2010-11 NBA Win Predictions (BobboFitos, 2010)
Posted: Fri Apr 15, 2011 7:46 pm
BobboFitos
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PostPosted: Wed Aug 11, 2010 8:35 pm Post subject: 2010-11 NBA Win Predictions Reply with quote
Not sure if others have worked on their projections or whatnot, but seems like this thread should start soon. (Reason I thought of this was http://sports.espn.go.com/nba/news/stor ... tStandings - ESPN released their expert picks) I wont have mine up for a little while, but just testing the waters for whenever people want to make their picks.
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back2newbelf
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PostPosted: Fri Aug 13, 2010 5:18 am Post subject: Reply with quote
I think the list from ESPN is quite solid. I don't think it'll be easy to make a substantially better predition. My (very early) guesses where that list can be improved the most:
Milwaukee(-)
New York(-)
Washington(-)
Cleveland(+)
Portland(+, might be a gamble though)
San Antonio(+)
Houston(-)
Phoenix(+)
Sacramento(+)
Golden State(+)
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BobboFitos
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PostPosted: Fri Aug 13, 2010 8:35 am Post subject: Reply with quote
back2newbelf wrote:
I think the list from ESPN is quite solid. I don't think it'll be easy to make a substantially better predition. My (very early) guesses where that list can be improved the most:
Milwaukee(-)
New York(-)
Washington(-)
Cleveland(+)
Portland(+, might be a gamble though)
San Antonio(+)
Houston(-)
Phoenix(+)
Sacramento(+)
Golden State(+)
Miami for sure. New Orleans for sure. But the latter is probably a little unfair since ESPN made their picks before the acquisition of Ariza.
I'd throw Charlotte in as well. Your list is solid, but I was struck at their underrating of the first two and overrating of the last. (By a substantial margin)
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schtevie
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PostPosted: Wed Aug 18, 2010 3:01 pm Post subject: Reply with quote
Well, let me try to enliven in some small way these summer doldrums and be a bit mean to approximately half of "ESPN's best basketball minds". Looking at the forecasted Eastern Conference standings, I see very little wisdom coming from the crowd in expecting the Heat to win only 61 games. And this is not just to quibble with the predicted value (I take the over, by the way.) What I am having trouble imagining is any plausible reasoning that led the more pessimistic half (approximate) of their 93 experts to an expected win total that must have been what? 55 games? 57? And more generally, it is a bit saddening to contemplate the implication that there is little statistical reasoning whatsoever that influenced this crowd.
The average over the last 20 years (a reasonable reference, I think) for the highest regular season win total in the NBA is approximately 64 games. So, straight off, for perspective, what we are being told, is that a team that was 47-35 last year and then acquired possibly the greatest crop of free agents, in the prime of their careers, in the history of the league won't really even approach the average best record in the league. Even a "naive" prediction, for those pessimistic, simply applying the historic second best record in the league (60 games), say, would surely have raised the overall estimate.
Instead some reasoning was used that drove down the average. But what could it have been? I am going to suppose that the basic consensus among the pessimists was the same as the optimists, that as a result of the transactions, Miami would be no better on defense but considerably better on offense. The difference being that the pessimists believed that offensive improvements would only add 10 to 12 wins, max.
It is this implication that seems completely daft. And on this point, neither APM voodoo nor Wins Produced magical regressions need to be invoked. If one believes that the current collection of offensive talent on the Heat is greater than that of last year's Heat roster as well as that of the Cavs, Raptors, and Wizards (and everyone believes this, no?) the inference is that 64 wins should be an approximate lower bound.
Fleshing out the point, LBJ, Bosh, and Miller all had a TS% of about 60%. And collectively they used 50% of their teams' scoring possessions (FGA + 0.44 FTA). Miami, by contrast, jettisoned half their roster, players that utilized 49% of last year's scoring possessions at an average TS% of 53%. As a first cut then, one should expect that half the offense should improve by 7%age points. In terms of Pythogorean Wins, on a base of last year's Miami points scored and allowed, this yields 64 wins (64.2, if it matters).
Now, one can argue that the Juwan Howards of the world are going to get some shots, driving down the average, against which is the more persuasive argument, that with LBJ, Bosh, and Miller on the court, that they and others are going to see their TS%s increase.
The bottom line however is that approximately 64 wins is a huge difference from what the ESPN pessimists were predicting.
What is the larger point?
It is not unreasonable to expect, what with the ubiquitous internet sources of basketball statistics, and public discussions dating back close to twenty years, that all NBA-related media would avail themselves of what is on offer and thereby improve their craft.
Perhaps I am reading too much into a silly poll, however. Maybe the participants weren't really paying much attention, for the anonymitiy? How about ESPN shows the predictions of each participant? And to further incentivize excellence, a modest proposal: How about mimicking the organizational structure of English Football and dividing the 93 experts into three leagues (or more). The experts that best predict the Heat record can form the Premier League, the following 31 would be in the Championship League, followed by League One, or whatever. Then each year thereafter, the bottom and top of each table would be relegated and promoted accordingly. That should better focus the imagination.
But then again, the rant aside, maybe I am just plain wrong about the Heat. How does one get to 58 or so wins with that roster, though? What is the argument?
P.S. And how does the ESPN average for the middling improvement of the Heat coherently relate to the predicted collapse of the James-less Cavs?
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Crow
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PostPosted: Wed Aug 18, 2010 8:52 pm Post subject: Reply with quote
If one was trying to make the expert panel's average a better predictor, I'd think it would help over years to vary the weights given to individual predictors or even knock some out based on performance as you did. Your structure might well be helpful- market just "the Premier League" prediction average or a variably weighted blend of the leagues.
Or there might be a more flexible or complicated or just different theory driven structure that would be even better that other trained stat experts are more able to suggest, describe and possibly apply.
I haven't really thought much about what my best guess for the Heat would be, at least yet. At first blush though I am not particularly bothered by an average prediction of 61 and I'd probably move fairly cautiously if I moved up.
Royce, do you feel you could post (this time or in the future with the notice and consent of the voters) some fairly high roll-up of the team prediction distributions for the predicted wins? Say the number of votes for over and under the average? Or the number of votes for 1 to 5 wins under or over the predicted average and the same for greater than 5 over or under the predicted average? You could even use large bands for reporting the results- say less than 10 votes in that win prediction range, or 10-30, or more than 30 or whatever to give some detail but not put anyone on a small island. I'd find that both interesting and helpful with regard to the Heat and other teams, if it were considered acceptable.
back2newbelf, can you clarify what your + and - signs mean? That ESPN is too high or low in your opinion or that you personally would adjust the prediction up or down as that sign indicates? I am not clear.
Last edited by Crow on Wed Aug 18, 2010 10:50 pm; edited 3 times in total
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Royce
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PostPosted: Wed Aug 18, 2010 10:31 pm Post subject: Reply with quote
I might be able to provide more info later, when I have more time.
As for the Heat ... a quick count reveals that 26 voters predicted fewer than 61 wins ... another 35 predicted fewer than 65 ... just to provide a couple of benchmarks that suggest in this case it's a little "easier" to pull the mean down than to lift it ... which is fairly obvious.
High: 71
Low: 50
Average prediction: 62.4
Adjusted average: 61.2
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erivera7
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PostPosted: Wed Aug 18, 2010 10:51 pm Post subject: Reply with quote
I'd like to know who predicted 50 wins for the Heat on the ESPN panel. For the record, I was one of the panelists and predicted 65 wins.
50 wins? That's ... a little absurd, even from the most pessimistic view.
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Kevin Pelton
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PostPosted: Wed Aug 18, 2010 11:05 pm Post subject: Reply with quote
I'm trying to come up with a technical term that explains why projections have to be regressed to the mean, but I can't think of such a thing. Suffice it to say that just because we know a team will win 64 games doesn't mean that whoever the best team is should be predicted to win 64 games.
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Crow
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PostPosted: Wed Aug 18, 2010 11:16 pm Post subject: Reply with quote
Since 1980-81 there have been 41 teams at or above 61 wins, 11 at or above 65 wins, 6 at or above 67 wins.
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DSMok1
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PostPosted: Wed Aug 18, 2010 11:52 pm Post subject: Reply with quote
Kevin Pelton wrote:
I'm trying to come up with a technical term that explains why projections have to be regressed to the mean, but I can't think of such a thing. Suffice it to say that just because we know a team will win 64 games doesn't mean that whoever the best team is should be predicted to win 64 games.
Yeah, that's a well known effect. We know about how good the best team will be, but we don't know which team that will be.
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Crow
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PostPosted: Thu Aug 19, 2010 1:03 am Post subject: Reply with quote
If the Heat get to 67 wins that would at least tie for 3rd best out of 800 some team seasons in the last 30 years or within the top 0.5th percentile. 65 will at least tie for 9th or close to top 1%. 61 would only be about top 5% but if they hit 65 you only miss by 4 games, which is still good for any one prediction.
