falcolombardi wrote:DraymondGold wrote:ty 4191 wrote:I was on the "Is Steph Curry Still Unappreciated" Thread and posted this:
As incredibly hyped as he's been, I still think he's perhaps still underestimated (in an ATG/historical sense):
All stats include the playoffs:
--Warriors since 2009-2010 without Curry playing: 76-134 (.362)
--Warriors since 2009-2010 with Curry playing: 643-328 (.662)
I challenge anyone to find a player with a really long career that has a bigger differential.
I was strongly encouraged to start a discussion just about this topic. I think it bears discussion.
So, who are the (other) most impactful players of all time, besides Curry, in terms of team winning percentage on/off or "WOWY"?
Huh, cool stat ty!

I did a similar WOWY estimation for Curry in the Greatest Peaks project (
https://forums.realgm.com/boards/viewtopic.php?p=100487575#p100487575)
It turns out there's different types of WOWY stats, just like there's different types of plus minus stats. It looks like you looked at how the record changes with and without a player -- but you could also look at how a team's point differential changes in games when a player plays vs when they don't. This is sort of like on-off stats, but here we're using margin of victory during a player's Games Played for the "on" sample and margin of victory during Games Injured/Rested as the "off" sample (rather than possessions played for the "on" sample and possessions rested for the "off" sample). In the link I posted above, I did an estimate (with a bit more uncertainty) for how Curry ranks all time, and he ends up 1st all time in this version of WOWY
The biggest issue is how to handle 2020; since Klay was also out for that year, the Warriors performed worse than if just Steph was out. So the two (lazy) options are to include 2020 but try to account for the fact that Klay was missing, or use the other non-2020 years. (or you could do a full regression to get the actual number, but that's a pain, so I'll just wait for Thinking Basketball to post it eventually).
Here's the all-time rank for 10-year prime, according to WOWY:
1. 2012-2022 (no 2020) Curry: +10.3 (with more uncertainty, since this is an approximation)
1. 2013-2022 (with 2020, but adjusting for Klay's absence): +10.2 (with more uncertainty, since this is an approximation)
2 tie. Prime Russell: +9.4
2 tie. Prime Robinson: +9.4
2 tie. Prime Nash: +9.4
5. Prime Magic: +8.3
Jordan's 8th all time, and LeBron's a bit lower after that. WOWY's definitely a noisy stat, but it's still interesting to see. The biggest trends I've noticed are that WOWY tends to rank playmakers very highly (over play finishers / iso scorers), as well as defensive anchors (over perimeter defenders). My guess is because playmakers and defensive anchors are harder to replace in a night-to-night gameplan, they end up being missed more in the games they miss.
As others have pointed out 10 year samples can be incredibly noisy even if the amount of games is decent cause the "control" in the study (the teammates and rival quality) can wildly change fron a missed game one season to a missed game 8 years later.
Seems like focusing on single seasons with a big missed game sample (10+ at least imo) or full seasons "before and after" a player may be more useful
Example russel leaving the championship celtics in 70 (past his prime to boot) and the team falling to 30 wins. A drop off comparable to the 99 bulls losing pippen, jordan, rodman and phil jackson
Hiya falcolombardi!

