I have a dataset of basketball player salaries and an estimation of how many wins they contributed to their teams over the season. So a reasonable thing to do with those numbers would be to divide the wins with their salary to get a number showing the value of their contract.
The problem is that some players have negative production, as in over the season they provided their team with, say, -2 wins. That makes sense basketball-wise but when doing the division, obviously, you get a negative number, which doesn't seem to really describe the value of the contract. A really low number normally would mean the player is out-producing his contract, but that's clearly not the case with negative value players.
So my question is, how would you evaluate those players' contracts?
Here's an example of the data just to be clear:
+-----------------+----------+-------+
| Player | Salary | Wins |
+-----------------+----------+-------+
| Carmelo Anthony | 25534253 | 0.16 |
| Rajon Rondo | 9000000 | -0.51 |
| Pascal Siakam | 1544951 | 11.88 |
| Stephen Curry | 37457154 | 14.43 |
| Kevin Knox | 3739920 | -5.67 |
| Isaiah Thomas | 2029463 | 0.00 |
| James Harden | 30431854 | 18.57 |
| LeBron James | 35654150 | 11.15 |
+-----------------+----------+-------+