If one of the big 3 missed 15+ games more than expected or if they collectively missed 15+ more than expected that might knock a couple games off the predicted based on individual data, or worse than average luck in close games could, or perhaps other things (chemistry on offense and / or defense or whatever) might.
Going to 63 - 65 for Miami instead of 61 and being right would have a modest impact on the overall average error contest. It would knock about 0.1 off the average error. But if you are trying to get to an average error of 7 or significantly below 7 every 0.1 is valuable.
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back2newbelf
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PostPosted: Thu Aug 19, 2010 5:27 am Post subject: Reply with quote
I don't think the Heat care about more than having home-court advantage and might rest some players once they feel they're "safe" in #1. That would result in
max(# of wins of all other teams) + 2 or so
the "+2" is obviously debatable, since they're so good, they might even win 60% of their games when two stars are resting. Miami's strength of schedule for the last ~10 games might be important here for the final projection
Quote:
back2newbelf, can you clarify what your + and - signs mean? That ESPN is too high or low in your opinion or that you personally would adjust the prediction up or down as that sign indicates?
+ means I expect more wins
some comments:
Golden State, after having had 32 PythWins, is finally getting their center back (Biedrins) and they get David Lee (which should definitely outweigh losing Watson, Maggette, Turiaf, Randolph) is projected to 29 wins. Hm.
I think New York has good potential to implode. My tea leaves tell me that Stoudemire will be pissed after 10 games because he's not used to not being spoonfed and all the losses, leading to a whole lot of chemistry issues (even if all goes well I don't expect them to win 37)
Portland(51 PythWins) probably gets more games out of -Oden, Camby, Przybilla, Batum-, all of which are very good players. I don't see them winning 49 games(more like.. 59).
Sacramento(29 PythWins, projected by ESPN to win 30): Just losing Nocioni would have made me predict them win 35 or so. They also get Cousins and Dalembert
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mtamada
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PostPosted: Thu Aug 19, 2010 4:40 pm Post subject: Reply with quote
Kevin Pelton wrote:
I'm trying to come up with a technical term that explains why projections have to be regressed to the mean, but I can't think of such a thing. Suffice it to say that just because we know a team will win 64 games doesn't mean that whoever the best team is should be predicted to win 64 games.
Yeah, there's undoubtedly a term out there, but I don't know what it is. By saying "regression to the mean", we're 90% there already. A more specific term in the context of forecasting, but which unfortunately doesn't quite fit this situation, is "winner's curse". An example, which also shows how it's in reality yet another manifestation of regression to the mean: if my best estimate of how the Rockets are going to do is 41-41, then I should (using just about any loss function) predict 41 wins for them. But if my best estimate for the Heat is 66 wins, then (for a wide range of reasonable loss functions) I should NOT predict 66 wins, I should regress my forecast a bit downward, to 63 or whatever. Because people who bid high for an item of unknown value are more likely to find that the item's true value is less than they had predicted.
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schtevie
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PostPosted: Wed Aug 25, 2010 11:26 pm Post subject: Reply with quote
I am hoping that Kevin and Mike will expand a bit upon their remarks. In particular, I don't see what "regression to the mean" or "loss functions" have to do with the issue at hand...at least the issue I raised.
The stable of ESPN writers were asked to estimate the mean of the ex ante distribution of wins for each team in the NBA. That 64 out of 93 came up with a number for Miami that was 64 or below is a bit disturbing, as it would seem to betray a lack of familiarity with or interest in statistics and statistical reasoning.
What can explain this result? It cannot be based upon what Crow seems to suggest, that one of the Heat stars misses an unexpected number of games. Because....that is unexpected, part of one tail of the distribution and not the mean.
Unless someone has some inside info, I see no evidence whatsoever that last year's numbers (in terms of games played and productivity, as a baseline) shouldn't be the basis for next. Opinions on the shape of that earth shouldn't differ.
Unless.
Unless there is really a widespread belief that the coaching staff of the Heat stinks. Or, put more kindly, that James and Wade are basically the same player necessarily implies that there is no way to have them on the court at the same time without significant decreases in their productivity (compared to previous years). And that no teammates will see better shots for their combined presence on the floor. But there is no such widespread belief.
And a final point. Estimating the Heat's record matters. Not in the sense that the ESPN poll matters. It matters because it provides as good of a test as one could possibly hope for. A test of one's understanding of the game of NBA basketball, offensive basketball in particular. There is no pretense of defense being a big part of the equation, so no black box there to worry about. And there are no age issues to inject additional uncertainty.
It will be an interesting season.
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Crow
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PostPosted: Thu Aug 26, 2010 12:50 am Post subject: Reply with quote
What specific assumptions are you making about injuries? The injury impact distribution will vary by team and the Heat could have more performance reducing injury impact than the average team.
James looks heavier to me and he is older. These things are both documented to increase injury risk. 2 of the last 3 years he has missed or passed on 6 and 7 games, the most of his career. 10 or more wouldn't surprise me. Bosh has missed 12 or more games 4 of the last 5 years. Wade has missed 20+ games in 3 of 7 years for a career average of 15. On quick inspection, that seems to add up to more than an average injury impact risk for leading players to me.
Diminishing return impacts for likely usage cuts for the big 3, shared rebounding, etc. can reasonably vary. Your in / out TS% change estimate for the offense is pretty rudimentary. How good will they be as a team from 3 pt land in quantity and FG%? None of the big 3 is anywhere close to even average on 3 point accuracy for their careers. That could matter in a way that overall TS% doesn't pick up exactly. They have other 3 point shooters but how many will they get up and how will the team averages turn out?
How well will they accept their roles and get along on the court? I can see a number of possible frictions that might hold performance somewhat below what a simple projection of past stats would predict.
Each additional win after 55 and 60 is probably increasingly tough (likely needing to win more against good teams to achieve this). A linear win estimate system might well predict too high.
Defense is hard to predict. Counterpart data at 82 games suggests Wade and James to be a little better than average 1 on 1 when facing a lot of starters, Bosh moderately worse. Another tool out there for individual impact estimates, but considering both 1 on 1 and help dimensions, was defensive 4 factors and it shows 2 of the big 3 to be weak (40th percentile or less) on 3 of the 4 defensive factors and 4 of those 12 ratings were in the weakest 16% of the league. It is hard to say how good the team defense will be with them in together at the core with a bit less room for defensive assistants to help than the Cavs or Heat could use as desired or needed with James and Wade. It is hard to say how quick the defense gets to its maximum or how consistent they will be.
How intensely focused and successful will they be in Miami-South Beach with all they want to do and will be asked to do off the court and with the constant media scrutiny? No other team will face this level of scrutiny and potential distraction or harm. It is also not unreasonable to expect that almost every team they face will try very hard to keep up or beat them, perhaps more so than against just any routine preseason #1 or #2.
The average wins of the two recent super teams (Boston and LA) who have won titles over their 2 peak was 62.5.
The average for the best team in the 11 seasons post the Jordan championships and the lockout was 62.7 actual wins. 5 times the leader was at 61 or less. 4 times at 65 or more. 62 was the median.
61 or 65. They are different. I am not sure yet which is better bet but I don't think it is so easy and obvious that 65 is better. It would take more a detailed presentation to convince me that 65 is clearly the better estimate and better than 63 as well. 63 seems a bit safer at this point to me on the surface but it would take very little in a detailed analysis to swing the estimate 2 games either way.
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back2newbelf
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PostPosted: Wed Sep 22, 2010 6:01 pm Post subject: Reply with quote
Could you post the entire vegas predictions or link to them, please. Thanks
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Crow
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PostPosted: Wed Sep 22, 2010 7:55 pm Post subject: Reply with quote
Links for General odds to win the title and
season win propositions for just the Heat and Lakers (at least so far) both listed here.
http://www.sportsbook.com/livesports/in ... basketball
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schtevie
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PostPosted: Thu Sep 23, 2010 9:17 am Post subject: Reply with quote
OK, time to revise and extend my remarks again, about expected injury/participation. A little voice in my head kept saying "What about Penny?".
Basically, the averages I presented didn't best address the circumstance facing DW this year. The assumption was that he would continue be a 35 mpg player at age 29. This served to screen out the "would be" 35 mpg players who dipped below that in year 29 for injury reasons. Back to the drawing board.
So, querying the lovely basketball-reference database, for 35 mpg 28 year old guards over the most recent 20 year range (1999-00 to 2008-09) we then follow these results to their 29 year old season. This picks up broken Penny and leads to a slightly different picture. (And again, for consistency, I culled out those players from the search results that either weren't career starters, had their 29th year in the lockout shortened season, or had the misfortune of perishing in European car accidents: Craig Ehlo, George McCloud, Scott Skiles, Spud Webb, Steve Smith, Drazen Petrovic, Doug Christie, and Tyrone Corbin).
