Statistical Analysis to help with trade ideas
As a Business Accounting major at SOU I get to play with numbers and ways of manipulating them all day. This inevitably leads to harebrained schemes to apply things I learn in class to basketball and the Trail Blazers in particular. With that preamble out of the way here is a little homebrewed statistical analysis for you.
First off my goal here is to evaluate a player's value in terms of his salary. You always see remarks about who is underpaid or overpaid for their production. I decided to take a relatively fair statistic John Hollinger's PER and compare it to player's salaries by position. UPDATE: League average PER is 15.00 averages here are caused by having all players included regardless of skill or playing time. Because a GM needs to fill a roster not just have starters.
|
Position |
AvgOfPER |
AvgOfSalary |
Cost per unit of PER |
|
C |
14.94 |
$4,521,830.02 |
$302,583.57 |
|
PF |
12.82 |
$5,212,908.30 |
$406,781.76 |
|
PG |
12.95 |
$4,551,158.26 |
$351,494.41 |
|
SF |
12.72 |
$4,508,426.77 |
$354,326.76 |
|
SG |
11.74 |
$4,619,267.88 |
$393,496.48 |
Disclaimer I didn't reorganize player positions so Tim Duncan is a Power Forward even if many think him more a center and so on with other players whose position is questionable.
Interestingly enough we already see that Power Forwards get paid the highest on average but actually Centers have higher average PERS. What do these numbers mean? With some baselines set for performance and price we can use some analysis to see where players compare to these "budgeted" amounts. Here I am going to use a Managerial Accounting tool based around Flexible budgeting. So the Average of PER and Salary for a position are going to be the "budgeted" amounts we will compare to "Actual" amounts aka real salaries and PERS.
|
Player |
Actual Production |
League Average |
|||
|
Actual PER X |
Actual PER X |
League Average PER X |
|||
|
Contract Rate |
League Budget Rate |
League Budget Rate |
|||
|
Actual Contract |
What Player "should" earn |
League Average |
We will have two variances in our final product:
- Difference between Actual Contract and What a Player should earn AKA Spending Variance
- difference between What a Player should earn and League Average AKA Efficiency Variance
So to actually get to some analysis here is Brandon Roy's breakdown
|
Brandon Roy |
Actual Production |
League Average |
|||
|
PER |
24.04 |
24.04 |
11.73903226 |
||
|
Cost per PER |
$128,296.17 |
$393,496.48 |
$393,496.48 |
||
|
$3,084,239.93 |
$9,459,655.40 |
$4,619,267.88 |
|||
|
$6,375,415.47 |
$4,840,387.52 |
||||
|
|
Spending Variance |
Efficiency variance |
|||
What this data tells us is that for his efficiency variance Brandon Roy should be paid 4.8 million more than the league average. The Spending Variance is where we see that Brandon does his PER of 24.04 for far less than budgeted, it should cost 6.4 million more to be exact. This shows us exactly what we already know that Brandon Roy is a good player who has a very low cost or good deal contract.
On the other end of the spectrum is Jermaine O'Neal who is very close to the league average in PER for Centers but has a ridiculously big contract in terms of production.
|
Jermaine O'Neal |
Actual Production |
League Average C |
|||
|
PER |
15.93 |
15.93 |
14.94406977 |
||
|
Cost per PER |
$1,341,619.59 |
$302,583.57 |
$302,583.57 |
||
|
$21,372,000.00 |
$4,820,156.32 |
$4,521,830.02 |
|||
|
($16,551,843.68) |
$298,326.29 |
||||
|
|
Spending Variance |
Efficiency variance |
|||
So we see that the Spending Variance on O'Neal's contract is very unfavorable at -16.5 million. I'm not even going to bother looking at guys like Stephon Marbury who haven't played a minute this season.
What use is this analysis? For a GM like Kevin Pritchard it can allow them to compare a player to league "budget" and see if they are under/over producing and whether they are under/over paid. For us we can look at Spending Variance to see whether a player is performing where we want them for trade purposes. UPDATE: The best value here is as an evaluation of where a player's value is compared to League averages. GM's might use a tool like this to come up with a starting point for a new contract negotiation.
I can do any players that you guys want but here are a few fun ones in terms of trade debate about Small Forwards.
