Okay diving in here
lessthanjake wrote:Is there a statistical basis for the higher views on Hakeem that some people have?
Yes, but it is probably not the sort of stat you're familiar using. And I think it's important to look at methodology here first..
lessthanjake wrote:AEnigma wrote:Well, RealGM crashed my post, so this will be kept briefer.
To start, WOWYR is a messy metric that can swing wildly with slight input adjustments or changes in approach, but all the same, Hakeem tends to post values similar to or even better than players like Duncan, Wilt, and Bird — and he has among the absolute best WOWY indicators.

And I think the bottom line is that the case for Hakeem is simply not really an advanced-metric-based case.
To be blunt here, an "advanced metric case" for a player pre-97(not named Jordan) is basically just the box-score as we do not have on/off. Unless you want to go off extremely noisy samples, there is the winning, there is how his team did with him and without him, and there is the box-score.
The "advanced metrics" you're thinking of(setting aside wowyr) are basically box-aggregates for Hakeem. The reason this is important to note is because those aggregates largely use block/steals to ascertain defensive value. Incidentally, when we cross-check box-aggregate scores with real-world impact, we find
A. Those aggregates consistently rate 2-way bigs lower than their impact would suggest(adjusted or "pure")
B. Those aggregates consistently rate higher guards than their real-world impact would suggest(adjusted or "pure")
C. Primary-paint protectors(big or otherwise) do much better by "winning" than they do by the box-score
The on-court reason for this as that smaller players aquire blocks/steals/rebounds often as a byproduct of what their bigger teammates do. There is also no way for a box-aggregate to penalize a bad gamble or to credit deterrence(when the presence of a big or a lebron/pippen esque wing prevents a shot from being attempted). This gets compunded when a stat like BPM actually gives a smaller player more credit for a block than they'd give a bigger player.
I can elaborate more, but the tldr is that when comparing two-way anchors with one-way anchors, the box-score will favor the latter which makes using it as an indication of a player being materially superior at generating wins wierd. It has utility with internal scaling and when you compare similar players, but Hakeem does not generate value the same way Jordan does.
It also so happens that despite being designed to be more stable, even advanced stats *with access to player-tracking and on/off still still score worse in predictivity and stability if they are not directly using an assessment of "winning" as a base(like RAPM).
Simply put, if the goal is to win and you are assessing players as contributors to winning, taking a two-way big and admoninshing them on the basis of RAPTOR(which doesn't even have on/off for hakeem) or BPM or even AUPM(which is BPM mixed with on/off) to an extent, you're probably underrated them.
With that in mind, I'm not sure exactly what you consider "high" but with "winning" Hakeem actually looks pretty comparable as a
rs player to the likes of Magic and MJ before we get to the playoffs where
-> Hakeem sees big box-improvement across the board
-> The Rockets as a team see big improvement
-> Hakeem beats a +10psrs team(per sansteere's top 100 teams calc) in his 2nd year(Magic beat one with way more help, Jordan has beaten one)
-> Hakeem's has the 2nd most wins as an srs underdog(Lebron is #1)
-> 2nd best winning percentage as an srs underdog among MVP's(Lebron is #1 again)
Consider Hakeem had the worst on and off court situation of the three by a landslide, consider it took until 92 for him to see his talents maximized schematically, and consider he played the most minutes of the three with no retirements in between, and I think you have a decent case for Hakeem being the best of the three(am actually considering he might have been but I'm not set there).
It also may not be "advanced" but such "real-world data" has certain advantages even if it there we had complete data for alternative impact metrics(we do not)...
-> Sample size. You can get much larger(per-season) samples of off(Ranging up to 82 full-games in a season).
-> Flexibility. You can freely make adjustments and curves as one seens fit. And if you know the direction a supporting cast improves, you can establish an upper-bound or lower-bound on a player's value(example: we set an upper-bound with Jordan by taking his 84 srs and subtracting it from the best regular season score the Bulls posted pre-triangle in 88, we take a lower-bound for Kareem's impact by taking what the Lakers were pre-trade and pretending they didn't lose a bunch of pieces to acquire Kareem)
-> Era-Adjustment. Being worth 7-points in 1969(Russell) is alot better than being worth 7 points in 88 or 2000. Metrics don't really adjust for that atm, you can(a simple way to do this is to track the difference between a player's team and their best possible opponents for a year or a period of years)
-> Real-world impact. Adjusted metrics like RAPM curve down outliers towards the norm. Super-valuable players tend to see their value misattributed to teammates
-> Rotation/Dependency. With real-world data we don't have to worry about wierd lineups or a team being caught off-guard with their best player leaving mid-game. You truly get to see how a team does without a key player.
-> No priors. Winning is noisy, but that noise can cut both ways.
All considered, while I can understand the temptation to dimiss that sort of "stat" as less sophisticated, there are advantages to keeping things "simple" which gets us to...
So there are a great deal of issues with WOWYR....
https://forums.realgm.com/boards/viewtopic.php?p=104353387#p104353387Think I cover things pretty thoroughly there but, quoting WOWYR's creator, here are they key ones:
In order to accurately solve for “what’s the most likely impact for Larry Bird on all of his lineups?” we need to know about the value of his teammates, like Reggie Lewis. And since Lewis only played a few years, his estimate is a bit fuzzy, and that in turn effects Bird’s estimate
Second, like any RAPM study that’s too long, it smoothes over differences between peak years, ignoring aging and injury. There are some ways around this — one of which is to use smaller time periods
Basically, two of the biggest advantages of WOWY/Indirect go away when we use WOWYR. Instead of 10-82 games from a season, you're working off 2(russell), 8(hakeem) or uh..,TBD with Jordan(as covered, it's never made clear if 94 or 95 are included).
The "adjustments" come from even tinier samples diluting the data further. And while it may be tempting to equate that to the adjustments made with RAPM...
Jaivl wrote:A regression is only as good as its data inputs.
WOWYR regresses RAPM using score differential by game, which is... at least 200 times worse than per-possession data in terms of granularity? (much worse than that actually)
It's an extremely ambitious and fun concept but its value is very limited, as shown by Ben himself... well, not really using it that much. I would just not use WOWYR unless it's for extremely rough classifications (i.e. "good" vs "bad").
EDIT: corrected by quarter -> by game
Incidentally WOWYR'S own creator barely features it in his writeups or videos.
But it’s just a bit surprising to me how high most people on this particular sub-forum seem to be on him, when I see his case as being less metric-based than most.
The forum is more "impact on winning" based. But the type of metrics you are bringing up are weighed less on this board than others specially because they are not well tied to winning. They were more frequently used a year ago, but since that period, I think there's been a decline in how seriously they've been taken, probably in part due to threads like the one I linked above.
History also favors Olajuwon. Going by winning, players who can anchor defenses consistently score as the most valuable and successful players with Russell running the 60's to an extent no player has since. Lebron, Duncan, and KG rule data-ball empirically, and the 70's was all Kareem's.
The most consistent winners were Russell and Duncan. Russell and Kareem experienced the most team success of any MVP.
Russell, Kareem and Lebron are the three biggest historical outliers by discernible "impact" whether you look at peak, prime, post-prime, pre-prime or pre-nba(using Lebron's college-age years for this comparison).
Hakeem is probably the most similar to Russell defensively(possibly excepting Davis) and is also an all-time post scorer.
Based on what usually happens, it would
make sense for Hakeem to be a league-best candidate and as it so happens, the largest data samples we do have suggest he was. Especially when it mattered most.