The overall results:
(1) These guards which participated in 73.4 games when they were 28, saw a drop-off the following year, playing in 70.3 games (and playing 35.4 mpg).
(2) For the eight players over the past 20 years having Wade's history of 67.3 games played per season by the age of 28 (these are: Vince Carter, Jerry Stackhouse, Eric Snow, Baron Davis, Anfernee Hardaway, Ron Harper, Tim Hardaway, and Larry Hughes) things look grimmer, their average year 29 consists of 60.5 games (and 33.2 mpg). (And if you add in the two players just above the cut-off, Lindsey Hunter and Chauncey Billups, who averaged 67.3 and 67.7 games per year by age 28, the average of games played in year 29 moves up significantly to 64.7.)
(3) For what it's worth (not much) the player, actually whose experience most looks like Wade's in this framework is Vince Carter, who missed significant amount of games at ages 22, 25 and 26 (though I am certainly not saying the injury history of these two players was similar) and he showed up for 79 games at age 29.
But a little context on point (2). What drives down the average are the data for Penny and Stackhouse (4 and 26 games played, when 29, respectively). Without Penny, the average goes to 68.6 and without both, we return to 75.7.
Would it be cherry-picking to remove them in terms of properly gauging expectations? Yes, in a sense that we have a really small sample here (I await Neil's multivariate analysis for better results) and we shouldn't chuck out data. But, no, in the sense that these two guys were injured before their 29th year old season began. Accordingly, if Wade clears training camp healthy enough to start the first game, the unfortunate experiences of Penny and Stackhouse don't logically apply.
According to these revisions, perhaps I should change my beliefs? Heat win between 64 and 69 games? Nah. Never mind.
P.S. More interesting is another apparent implication of the games played data. If you sort the results (again, average games played per season in up to seven years prior to and including 28, but not including the lock-out year data in the average....whew) by total years in the NBA by age 28, there is a more ominous trend apparent.
6 year veteran guards playing 35 mpg or more at age 28 (that is those entering the league who were 23 at midpoint in their first season) played in 76.1 games the following year. 7 year veterans, those who entered at age 22, their season averaged only 71.25 games at age 29 (75.7 if you kick out Penny). 8 year veterans, their next year's participation drops to 65.4 games (sample of eight). 9 year: 65 games (sample of four). 10 year: 55 games (sample of two). Then 11 year: 74 games (sample of one: Kobe!). Taking the 8 year and over average, the drop is to 60.9 games.
What is the point? Well, if someone wishes they can extend the analysis to expectations for 30 year guards, inclusive of the age 29 season, but if the results are similar, I wouldn't bank on a three-peat just yet in Miami.
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mtamada
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PostPosted: Wed Oct 06, 2010 1:45 am Post subject: Reply with quote
schtevie wrote:
I am hoping that Kevin and Mike will expand a bit upon their remarks. In particular, I don't see what "regression to the mean" or "loss functions" have to do with the issue at hand...at least the issue I raised.
Sorry, late reply here. My expansion starts with an example: one of the major ways of utilizing regression to the mean is with Stein estimators. The classic example is if it's two weeks into the baseball season and you see a player who's currently batting .412, and you want to predict what his batting average for the rest of the season will be, you do not (if you're smart) use the unbiased estimate of .412. You want to purposely use a biased estimate, and regress to the mean, because extreme performances are unlikely to be sustained.
The key word is extreme. Stein estimators are remarkable because "extreme" and "mean" can be used in a variety of situations; the baseball example is intuitively obvious, not so obvious is that the mean that you regress to doesn't even have to be the mean of baseball players' batting averages (although obviously, the more similar the variables are to each other, the better the Stein estimator will perform, e.g. if you have data on that same player from other seasons, that can be better than using the mean of all other baseball players).
Bottom line, it doesn't have to be two-week baseball averages. ANY extreme value is more likely to regress to the mean rather than maintain (or be realized) at its extreme value.
And this includes extreme forecasts. We're not talking about two weeks into the basketball season, but as I described above, it doesn't matter. The same principles hold.
Do NBA teams sometimes win 72 games? Yes sometimes they do. But you don't get rich by betting on it happening.
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schtevie
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PostPosted: Wed Oct 06, 2010 9:11 pm Post subject: Reply with quote
Mike, I am still not getting the relevance. Further advice requested.
I was being unkind to a significant portion of the ESPN electorate because they had provided guesstimates of the expected performance of the 2010-11 Heat that were, to my reckoning, at variance with what the fundamentals suggest. The issue, as I understand it, is what is the best estimate of the mean to which performance should regress?
For my approximation, I estimated the effect of James et al. on points scored then added it in to B-R's Pythagorean Wins formula for a Miami Heat baseline. This is a simple production function, with the additional input being the change in expected points (= 2009-10 free agent TS% * vacated scoring opportunities with the Heat).
If the argument is that using last season's TS%s (basically career highs) is an error akin to a baseball player starting off the season hitting .412, I take the theoretical point. However, the assumption is bolstered by the evidence from aging curves which suggests that, for 25 year old players, the mean to which they will regress is rising.
The important known unknown - to paraphrase an infamous American - is the degree to which there are diminishing returns in offensive efficiency relating to overlapping responsibilities on offense. Against which there is a theoretical offset: having better teammates gives a player better scoring opportunities, all else equal. My "model" called this even: the free agents don't get worse, but the pre-existing Heat don't get better either. Anyway, this assumption has nothing to do with unforeseen regressions to the mean. Does it?
Finally, for completeness, there are no similar issues to be concerned about in translating estimated points to wins using the Pythagorean Wins formula, are there?
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mtamada
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PostPosted: Wed Oct 06, 2010 10:39 pm Post subject: Reply with quote
schtevie wrote:
Anyway, this assumption has nothing to do with unforeseen regressions to the mean. Does it?
That assumption, and the rest of the assumptions, indeed seemingly have nothing to do with unforeseen regressions to the mean. But that's why they're unforeseen.
I.e. your estimates are based on what the numbers tell you the expected outcome ought to be. Seemingly the best procedure. And indeed, for non-extreme estimates, it is the best procedure.
But when your estimates are extreme, i.e. when they are predicting an extreme outcome, that's when you start putting less weight on your numbers and more weight on the mean. Due simply to regression to the mean, which indeed has nothing to do with your assumptions, it just happens. And it's unforeseen (but foreseen by people who have the foresight to take regression to the mean into account).
If you draw 24 balls out of a barrel and 10 are white (and the other 14 are black), and someone asks you to estimate the percent of white balls in the barrel, then 10/24 = .417 is as good an estimate as you can come up with, yes? If that's all the information that you have, yes. But if you know that we're talking about the first 24 at bats of the season, then you have additional information (this is where the Bayesianism starts creeping in), and you say wait a minute, I do not believe that this batter is going to keep hitting .417 for the rest of the season.
If you run your LeBron James stats and take age curves into account and teammates and etc. etc. and the numbers tell you 72 wins, well that's as good an estimate as you can come up with, yes? If that's all the information that you have, yes. But if you know that we're talking about NBA teams, then you say wait a minute, NBA teams almost never win 72 games.
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DSMok1
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PostPosted: Thu Oct 07, 2010 12:08 pm Post subject: Reply with quote
Well said, Mike. You have to regress!
BTW, I am showing that James (+11.5) and Wade (+8.5) contribute nearly all of their advantage on offense (there's a lot bigger spread on offense in general--kind of like baseball). There is no way that an offense can run in the +19 efficiency range. No way an offense can even sniff that. The best offense ever was +9.2 (Dallas 2004). Now obviously, their teammates are not league average on offense, though Bosh was a +4.8 on offense last year. That said, I expect tremendous regression to the mean--even a + 10 offense would be astounding. And most teams with such an offensive efficiency can't maintain even average on the other end of the court.
For reference, James, Wade, and Bosh show as +2.2, +1.9, and +0 on the defensive end.
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BobboFitos
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PostPosted: Thu Oct 07, 2010 10:42 pm Post subject: Reply with quote
DSMok1 wrote:
Well said, Mike. You have to regress!
BTW, I am showing that James (+11.5) and Wade (+8.5) contribute nearly all of their advantage on offense (there's a lot bigger spread on offense in general--kind of like baseball). There is no way that an offense can run in the +19 efficiency range. No way an offense can even sniff that. The best offense ever was +9.2 (Dallas 2004). Now obviously, their teammates are not league average on offense, though Bosh was a +4.8 on offense last year. That said, I expect tremendous regression to the mean--even a + 10 offense would be astounding. And most teams with such an offensive efficiency can't maintain even average on the other end of the court.
For reference, James, Wade, and Bosh show as +2.2, +1.9, and +0 on the defensive end.
Is it really so hard to imagine this years heat team being the best offense ever, though? I agree you can't just simply "merge" their APM rating or SPM rating or whatever, but I don't think it's a bad bet that they'll have a >+10 offense.
