. However, there is still valuable information in regular season record. For example, it is record that determines playoff seeding, not SRS, and of course seeding affects how difficult your playoff run will be.
There are teams that seem to consistently (slightly) outperform or underperform in their record vs SRS. These are teams that are better or worse at closing out close games, relative to their SRS. This can be found when a team’s actual record differs from their expected record based on their SRS.
The problem: since we’re dealing with small samples (1, 2, or 3 wins over/under the expected wins), most of the signal will be obscured by noise. But we can try to tease out the signal from the noise by 1) looking at years when there’s a significant difference between actual wins and expected wins then applying context, or 2) by looking at multi-year samples. Here, I’ve done the latter. Specifically, I’ve looked at the best players’ teams across 10-year primes to see how their actual record compares to their SRS-expected record.
Here are how the top players' teams look:
Player // # wins per season - # expected wins per season // # seasons outperforming expectations - # seasons underperforming expectations
Russell: +1.3 extra wins per season, 5 extra seasons outperforming expectations
Wilt: +0.1, 1
Kareem: -1.9, -6
Bird: +1.8, 5
Magic: +1.9, 6
Jordan: -0.1, 0
Hakeem: +1.8, 4
Shaq: +1.7, 6
Duncan: -1.6, -4
Garnett: +0.1, 2
LeBron: +2.0, 6
Curry: +0, 0
Putting players’ teams into tiers, we have
Teams perform better than expected: LeBron +2, Magic +1.9, Hakeem + 1.8*, Bird +1.8, Shaq +1.7*, Russell +1.3
Teams perform similar to expected: Wilt +0.1*, KG +0.1, Curry +0, Jordan -0.1
Teams perform worse than expected: Duncan -1.6, Kareem -1.9
*Hakeem rises above Magic if we shift his 10-year prime, falls below if not.
*Shaq rises if we shift his 10-year prime
*Wilt stays over KG if we use his younger 10-best years, falls below Curry if we use his older 10-best years.
The raw data: Wins vs Expected Wins
Spoiler:
Comments
How much can we take from this? Well, probably not too much. As above, the primary uncertainty comes from the fact that this measurement is so noisy. Still, there are additional sources of error:
-Systemic Error: Blowout games are known to make SRS less accurate. Do blowout games limit accuracy here? For example, high-SRS superteams might be extra likely (relative to their record) to have blowout victories, over-inflating their SRS relative to their record. Likewise, low-SRS lottery teams might be extra likely (relative to their record) to have blowout losses, under-inflating their SRS relative to their record. If so, then players on the best teams might be underrated and players on the worst teams might be overrated here (or vice-versa if the opposite were the case). We’d need to look across a larger sample of teams to find out.
-Potential Error: do injuries affect SRS and record in different ways? For example, if a teammate gets injured for one game, does that drop SRS by a smaller amount but make it more likely to lose that one game? (This may relate to resolution)
-Measurement Error: Resolution limits. You can have 6.05 SRS but you can’t have 60.5 wins. This limits how accurately we can compare record and SRS.
For potential next steps, we might try to address these errors (e.g. curving down the effect of blowouts / treating injuries more carefully), consider playoff data (where some teams may improve or worsen), or look more specifically at close games only. Or perhaps everything is too noisy to believe anything.
Regardless, it was still interesting to look at! And it could be argued to mentally ever-so-slightly curve-up the teams of prime LeBron, Magic, Hakeem, Bird, Shaq, Russell; mentally maintain the teams of prime Wilt, KG, Curry, and Jordan; and mentally curve down the teams of prime Duncan and Kareem. Or… perhaps not. The biggest change is only ~2.5% increase or decrease in games won compared to the expected wins, so it’s pretty small regardless.
What do y’all think? Is there any signal to find in this noise? How good are the best players’ teams at closing out games, relative to how good the teams are?
Probably not many! Which may point us back to taking these large ~10-year samples, or perhaps this would only give us a handle on smaller stretches where teams drastically over-performed or underperformed. 
