One of my favorite lines in the Wages of Wins was actually written by Allen Barra:
“Stat Nerds” they snort contemptuously at me, and probably at you, too, if you’re smart enough to have picked up this book-but the truth is that they depend as much on numbers as anyone else when it comes to making decisions. What else, after all, are you going to rely on? What, in the final analysis, are statistics but a record of what a player does when you’re not watching him? And we don’t have time to watch 99 percent of the players 99 percent of the time.
This quote captures the essence of statistical analysis. Statistical analysis is not a substitute for watching games. Statistical analysis helps you understand what you are watching.
Although proper statistical analysis is important, it’s important to note (as I noted yesterday) that statistical analysis is not a crystal ball. We can’t look at the numbers and know the future with absolute precision. In other words, just because Erich Doerr called the outcome of the NCAA championship game before the tournament started in 2008, we should not think this will happen every year (so please don’t bet your life-savings on next year’s forecast).
Erich based his forecast on a Monte Carlo simulation, which primarily employed each team’s offensive and defensive efficiency. For the NBA playoffs I am going to take the same approach. Well, I’m not going to bother with a simulation. But I am going to offer a forecast utilizing each team’s efficiency measures (and yes, I did do this a few days ago, but now we have the final numbers for the regular season).
First, let’s look at the data.
Table One: 2008 Playoffs by the Numbers
From Table One we see that the best offensives – in terms of offensive efficiency – are offered by Phoenix, Utah, and the LA Lakers. The best defensives – in terms of defensive efficiency – are in Boston, Houston, and San Antonio.
Efficiency Differential considers both efficiency measures, and hence tells us about the quality of the entire team. When we turn to efficiency differential we see that Boston, Detroit, and the LA Lakers were the best teams this season.
With this information in hand, we can now forecast the playoffs (and yes, I am a couple of days late but the regular season data hasn’t changed in that time).
Eastern Conference Forecast
First Round
Boston over Atlanta
Detroit over Philadelphia
Orlando over Toronto
Washington over Cleveland
Second Round
Boston over Washington
Detroit over Orlando
Conference Finals
Boston over Detroit
Western Conference Forecast
First Round
LA Lakers over Denver
New Orleans over Dallas
San Antonio over Phoenix
Utah over Houston
Second Round
LA Lakers over Utah
New Orleans over San Antonio
Conference Finals
LA Lakers over New Orleans
And in the NBA Finals
Boston over LA Lakers
The above forecast is based solely on each team’s efficiency differential for the season. There are two additional factors we should consider in looking towards the future.
Mid-Season Trades
Several teams made mid-season moves. And given these moves, the players being brought into the playoffs are not the same as the players who generated the observed differential.
For example, the Suns had a 6.2 differential before acquiring Shaq, and a 3.54 afterwards. This leads us to think that San Antonio and Phoenix – despite the first game of the series – is not as close as the differential for the season would suggest.
The Dallas Mavericks also made a major trade. Before the acquisition of Jason Kidd, Dallas had a 4.27 differential. After this trade – despite injuries to Dirk Nowitzki and Josh Howard – Dallas had a 5.99 differential. This tells us that Dallas could be favored to defeat New Orleans, as well as their potential second round opponent (either San Antonio or Phoenix).
Home-Court Advantage
Last year I placed third in the True Hoop Stat Geek Smackdown. Here is what I said last summer about this contest:
The similarity between Jason Kubatko’s picks and my own extended throughout the competition. In 11 out of 15 series, Kubatko and I had the same winner in the same number of games. Yes, 73% of the time we had exactly the same forecast.
Here is where we differed:
Rockets vs. Jazz: I had the Rockets in seven. Kubatko had the Rockets in five. Jazz won the series in seven.
Cavaliers vs. Wizards: I had the Cavs in four, Kubatko had the Cavs in five. Cavs won in four.
Cavaliers vs. Nets: I had the Cavs in seven, Kubatko had the Cavs in five. Cavs won in six.
Pistons vs. Bulls. I had the Bulls in six, Kubatko had the Pistons in seven. Pistons won in six.
In the end, the Pistons and Bulls were my un-doing. In discussing his victory, Kubatko revealed his methodology. Kubatko said he picked teams strictly by the numbers, which is also what I did. In other words, we each tried to ignore how it looked like a team was playing in the playoffs. Consequently we each picked the Jazz to defeat the Warriors in five.