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schtevie
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PostPosted: Sun Oct 10, 2010 9:45 am Post subject: Reply with quote
Mike, perhaps one or more of the ESPN anonyms who put the Heat in the 50s feels a bit better about his or her estimate, for your emphasis of the centrality of "regression to the mean" when it comes to extreme estimates. In the instance, however, I don't think there is much succor to be found in the concept.
I am not arguing with its general utility, nor the importance of recognizing its scope. Indeed, returning to the initial focus of this string, for anyone who is a bit lazy but who still wants a good chance at winning (and certainly not losing) this year's prediction competition, a simple rule of thumb will get you far: take last year's team records and regress them to the mean a bit (say -0.2 or -0.3 for each win above average). With an ad hoc adjustment for the Heat (and other teams that had clear changes in strength) and you'll be in the mix at the finish. Guaranteed.
But invoking "regression to the mean" arguments won't help much in justifying low-ball estimates for the Heat, primarily because what appears to be an extreme estimate, isn't really. And to the extent that an ex post adjustment need to be made to an estimated outcome, "regression to the mean" isn't the relevant concept. (I am pretty sure.)
To take the most important example, extrapolating LBJ's past performance is not evidence of an extreme estimate, precisely because he is an extremely good player. His performances year to year are highly correlated. We are not talking here about an average baseball player who starts the season hitting .417 with 24 at bats. For TS% (the basis of my simple model) there is a multi-year record of nearly 2000 scoring possessions per season. And in terms of how consistent we should expect his performance to be, we can get a sense of to where he might regress, by looking at TS% for the appropriate age and position cohort.
Taking as a relevant sample the last six years (the starting year, 2004-05, chosen so as to have a more similar year to year average scoring propensity in the NBA) for forwards playing 25 mpg or more at a specific age, these are the LBJ's TS% percentiles at ages 20 to 25: 82, 76, 75, 71, 86, and 90. And the non-regression story is essentially identical with Bosh.
OK, so perhaps the relevant regression is to the 80th percentile of this distribution, so perhaps a decrease of 1.5 percentage points in TS% on this account? Against which we are looking at expected improvement due to maturity, suggested by LBJ's increasing propensity to get to the free throw line. The bottom line is that, on net, regression to the mean, at least on the account of expected individual performances anyway, shouldn't be the reason for downgrading the "expected" performance of the Heat this year.
If one is looking for such a reason, it can be found by invoking the assumed concavity of the basketball production function. In such an instance, the wins produced by the expected value of inputs is greater than the expected wins generated by the ex ante distribution of such inputs. Maybe the production function is really concave, and this is the argument that the aforementioned section of the ESPN electorate was invoking?
Finally, DSMok1, any chance you might provide a complete estimate for the Heat using your SAPM numbers? Whatever it turns out to be, "regression to the mean" shouldn't be the argument invoked to explain any expected deviation from reality. Any notional overshooting of the estimate will more properly be on account of fundamentals: the fact that James and Wade play functionally similar positions; what an estimate based on simple addition of SAPM doesn't take into account.
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PostPosted: Sun Oct 10, 2010 3:16 pm Post subject: Reply with quote
ASPM would be the right acronym. Advanced Statistical Plus-Minus. Yes, I intend to try to create projections for every player in the league and then create team projections from that. A major problem, though, is how to forecast playing time. That's pretty tricky.
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PostPosted: Sun Oct 10, 2010 5:01 pm Post subject: Reply with quote
In a quick scan of predictions for the Heat I find about 1/3rd in the low 60s, 1/3rd in the mid 60s and 1/3rd in the high 60s.
The impact of big 3s on their usage has been covered some but I went back to check before-after on TS% and Win Shares. Using big usage duos and triplets identified from recent years by Neal at B-R, I found, in rounded terms, TS%s went up for about 70% of the time for those stars while Win Shares went up about 60% of the time. Actual team wins went up by an average of just 2 games over the previous season of the team where the new pair or trio played. There were a couple of huge successes (Boston 07-08 and Cavs 08-09) but a couple of big flops and most were small to modest gains.
It also seems worth noting that both Wade and James have seen attempts to create new big 2s and 3s. James-Williams in 08-09 worked for both guys in the regular season and big for the team. James-Williams-Jamison in 2009-10 didn't work out in the 2010 playoffs. Wade-O'Neal-Walker actually slipped from the previous regular season in team wins but won the title. All 3 improve on TS% while 2 of the 3 improved on WinShares. Wade-Davis was a flop for the team and both players but it wasn't the only reason for the team fall.
The 2003-4 season in LA was good for Payton on both TS% and Win Shares, a split decision for Malone, neutral on one, down on the other for Kobe, down on both for O'Neal. Not enough opportunity for efficiency / effectiveness / glory to spread all the way around?
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greyberger
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PostPosted: Sun Oct 10, 2010 11:00 pm Post subject: Reply with quote
Very interesting. When the focus is on Lebron and Wade, I wonder how they'll be dispatched - if the idea is to keep at least one of them on the court in every meaningful minute, usage will vary a lot from lineup to lineup. For the appearance of it you can't use Dwayne Wade as a sixth-man, but having him in and fresh when Lebron and Bosh are taking their first rest might be the best way to do it.
With Wade and James you have to figure the flexibility is there, both in the general sense and the 'skill curves' sense. I'd be more worried about nailing the rotation than whether the 'best 5 in' lineup is as good as advertised.
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PostPosted: Mon Oct 11, 2010 12:17 am Post subject: Reply with quote
Nailing the rotation...
The first 10-20 games will probably supercede whatever plan comes before it, but let's look into it.
i'll begin with Wade starting. Who should his backcourt partner be? Chalmers, Arroyo (or House, Miller, James or somebody from the deep bench) Let's stick with the Chalmers-Arroyo choice for now. Wade was modestly better with Arroyo than Chalmers on raw +/-. Who has the larger assist% or lower usage? Arroyo slightly larger assist% and lower usage ratio. I might opt for Arroyo not that it is a huge deal either way. Neither is a good 3 point shooter.
Put James at SF, Bosh at PF. Who starts at center? Anthony, Haslem, Big Z or Magliore? Anthony is by far far the lightest defensive rebounder. Is that pivotal? Maybe not given James edge but it depends on how dominant they want to be on that. His has the lowest usage. Maybe they consider that more important so the main guys get early touches. I probably wouldn't go Anthony first unless that is his main block of time and you want to get that out of the way. But I'm guessing they will. I don't know if that will be a big deal or not. Time will tell. They can change and probably will. Or at least I'd think some experiment makes sense in the long-run before the playoffs.
First off bench? Maybe Haslem for Anthony about 6 minutes in? Then to my thinking at 8 minutes in Bosh sits and Haslem slides and another center enters. Chalmers in at the 6 or 8 mark. Who’s next off James or Wade? I’ll say Wade and so Miller enters at the 10 minute mark. At the start of the 2nd quarter James sits. Bosh re-enters. Arroyo or Chambers choice depends a bit on how well each did. But lets say Arroyo is back in. At 4 minutes into the 2nd quarter Wade and James re-enter with Arroyo. Some center is playing and I haven’t a clue which it will be and am not that motivated to select between them or they go small for a bit. Haslem subs Bosh with 4 minutes left. They finish the half.
They probably run the second half a bit differently but I am just going to double the minutes from this first half for now. That would give you:
Arroyo 20-24 minutes
Chalmers 24-28
(Even a little more or less of each is possible depending of how they and team do as it is a pretty key job.)
Wade 36
Miller 12
Other wing 8 (could be partly or all Miller at times depending on if his is going well and if the opponent is tough)
James 36
TBA 4 (Bosh or James as needed, but might be worth keeping them fresh though)
Bosh 32
Anthony 16 max
Haslem 24
Other centers 24 or maybe a bit more
This is just spur of the moment, first draft but how does that sound or compare to other people’s assumptions or ideas?
In the long-run it will of course depend on how these lineups perform and how teams attack them.
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erivera7
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PostPosted: Mon Oct 11, 2010 1:01 am Post subject: Reply with quote
I really think Mike Miller needs to start for the Heat, but that's my opinion. I've watched the Heat play against the Pistons and Thunder, and with the amount of time the ball will be in James' hands (Wade, too) to be the facilitator of the offense, I think it'd behoove Erik Spoelstra if he didn't have Miller on the court with the starters. I mean, that's why they signed Miller in the first place ... to serve as the team's primary spot-up shooter.
The alignment defensively is another story, but that's my initial impression.
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PostPosted: Mon Oct 11, 2010 1:30 am Post subject: Reply with quote
I included the possibility Miller starts, though I still lean against it. The argument for as you say is spot up 3 point shooting. The argument against would be will the big 3 leave many shots for that.
He probably plays more than I first suggested or maybe even allowed with expansion over the other wings by also reducing Arroyo or Chambers or playing smaller more often (cutting the center time). I do expect he'll play more in the playoffs by some combination of these means.