|
Richard Jefferson |
Actual Production |
League Average SF |
|||
|
PER |
14.28 |
14.28 |
12.72 |
||
|
Cost per PER |
$924,369.75 |
$354,326.76 |
$354,326.76 |
||
|
$13,200,000.00 |
$5,059,786.12 |
$4,508,426.77 |
|||
|
($8,140,213.88) |
$551,359.35 |
||||
|
|
Spending Variance |
Efficiency variance |
|||
|
Luol Deng |
Actual Production |
League Average SF |
|||
|
PER |
15.15 |
15.15 |
12.72 |
||
|
Cost per PER |
$619,471.95 |
$354,326.76 |
$354,326.76 |
||
|
$9,385,000.00 |
$5,368,050.40 |
$4,508,426.77 |
|||
|
($4,016,949.60) |
$859,623.63 |
||||
|
|
Spending Variance |
Efficiency variance |
|||
|
John Salmons |
Actual Production |
League Average SF |
|||
|
PER |
16.25 |
16.25 |
12.72 |
||
|
Cost per PER |
$314,092.31 |
$354,326.76 |
$354,326.76 |
||
|
$5,104,000.00 |
$5,757,809.84 |
$4,508,426.77 |
|||
|
$653,809.84 |
$1,249,383.06 |
||||
|
|
Spending Variance |
Efficiency variance |
|||
|
Gerald Wallace |
Actual Production |
League Average SF |
|||
|
PER |
18.32 |
18.32 |
12.72 |
||
|
Cost per PER |
$518,558.95 |
$354,326.76 |
$354,326.76 |
||
|
$9,500,000.00 |
$6,491,266.23 |
$4,508,426.77 |
|||
|
($3,008,733.77) |
$1,982,839.45 |
||||
|
|
Spending Variance |
Efficiency variance |
|||
|
Shane Battier |
Actual Production |
League Average SF |
|||
|
PER |
9.35 |
9.35 |
12.72 |
||
|
Cost per PER |
$93,475.94 |
$354,326.76 |
$354,326.76 |
||
|
$874,000.00 |
$3,312,955.20 |
$4,508,426.77 |
|||
|
$2,438,955.20 |
($1,195,471.57) |
||||
|
|
Spending Variance |
Efficiency variance |
|||
I will try to get to any requests for further player analysis within 24 hours
UPDATE added Travis Outlaw and Vince Carter
|
Travis Outlaw |
Actual Production |
League Average SF |
|||
|
PER |
14.67 |
14.67 |
12.72 |
||
|
Cost per PER |
$272,665.30 |
$354,326.76 |
$354,326.76 |
||
|
$4,000,000.00 |
$5,197,973.56 |
$4,508,426.77 |
|||
|
$1,197,973.56 |
$689,546.78 |
||||
|
|
Spending Variance |
Efficiency variance |
|||
|
Vince Carter |
Actual Production |
League Average SF |
|||
|
PER |
20.51 |
20.51 |
12.72 |
||
|
Cost per PER |
$717,899.80 |
$354,326.76 |
$354,326.76 |
||
|
$14,724,125.00 |
$7,267,241.83 |
$4,508,426.77 |
|||
|
($7,456,883.17) |
$2,758,815.06 |
||||
|
|
Spending Variance |
Efficiency variance |
|||
Now the NBA being a Star based league we see that in general highly productive players are paid more for their production then the League 'budget'. However in a time of financial crunch like right now these numbers can help you see who might cost you more then he actually gives in terms of dollars for performance.
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Comments
This doesn't help all that much with trades (due to NBA rules)
but this is awesome info nonetheless. Teams that must follow the NBA salary cap to the dollar would be wise to take this information into account.
As the PER values actual stats, it makes sense that centers (the position that gets the most rebounds) followed by power forwards lead the way. It also makes sense, since assists are also factored in, that point guards are next on the list.
It should also be noted, that while you listed the average players PER, the average PER in general is 15 (I believe that’s what Hollinger puts it to). The reason for the discrepancy is that there are a smaller amount of players logging major minutes. The ones that post higher PER’s get the majority of minutes, and push the average and median PER down.
When considering trades it’s important not to go for PER versus the average or median, but versus the average starter (15th at a position). Its also important to realize that PER is pretty sketchy in regards to how it evaluates defense, which besides defensive rebounds and to a small degree blocks and steals it really doesn’t do.
Of course this dosn’t take Salary Cap rules into perspective thats what tools like ESPN’s Trade Machine are for. I wanted to look at the situation purely from a bang for you buck perspective of a GM. Also I agree that PER somewhat devalues “defensive” players but I wanted an overall value marker that would be relatively fair, If anyone has a better metric that I can actually get some raw data for the league I would use that instead.
Yeah PER is averaged to 15 for league. I considered using Qualified PER which limits the numbers to only players who average enough minutes per game but that would change the salaries from total average cost to only players who log minutes and every team needs some “practice players” and filler guys in case of injury.
The Analysis is actually most valuable when you look at it from a GM’s perspective of valuing players on a roster and how much money they “deserve” on an upcoming resigning.
Good stuff
The formatting is a little confusing, but the analysis is a beacon of rational analysis in the trade-deadline sea of exclamation points and simplistic commentary. Nicely done.
Interestingly, Trout would grade out just below Salmons on the efficiency list. His PER is higher than Jefferson and he makes, what, 40% as much money?
The other interesting guy to look at would be the much hated VC. I hate Vince as much as the next guy, but there’s no denying he’s a step above these other guys in terms of production. His PER is over 20 and that’s near a career low. Even though he’s expensive, he would probably be the most bang for the buck out of the guys the Blazers are looking at.
I like Wallace (or, certainly, Butler) better because they’re younger and provide an upgrade on perimeter D, which is where the Blazers REALLY need help. But this perspective sheds a little light on why KP’s interest in Carter may be legit.
Q: Is Greg favoring his knee?
Frye: He favors dunking on your head, that's what he favors.
Unfortunately my pretty excel built charting goes out the window when you try to actually post things, but Yes the idea is just generally confusing its from a 400 level (AKA Senior) Cost Accounting class this exercise was as much about me locking down the concept by applying it as it was about useful analysis. I am going to add some more info to the original post including Travis and Vince’s data

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