eWins and other accrediting systems (MikeG, 2010)
Posted: Fri Apr 15, 2011 9:40 am
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Author Message Mike G
Joined: 14 Jan 2005
Posts: 3615
Location: Hendersonville, NC
Posted: Mon Sep 24, 2007 6:43 am Post subject: eWins and other Individual Wins accrediting systems
(This thread is a spinoff from another.) I'm feeling prompted (again) to ask a rather open-ended question. In placing individual (player) accountability for (team) wins, should individual wins add up to... 1)... actual team wins? 2)... team statistical performance, i.e., pythagorean expected wins? 3)... neither? I think WS does #1, and PW shoots for #2. When I did eW, I didn't know if either was the better target. If you are considering individual wins (IW, to be generic) to be a stat that players accumulate, then the best teams -- which may win 2-3 times as many games as the worst teams -- might have 2-3 times as many IW distributed among their rosters. But an elite team may only score 15-20% more points (as differential) than a cellar-dwellar. All the things that go into point diff -- TO, Reb, Ast, Stl, Blk... -- are generally also within a similar range. If IW are a quantity of something real, and the bottom-line team quantities -- points scored -- are within 20% of one another, then is it practical to suppose players on a weak team are really only generating half (or less) of something than those on better teams? The pat answer is, "They're generating only a fraction of the wins". Sure, but the stats they generate indicate that they're making their team more competitive, more often within striking distance, with a good rally or defensive outburst. In fact, we might define all player contributions as being stratified into levels that (1) make their team less terrible, (2) make them competitive, (3) propel them to wins. I propose that any system forcing player IW's to sum to team wins (or PythWins) requires artificial support to do so. Players are deemed to be from excellent to terrible on defense, basically. Yet the same players don't carry over their excellence (or lack thereof) from good teams to bad teams. This doesn't seem intuitively believable to me. The eWin system doesn't suppose that a players' defense becomes many times better or worse when he changes teams. They also don't add up to team wins. Team eW still add up hierarchically so that the best teams are best. But they aren't 2-3 times as good as the bottom teams; only some 50-60% better. Everyone has a different intuitive sense of 'good' and 'bad'. At one time, a 40% FG rate was 'good'. At this point, I won't even get into 'individual losses'._________________` 36% of all statistics are wrongLast edited by Mike G on Mon Sep 24, 2007 10:02 am; edited 1 time in total
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deepak
Joined: 26 Apr 2006
Posts: 665
Posted: Mon Sep 24, 2007 10:01 am Post subject:
Quote:
If you are considering individual wins (IW, to be generic) to be a stat that players accumulate, then the best teams -- which may win 3-4 times as many games as the worst teams -- might have 3-4 times as many IW distributed among their rosters. But an elite team may only score 15-20% more points (as differential) than a cellar-dwellar. All the things that go into point diff -- TO, Reb, Ast, Stl, Blk... -- are generally also within a similar range. If IW are a quantity of something real, and the bottom-line team quantities -- points scored -- are within 20% of one another, then is it practical to suppose players on a weak team are really only generating half (or less) of something than those on better teams?
Aren't you assuming that IW can be formulated as a linear combination of box score stats? As I see it, wins are only indirectly determined by such stats. Something like: stats -> point diff, possessions -> estimate for wins Edit: Hmm, nevermind. I misunderstood your point.
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Mike G
Joined: 14 Jan 2005
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Location: Hendersonville, NC
Posted: Mon Sep 24, 2007 10:19 am Post subject:
Yes, if I understand what you're saying. eWins takes boxscore stats, scales them to Team/Opponent productions, and then predicts Wins non-proportionally. Expected team wins (for an 82G season) are: xW = eW*2 - 41 So a 61-win team typically totals 51 eW. A 21-win team totals 31 eW. The good team isn't 3X as good as the bad one, but only 1.65 times as good. Here, 'good' is effectively defined as 'total talent above replacement level'._________________` 36% of all statistics are wrong
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Mountain
Joined: 13 Mar 2007
Posts: 1527
Posted: Mon Sep 24, 2007 10:24 am Post subject:
An Individual Win metric probably should compare to league average or replacement level on stats or to average or replacement level player. I'd be wary of one that didnt and didnt fully. It is the difference from these baselines that affects winning and losing not the total stat level or total player level. EWins compares to replacement player. From your formula in the other thread it looks like a T=15+ for 2000+ minutes starts to contribute eWins. Not sure if T=15 is at or above/below mean or how closely eWins tracks with PER but does it in fact boil down to saying it takes a statistically above average player to contribute individually to wins? In reality players are the sum of their individual stats and team effects above and beyond those individual stats. Dan's overall +/- has both (and from offense and defense) with individual generally the far heavier weight though it probably varies by type of role player. The pure +/- tries to capture the uncounted team effects. This metric appears comprehensive in scope. Berri's Wins Produced uses league average performance on shooting. That isn't a terrible choice in itself but maybe the mistake is the mix he sets it in, one that doesnt not do the same for rebounds, etc. at least for Wins Produced. His PAWS/min uses replacement player. PAWS/min is more palatable to me as positional average performance is a main design feature and the shooting formula decision at least hits all the players at the position the same but it might be more acceptable to many here to re-run Berri's formula with shooting break-even at replacement player shooting level or some more neutral or statistically driven level. Anybody done or interested in doing this? Berri's metric does incorporate the impact of overall team defense on scoreboard but in a crude equal way (something PER is lacking, but just as crude as player W-L off of OR and DR ratings). Is it missing the offensive team effects of players or is that getting mixed in with the "team adjustment"?Last edited by Mountain on Mon Sep 24, 2007 10:39 am; edited 3 times in total
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deepak
Joined: 26 Apr 2006
Posts: 665
Posted: Mon Sep 24, 2007 10:32 am Post subject:
I think this really depends on what we're trying to describe: (a) Do we want to measure how much credit a player should get for his team's success? If so, then it makes sense for the IWs to add up to team wins (or expected team wins). (b) Or do we want to measure player performance, irrespective of his team's success? If so, then the eWins system makes more sense to me. More practically, I think we'd like to know how much a player would contribute to the success of a future team. That is, if I have a new roster I put together, how successful can I expect this team to be, and how much would each player contribute? For this purpose, which type of metric would be more useful -- (a) or (b)?
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Mountain
Joined: 13 Mar 2007
Posts: 1527
Posted: Mon Sep 24, 2007 10:49 am Post subject:
The 2:1 ratio of wins / statistical performance difference you observe with EWins Mike, I have observed with team minutes weighted tendex and team PER too so this appears to a rough universal rather than system specific. And caused by crediting possession affecting actions as well as scoring actions. I think Nick S spent a good of time talking about accounting and touches on this.
