The point of a CourtsideIQ profile is not to find one number that wins every basketball argument. It is to separate questions that a single ranking can hide.
Begin with the player's role, then read the five lenses together. The result should be a more precise basketball question—not a claim that the model has seen everything.
01 / REI: how well does he perform this job?
Role Efficiency Index evaluates a player against the inputs and targets selected for his assigned role. A Primary Creator is judged through a different mix of responsibilities than a Floor Spacer or Defensive Anchor. That distinction is the starting point, not a detail to remove after sorting the table.
Compare players within the same role first. A specialist with a higher REI than a lead creator has not necessarily shown that he can run an offense. He may be doing a narrower job extremely well. Open the role inputs and inspect which components account for the result before using the ranking to argue for a larger role.
02 / VSE: what happens when efficiency meets scoring responsibility?
Volume Scoring Efficiency considers scoring efficiency alongside scoring load. It helps distinguish efficient scoring on a smaller workload from efficient scoring while carrying more offensive responsibility. The model's scoring lens is not a complete offensive grade: passing, turnovers, and role demands still deserve separate attention.
A movement in VSE should prompt you to inspect both efficiency and workload. A player can improve an efficiency percentage while taking on less responsibility. The percentage alone does not tell you whether the offensive task became easier.
03 / PIV: what value is created with the possessions used?
Possession Impact Value brings scoring, assists, and turnovers into a possession-oriented calculation. On the public display it is transformed onto the site's impact scale. It is not a literal number of points added to the scoreboard or a percentage chance of winning.
Read a strong PIV beside the underlying production and ball-security inputs. A player whose impact comes through passing may be useful in a way that points per game alone understates. That does not settle whether he can reproduce it against a different defense, with different teammates, or in a different role.
04 / PFE: how effectively are plays completed?
Player Finishing Efficiency uses scoring, assists, attempts, and turnovers to evaluate possession endings. Despite the word “finishing,” it is not simply rim field-goal percentage, a shot-location map, or an eye-test grade of layup technique.
This distinction matters when evaluating an elite creator. Creating a difficult opportunity and completing an opportunity efficiently are related but different tasks. A lower PFE does not erase a player's ability to generate offense; it tells you to investigate the cost and outcome of those possessions.
05 / Smart CVR: what does the production look like at this salary?
Smart Contract Value Rating puts production into salary context. The public reference point is 100 for fair model value. Above that level suggests more value for the modeled salary basis; below it suggests less. A 125 is not “25 percent underpaid,” and it is not a proposed dollar salary.
Salary accuracy is essential. A stale contract, a missing annual amount, or a different season can change the story. See the worked contract-value example for why a strong score on a low salary is different from a recommendation for the next deal.
When the lenses disagree, investigate
Suppose a player rates well in his role and provides good salary value but trails comparable creators in scoring efficiency. Those results need not contradict one another. His passing or other role inputs may support his REI, while his current salary supports Smart CVR. The useful next step is to identify the source of the disagreement, not average the scores into a new unofficial rating.
Likewise, a high scorer with weaker possession or finishing numbers might be taking difficult shots, turning the ball over, or operating under a workload the surrounding lineup cannot absorb. The profile helps locate a trade-off; it does not identify its cause by itself.
A repeatable reading sequence
- Confirm the context. Check player identity, team, season, role, minutes, and salary basis.
- Check completeness. Look for missing inputs and small samples before interpreting a decimal as precision.
- Choose a peer group. Start with the same role and inspect meaningful differences in responsibility.
- Follow the disagreement. Use the individual inputs to explain why two lenses tell different stories.
- Keep the claim narrow. Separate current performance from a prediction about a new team, role, or contract.
Use the role rankings to try that sequence and the methodology to inspect the formulas and tier definitions. These are model-informed comparisons, not substitutes for film, lineup context, or verified contract information.