He'll probably be used with the big 3 more as you suggest in the 2nd half of games than my rough doubling of the hypothetical first half plan suggests.
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PostPosted: Wed Aug 11, 2010 8:35 pm Post subject: 2010-11 NBA Win Predictions Reply with quote
Not sure if others have worked on their projections or whatnot, but seems like this thread should start soon. (Reason I thought of this was http://sports.espn.go.com/nba/news/stor ... tStandings - ESPN released their expert picks) I wont have mine up for a little while, but just testing the waters for whenever people want to make their picks.
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PostPosted: Fri Aug 13, 2010 5:18 am Post subject: Reply with quote
I think the list from ESPN is quite solid. I don't think it'll be easy to make a substantially better predition. My (very early) guesses where that list can be improved the most:
Milwaukee(-)
New York(-)
Washington(-)
Cleveland(+)
Portland(+, might be a gamble though)
San Antonio(+)
Houston(-)
Phoenix(+)
Sacramento(+)
Golden State(+)
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PostPosted: Fri Aug 13, 2010 8:35 am Post subject: Reply with quote
back2newbelf wrote:
I think the list from ESPN is quite solid. I don't think it'll be easy to make a substantially better predition. My (very early) guesses where that list can be improved the most:
Milwaukee(-)
New York(-)
Washington(-)
Cleveland(+)
Portland(+, might be a gamble though)
San Antonio(+)
Houston(-)
Phoenix(+)
Sacramento(+)
Golden State(+)
Miami for sure. New Orleans for sure. But the latter is probably a little unfair since ESPN made their picks before the acquisition of Ariza.
I'd throw Charlotte in as well. Your list is solid, but I was struck at their underrating of the first two and overrating of the last. (By a substantial margin)
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schtevie
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PostPosted: Wed Aug 18, 2010 3:01 pm Post subject: Reply with quote
Well, let me try to enliven in some small way these summer doldrums and be a bit mean to approximately half of "ESPN's best basketball minds". Looking at the forecasted Eastern Conference standings, I see very little wisdom coming from the crowd in expecting the Heat to win only 61 games. And this is not just to quibble with the predicted value (I take the over, by the way.) What I am having trouble imagining is any plausible reasoning that led the more pessimistic half (approximate) of their 93 experts to an expected win total that must have been what? 55 games? 57? And more generally, it is a bit saddening to contemplate the implication that there is little statistical reasoning whatsoever that influenced this crowd.
The average over the last 20 years (a reasonable reference, I think) for the highest regular season win total in the NBA is approximately 64 games. So, straight off, for perspective, what we are being told, is that a team that was 47-35 last year and then acquired possibly the greatest crop of free agents, in the prime of their careers, in the history of the league won't really even approach the average best record in the league. Even a "naive" prediction, for those pessimistic, simply applying the historic second best record in the league (60 games), say, would surely have raised the overall estimate.
Instead some reasoning was used that drove down the average. But what could it have been? I am going to suppose that the basic consensus among the pessimists was the same as the optimists, that as a result of the transactions, Miami would be no better on defense but considerably better on offense. The difference being that the pessimists believed that offensive improvements would only add 10 to 12 wins, max.
It is this implication that seems completely daft. And on this point, neither APM voodoo nor Wins Produced magical regressions need to be invoked. If one believes that the current collection of offensive talent on the Heat is greater than that of last year's Heat roster as well as that of the Cavs, Raptors, and Wizards (and everyone believes this, no?) the inference is that 64 wins should be an approximate lower bound.
Fleshing out the point, LBJ, Bosh, and Miller all had a TS% of about 60%. And collectively they used 50% of their teams' scoring possessions (FGA + 0.44 FTA). Miami, by contrast, jettisoned half their roster, players that utilized 49% of last year's scoring possessions at an average TS% of 53%. As a first cut then, one should expect that half the offense should improve by 7%age points. In terms of Pythogorean Wins, on a base of last year's Miami points scored and allowed, this yields 64 wins (64.2, if it matters).
Now, one can argue that the Juwan Howards of the world are going to get some shots, driving down the average, against which is the more persuasive argument, that with LBJ, Bosh, and Miller on the court, that they and others are going to see their TS%s increase.
The bottom line however is that approximately 64 wins is a huge difference from what the ESPN pessimists were predicting.
What is the larger point?
It is not unreasonable to expect, what with the ubiquitous internet sources of basketball statistics, and public discussions dating back close to twenty years, that all NBA-related media would avail themselves of what is on offer and thereby improve their craft.
Perhaps I am reading too much into a silly poll, however. Maybe the participants weren't really paying much attention, for the anonymitiy? How about ESPN shows the predictions of each participant? And to further incentivize excellence, a modest proposal: How about mimicking the organizational structure of English Football and dividing the 93 experts into three leagues (or more). The experts that best predict the Heat record can form the Premier League, the following 31 would be in the Championship League, followed by League One, or whatever. Then each year thereafter, the bottom and top of each table would be relegated and promoted accordingly. That should better focus the imagination.
But then again, the rant aside, maybe I am just plain wrong about the Heat. How does one get to 58 or so wins with that roster, though? What is the argument?
P.S. And how does the ESPN average for the middling improvement of the Heat coherently relate to the predicted collapse of the James-less Cavs?
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Crow
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PostPosted: Wed Aug 18, 2010 8:52 pm Post subject: Reply with quote
If one was trying to make the expert panel's average a better predictor, I'd think it would help over years to vary the weights given to individual predictors or even knock some out based on performance as you did. Your structure might well be helpful- market just "the Premier League" prediction average or a variably weighted blend of the leagues.
Or there might be a more flexible or complicated or just different theory driven structure that would be even better that other trained stat experts are more able to suggest, describe and possibly apply.
I haven't really thought much about what my best guess for the Heat would be, at least yet. At first blush though I am not particularly bothered by an average prediction of 61 and I'd probably move fairly cautiously if I moved up.
Royce, do you feel you could post (this time or in the future with the notice and consent of the voters) some fairly high roll-up of the team prediction distributions for the predicted wins? Say the number of votes for over and under the average? Or the number of votes for 1 to 5 wins under or over the predicted average and the same for greater than 5 over or under the predicted average? You could even use large bands for reporting the results- say less than 10 votes in that win prediction range, or 10-30, or more than 30 or whatever to give some detail but not put anyone on a small island. I'd find that both interesting and helpful with regard to the Heat and other teams, if it were considered acceptable.
back2newbelf, can you clarify what your + and - signs mean? That ESPN is too high or low in your opinion or that you personally would adjust the prediction up or down as that sign indicates? I am not clear.
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PostPosted: Wed Aug 18, 2010 10:31 pm Post subject: Reply with quote
I might be able to provide more info later, when I have more time.
As for the Heat ... a quick count reveals that 26 voters predicted fewer than 61 wins ... another 35 predicted fewer than 65 ... just to provide a couple of benchmarks that suggest in this case it's a little "easier" to pull the mean down than to lift it ... which is fairly obvious.
High: 71
Low: 50
Average prediction: 62.4
Adjusted average: 61.2
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PostPosted: Wed Aug 18, 2010 10:51 pm Post subject: Reply with quote
I'd like to know who predicted 50 wins for the Heat on the ESPN panel. For the record, I was one of the panelists and predicted 65 wins.
50 wins? That's ... a little absurd, even from the most pessimistic view.
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PostPosted: Wed Aug 18, 2010 11:05 pm Post subject: Reply with quote
I'm trying to come up with a technical term that explains why projections have to be regressed to the mean, but I can't think of such a thing. Suffice it to say that just because we know a team will win 64 games doesn't mean that whoever the best team is should be predicted to win 64 games.
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Crow
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PostPosted: Wed Aug 18, 2010 11:16 pm Post subject: Reply with quote
Since 1980-81 there have been 41 teams at or above 61 wins, 11 at or above 65 wins, 6 at or above 67 wins.
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DSMok1
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PostPosted: Wed Aug 18, 2010 11:52 pm Post subject: Reply with quote
Kevin Pelton wrote:
I'm trying to come up with a technical term that explains why projections have to be regressed to the mean, but I can't think of such a thing. Suffice it to say that just because we know a team will win 64 games doesn't mean that whoever the best team is should be predicted to win 64 games.
Yeah, that's a well known effect. We know about how good the best team will be, but we don't know which team that will be.
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PostPosted: Thu Aug 19, 2010 1:03 am Post subject: Reply with quote
If the Heat get to 67 wins that would at least tie for 3rd best out of 800 some team seasons in the last 30 years or within the top 0.5th percentile. 65 will at least tie for 9th or close to top 1%. 61 would only be about top 5% but if they hit 65 you only miss by 4 games, which is still good for any one prediction.
If one of the big 3 missed 15+ games more than expected or if they collectively missed 15+ more than expected that might knock a couple games off the predicted based on individual data, or worse than average luck in close games could, or perhaps other things (chemistry on offense and / or defense or whatever) might.