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Mike G
Joined: 14 Jan 2005
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Location: Hendersonville, NC
Posted: Mon Sep 24, 2007 10:56 am Post subject:
Mountain: Of course average players contribute to wins. Replacement T was figured at 11.7 last year; over 400 players met this level, 13-14 per team. All contribute a net positive. The 30 top 'sub-replacement' types (in minutes played) averaged 37%TS. 30 guys around 11.7 (15+ and 15-) averaged .433. Last I checked, a PER of 15 was roughly equal to a T of 26. This varies from team to team, as T rates actually correspond to team strength. Deepak: eWins ranks players on a given team; thus gives due credit for that team's success. It also gives a Kevin Garnett (great player/terrible team) with more 'credit for success' than a Jason Terry (good player/great team) -- since KG takes an otherwise-NBDL lineup and makes them competitive -- unlike some other IW systems. If you are building a team and adding last year's player eW rates (properly allotting minutes/positions), you will do very well in predicting this year's wins. PW and WS, as far as I know, make no claim along these lines; much of their credits are tied up in 'team defensive' schemes. Remember, eWins is very cognizant of team success. The factors of Tm/Opp Pts and Reb are what distinguish it from others. But the scaling is much less drastic than what is found in W-L records._________________` 36% of all statistics are wrongLast edited by Mike G on Mon Sep 24, 2007 11:10 am; edited 1 time in total
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Mountain
Joined: 13 Mar 2007
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Posted: Mon Sep 24, 2007 11:07 am Post subject:
Mike, my bad, I was thinking of wins against an average team level, 41, (as in some metrics I have worked on conceptually) rather than wins period. Certainly players below average will contribute to wins period. Different scale. So a TS+26 playing starter minutes would contribute somewhere in the range of 6-8 wins. that makes sense. I like the innovative features of EWins, hence supported scoring it against other more widely publicized measures.Tm/Opp Pts does incorporate shot defense (with everything that affects opponent points), though the team defensive result is assigned to all equally, correct (as in some other systems)? Would you have any interest in modifying to base it off of say a 50% weight of team opponent scoring and 50% estimated counterpart scoring? Giving EWins another distinction, that perhaps puts it closer to what is happening by recognizing at least some- call it half to start- of shot defense is local?Last edited by Mountain on Mon Sep 24, 2007 2:19 pm; edited 1 time in total
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Mike G
Joined: 14 Jan 2005
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Location: Hendersonville, NC
Posted: Mon Sep 24, 2007 12:13 pm Post subject:
Mtn, I greatly appreciate the shout-out, as I don't really think eWins is 'well known', unless you are a thorough reader of these forums. Also thanks for reminding of Nick S's work a few weeks back; I was heavily curious where he would take that. Dan D (Statman) is another to watch. But I'm very skeptical of 'counterpart' effects. The Spurs don't match up with others' positions, and they're the flagship franchise of the NBA. Coaching quirks are unpredictable. Players don't have positions, on O and on D, in my view, and the best players will always be just Players. Fixing things at the 90% level is a lot closer to 100 than to 50. That's how I think of team effects: You can go to many times more work for the next few % of accuracy. You still win by outscoring your opponent, and the points-ratio is what determines wins._________________` 36% of all statistics are wrong
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NickS
Joined: 30 Dec 2004
Posts: 384
Posted: Mon Sep 24, 2007 12:24 pm Post subject:
Mike G wrote:
Also thanks for reminding of Nick S's work a few weeks back; I was heavily curious where he would take that.
Thanks for reminding me that I'm not forgotten. I have been meaning to do some additional work on that before the season starts, but work keeps interfering. My argument for a system based on "player wins" adding up to expected wins rather than actual wins was made here and was relatively simple: "The argument for using "expected" is that it keeps everything on the same "scale". So two teams with the same defensive eFG% will get credit for the same number of "wins" from their eFG% defense." "The other reason is that if someone calculates this in-season, expected wins are probably a better predictor of future success than actual wins particularly over a small sample size (in other words, if you calculate the numbers after 10 games, and two teams are both 6-4 but one team has a +8 point differential and the other team has a +0 point differential, the differential is a more accurate measure of ability than record)" I would add to that the idea that expected wins is a better way to compare the strength of teams historically and, therefore, a better way to compare the performance of players from different seasons.
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Mountain
Joined: 13 Mar 2007
Posts: 1527
Posted: Mon Sep 24, 2007 12:36 pm Post subject:
Ok Mike, I understand your perspective. I've shared my perspective about adding individual shot defense enough. DCS has it. I will look to that more and maybe create my own version of it later.
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Mountain
Joined: 13 Mar 2007
Posts: 1527
Posted: Mon Sep 24, 2007 1:06 pm Post subject:
Well Mike, EWins goes primetime with Henry Abbott's mention of it and link to this board about it this morning. If folks haven't seen it yet: http://myespn.go.com/nba/truehoop Dan and David's presentation gets more publicity and discussion too. (And in a bankshot WARP as presented by DW might get some exposure.) P.S. I found this formula in the mentioned player ranking thread that covers EWins T = Sco + .98*Reb + 1.335*Ast - .25*PF + 1.5*Stl - 1.5*TO + 1.75*Blk Still accurate?
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mateo82
Joined: 06 Aug 2005
Posts: 211
Posted: Mon Sep 24, 2007 5:02 pm Post subject:
Well, I would think it would have to measure expected wins, since the difference between expected wins and actual wins is essential chance
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Mike G
Joined: 14 Jan 2005
Posts: 3615
Location: Hendersonville, NC
Posted: Tue Sep 25, 2007 7:10 am Post subject:
mateo82 wrote:
Well, I would think it would have to measure expected wins, since the difference between expected wins and actual wins is essential chance
Chance, or 'tanking'. How 'bout them Celtics? -- shoulda won 32 games but only won 24. WS total 24 (X3), while PW total 32. The difference is significant. Mtn, those are one version of the weights to arrive at T. In playoffs, they can change quite a bit; for seasons, pretty close to what you have (1.5 for blocks is more typical, and .99 for Reb.) The weights change a bit for 'best fit' between wins and eWins. Other parameters also change, within some limits._________________` 36% of all statistics are wrong
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Mountain
Joined: 13 Mar 2007
Posts: 1527
Posted: Tue Sep 25, 2007 12:31 pm Post subject:
Thanks for sharing Mike. It will take some time to look at. If I have any observations or questions that might be worthwhile I'll pass them along later.