I have some agreements, and some disagreements. Let's go for where I disagree first:
The pushback: You suggest that long-term WOWY studies are too noisy, because it's too difficult to control for the teammate and opponent quality. To be blunt: I definitely disagree. We've been controlling for teammate and opponent quality for two decades now... otherwise getting from on/off to Adjusted Plus Minus or RAPM would be impossible. Controlling for teammate and opponent quality is the very thing we do when taking on/off data and calculating APM or RAPM.
It turns out you can do the same treatment with WOWY data. For example, you might use per-game SRS instead of MoV to account for opponent quality, and you might use a regression to find WOWY for every player on your team to account for teammate quality in games when multiple teammates sit out. These are the kind of corrections that Thinking Basketball actually applies when calculating 10-year Prime WOWYR. So to reiterate: WOWY
R does indeed correct for opponent and teammate quality, just like RAPM does.
The agreement: That said, these kinds of corrections for teammate/opponent quality are difficult for people who just want to do a back-of-the-napkin approximation without using a bunch of code to solve a massive regression problem. As I openly admitted in my Curry WOWY estimation (see the link in my last post), I didn't do a careful consideration of varying opponent/teammate quality specifically because the problem gets a lot harder, which leads to the greater uncertainty I mentioned.
When people want a quicker alternative to the full teammate/opponent correction, I definitely agree that it can be good to look at scenarios where a player misses a lot of time (e.g. some late 60s years for Jerry West), or when a player has just been drafted/traded/retired.
But: my one caution for this latter method (using single-season samples when a player is drafted/traded/retires) is to make sure you're doing an apples-to-apples comparison. Looking at when Russell retired after 69 vs when Jordan retired after 98 might tell you something about the WOWY value of 68 Russell and 98 Jordan, but that doesn't necessarily apply to 64 Russell vs 91 Jordan. The nice thing about 10-year samples is you're more likely to be comparing apples-to-apples (Russell's 10 year prime vs Jordan's 10 year prime).
And as people have mentioned, you want to be careful to consider context either way... for example, Stockton' only missed 22 games in his 10-year prime (and they only came at the start/end of his prime), so Stockton's off sample might be extra noisy/wonky.
AEnigma wrote:DraymondGold wrote:Here's the all-time rank for 10-year prime, according to WOWY:
1. 2012-2022 (no 2020) Curry: +10.3 (with more uncertainty, since this is an approximation)
1. 2013-2022 (with 2020, but adjusting for Klay's absence): +10.2 (with more uncertainty, since this is an approximation)
2 tie. Prime Russell: +9.4
2 tie. Prime Robinson: +9.4
2 tie. Prime Nash: +9.4
5. Prime Magic: +8.3
Jordan's 8th all time, and LeBron's a bit lower after that. WOWY's definitely a noisy stat, but it's still interesting to see.
This is Ben’s (well, not strictly Ben’s, but he is the one who posted it) “Game-Level Adjusted Plus/Minus” (GPM) metric, not WOWY or even his own WOWYR (or its various iterations).
https://thinkingbasketball.net/tag/wowyr/
You're quite right! I used GPM over WOWYR because GPM's a bit more of a "pure"/simple statistic (at the possible cost of being a little noisier/less consistent), so it was closer to my ballpark estimation for Curry. I mentioned that the list is from GPM in the post I linked. Perhaps I could have used just WOWY instead of GPM or WOWYR (which is sort of parallel to using on/off instead of APM or RAPM), but I wasn't sure where to find a list of Prime WOWY.
Which leads me to my second question...
AEnigma wrote:Purer “prime” WOWY is more like (Curry? >) Garnett > Lebron > Shaq > Nash > Bird > Hakeem > Magic > Robinson > Duncan > Kobe > Jordan. With the acknowledgment that the purer form is even more variable, it does still correlate reasonably well to longer RAPM and on/off studies, with Lebron, Garnett, and Shaq (and Curry) maintaining as the top ~ten-year prime performers since 1994/97.
Thanks for the Prime WOWY list!

Do you mind sharing the link? The only link I found was for Prime WOWYR and Prime GPM.
Dutchball97 wrote:DraymondGold wrote:...
I think this possibly shows a flaw with building your entire defense or offense around one person because the moment they go to the bench it all falls apart. I do wonder how often this is by design (not investing much in a back-up because you want to play your main man as much as possible anyway and you still need to invest elsewhere too) or because of there simply being a shortage of good playmakers and defensive anchors available as back-ups. I feel like on/off stats could really benefit from the context of whether someone is breaking the stat because the team is built around them and their back-ups are terrible or if they're destroying the on/off stats despite having capable back-ups.
Strong agree here!

it would be fantastic to have some more consistent way of telling how much plus minus is from terrible/ill-fitting back-ups or not.
[not to retread the oft-repeated LBJ-MJ debate, but this ties into the discussion from that '5-year On/off Study data for LBJ/MJ' thread a few months back.... MJ has a better 'on' numbers than LBJ, but LBJ's teams have a massively worse 'off' numbers. This gives LBJ better overall on/off, but one could argue that it's just because LBJ's teams had worse-fitting backups than MJ. Anyway...]
I do think at least some of WOWY's preference for playmakers/defensive anchors is from a shortage of good backups, more than "by design" as you say. Imagine you're on a Steve Nash team and Nash is sitting for one night. Nash pretty clearly runs your entire offense when he's on the court. So what do you do when Nash sits?
Option A: Adjust your rotation. You can have your bench point guard (e.g. Marcus Banks) go from ~11 minutes per game to ~35+ minutes per game, hope he survives the minutes, and hope the rest of the starting lineup adjusts to having a different primary playmaker.... but this is pretty clearly a poor idea.
Option B: Keep your rotations fairly steady, but redesign the offensive scheme of the starting lineup to adjust for the missing Nash. Perhaps you have a combination of more playmaking from Barbossa and Diaw, along with more iso from Amar'e. This is also a pretty poor idea if Nash is missing for just one night, as it can be pretty hard to change an entire offensive scheme overnight.
Option C: attempt some combination of A and B, but end up playing terribly and lose the game.
Most teams probably end up with option C. This will increase Nash's "off" sample in WOWY, thus giving him better WOWY numbers. You can imagine a similar process happening for other offensive playmakers and defensive anchors/leaders. My guess is this is (at least partially) why WOWY likes these kinds of players so much.