Every Player at Halftime of the 2007-08 Season
Reviewing Every Player on Every Team was a post offered last month. This column reported every player’s WP48 [Wins Produced per 48 minutes] and Wins Produced somewhere around the quarter-pole of the season.
On Tuesday night, the Atlanta Hawks finally played their 41^{st} game. So now every team has reached the midpoint of the season.
Over the next few days I will offer some thought on the first half of the 2007-08 campaign. For now, though, here is every player in the NBA after 41 games.
Table One: All NBA Players after 41 games of the 2007-08 season
A few notes to consider in looking at this table:
1. Players are ranked in terms of Wins Produced. So this might make finding your favorite player a bit difficult. Soon I will post the results organized by team.
2. Projected Wins Produced is simply Wins Produced *2. This assumes that what you did in the first half – including minutes played – stays the same in the second half. Obviously for a player like Andrew Bynum – who is injured – this is not true. So keep that in mind in looking at the projections.
3. If a player played for multiple teams he is listed twice.
4. The results don’t appear much different from what I posted in December. Seven of the top ten players in December are still in the Top Ten at the mid-point of the season.
5. Here is what the All-Star game rosters would look like if fans and coaches only considered Wins Produced. I will comment more on the All-Star game in a future post. For now, though, I just wanted to note that WordPress does allow me to put tables directly into the posts. These are not pretty, but I think they can be read.
Rank |
Western Conference Stars |
WP48 |
Wins Produced |
Starters | |||
4 |
Chris Paul |
0.377 |
11.4 |
10 |
Steve Nash |
0.321 |
9.1 |
7 |
Shawn Marion |
0.314 |
9.6 |
16 |
Carlos Boozer |
0.281 |
8.1 |
2 |
Marcus Camby |
0.437 |
12.8 |
Reserves | |||
17 |
Baron Davis |
0.237 |
7.9 |
18 |
Kobe Bryant |
0.240 |
7.6 |
27 |
Dirk Nowitzki |
0.204 |
6.4 |
31 |
Josh Howard |
0.202 |
5.8 |
8 |
Tyson Chandler |
0.323 |
9.4 |
13 |
Tim Duncan |
0.322 |
8.4 |
15 |
Chris Kaman |
0.256 |
8.2 |
Rank |
Eastern Conference Stars |
WP48 |
Wins Produced |
Starters | |||
5 |
Jason Kidd |
0.348 |
10.8 |
9 |
Chauncey Billups |
0.335 |
9.2 |
3 |
Kevin Garnett |
0.398 |
11.9 |
6 |
LeBron James |
0.331 |
9.9 |
1 |
Dwight Howard |
0.440 |
14.6 |
Reserves | |||
12 |
Jose Calderon |
0.319 |
8.5 |
28 |
Mike Dunleavy |
0.215 |
6.3 |
11 |
Caron Butler |
0.253 |
8.5 |
25 |
Paul Pierce |
0.205 |
6.7 |
30 |
Samuel Dalembert |
0.207 |
5.9 |
29 |
Antawn Jamison |
0.175 |
5.9 |
32 |
Emeka Okafor |
0.203 |
5.7 |
In closing this post I wanted to repeat something I said back in December. Specifically, I wanted to repost the following observation I offered on baseball stats – an observation that I think applies to those looking at statistical analysis of the NBA.
A Comment on Statheads in Baseball
My first love growing up in Detroit was baseball. A good part of my youth was spent collecting baseball cards and I spent many hours looking at the numbers on the back of each card. Such numbers are – by Sabermetric standards – quite simple. Hits, runs, RBIs, and of course batting average are the primary stats you tended to see back in the 1970s. At that time there was no mention of OPS or any other “advanced” metric.
And of course we didn’t need such stuff. Baseball fans knew who the best players were. Although we looked at the numbers, all we had to do was watch the players and we could tell who was “good” and who was “bad.”
Now, thanks to Bill James and others of his ilk, we have all these new numbers. And of course people look at these numbers as if they “prove” something. But anyone who knows baseball knows that these numbers don’t prove anything.
For example, consider a number like Runs Created. Runs Created^{ }supposedly considers everything a player does offensively and tells us how many runs a player “creates.” And since creating runs is the purpose of offense in baseball, Runs Created should tell us who is “better” or “worse.”
But all you have to do is look at the numbers and you can see that these Sabermetric numbers don’t tell us anything. Consider the rankings posted by ESPN of each hitter in terms of Runs Created per 27 outs. Fourth on the list is Carlos Pena. As a Tigers fan I am quite familiar with Mr. Pena. Pena played more than three seasons in Detroit and never saw his batting average go above 0.250. He was so talented he couldn’t even make the Tigers roster in 2006 and consequently spent most of that season in the minors.
Meanwhile, Albert Pujols spent 2005 “proving” that he was the Most Valuable Player in the National League. In 2006 Pujols finished second in voting for the MVP award. And then this past season Pujols hit 0.327 while Pena only hit 0.282. For those non-math majors out there, that’s a 45 point difference.
But the Runs Created stat ranks Pujols as only the 13^{th} best player in baseball. Yes, Pujols – the 2005 MVP – is ranked nine spots below a player who spent 2006 in the minors with a batting average in 2007 that was 45 points lower.
When you see stuff like that you have to say, “these Sabermetric stat-heads need to get their head out of their computers and go watch a game. Pena better than Pujols? Yea, I think the Devil Rays would make that trade in a second.”
A Note for the Non-Satirical
Of course, no Sabermetrician would look at Runs Created in 2007 and declare that Pena is “better” than Pujols for all time. One would look at these numbers, though, and say that Pena was pretty good this past season.
Well, we would say that if we looked past batting average. In terms of this archaic 19^{th} century stat, Pena was only the 83^{rd} best hitter in baseball last year. There were only 162 hitters who qualified for the rankings last year, so batting average lists Pena in the bottom half of all hitters. The more advanced stats, though, place him in the top five. Given the flaws in batting average, we tend to believe the more advanced stats.
But even though we believe the advanced stats, we don’t look at results for one year and declare that this trumps the entire history we have on two players. Again, numbers help us think. Numbers do not do our thinking for us.
– 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.