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Author Message Mountain
Joined: 13 Mar 2007
Posts: 1527
Posted: Tue Sep 25, 2007 3:22 pm Post subject:
On EWins formula my initial reaction is assists weight is higher than my past practice / prejudice but I'll have to go back and look at all the measures of assist impact and reassess. The spreadsheet is large with many formulas and I certainly haven't mastered them (and may not) ... but I did a quick compilation of EWins for 6 main Sonics last season and put them in a table with WinShare scores at basketball-reference.com and Wins Produced. To normalize them I pro-rated the EWins and WinsProduced scores from their expected wins basis to a pro-rated version of actual wins (ok or disagree?). WinShares are based on actual wins but I divided by 3 to get Wins. Wins Produced allows negative scores and that helps account for its higher scroes for the best players, at least partially. For what it might be worth to the discussion I present this data: prorated to actual W WShares WProd EWins Average allen,ray 5.3 8.1 6.2 6.6 lewis,rashard 6.3 7.8 6.3 6.8 wilcox,chris 5.3 5.3 5.5 5.4 ridnour,luke 2.0 1.9 2.9 2.3 collison,nick 4.0 5.1 3.7 4.3 watson,earl 1.7 3.2 2.5 2.4 Score/Avg for blend WShares WProd EWins allen,ray 0.81 1.24 0.95 lewis,rashard 0.93 1.15 0.93 wilcox,chris 0.99 0.99 1.02 ridnour,luke 0.88 0.83 1.29 collison,nick 0.93 1.20 0.87 watson,earl 0.68 1.30 1.02 Anyone have comments or questions about these results? Obviously a full league correlation study amongst these (and possibly others) could be done to try to identify why they move the way they do and in relation to each other. Going multi-year would add robustness. But at the surface they track fairly closely and in line with my subjective guesses before I looked up the values. The existing tools may be pretty good for first cut purposes.Last edited by Mountain on Wed Sep 26, 2007 12:15 pm; edited 1 time in total
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Mike G
Joined: 14 Jan 2005
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Location: Hendersonville, NC
Posted: Wed Sep 26, 2007 6:13 am Post subject:
I do weigh Ast rate more heavily than Sco or Reb rates. This is made possible (still makes better correlation between eW and PythW) by a couple of factors: -- There's an estimate for players % of FG unassisted. Players' Sco rates are boosted (or depressed) by whether this % is more or less than average. -- Ast rates are moved by the factor (TmPts/OppPts)^1.5 This 2nd factor makes Ridnour's Ast rate 5.61, rather than 5.69; and he has .04 fewer eWins on the year. Assists are important as a proxy for lots of essential actions which do not become boxscore stats: bringing the ball up, spacing the floor, and of course all the passes that aren't assists (because the receiver either passed or missed)._________________` 36% of all statistics are wrong
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Mountain
Joined: 13 Mar 2007
Posts: 1527
Posted: Thu Dec 11, 2008 12:38 pm Post subject:
How do the top teams look on eWins distribution by player or by minutes weighted position? Ever calculate regular season league averages for teams or just playoff teams or top 4 or recent champion averages? Or for scoring, rebounding and assist rates? How about similar distributions for other metrics? Any advocate / user of them want to share these?
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jkubatko
Joined: 05 Jan 2005
Posts: 702
Location: Columbus, OH
Posted: Thu Dec 11, 2008 2:33 pm Post subject:
Wow, resurrecting a thread that's been dead for almost 15 months. That might be a record or something._________________Regards, Justin Kubatko Basketball-Reference.com
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Mountain
Joined: 13 Mar 2007
Posts: 1527
Posted: Thu Dec 11, 2008 3:46 pm Post subject:
Nope. Now this thread didn't need to be resurrected but I went looking for old threads because there is good stuff in the archives worth recalling and eWins is a worthy topic folks occasionally ask for more background on and in this case the title fit with my comments so I just went with it. In what other field of research would referencing a conversation from 15 months ago be treated as unusual or unwelcome? Is always staying in the moment and the chatter of the few days being argued as preferable / better?
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Mike G
Joined: 14 Jan 2005
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Location: Hendersonville, NC
Posted: Fri Dec 12, 2008 7:40 am Post subject:
Mountain wrote:
How do the top teams look on eWins distribution by player or by minutes weighted position? Ever calculate regular season league averages for teams or just playoff teams or top 4 or recent champion averages? Or for scoring, rebounding and assist rates?
eWins gives credit to players, for their team's wins. A team's eWins can be guessed by the formula: eW = (pW + 41)/2 - where pW is pythagorean. Ranking teams by Sco, Reb, and Ast could be done by checking their PtDiff, Reb% and Ast%, I think. I've never used team rates in those categories. You can download this year's file and play with it, sort by position, etc. Not sure what you're asking about, at the top._________________` 36% of all statistics are wrong
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Neil Paine
Joined: 13 Oct 2005
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Location: Atlanta, GA
Posted: Fri Dec 12, 2008 11:06 am Post subject:
Refresh my memory, what's the rationale behind this part? Quote:
eW = (pW + 41)/2
Shouldn't eW = pW? Or eW = W?
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Mountain
Joined: 13 Mar 2007
Posts: 1527
Posted: Fri Dec 12, 2008 3:11 pm Post subject:
I am basically wondering about team structure or DNA as I have in the past with types but now thinking about it in terms of impact independent of style of play. Do the top teams have a certain. frequently similar distribution of eWins contributed by players down the ranks from the stars to the first line bench guys? I think it is also worth checking if there is a similar distribution for successful teams by where the eWin contributors actually play, where the major impacts come from by position. Calculating regular season league averages for teams or just playoff teams or top 4 or recent champion averages would give information to assess whether a certain type of eWin contribution or position pattern where the contributions come from appears to matter. Looking at scoring, rebounding and assist rates would be taking that pattern analysis / recognition exercise deeper into the details. Maybe the structure of impact thru the rotation or position don't matter or matter much. Maybe it is just get edge wherever you can. But I'd guess that probably the structure of today's game will give an edge to some designs over others, so why not look and try to understand the patterns better than anybody else and make your best educated guess on the pattern to choose or tweak what you've got and can get it in that direction as far as you can. This could and should (in my mind) by done with offensive/defensive adjusted splits and net counterpart data and could be done for other box-score based metrics too if you prefer one of them to eWins or just want to study and see as much as you can. Maybe I'll work thru it using your file Mike, maybe not. Checking what you've done and throwing the idea out there for any interested. I assume this type exercise gets done in the best analytic shops. I would do it if I had that role. The distribution of contributions has to be considered in the context of 5 man lineups and the rotation. That is where the rubber meets the road. So then you get back to needing the adjusted 5 man lineup data I advocated some for, Eli produced a first cut of before getting snapped up and brought inside. Roland at 82 games & with a team and perhaps other insiders may have it as well. That is probably the most important data out there or out there to get for this team game. Or at least the most important supplement to the rest of what is out there in public. How important is context for impact, all told? I assume it is more than enough to make the difference between winning a title and losing the conference finals. If so then it is vital. I don't think just summing individual stats produces essentially the team result or is the sufficient projection / planning approach. The last few (or even more than a few) points influenced by context demand context based analytics.
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Mike G
Joined: 14 Jan 2005
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Location: Hendersonville, NC
Posted: Sun Dec 14, 2008 5:05 am Post subject:
davis21wylie2121 wrote:
Refresh my memory, what's the rationale behind this part? Quote:
eW = (pW + 41)/2
Shouldn't eW = pW? Or eW = W?
