Although the trade talk surrounding Carmelo Anthony has begun to die down, it will likely crop up again before the season is over. Coverage and opinions about the value of Carmelo have varied wildly. Both Tom Haberstroh of ESPN and David Berri of the Wages of Wins spent some time this summer arguing that Carmelo doesn’t have the statistical credentials of an elite player. I am paraphrasing heavily, but the gist of their arguments was that Carmelo provides little besides scoring. In addition he has a reputation as a terrific scorer because of the volume of his scoring as opposed to his offensive efficiency. David Berri hit on the idea of Carmelo’s relative value again last week:
Yes, he can score. But his scoring is primarily due to his willingness to take many shots. He is not a particularly efficient scorer. And he doesn’t help out much with any other facet of the game.
I won’t argue with either writer about the deficiencies in Carmelo’s all around game, but I wanted to use Expected Scoring to take a look at his scoring efficiency a little more closely. Expected Scoring is a way of looking at scoring efficiency that I have been playing with the past few weeks. Here is an explanation of Expected Scoring borrowed from one of my earlier posts:
An excellent series of posts from Albert Lyu at Think Blue Crew on the value of blocked shots, gave me another idea and another piece of data to factor in. For the second post in this series Lyu calculated the Expected Points Per Shot by location. This information gave me another way to examine a player’s shot selection. Another way to think of Expected Points Per Shot, is the average number of points scored on a shot attempt. For example, over the last 4 NBA seasons, factoring in makes and misses, a field goal attempt at the rim was worth an average of 1.208 points.
Using numbers from Hoopdata’s Shot Location Database, and the Expected Points Per Shot from Lyu’s post I was able to calculate what I am calling Expected Points per 40 Minutes (XPts/40). I began by calculating each players XPts/40 from each area of the floor. To do that I took each player’s per 40 minute field goal attempts from each area of the floor and multiplied it by the expected Points Per Shot for that location. Adding these categories together results in XPts/40. Another way to think about this is, given a player’s per 40 minute shot selection, how many points would he score, shooting the average percentage from each location. The numbers I borrowed from Lyu are below:
- At Rim – 1.208
- <10ft. – 0.856
- 10-15ft. – 0.783
- 16-23ft. – 0.801
- 3PT – 1.081
- I needed to include Free Throws, so I used 0.759 the league average for last season.
The crucial piece of Expected Scoring is then comparing it to the actual number of points a player scored from each location. This gives you a representation of how a player shot the ball compared to the league average but expresses it in points scored. I am calling this stat the Point Differental.
On to Carmelo. Below is a table showing his Expected Points, Actual Points and Point Differential for each area of the floor, covering the last four seasons (all numbers are per40 minutes):
As you can see, outside of an terrific 2008 season, where he scored at a rate 1.22 points better than expected, Carmelo has not stood out as an overly efficient scorer. Breaking the numbers down by location you can see that there is no particular area of the floor where he stands out. He has consistently been a better than expected free throw shooter but not by a significant margin. In addition, he has not had a single floor location over the past 4 seasons where he has scored over 1.00 points more than expected. Essentially, his numbers have fluctuated season to season, but have hovered just below or just above what should be expected. In addition, 2 of the 4 seasons in which he had an overall positive Point Differential, 2007 and 2010, the positive difference is entirely attributable to his above expected scoring from the free throw line.
The one point I would make in Carmelo’s defense is that there are not many players who have even average scoring ability from every area of the floor. My Expected Scoring breakdown for individual player’s from a few weeks ago shows these same numbers for a few other players. Just for comparison Carmelo scores at the rim in about the same quantity and with a similar Point Differential to Tyreke Evans. But Carmelo scores in much greater quantity AND with a higher Point Differential than Evans on long jumpers and 3PTs. While this scoring versatility doesn’t equate with overall efficiency there is something to be said for having one player with the capability to be an average shooter from every area of the floor.
The issue is that this versatility has provided a reputation and monetary compensation way out of whack with it’s ability to win basketball games. For half the price, in a more structured, complimentary role on a good team, Carmelo could be an incredible value. As a max player, asked to carry team by scoring in volume, it’s difficult to imagine Carmelo ever living up to expectations.