But whereas I only considered efficiency differential, Kubatko considered both the quality of the two teams and home court advantage. And when you consider home court advantage we see that the Pistons should have been slight favorites to defeat the Bulls. So I failed because I ignored home-court advantage (which was a bit stupid on my part).
To summarize: Last year I only considered efficiency differential. Kubatko considered team quality and home court advantage. The latter factor appeared to give him the decisive edge.
If we consider home-court advantage, then I think Cleveland should be favored to defeat Washington. And New Orleans – despite the Jason Kidd trade – could be favored to defeat Dallas.
And this is exactly how Kubatko calls these series.
About the Smackdown
Henry Abbott graciously invited me to participate in the Smackdown this year. Unfortunately, I don’t think I am going to have the time to do this (there is also another constraint that I will explain in a few months). Although I don’t have the time to participate in this challenge, I did offer Henry my forecast of the Smackdown.
I predict that Kubatko repeats.
The best predictor of these games is efficiency differential and home court advantage. I think that’s Kubatko’s basic model (I could be wrong about that, but I think that is what he considers), therefore I think he will repeat.
Henry did say he hopes I can participate next year, and hopefully I can take him up on that invitation. Certainly I hope I will have more free time in 2009 (at least, I better have more free time in 2009).
– DJ
Our research on the NBA was summarized HERE.
The Technical Notes at wagesofwins.com provides substantially more information on the published research behind Wins Produced and Win Score
Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:
Simple Models of Player Performance
What Wins Produced Says and What It Does Not Say
Introducing PAWSmin — and a Defense of Box Score Statistics
Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.
Wages of Wins Journal 
stephanie
April 21, 2008
So after watching Denver get stomped by LA I was thinking about Allen Iverson. As you’ve shown in many articles he is barely an above average player in terms of win score. I was thinking that as he gets older and loses a step he may be forced to play off the bench, play smarter in terms of shot selection and working within a system and distribute the ball more than usual. Is it possible that his win score could actually go up as he ages? Are there any notable examples in your research of players contributing more as they age into their mid to late 30s? I’m guessing it’s very rare but not completely impossible.
Also, with all this talk of efficiency differentials and projected wins and all that I’d love to know if there’s a resource where I can see this applied to all the post seasons in the last 30 years or so. My searches have come up short. How often do major upsets in terms of efficiency differential occur? Or how often is that just a fluke instead of injuries or trades? Those are the kind of things I wonder about. I plan on getting the WoW book eventually so if it’s in there just tell me and I’ll shut up about it.
But…for example, I’m under the impression that the mid 90s Rockets, in terms of eff. def., were one of the weakest champions of all times. Yet they won back to back titles and they beat many teams in seven game series, in many cases without home court advantage. And they had a worse record and a worse eff dec. Was all of that a huge streak of luck? Was Hakeem the Dream just playing out of his mind in the post season? Are there reasons they were the only #6 seed to win a title that I’m ignorant of? Were they plagued by season injuries that healed before the playoffs or something?
stephanie
April 21, 2008
My above post’s grammar is a good example of being in a pre-coffee fog. And being used to posting and then fixing mistakes with the edit button.
Rick
April 21, 2008
Well, the one thing that kept SA’s efficiency differential so low was the fact that its three stars, especially Duncan play far fewer minutes in the regular season than the playoffs. If Duncan were to average close to 40 mins/game (as he does during the playoffs), SA’s differential would be higher. No other Western conference team can claim to rest its stars as much as SA does and that does distort your analysis…
Owen
April 21, 2008
Stephanie – Basketball Reference is always a great resource. You can see the teams efficiency differentials and check out their rosters. The first championship Rockets team was actually pretty good. They had an expected Win-Loss in 93-94 of 70.7%. There record wasn’t that good the next year, with an expected win loss of just 57.3. But I would think adding Drexler after the halfway mark probably improved their chances of winning the title beyond what their efficiency differential might have suggested.
Wy
April 21, 2008
The differentials can’t predict everything.
After Drexler came to Houston in 95, Rockets had a losing record of 17-18. You can imagine that their differentials would’ve been worse too.
stephanie
April 21, 2008
I know about basketball reference but you have to calculate the differential yourself and then look at their opponents and do them too. I’m pretty lazy, which is why I’d like something that had everything laid out already. But I’m pretty curious so I’m going to spend some time on this.