No, eW = Equivalent Wins a player adds to a hypothetical average team. The rationale is that when I add a team's player eWins, it just happens that pW = 2*eW - 41 One system that ties player wins to team wins is Win Shares. Recall that players for the Celtics last year were all on bad teams the year before. Here are some WS and eW, per 484 minutes; and a 'prediction' based on their actual 2008 minutes x their 2007 win-producing rates: Code:
eWins/484 eW? Min WS/484 WS? Celtics 2007 2008 Pre08 (2008) 2007 2008 Pre08 Pierce 1.86 1.85 11.1 2874 1.50 2.05 8.9 Allen,R 1.62 1.31 8.8 2624 1.37 1.75 7.4 Garnett 2.22 2.50 10.7 2328 1.70 2.62 8.2 Rondo 0.74 1.24 3.5 2306 0.63 1.49 3.0 Perkins 0.45 1.14 1.8 1912 0.43 1.54 1.7 totals: 35.8 12044 29.3
eWins says the youngsters improved dramatically, while the vets were pretty much the same (Ray cancelling KG). WS says everyone improved stupendously, in their win-producing attributes. Of course, in retrospect we know the defense improved a lot, chemistry was superb, etc. But without knowing those specifics, we can look at the totals at the bottom. Note that the minutes has about 7000 unaccounted for in this short list. eWins (predicted) is 6.5 more than WS. This is really as much as 13 more wins expected (as in 2*eW-41) from just these 5 players, without any change in previous win rates. Because WS are depressed for players on bad teams, there's no built-in way to predict wins when these players are gathered together to form a much better team -- is there?_________________` 36% of all statistics are wrong
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Neil Paine
Joined: 13 Oct 2005
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Location: Atlanta, GA
Posted: Sun Dec 14, 2008 1:41 pm Post subject:
I think you're confusing ability with value again... The "wins a player adds to a hypothetical average team" would fall under the category of ability, an attempt to completely remove the player from his actual context and drop him into a different context. So in this sense, eWins is apparently trying to measure ability. Win Shares wants to measure value -- and the sum of a team's players' "wins added" must be tied to the actual # of wins (real or pythagorean) the team produced in reality. In a value measure, it makes absolutely no sense to artificially allocate more wins to a bad team's players (or less to a good team's ones) than the team actually won in real life. The whole must (roughly) equal the sum of its parts. So, as it turns out, comparing eW to WS is like comparing apples and oranges. And I don't think I realized this until right now.
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Mike G
Joined: 14 Jan 2005
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Location: Hendersonville, NC
Posted: Sun Dec 14, 2008 2:11 pm Post subject:
davis21wylie2121 wrote:
.. an attempt to completely remove the player from his actual context and drop him into a different context..
Actually, the opposite. E-Wins isn't tied to context, but is a universal expression of Value, independent of context. If a player's value is only relative to where he played in a given season (or part-season), what does that tell us about his value? Not much, I think. If you drive a car across the Plains and get 35 mpg -- and it's known that you had a tailwind averaging 20 mph -- wouldn't it be worth knowing what your car's mpg is in the absence of wind? Or into a 20 mpg headwind? The fleeting 'value' of your high-mpg car might be a useful quantity to quote, if you're trying to sell your car. But by accounting for the context (of the tailwind), one gets a more accurate description. A role player on a great team may shop himself around the league and get paid more by a lesser team. Does his 'value' decrease, if equal production creates fewer WS? Team eWins rank teams in just the same order as PythWins rank them. There's no artificial adjustment made. Player wins don't sum to team wins. The thread starts with these inquiries. The whole does equal the sum, in context._________________` 36% of all statistics are wrong
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Mike G
Joined: 14 Jan 2005
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Location: Hendersonville, NC
Posted: Sun Dec 14, 2008 2:26 pm Post subject:
Try this thought experiment. You and I and 2 other guys are playing games of 2-on-2. We are all equal players (ability, value), and we split 20 games, 10-10. We all have essentially equal WS, eW, whatever: Just about 5.0 apiece. Then your teammate gets hurt. To continue our 'league', you draft a guy who is just a stiff. He can do very little to contribute. We double team you, and make him miss his occasional shot by yelling at him. Now it's very difficult for you to win a game. You may win one of 20, because we were hung-over perhaps. In 20 games, you may get 20% more points, taking 80% more shots; double your turnovers, etc. By most measures you've been more productive and less efficient. But eWins says you're the same player you have been. Yet, your win shares have plunged to nearly zero. Some ratings would have you negative. Has your 'value' gone to near-zero? Your team might total 5.5 eW in 20 games, to my team's 14.5 . eWins : 5.5*2 - 10 = 1.0 In other words, by just maintaining your productivity, with a teammate about 1/10 as productive, your team is expected to win 1 game in 20. And your 'value' is constant; as (I think) it should be._________________` 36% of all statistics are wrong
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jkubatko
Joined: 05 Jan 2005
Posts: 702
Location: Columbus, OH
Posted: Sun Dec 14, 2008 2:27 pm Post subject:
Mike G wrote:
One system that ties player wins to team wins is Win Shares. Recall that players for the Celtics last year were all on bad teams the year before. Here are some WS and eW, per 484 minutes; and a 'prediction' based on their actual 2008 minutes x their 2007 win-producing rates: Code:
eWins/484 eW? Min WS/484 WS? Celtics 2007 2008 Pre08 (2008) 2007 2008 Pre08 Pierce 1.86 1.85 11.1 2874 1.50 2.05 8.9 Allen,R 1.62 1.31 8.8 2624 1.37 1.75 7.4 Garnett 2.22 2.50 10.7 2328 1.70 2.62 8.2 Rondo 0.74 1.24 3.5 2306 0.63 1.49 3.0 Perkins 0.45 1.14 1.8 1912 0.43 1.54 1.7 totals: 35.8 12044 29.3
Wait a second... You've already said pW = 2 * eW - 41. So using the numbers above, doesn't that mean that eW suggests that this team would be projected to win at least (2 * 35.8) - 41 = 30.6 games? And isn't that very close to the Win Shares projection of 29.3 wins?_________________Regards, Justin Kubatko Basketball-Reference.com
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Neil Paine
Joined: 13 Oct 2005
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Location: Atlanta, GA
Posted: Sun Dec 14, 2008 2:34 pm Post subject:
This is what I'm trying to say: There is no such thing as a "universal expression of Value". That's called "Ability". Value embraces context (if a player is on a bad team, so be it), while ability rejects it. I hate to break it to you, but if you're attempting to show how many wins a player produced on a theoretical average team, that's an ability metric, not a value metric, because you've tried to remove a player from his actual context.
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Neil Paine
Joined: 13 Oct 2005
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Location: Atlanta, GA
Posted: Sun Dec 14, 2008 2:49 pm Post subject:
If I may quote Ed Kupfer for a moment: Ed Küpfer wrote:
Imagine a two-on-two tournament. The favoured team is comprised of one mediocre player and one player so great, he ranks among the best of all time. Now imagine that every opponent is determined not to let the great player beat them, that they will double-team him continuously and force the mediocre player to shoot. Now, because of the double-team, the mediocre player has no one defending him, and scores pretty much at will. Opponents, still fearing the great player's awesome talent, stay with the double-teams, and keep hoping that the mediocre will miss, which is unlikely since they aren't really defending him. Now, regardless of how the team fared in the tournament, the stats will show that the mediocre player contributed far more value than the great player, becuase, as it turned out, he was the one taking—and making—all the shots. Our stats will give the mediocre player the MVP. This is the way it should be. Just remember that most valuable does not mean most talented.