Going to 63 - 65 for Miami instead of 61 and being right would have a modest impact on the overall average error contest. It would knock about 0.1 off the average error. But if you are trying to get to an average error of 7 or significantly below 7 every 0.1 is valuable.
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PostPosted: Thu Aug 19, 2010 5:27 am Post subject: Reply with quote
I don't think the Heat care about more than having home-court advantage and might rest some players once they feel they're "safe" in #1. That would result in
max(# of wins of all other teams) + 2 or so
the "+2" is obviously debatable, since they're so good, they might even win 60% of their games when two stars are resting. Miami's strength of schedule for the last ~10 games might be important here for the final projection
Quote:
back2newbelf, can you clarify what your + and - signs mean? That ESPN is too high or low in your opinion or that you personally would adjust the prediction up or down as that sign indicates?
+ means I expect more wins
some comments:
Golden State, after having had 32 PythWins, is finally getting their center back (Biedrins) and they get David Lee (which should definitely outweigh losing Watson, Maggette, Turiaf, Randolph) is projected to 29 wins. Hm.
I think New York has good potential to implode. My tea leaves tell me that Stoudemire will be pissed after 10 games because he's not used to not being spoonfed and all the losses, leading to a whole lot of chemistry issues (even if all goes well I don't expect them to win 37)
Portland(51 PythWins) probably gets more games out of -Oden, Camby, Przybilla, Batum-, all of which are very good players. I don't see them winning 49 games(more like.. 59).
Sacramento(29 PythWins, projected by ESPN to win 30): Just losing Nocioni would have made me predict them win 35 or so. They also get Cousins and Dalembert
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PostPosted: Thu Aug 19, 2010 4:40 pm Post subject: Reply with quote
Kevin Pelton wrote:
I'm trying to come up with a technical term that explains why projections have to be regressed to the mean, but I can't think of such a thing. Suffice it to say that just because we know a team will win 64 games doesn't mean that whoever the best team is should be predicted to win 64 games.
Yeah, there's undoubtedly a term out there, but I don't know what it is. By saying "regression to the mean", we're 90% there already. A more specific term in the context of forecasting, but which unfortunately doesn't quite fit this situation, is "winner's curse". An example, which also shows how it's in reality yet another manifestation of regression to the mean: if my best estimate of how the Rockets are going to do is 41-41, then I should (using just about any loss function) predict 41 wins for them. But if my best estimate for the Heat is 66 wins, then (for a wide range of reasonable loss functions) I should NOT predict 66 wins, I should regress my forecast a bit downward, to 63 or whatever. Because people who bid high for an item of unknown value are more likely to find that the item's true value is less than they had predicted.
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schtevie
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PostPosted: Wed Aug 25, 2010 11:26 pm Post subject: Reply with quote
I am hoping that Kevin and Mike will expand a bit upon their remarks. In particular, I don't see what "regression to the mean" or "loss functions" have to do with the issue at hand...at least the issue I raised.
The stable of ESPN writers were asked to estimate the mean of the ex ante distribution of wins for each team in the NBA. That 64 out of 93 came up with a number for Miami that was 64 or below is a bit disturbing, as it would seem to betray a lack of familiarity with or interest in statistics and statistical reasoning.
What can explain this result? It cannot be based upon what Crow seems to suggest, that one of the Heat stars misses an unexpected number of games. Because....that is unexpected, part of one tail of the distribution and not the mean.
Unless someone has some inside info, I see no evidence whatsoever that last year's numbers (in terms of games played and productivity, as a baseline) shouldn't be the basis for next. Opinions on the shape of that earth shouldn't differ.
Unless.
Unless there is really a widespread belief that the coaching staff of the Heat stinks. Or, put more kindly, that James and Wade are basically the same player necessarily implies that there is no way to have them on the court at the same time without significant decreases in their productivity (compared to previous years). And that no teammates will see better shots for their combined presence on the floor. But there is no such widespread belief.
And a final point. Estimating the Heat's record matters. Not in the sense that the ESPN poll matters. It matters because it provides as good of a test as one could possibly hope for. A test of one's understanding of the game of NBA basketball, offensive basketball in particular. There is no pretense of defense being a big part of the equation, so no black box there to worry about. And there are no age issues to inject additional uncertainty.
It will be an interesting season.
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PostPosted: Thu Aug 26, 2010 12:50 am Post subject: Reply with quote
What specific assumptions are you making about injuries? The injury impact distribution will vary by team and the Heat could have more performance reducing injury impact than the average team.
James looks heavier to me and he is older. These things are both documented to increase injury risk. 2 of the last 3 years he has missed or passed on 6 and 7 games, the most of his career. 10 or more wouldn't surprise me. Bosh has missed 12 or more games 4 of the last 5 years. Wade has missed 20+ games in 3 of 7 years for a career average of 15. On quick inspection, that seems to add up to more than an average injury impact risk for leading players to me.
Diminishing return impacts for likely usage cuts for the big 3, shared rebounding, etc. can reasonably vary. Your in / out TS% change estimate for the offense is pretty rudimentary. How good will they be as a team from 3 pt land in quantity and FG%? None of the big 3 is anywhere close to even average on 3 point accuracy for their careers. That could matter in a way that overall TS% doesn't pick up exactly. They have other 3 point shooters but how many will they get up and how will the team averages turn out?
How well will they accept their roles and get along on the court? I can see a number of possible frictions that might hold performance somewhat below what a simple projection of past stats would predict.
Each additional win after 55 and 60 is probably increasingly tough (likely needing to win more against good teams to achieve this). A linear win estimate system might well predict too high.
Defense is hard to predict. Counterpart data at 82 games suggests Wade and James to be a little better than average 1 on 1 when facing a lot of starters, Bosh moderately worse. Another tool out there for individual impact estimates, but considering both 1 on 1 and help dimensions, was defensive 4 factors and it shows 2 of the big 3 to be weak (40th percentile or less) on 3 of the 4 defensive factors and 4 of those 12 ratings were in the weakest 16% of the league. It is hard to say how good the team defense will be with them in together at the core with a bit less room for defensive assistants to help than the Cavs or Heat could use as desired or needed with James and Wade. It is hard to say how quick the defense gets to its maximum or how consistent they will be.
How intensely focused and successful will they be in Miami-South Beach with all they want to do and will be asked to do off the court and with the constant media scrutiny? No other team will face this level of scrutiny and potential distraction or harm. It is also not unreasonable to expect that almost every team they face will try very hard to keep up or beat them, perhaps more so than against just any routine preseason #1 or #2.
The average wins of the two recent super teams (Boston and LA) who have won titles over their 2 peak was 62.5.
The average for the best team in the 11 seasons post the Jordan championships and the lockout was 62.7 actual wins. 5 times the leader was at 61 or less. 4 times at 65 or more. 62 was the median.
61 or 65. They are different. I am not sure yet which is better bet but I don't think it is so easy and obvious that 65 is better. It would take more a detailed presentation to convince me that 65 is clearly the better estimate and better than 63 as well. 63 seems a bit safer at this point to me on the surface but it would take very little in a detailed analysis to swing the estimate 2 games either way.
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back2newbelf
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PostPosted: Wed Sep 22, 2010 6:01 pm Post subject: Reply with quote
Could you post the entire vegas predictions or link to them, please. Thanks
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Crow
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PostPosted: Wed Sep 22, 2010 7:55 pm Post subject: Reply with quote
Links for General odds to win the title and
season win propositions for just the Heat and Lakers (at least so far) both listed here.
http://www.sportsbook.com/livesports/in ... basketball
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schtevie
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PostPosted: Thu Sep 23, 2010 9:17 am Post subject: Reply with quote
OK, time to revise and extend my remarks again, about expected injury/participation. A little voice in my head kept saying "What about Penny?".
Basically, the averages I presented didn't best address the circumstance facing DW this year. The assumption was that he would continue be a 35 mpg player at age 29. This served to screen out the "would be" 35 mpg players who dipped below that in year 29 for injury reasons. Back to the drawing board.
So, querying the lovely basketball-reference database, for 35 mpg 28 year old guards over the most recent 20 year range (1999-00 to 2008-09) we then follow these results to their 29 year old season. This picks up broken Penny and leads to a slightly different picture. (And again, for consistency, I culled out those players from the search results that either weren't career starters, had their 29th year in the lockout shortened season, or had the misfortune of perishing in European car accidents: Craig Ehlo, George McCloud, Scott Skiles, Spud Webb, Steve Smith, Drazen Petrovic, Doug Christie, and Tyrone Corbin).
The overall results:
(1) These guards which participated in 73.4 games when they were 28, saw a drop-off the following year, playing in 70.3 games (and playing 35.4 mpg).