Tommy_Grand
April 21, 2008
There is a move (reasonably common) I believe your metric fails to incorporate. It is: when a scorer (often a guard) takes a shot despite knowing he (or she) will likely miss, because he (or she) correctly recognizes that a teamate (usually a forward or center) will perfectly positioned for the “put back,” “tip in,” or (worst case) offensive rebound. This move is a great way to negate shot-blocking; I see good players utilize it often.
Would you call it a “good miss” or a “shooting assist?” I dunno.
But unless I misunderstand your numbers (which happens often), this productive tactic is not included in assessing a player’s production. In fact, a player who did this often (left say 2-3 shots on the rim for Dwight Howard to dunk) would see his win score go down: his shooting % declines b/c they are considered missed shots (except some go in) and are usually not deemed assists. I suppose if scorekeepers did a better job of crediting players for assists when this happens, it would be included in the model. But I dont think that happens right now.
I await a thorough edification and education.
antonio
April 21, 2008
you can’t really include that because it is not kept track of and it is also a judgement call whether or not the shooter shot because he saw the rebounder. also, it happens so rarely, that the effect it would have on one players stats is probably insignificant. I can’t think of one player who is known for doing this.
Tommy_Grand
April 22, 2008
This season, I’ve seen Chris Paul, Baron Davis, and Raymond Felton do it. If you watch New Orleans , you will see Tyson chandler get 2-3 easy putbacks/dunks off zany Paul misses.
Since CP3 is a good shooter and has good judgment, I perceive these as intentional. But that’s subjective. I suppose these easy putbacks might be deemed mere luck (or excellence on the part of Tyson Chandler). One reason for my opinion is that I’ve heard some successful NBA coaches talking about getting guards to do this more. In particular, I remember Greg Popovich discussing his efforts in the off season to urge Parker to get the ball to the rim and let the Spurs’ “garbage men” (eg Oberto, Robert Horry, even Duncan on occasion) tip it in. I also heard/read Mike Brown saying he wanted his PGs to “just put it up there and let Lebron and Z clean it up.”
So, in my unscientific opinion, it happens somewhat often with some players. But you’re right: the subjectivity involved makes it a difficult datum to capture.
The Franchise
April 23, 2008
I can definitely understand that strategy, and it is a limitation of the WP formula. It does make sense that it is better to take shots when the chances of offensive rebounds are higher, since the risk of a negative outcome is lower. Anyone that plays pickup games should know this; such contests can be very lopsided if one team is particularly effective on the offensive glass.
Of course, this strategy still relies on the skill of the big men, counting on their ability to rebound and make put-back shots.
antonio
April 24, 2008
you noted players who have done it, but i think its more of an out of the blue scenario than something that consistently happens. i live in new orleans, and i can say that chris paul does not do this 2-3 times a game. While I do believe this happens, I don’t believe it is significant enough to change a players ranking in any metric. Also, I think what the more common thing to do is if a player sees that they have men under the basket and the other team does not, just to shoot the ball (still trying to make it in), but only shooting because there is a greater chance their miss will be cleaned up. I still think a lot of the time it is not an intentional miss
Tommy_Grand
April 25, 2008
“I think what the more common thing to do is if a player sees that they have men under the basket and the other team does not, just to shoot the ball (still trying to make it in), but only shooting because there is a greater chance their miss will be cleaned up. I still think a lot of the time it is not an intentional miss”
Antonio, I agree 100%. I must have done a bad job of writing. I do NOT mean the players miss shots intentionally. What I mean to say is, some guards take low % shots b/c they know someone has their back. They will either make it or a teamate gets an easy put back. They dont try to miss, but they wouldnt take the risky shot if their teamate wasnt there. Instead, they would work for a higher percentage look.
I do think this situation happens 3-4 times per game. Maybe 1 time in 4, the shot falls, and people are like, damn! his coach hates him shooting that one. Then, maybe 2 times out of 4, a teamate gets an easy tip in, dunk, or offensive board. The remaining 25% of the “bad” shots kick out to a defender.
So 75% of the time, it’s a good play, but 75% the time the shooter’s WOW score goes down — since the play is recorded as a missed shot.
Ordinarily, coaches dont want you to live on jumpers if you’re guarded. But if an awesome center is standing alone under the basket (and you cant see a passing lane) they’ll tell you take a high risk shot. Of course, try like hell to make it, but it’s ok to take risky shots if your teamate can throw it down.
Sorry if I didnt explain myself well.
Animal
April 26, 2008
Dave Berri for President!
Tyson
June 4, 2008
You only got one pick wrong leading up to the NBA Finals. That’s impressive, even considering that it’s a small sample size.