Pertaining to this discussion, eW is apparently trying to measure talent; WS is trying to measure literal value.
Author Message Mike G
Joined: 14 Jan 2005
Posts: 3615
Location: Hendersonville, NC
Posted: Mon Sep 24, 2007 6:43 am Post subject: eWins and other Individual Wins accrediting systems
(This thread is a spinoff from another.) I'm feeling prompted (again) to ask a rather open-ended question. In placing individual (player) accountability for (team) wins, should individual wins add up to... 1)... actual team wins? 2)... team statistical performance, i.e., pythagorean expected wins? 3)... neither? I think WS does #1, and PW shoots for #2. When I did eW, I didn't know if either was the better target. If you are considering individual wins (IW, to be generic) to be a stat that players accumulate, then the best teams -- which may win 2-3 times as many games as the worst teams -- might have 2-3 times as many IW distributed among their rosters. But an elite team may only score 15-20% more points (as differential) than a cellar-dwellar. All the things that go into point diff -- TO, Reb, Ast, Stl, Blk... -- are generally also within a similar range. If IW are a quantity of something real, and the bottom-line team quantities -- points scored -- are within 20% of one another, then is it practical to suppose players on a weak team are really only generating half (or less) of something than those on better teams? The pat answer is, "They're generating only a fraction of the wins". Sure, but the stats they generate indicate that they're making their team more competitive, more often within striking distance, with a good rally or defensive outburst. In fact, we might define all player contributions as being stratified into levels that (1) make their team less terrible, (2) make them competitive, (3) propel them to wins. I propose that any system forcing player IW's to sum to team wins (or PythWins) requires artificial support to do so. Players are deemed to be from excellent to terrible on defense, basically. Yet the same players don't carry over their excellence (or lack thereof) from good teams to bad teams. This doesn't seem intuitively believable to me. The eWin system doesn't suppose that a players' defense becomes many times better or worse when he changes teams. They also don't add up to team wins. Team eW still add up hierarchically so that the best teams are best. But they aren't 2-3 times as good as the bottom teams; only some 50-60% better. Everyone has a different intuitive sense of 'good' and 'bad'. At one time, a 40% FG rate was 'good'. At this point, I won't even get into 'individual losses'._________________` 36% of all statistics are wrongLast edited by Mike G on Mon Sep 24, 2007 10:02 am; edited 1 time in total
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deepak
Joined: 26 Apr 2006
Posts: 665
Posted: Mon Sep 24, 2007 10:01 am Post subject:
Quote:
If you are considering individual wins (IW, to be generic) to be a stat that players accumulate, then the best teams -- which may win 3-4 times as many games as the worst teams -- might have 3-4 times as many IW distributed among their rosters. But an elite team may only score 15-20% more points (as differential) than a cellar-dwellar. All the things that go into point diff -- TO, Reb, Ast, Stl, Blk... -- are generally also within a similar range. If IW are a quantity of something real, and the bottom-line team quantities -- points scored -- are within 20% of one another, then is it practical to suppose players on a weak team are really only generating half (or less) of something than those on better teams?
Aren't you assuming that IW can be formulated as a linear combination of box score stats? As I see it, wins are only indirectly determined by such stats. Something like: stats -> point diff, possessions -> estimate for wins Edit: Hmm, nevermind. I misunderstood your point.
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Mike G
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Posted: Mon Sep 24, 2007 10:19 am Post subject:
Yes, if I understand what you're saying. eWins takes boxscore stats, scales them to Team/Opponent productions, and then predicts Wins non-proportionally. Expected team wins (for an 82G season) are: xW = eW*2 - 41 So a 61-win team typically totals 51 eW. A 21-win team totals 31 eW. The good team isn't 3X as good as the bad one, but only 1.65 times as good. Here, 'good' is effectively defined as 'total talent above replacement level'._________________` 36% of all statistics are wrong
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Mountain
Joined: 13 Mar 2007
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Posted: Mon Sep 24, 2007 10:24 am Post subject:
An Individual Win metric probably should compare to league average or replacement level on stats or to average or replacement level player. I'd be wary of one that didnt and didnt fully. It is the difference from these baselines that affects winning and losing not the total stat level or total player level. EWins compares to replacement player. From your formula in the other thread it looks like a T=15+ for 2000+ minutes starts to contribute eWins. Not sure if T=15 is at or above/below mean or how closely eWins tracks with PER but does it in fact boil down to saying it takes a statistically above average player to contribute individually to wins? In reality players are the sum of their individual stats and team effects above and beyond those individual stats. Dan's overall +/- has both (and from offense and defense) with individual generally the far heavier weight though it probably varies by type of role player. The pure +/- tries to capture the uncounted team effects. This metric appears comprehensive in scope. Berri's Wins Produced uses league average performance on shooting. That isn't a terrible choice in itself but maybe the mistake is the mix he sets it in, one that doesnt not do the same for rebounds, etc. at least for Wins Produced. His PAWS/min uses replacement player. PAWS/min is more palatable to me as positional average performance is a main design feature and the shooting formula decision at least hits all the players at the position the same but it might be more acceptable to many here to re-run Berri's formula with shooting break-even at replacement player shooting level or some more neutral or statistically driven level. Anybody done or interested in doing this? Berri's metric does incorporate the impact of overall team defense on scoreboard but in a crude equal way (something PER is lacking, but just as crude as player W-L off of OR and DR ratings). Is it missing the offensive team effects of players or is that getting mixed in with the "team adjustment"?Last edited by Mountain on Mon Sep 24, 2007 10:39 am; edited 3 times in total
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deepak
Joined: 26 Apr 2006
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Posted: Mon Sep 24, 2007 10:32 am Post subject:
I think this really depends on what we're trying to describe: (a) Do we want to measure how much credit a player should get for his team's success? If so, then it makes sense for the IWs to add up to team wins (or expected team wins). (b) Or do we want to measure player performance, irrespective of his team's success? If so, then the eWins system makes more sense to me. More practically, I think we'd like to know how much a player would contribute to the success of a future team. That is, if I have a new roster I put together, how successful can I expect this team to be, and how much would each player contribute? For this purpose, which type of metric would be more useful -- (a) or (b)?
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Mountain
Joined: 13 Mar 2007
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Posted: Mon Sep 24, 2007 10:49 am Post subject:
The 2:1 ratio of wins / statistical performance difference you observe with EWins Mike, I have observed with team minutes weighted tendex and team PER too so this appears to a rough universal rather than system specific. And caused by crediting possession affecting actions as well as scoring actions. I think Nick S spent a good of time talking about accounting and touches on this.