(2) For the eight players over the past 20 years having Wade's history of 67.3 games played per season by the age of 28 (these are: Vince Carter, Jerry Stackhouse, Eric Snow, Baron Davis, Anfernee Hardaway, Ron Harper, Tim Hardaway, and Larry Hughes) things look grimmer, their average year 29 consists of 60.5 games (and 33.2 mpg). (And if you add in the two players just above the cut-off, Lindsey Hunter and Chauncey Billups, who averaged 67.3 and 67.7 games per year by age 28, the average of games played in year 29 moves up significantly to 64.7.)
(3) For what it's worth (not much) the player, actually whose experience most looks like Wade's in this framework is Vince Carter, who missed significant amount of games at ages 22, 25 and 26 (though I am certainly not saying the injury history of these two players was similar) and he showed up for 79 games at age 29.
But a little context on point (2). What drives down the average are the data for Penny and Stackhouse (4 and 26 games played, when 29, respectively). Without Penny, the average goes to 68.6 and without both, we return to 75.7.
Would it be cherry-picking to remove them in terms of properly gauging expectations? Yes, in a sense that we have a really small sample here (I await Neil's multivariate analysis for better results) and we shouldn't chuck out data. But, no, in the sense that these two guys were injured before their 29th year old season began. Accordingly, if Wade clears training camp healthy enough to start the first game, the unfortunate experiences of Penny and Stackhouse don't logically apply.
According to these revisions, perhaps I should change my beliefs? Heat win between 64 and 69 games? Nah. Never mind.
P.S. More interesting is another apparent implication of the games played data. If you sort the results (again, average games played per season in up to seven years prior to and including 28, but not including the lock-out year data in the average....whew) by total years in the NBA by age 28, there is a more ominous trend apparent.
6 year veteran guards playing 35 mpg or more at age 28 (that is those entering the league who were 23 at midpoint in their first season) played in 76.1 games the following year. 7 year veterans, those who entered at age 22, their season averaged only 71.25 games at age 29 (75.7 if you kick out Penny). 8 year veterans, their next year's participation drops to 65.4 games (sample of eight). 9 year: 65 games (sample of four). 10 year: 55 games (sample of two). Then 11 year: 74 games (sample of one: Kobe!). Taking the 8 year and over average, the drop is to 60.9 games.
What is the point? Well, if someone wishes they can extend the analysis to expectations for 30 year guards, inclusive of the age 29 season, but if the results are similar, I wouldn't bank on a three-peat just yet in Miami.
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mtamada
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PostPosted: Wed Oct 06, 2010 1:45 am Post subject: Reply with quote
schtevie wrote:
I am hoping that Kevin and Mike will expand a bit upon their remarks. In particular, I don't see what "regression to the mean" or "loss functions" have to do with the issue at hand...at least the issue I raised.
Sorry, late reply here. My expansion starts with an example: one of the major ways of utilizing regression to the mean is with Stein estimators. The classic example is if it's two weeks into the baseball season and you see a player who's currently batting .412, and you want to predict what his batting average for the rest of the season will be, you do not (if you're smart) use the unbiased estimate of .412. You want to purposely use a biased estimate, and regress to the mean, because extreme performances are unlikely to be sustained.
The key word is extreme. Stein estimators are remarkable because "extreme" and "mean" can be used in a variety of situations; the baseball example is intuitively obvious, not so obvious is that the mean that you regress to doesn't even have to be the mean of baseball players' batting averages (although obviously, the more similar the variables are to each other, the better the Stein estimator will perform, e.g. if you have data on that same player from other seasons, that can be better than using the mean of all other baseball players).
Bottom line, it doesn't have to be two-week baseball averages. ANY extreme value is more likely to regress to the mean rather than maintain (or be realized) at its extreme value.
And this includes extreme forecasts. We're not talking about two weeks into the basketball season, but as I described above, it doesn't matter. The same principles hold.
Do NBA teams sometimes win 72 games? Yes sometimes they do. But you don't get rich by betting on it happening.
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schtevie
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PostPosted: Wed Oct 06, 2010 9:11 pm Post subject: Reply with quote
Mike, I am still not getting the relevance. Further advice requested.
I was being unkind to a significant portion of the ESPN electorate because they had provided guesstimates of the expected performance of the 2010-11 Heat that were, to my reckoning, at variance with what the fundamentals suggest. The issue, as I understand it, is what is the best estimate of the mean to which performance should regress?
For my approximation, I estimated the effect of James et al. on points scored then added it in to B-R's Pythagorean Wins formula for a Miami Heat baseline. This is a simple production function, with the additional input being the change in expected points (= 2009-10 free agent TS% * vacated scoring opportunities with the Heat).
If the argument is that using last season's TS%s (basically career highs) is an error akin to a baseball player starting off the season hitting .412, I take the theoretical point. However, the assumption is bolstered by the evidence from aging curves which suggests that, for 25 year old players, the mean to which they will regress is rising.
The important known unknown - to paraphrase an infamous American - is the degree to which there are diminishing returns in offensive efficiency relating to overlapping responsibilities on offense. Against which there is a theoretical offset: having better teammates gives a player better scoring opportunities, all else equal. My "model" called this even: the free agents don't get worse, but the pre-existing Heat don't get better either. Anyway, this assumption has nothing to do with unforeseen regressions to the mean. Does it?
Finally, for completeness, there are no similar issues to be concerned about in translating estimated points to wins using the Pythagorean Wins formula, are there?
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mtamada
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PostPosted: Wed Oct 06, 2010 10:39 pm Post subject: Reply with quote
schtevie wrote:
Anyway, this assumption has nothing to do with unforeseen regressions to the mean. Does it?
That assumption, and the rest of the assumptions, indeed seemingly have nothing to do with unforeseen regressions to the mean. But that's why they're unforeseen.
I.e. your estimates are based on what the numbers tell you the expected outcome ought to be. Seemingly the best procedure. And indeed, for non-extreme estimates, it is the best procedure.
But when your estimates are extreme, i.e. when they are predicting an extreme outcome, that's when you start putting less weight on your numbers and more weight on the mean. Due simply to regression to the mean, which indeed has nothing to do with your assumptions, it just happens. And it's unforeseen (but foreseen by people who have the foresight to take regression to the mean into account).
If you draw 24 balls out of a barrel and 10 are white (and the other 14 are black), and someone asks you to estimate the percent of white balls in the barrel, then 10/24 = .417 is as good an estimate as you can come up with, yes? If that's all the information that you have, yes. But if you know that we're talking about the first 24 at bats of the season, then you have additional information (this is where the Bayesianism starts creeping in), and you say wait a minute, I do not believe that this batter is going to keep hitting .417 for the rest of the season.
If you run your LeBron James stats and take age curves into account and teammates and etc. etc. and the numbers tell you 72 wins, well that's as good an estimate as you can come up with, yes? If that's all the information that you have, yes. But if you know that we're talking about NBA teams, then you say wait a minute, NBA teams almost never win 72 games.
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DSMok1
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PostPosted: Thu Oct 07, 2010 12:08 pm Post subject: Reply with quote
Well said, Mike. You have to regress!
BTW, I am showing that James (+11.5) and Wade (+8.5) contribute nearly all of their advantage on offense (there's a lot bigger spread on offense in general--kind of like baseball). There is no way that an offense can run in the +19 efficiency range. No way an offense can even sniff that. The best offense ever was +9.2 (Dallas 2004). Now obviously, their teammates are not league average on offense, though Bosh was a +4.8 on offense last year. That said, I expect tremendous regression to the mean--even a + 10 offense would be astounding. And most teams with such an offensive efficiency can't maintain even average on the other end of the court.
For reference, James, Wade, and Bosh show as +2.2, +1.9, and +0 on the defensive end.
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BobboFitos
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PostPosted: Thu Oct 07, 2010 10:42 pm Post subject: Reply with quote
DSMok1 wrote:
Well said, Mike. You have to regress!
BTW, I am showing that James (+11.5) and Wade (+8.5) contribute nearly all of their advantage on offense (there's a lot bigger spread on offense in general--kind of like baseball). There is no way that an offense can run in the +19 efficiency range. No way an offense can even sniff that. The best offense ever was +9.2 (Dallas 2004). Now obviously, their teammates are not league average on offense, though Bosh was a +4.8 on offense last year. That said, I expect tremendous regression to the mean--even a + 10 offense would be astounding. And most teams with such an offensive efficiency can't maintain even average on the other end of the court.
For reference, James, Wade, and Bosh show as +2.2, +1.9, and +0 on the defensive end.
Is it really so hard to imagine this years heat team being the best offense ever, though? I agree you can't just simply "merge" their APM rating or SPM rating or whatever, but I don't think it's a bad bet that they'll have a >+10 offense.
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schtevie
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PostPosted: Sun Oct 10, 2010 9:45 am Post subject: Reply with quote
Mike, perhaps one or more of the ESPN anonyms who put the Heat in the 50s feels a bit better about his or her estimate, for your emphasis of the centrality of "regression to the mean" when it comes to extreme estimates. In the instance, however, I don't think there is much succor to be found in the concept.