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Mike G
Joined: 14 Jan 2005
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Posted: Mon Sep 24, 2007 10:56 am Post subject:
Mountain: Of course average players contribute to wins. Replacement T was figured at 11.7 last year; over 400 players met this level, 13-14 per team. All contribute a net positive. The 30 top 'sub-replacement' types (in minutes played) averaged 37%TS. 30 guys around 11.7 (15+ and 15-) averaged .433. Last I checked, a PER of 15 was roughly equal to a T of 26. This varies from team to team, as T rates actually correspond to team strength. Deepak: eWins ranks players on a given team; thus gives due credit for that team's success. It also gives a Kevin Garnett (great player/terrible team) with more 'credit for success' than a Jason Terry (good player/great team) -- since KG takes an otherwise-NBDL lineup and makes them competitive -- unlike some other IW systems. If you are building a team and adding last year's player eW rates (properly allotting minutes/positions), you will do very well in predicting this year's wins. PW and WS, as far as I know, make no claim along these lines; much of their credits are tied up in 'team defensive' schemes. Remember, eWins is very cognizant of team success. The factors of Tm/Opp Pts and Reb are what distinguish it from others. But the scaling is much less drastic than what is found in W-L records._________________` 36% of all statistics are wrongLast edited by Mike G on Mon Sep 24, 2007 11:10 am; edited 1 time in total
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Mountain
Joined: 13 Mar 2007
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Posted: Mon Sep 24, 2007 11:07 am Post subject:
Mike, my bad, I was thinking of wins against an average team level, 41, (as in some metrics I have worked on conceptually) rather than wins period. Certainly players below average will contribute to wins period. Different scale. So a TS+26 playing starter minutes would contribute somewhere in the range of 6-8 wins. that makes sense. I like the innovative features of EWins, hence supported scoring it against other more widely publicized measures.Tm/Opp Pts does incorporate shot defense (with everything that affects opponent points), though the team defensive result is assigned to all equally, correct (as in some other systems)? Would you have any interest in modifying to base it off of say a 50% weight of team opponent scoring and 50% estimated counterpart scoring? Giving EWins another distinction, that perhaps puts it closer to what is happening by recognizing at least some- call it half to start- of shot defense is local?Last edited by Mountain on Mon Sep 24, 2007 2:19 pm; edited 1 time in total
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Mike G
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Posted: Mon Sep 24, 2007 12:13 pm Post subject:
Mtn, I greatly appreciate the shout-out, as I don't really think eWins is 'well known', unless you are a thorough reader of these forums. Also thanks for reminding of Nick S's work a few weeks back; I was heavily curious where he would take that. Dan D (Statman) is another to watch. But I'm very skeptical of 'counterpart' effects. The Spurs don't match up with others' positions, and they're the flagship franchise of the NBA. Coaching quirks are unpredictable. Players don't have positions, on O and on D, in my view, and the best players will always be just Players. Fixing things at the 90% level is a lot closer to 100 than to 50. That's how I think of team effects: You can go to many times more work for the next few % of accuracy. You still win by outscoring your opponent, and the points-ratio is what determines wins._________________` 36% of all statistics are wrong
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NickS
Joined: 30 Dec 2004
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Posted: Mon Sep 24, 2007 12:24 pm Post subject:
Mike G wrote:
Also thanks for reminding of Nick S's work a few weeks back; I was heavily curious where he would take that.
Thanks for reminding me that I'm not forgotten. I have been meaning to do some additional work on that before the season starts, but work keeps interfering. My argument for a system based on "player wins" adding up to expected wins rather than actual wins was made here and was relatively simple: "The argument for using "expected" is that it keeps everything on the same "scale". So two teams with the same defensive eFG% will get credit for the same number of "wins" from their eFG% defense." "The other reason is that if someone calculates this in-season, expected wins are probably a better predictor of future success than actual wins particularly over a small sample size (in other words, if you calculate the numbers after 10 games, and two teams are both 6-4 but one team has a +8 point differential and the other team has a +0 point differential, the differential is a more accurate measure of ability than record)" I would add to that the idea that expected wins is a better way to compare the strength of teams historically and, therefore, a better way to compare the performance of players from different seasons.
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Mountain
Joined: 13 Mar 2007
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Posted: Mon Sep 24, 2007 12:36 pm Post subject:
Ok Mike, I understand your perspective. I've shared my perspective about adding individual shot defense enough. DCS has it. I will look to that more and maybe create my own version of it later.
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Mountain
Joined: 13 Mar 2007
Posts: 1527
Posted: Mon Sep 24, 2007 1:06 pm Post subject:
Well Mike, EWins goes primetime with Henry Abbott's mention of it and link to this board about it this morning. If folks haven't seen it yet: http://myespn.go.com/nba/truehoop Dan and David's presentation gets more publicity and discussion too. (And in a bankshot WARP as presented by DW might get some exposure.) P.S. I found this formula in the mentioned player ranking thread that covers EWins T = Sco + .98*Reb + 1.335*Ast - .25*PF + 1.5*Stl - 1.5*TO + 1.75*Blk Still accurate?
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mateo82
Joined: 06 Aug 2005
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Posted: Mon Sep 24, 2007 5:02 pm Post subject:
Well, I would think it would have to measure expected wins, since the difference between expected wins and actual wins is essential chance
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Mike G
Joined: 14 Jan 2005
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Location: Hendersonville, NC
Posted: Tue Sep 25, 2007 7:10 am Post subject:
mateo82 wrote:
Well, I would think it would have to measure expected wins, since the difference between expected wins and actual wins is essential chance
Chance, or 'tanking'. How 'bout them Celtics? -- shoulda won 32 games but only won 24. WS total 24 (X3), while PW total 32. The difference is significant. Mtn, those are one version of the weights to arrive at T. In playoffs, they can change quite a bit; for seasons, pretty close to what you have (1.5 for blocks is more typical, and .99 for Reb.) The weights change a bit for 'best fit' between wins and eWins. Other parameters also change, within some limits._________________` 36% of all statistics are wrong
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Mountain
Joined: 13 Mar 2007
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Posted: Tue Sep 25, 2007 12:31 pm Post subject:
Thanks for sharing Mike. It will take some time to look at. If I have any observations or questions that might be worthwhile I'll pass them along later.
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Author Message Mountain
Joined: 13 Mar 2007
Posts: 1527
Posted: Tue Sep 25, 2007 3:22 pm Post subject:
On EWins formula my initial reaction is assists weight is higher than my past practice / prejudice but I'll have to go back and look at all the measures of assist impact and reassess. The spreadsheet is large with many formulas and I certainly haven't mastered them (and may not) ... but I did a quick compilation of EWins for 6 main Sonics last season and put them in a table with WinShare scores at basketball-reference.com and Wins Produced. To normalize them I pro-rated the EWins and WinsProduced scores from their expected wins basis to a pro-rated version of actual wins (ok or disagree?). WinShares are based on actual wins but I divided by 3 to get Wins. Wins Produced allows negative scores and that helps account for its higher scroes for the best players, at least partially. For what it might be worth to the discussion I present this data: prorated to actual W WShares WProd EWins Average allen,ray 5.3 8.1 6.2 6.6 lewis,rashard 6.3 7.8 6.3 6.8 wilcox,chris 5.3 5.3 5.5 5.4 ridnour,luke 2.0 1.9 2.9 2.3 collison,nick 4.0 5.1 3.7 4.3 watson,earl 1.7 3.2 2.5 2.4 Score/Avg for blend WShares WProd EWins allen,ray 0.81 1.24 0.95 lewis,rashard 0.93 1.15 0.93 wilcox,chris 0.99 0.99 1.02 ridnour,luke 0.88 0.83 1.29 collison,nick 0.93 1.20 0.87 watson,earl 0.68 1.30 1.02 Anyone have comments or questions about these results? Obviously a full league correlation study amongst these (and possibly others) could be done to try to identify why they move the way they do and in relation to each other. Going multi-year would add robustness. But at the surface they track fairly closely and in line with my subjective guesses before I looked up the values. The existing tools may be pretty good for first cut purposes.Last edited by Mountain on Wed Sep 26, 2007 12:15 pm; edited 1 time in total
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Mike G
Joined: 14 Jan 2005
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Posted: Wed Sep 26, 2007 6:13 am Post subject:
I do weigh Ast rate more heavily than Sco or Reb rates. This is made possible (still makes better correlation between eW and PythW) by a couple of factors: -- There's an estimate for players % of FG unassisted. Players' Sco rates are boosted (or depressed) by whether this % is more or less than average. -- Ast rates are moved by the factor (TmPts/OppPts)^1.5 This 2nd factor makes Ridnour's Ast rate 5.61, rather than 5.69; and he has .04 fewer eWins on the year. Assists are important as a proxy for lots of essential actions which do not become boxscore stats: bringing the ball up, spacing the floor, and of course all the passes that aren't assists (because the receiver either passed or missed)._________________` 36% of all statistics are wrong
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Mountain
Joined: 13 Mar 2007
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Posted: Thu Dec 11, 2008 12:38 pm Post subject:
How do the top teams look on eWins distribution by player or by minutes weighted position? Ever calculate regular season league averages for teams or just playoff teams or top 4 or recent champion averages? Or for scoring, rebounding and assist rates? How about similar distributions for other metrics? Any advocate / user of them want to share these?
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jkubatko
Joined: 05 Jan 2005
Posts: 702
Location: Columbus, OH
Posted: Thu Dec 11, 2008 2:33 pm Post subject:
Wow, resurrecting a thread that's been dead for almost 15 months. That might be a record or something._________________Regards, Justin Kubatko Basketball-Reference.com
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Mountain
Joined: 13 Mar 2007
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Posted: Thu Dec 11, 2008 3:46 pm Post subject:
Nope. Now this thread didn't need to be resurrected but I went looking for old threads because there is good stuff in the archives worth recalling and eWins is a worthy topic folks occasionally ask for more background on and in this case the title fit with my comments so I just went with it. In what other field of research would referencing a conversation from 15 months ago be treated as unusual or unwelcome? Is always staying in the moment and the chatter of the few days being argued as preferable / better?
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Mike G
Joined: 14 Jan 2005
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Posted: Fri Dec 12, 2008 7:40 am Post subject:
Mountain wrote:
How do the top teams look on eWins distribution by player or by minutes weighted position? Ever calculate regular season league averages for teams or just playoff teams or top 4 or recent champion averages? Or for scoring, rebounding and assist rates?
eWins gives credit to players, for their team's wins. A team's eWins can be guessed by the formula: eW = (pW + 41)/2 - where pW is pythagorean. Ranking teams by Sco, Reb, and Ast could be done by checking their PtDiff, Reb% and Ast%, I think. I've never used team rates in those categories. You can download this year's file and play with it, sort by position, etc. Not sure what you're asking about, at the top._________________` 36% of all statistics are wrong
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Neil Paine
Joined: 13 Oct 2005
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Location: Atlanta, GA
Posted: Fri Dec 12, 2008 11:06 am Post subject:
Refresh my memory, what's the rationale behind this part? Quote:
eW = (pW + 41)/2
Shouldn't eW = pW? Or eW = W?
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Mountain
Joined: 13 Mar 2007
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Posted: Fri Dec 12, 2008 3:11 pm Post subject:
I am basically wondering about team structure or DNA as I have in the past with types but now thinking about it in terms of impact independent of style of play. Do the top teams have a certain. frequently similar distribution of eWins contributed by players down the ranks from the stars to the first line bench guys? I think it is also worth checking if there is a similar distribution for successful teams by where the eWin contributors actually play, where the major impacts come from by position. Calculating regular season league averages for teams or just playoff teams or top 4 or recent champion averages would give information to assess whether a certain type of eWin contribution or position pattern where the contributions come from appears to matter. Looking at scoring, rebounding and assist rates would be taking that pattern analysis / recognition exercise deeper into the details. Maybe the structure of impact thru the rotation or position don't matter or matter much. Maybe it is just get edge wherever you can. But I'd guess that probably the structure of today's game will give an edge to some designs over others, so why not look and try to understand the patterns better than anybody else and make your best educated guess on the pattern to choose or tweak what you've got and can get it in that direction as far as you can. This could and should (in my mind) by done with offensive/defensive adjusted splits and net counterpart data and could be done for other box-score based metrics too if you prefer one of them to eWins or just want to study and see as much as you can. Maybe I'll work thru it using your file Mike, maybe not. Checking what you've done and throwing the idea out there for any interested. I assume this type exercise gets done in the best analytic shops. I would do it if I had that role. The distribution of contributions has to be considered in the context of 5 man lineups and the rotation. That is where the rubber meets the road. So then you get back to needing the adjusted 5 man lineup data I advocated some for, Eli produced a first cut of before getting snapped up and brought inside. Roland at 82 games & with a team and perhaps other insiders may have it as well. That is probably the most important data out there or out there to get for this team game. Or at least the most important supplement to the rest of what is out there in public. How important is context for impact, all told? I assume it is more than enough to make the difference between winning a title and losing the conference finals. If so then it is vital. I don't think just summing individual stats produces essentially the team result or is the sufficient projection / planning approach. The last few (or even more than a few) points influenced by context demand context based analytics.
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Mike G
Joined: 14 Jan 2005
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Posted: Sun Dec 14, 2008 5:05 am Post subject:
davis21wylie2121 wrote:
Refresh my memory, what's the rationale behind this part? Quote:
eW = (pW + 41)/2
Shouldn't eW = pW? Or eW = W?