I am not arguing with its general utility, nor the importance of recognizing its scope. Indeed, returning to the initial focus of this string, for anyone who is a bit lazy but who still wants a good chance at winning (and certainly not losing) this year's prediction competition, a simple rule of thumb will get you far: take last year's team records and regress them to the mean a bit (say -0.2 or -0.3 for each win above average). With an ad hoc adjustment for the Heat (and other teams that had clear changes in strength) and you'll be in the mix at the finish. Guaranteed.
But invoking "regression to the mean" arguments won't help much in justifying low-ball estimates for the Heat, primarily because what appears to be an extreme estimate, isn't really. And to the extent that an ex post adjustment need to be made to an estimated outcome, "regression to the mean" isn't the relevant concept. (I am pretty sure.)
To take the most important example, extrapolating LBJ's past performance is not evidence of an extreme estimate, precisely because he is an extremely good player. His performances year to year are highly correlated. We are not talking here about an average baseball player who starts the season hitting .417 with 24 at bats. For TS% (the basis of my simple model) there is a multi-year record of nearly 2000 scoring possessions per season. And in terms of how consistent we should expect his performance to be, we can get a sense of to where he might regress, by looking at TS% for the appropriate age and position cohort.
Taking as a relevant sample the last six years (the starting year, 2004-05, chosen so as to have a more similar year to year average scoring propensity in the NBA) for forwards playing 25 mpg or more at a specific age, these are the LBJ's TS% percentiles at ages 20 to 25: 82, 76, 75, 71, 86, and 90. And the non-regression story is essentially identical with Bosh.
OK, so perhaps the relevant regression is to the 80th percentile of this distribution, so perhaps a decrease of 1.5 percentage points in TS% on this account? Against which we are looking at expected improvement due to maturity, suggested by LBJ's increasing propensity to get to the free throw line. The bottom line is that, on net, regression to the mean, at least on the account of expected individual performances anyway, shouldn't be the reason for downgrading the "expected" performance of the Heat this year.
If one is looking for such a reason, it can be found by invoking the assumed concavity of the basketball production function. In such an instance, the wins produced by the expected value of inputs is greater than the expected wins generated by the ex ante distribution of such inputs. Maybe the production function is really concave, and this is the argument that the aforementioned section of the ESPN electorate was invoking?
Finally, DSMok1, any chance you might provide a complete estimate for the Heat using your SAPM numbers? Whatever it turns out to be, "regression to the mean" shouldn't be the argument invoked to explain any expected deviation from reality. Any notional overshooting of the estimate will more properly be on account of fundamentals: the fact that James and Wade play functionally similar positions; what an estimate based on simple addition of SAPM doesn't take into account.
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DSMok1
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PostPosted: Sun Oct 10, 2010 3:16 pm Post subject: Reply with quote
ASPM would be the right acronym. Advanced Statistical Plus-Minus. Yes, I intend to try to create projections for every player in the league and then create team projections from that. A major problem, though, is how to forecast playing time. That's pretty tricky.
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Crow
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PostPosted: Sun Oct 10, 2010 5:01 pm Post subject: Reply with quote
In a quick scan of predictions for the Heat I find about 1/3rd in the low 60s, 1/3rd in the mid 60s and 1/3rd in the high 60s.
The impact of big 3s on their usage has been covered some but I went back to check before-after on TS% and Win Shares. Using big usage duos and triplets identified from recent years by Neal at B-R, I found, in rounded terms, TS%s went up for about 70% of the time for those stars while Win Shares went up about 60% of the time. Actual team wins went up by an average of just 2 games over the previous season of the team where the new pair or trio played. There were a couple of huge successes (Boston 07-08 and Cavs 08-09) but a couple of big flops and most were small to modest gains.
It also seems worth noting that both Wade and James have seen attempts to create new big 2s and 3s. James-Williams in 08-09 worked for both guys in the regular season and big for the team. James-Williams-Jamison in 2009-10 didn't work out in the 2010 playoffs. Wade-O'Neal-Walker actually slipped from the previous regular season in team wins but won the title. All 3 improve on TS% while 2 of the 3 improved on WinShares. Wade-Davis was a flop for the team and both players but it wasn't the only reason for the team fall.
The 2003-4 season in LA was good for Payton on both TS% and Win Shares, a split decision for Malone, neutral on one, down on the other for Kobe, down on both for O'Neal. Not enough opportunity for efficiency / effectiveness / glory to spread all the way around?
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greyberger
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PostPosted: Sun Oct 10, 2010 11:00 pm Post subject: Reply with quote
Very interesting. When the focus is on Lebron and Wade, I wonder how they'll be dispatched - if the idea is to keep at least one of them on the court in every meaningful minute, usage will vary a lot from lineup to lineup. For the appearance of it you can't use Dwayne Wade as a sixth-man, but having him in and fresh when Lebron and Bosh are taking their first rest might be the best way to do it.
With Wade and James you have to figure the flexibility is there, both in the general sense and the 'skill curves' sense. I'd be more worried about nailing the rotation than whether the 'best 5 in' lineup is as good as advertised.
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Crow
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PostPosted: Mon Oct 11, 2010 12:17 am Post subject: Reply with quote
Nailing the rotation...
The first 10-20 games will probably supercede whatever plan comes before it, but let's look into it.
i'll begin with Wade starting. Who should his backcourt partner be? Chalmers, Arroyo (or House, Miller, James or somebody from the deep bench) Let's stick with the Chalmers-Arroyo choice for now. Wade was modestly better with Arroyo than Chalmers on raw +/-. Who has the larger assist% or lower usage? Arroyo slightly larger assist% and lower usage ratio. I might opt for Arroyo not that it is a huge deal either way. Neither is a good 3 point shooter.
Put James at SF, Bosh at PF. Who starts at center? Anthony, Haslem, Big Z or Magliore? Anthony is by far far the lightest defensive rebounder. Is that pivotal? Maybe not given James edge but it depends on how dominant they want to be on that. His has the lowest usage. Maybe they consider that more important so the main guys get early touches. I probably wouldn't go Anthony first unless that is his main block of time and you want to get that out of the way. But I'm guessing they will. I don't know if that will be a big deal or not. Time will tell. They can change and probably will. Or at least I'd think some experiment makes sense in the long-run before the playoffs.
First off bench? Maybe Haslem for Anthony about 6 minutes in? Then to my thinking at 8 minutes in Bosh sits and Haslem slides and another center enters. Chalmers in at the 6 or 8 mark. Who’s next off James or Wade? I’ll say Wade and so Miller enters at the 10 minute mark. At the start of the 2nd quarter James sits. Bosh re-enters. Arroyo or Chambers choice depends a bit on how well each did. But lets say Arroyo is back in. At 4 minutes into the 2nd quarter Wade and James re-enter with Arroyo. Some center is playing and I haven’t a clue which it will be and am not that motivated to select between them or they go small for a bit. Haslem subs Bosh with 4 minutes left. They finish the half.
They probably run the second half a bit differently but I am just going to double the minutes from this first half for now. That would give you:
Arroyo 20-24 minutes
Chalmers 24-28
(Even a little more or less of each is possible depending of how they and team do as it is a pretty key job.)
Wade 36
Miller 12
Other wing 8 (could be partly or all Miller at times depending on if his is going well and if the opponent is tough)
James 36
TBA 4 (Bosh or James as needed, but might be worth keeping them fresh though)
Bosh 32
Anthony 16 max
Haslem 24
Other centers 24 or maybe a bit more
This is just spur of the moment, first draft but how does that sound or compare to other people’s assumptions or ideas?
In the long-run it will of course depend on how these lineups perform and how teams attack them.
Last edited by Crow on Mon Oct 11, 2010 1:36 am; edited 1 time in total
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erivera7
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PostPosted: Mon Oct 11, 2010 1:01 am Post subject: Reply with quote
I really think Mike Miller needs to start for the Heat, but that's my opinion. I've watched the Heat play against the Pistons and Thunder, and with the amount of time the ball will be in James' hands (Wade, too) to be the facilitator of the offense, I think it'd behoove Erik Spoelstra if he didn't have Miller on the court with the starters. I mean, that's why they signed Miller in the first place ... to serve as the team's primary spot-up shooter.
The alignment defensively is another story, but that's my initial impression.
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Crow
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PostPosted: Mon Oct 11, 2010 1:30 am Post subject: Reply with quote
I included the possibility Miller starts, though I still lean against it. The argument for as you say is spot up 3 point shooting. The argument against would be will the big 3 leave many shots for that.
He probably plays more than I first suggested or maybe even allowed with expansion over the other wings by also reducing Arroyo or Chambers or playing smaller more often (cutting the center time). I do expect he'll play more in the playoffs by some combination of these means.
He'll probably be used with the big 3 more as you suggest in the 2nd half of games than my rough doubling of the hypothetical first half plan suggests.