No, eW = Equivalent Wins a player adds to a hypothetical average team. The rationale is that when I add a team's player eWins, it just happens that pW = 2*eW - 41 One system that ties player wins to team wins is Win Shares. Recall that players for the Celtics last year were all on bad teams the year before. Here are some WS and eW, per 484 minutes; and a 'prediction' based on their actual 2008 minutes x their 2007 win-producing rates: Code:
eWins/484 eW? Min WS/484 WS? Celtics 2007 2008 Pre08 (2008) 2007 2008 Pre08 Pierce 1.86 1.85 11.1 2874 1.50 2.05 8.9 Allen,R 1.62 1.31 8.8 2624 1.37 1.75 7.4 Garnett 2.22 2.50 10.7 2328 1.70 2.62 8.2 Rondo 0.74 1.24 3.5 2306 0.63 1.49 3.0 Perkins 0.45 1.14 1.8 1912 0.43 1.54 1.7 totals: 35.8 12044 29.3
eWins says the youngsters improved dramatically, while the vets were pretty much the same (Ray cancelling KG). WS says everyone improved stupendously, in their win-producing attributes. Of course, in retrospect we know the defense improved a lot, chemistry was superb, etc. But without knowing those specifics, we can look at the totals at the bottom. Note that the minutes has about 7000 unaccounted for in this short list. eWins (predicted) is 6.5 more than WS. This is really as much as 13 more wins expected (as in 2*eW-41) from just these 5 players, without any change in previous win rates. Because WS are depressed for players on bad teams, there's no built-in way to predict wins when these players are gathered together to form a much better team -- is there?_________________` 36% of all statistics are wrong
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Neil Paine
Joined: 13 Oct 2005
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Location: Atlanta, GA
Posted: Sun Dec 14, 2008 1:41 pm Post subject:
I think you're confusing ability with value again... The "wins a player adds to a hypothetical average team" would fall under the category of ability, an attempt to completely remove the player from his actual context and drop him into a different context. So in this sense, eWins is apparently trying to measure ability. Win Shares wants to measure value -- and the sum of a team's players' "wins added" must be tied to the actual # of wins (real or pythagorean) the team produced in reality. In a value measure, it makes absolutely no sense to artificially allocate more wins to a bad team's players (or less to a good team's ones) than the team actually won in real life. The whole must (roughly) equal the sum of its parts. So, as it turns out, comparing eW to WS is like comparing apples and oranges. And I don't think I realized this until right now.
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Mike G
Joined: 14 Jan 2005
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Location: Hendersonville, NC
Posted: Sun Dec 14, 2008 2:11 pm Post subject:
davis21wylie2121 wrote:
.. an attempt to completely remove the player from his actual context and drop him into a different context..
Actually, the opposite. E-Wins isn't tied to context, but is a universal expression of Value, independent of context. If a player's value is only relative to where he played in a given season (or part-season), what does that tell us about his value? Not much, I think. If you drive a car across the Plains and get 35 mpg -- and it's known that you had a tailwind averaging 20 mph -- wouldn't it be worth knowing what your car's mpg is in the absence of wind? Or into a 20 mpg headwind? The fleeting 'value' of your high-mpg car might be a useful quantity to quote, if you're trying to sell your car. But by accounting for the context (of the tailwind), one gets a more accurate description. A role player on a great team may shop himself around the league and get paid more by a lesser team. Does his 'value' decrease, if equal production creates fewer WS? Team eWins rank teams in just the same order as PythWins rank them. There's no artificial adjustment made. Player wins don't sum to team wins. The thread starts with these inquiries. The whole does equal the sum, in context._________________` 36% of all statistics are wrong
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Mike G
Joined: 14 Jan 2005
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Posted: Sun Dec 14, 2008 2:26 pm Post subject:
Try this thought experiment. You and I and 2 other guys are playing games of 2-on-2. We are all equal players (ability, value), and we split 20 games, 10-10. We all have essentially equal WS, eW, whatever: Just about 5.0 apiece. Then your teammate gets hurt. To continue our 'league', you draft a guy who is just a stiff. He can do very little to contribute. We double team you, and make him miss his occasional shot by yelling at him. Now it's very difficult for you to win a game. You may win one of 20, because we were hung-over perhaps. In 20 games, you may get 20% more points, taking 80% more shots; double your turnovers, etc. By most measures you've been more productive and less efficient. But eWins says you're the same player you have been. Yet, your win shares have plunged to nearly zero. Some ratings would have you negative. Has your 'value' gone to near-zero? Your team might total 5.5 eW in 20 games, to my team's 14.5 . eWins : 5.5*2 - 10 = 1.0 In other words, by just maintaining your productivity, with a teammate about 1/10 as productive, your team is expected to win 1 game in 20. And your 'value' is constant; as (I think) it should be._________________` 36% of all statistics are wrong
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jkubatko
Joined: 05 Jan 2005
Posts: 702
Location: Columbus, OH
Posted: Sun Dec 14, 2008 2:27 pm Post subject:
Mike G wrote:
One system that ties player wins to team wins is Win Shares. Recall that players for the Celtics last year were all on bad teams the year before. Here are some WS and eW, per 484 minutes; and a 'prediction' based on their actual 2008 minutes x their 2007 win-producing rates: Code:
eWins/484 eW? Min WS/484 WS? Celtics 2007 2008 Pre08 (2008) 2007 2008 Pre08 Pierce 1.86 1.85 11.1 2874 1.50 2.05 8.9 Allen,R 1.62 1.31 8.8 2624 1.37 1.75 7.4 Garnett 2.22 2.50 10.7 2328 1.70 2.62 8.2 Rondo 0.74 1.24 3.5 2306 0.63 1.49 3.0 Perkins 0.45 1.14 1.8 1912 0.43 1.54 1.7 totals: 35.8 12044 29.3
Wait a second... You've already said pW = 2 * eW - 41. So using the numbers above, doesn't that mean that eW suggests that this team would be projected to win at least (2 * 35.8) - 41 = 30.6 games? And isn't that very close to the Win Shares projection of 29.3 wins?_________________Regards, Justin Kubatko Basketball-Reference.com
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Neil Paine
Joined: 13 Oct 2005
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Location: Atlanta, GA
Posted: Sun Dec 14, 2008 2:34 pm Post subject:
This is what I'm trying to say: There is no such thing as a "universal expression of Value". That's called "Ability". Value embraces context (if a player is on a bad team, so be it), while ability rejects it. I hate to break it to you, but if you're attempting to show how many wins a player produced on a theoretical average team, that's an ability metric, not a value metric, because you've tried to remove a player from his actual context.
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Neil Paine
Joined: 13 Oct 2005
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Location: Atlanta, GA
Posted: Sun Dec 14, 2008 2:49 pm Post subject:
If I may quote Ed Kupfer for a moment: Ed Küpfer wrote:
Imagine a two-on-two tournament. The favoured team is comprised of one mediocre player and one player so great, he ranks among the best of all time. Now imagine that every opponent is determined not to let the great player beat them, that they will double-team him continuously and force the mediocre player to shoot. Now, because of the double-team, the mediocre player has no one defending him, and scores pretty much at will. Opponents, still fearing the great player's awesome talent, stay with the double-teams, and keep hoping that the mediocre will miss, which is unlikely since they aren't really defending him. Now, regardless of how the team fared in the tournament, the stats will show that the mediocre player contributed far more value than the great player, becuase, as it turned out, he was the one taking—and making—all the shots. Our stats will give the mediocre player the MVP. This is the way it should be. Just remember that most valuable does not mean most talented.
Pertaining to this discussion, eW is apparently trying to measure talent; WS is trying to measure literal value.