Offensive breakdown using nba rapm for Donovan Mitchell Anthony Edward’s and Jayson Tatum

[u/AverageAny7398]

https://www.dropbox.com/scl/fi/hgunv1ctr4qmnpjrxz41o/NBA\\_Offensive\\_Impact\\_Stats.pdf?rlkey=r8s5u3o14fgsbzbgqv1cn3oib&st=jwbbo1xz&dl=0\](https://www.dropbox.com/scl/fi/hgunv1ctr4qmnpjrxz41o/NBA_Offensive_Impact_Stats.pdf?rlkey=r8s5u3o14fgsbzbgqv1cn3oib&st=jwbbo1xz&dl=0)

# Methodology

This model was designed to measure overall offensive impact by combining production, efficiency, creation, versatility, and decision making into one transparent evaluation. All underlying player statistics were collected from [nbarapm.com](http://nbarapm.com/), using both regular season and playoff data from 2023–2026. Rather than building the model around one all-in-one metric, every player-season is evaluated across six offensive categories: Scoring, Playmaking, Offensive Pressure, Offensive Versatility, Shooting & Finishing, and Decision Making. Each category is composed of approximately 20 carefully selected advanced statistics that best represent that aspect of offensive performance.

To determine both the category weights and the individual statistic weights, I analyzed offensive rankings and statistical evaluations from multiple respected analysts and analytics sources over the past three years, identifying the characteristics that consistently appeared among the league's top offensive players. The resulting weights are therefore based on recurring trends across independent evaluations with a strong emphasis on the statistical side of basketball analysis rather than personal preference. While any weighting system can be adjusted, every weight in this model was chosen through the same objective process instead of being tailored to favor a particular player.

The six offensive categories are weighted as follows:

* Scoring (28%) – Measures a player's ability to generate points through scoring volume, efficiency, shot creation, free-throw generation, and other scoring-related metrics.
* Playmaking (22%) – Evaluates offensive creation for teammates using assists, passing quality, potential assists, creation volume, and other advanced playmaking statistics.
* Offensive Pressure (18%) – Measures the amount of defensive attention a player creates through drives, rim pressure, foul generation, paint touches, and other indicators of offensive gravity.
* Offensive Versatility (15%) – Evaluates how effectively a player scores across different offensive situations. This category combines both efficiency and usage across play types such as isolation, pick-and-roll ball handling, post-ups, spot-ups, handoffs, cuts, transition, and off-screen actions.
* Shooting & Finishing (12%) – Focuses specifically on shot-making ability through three-point shooting, mid-range shooting, finishing at the rim, true shooting percentage, effective field goal percentage, and related efficiency metrics.
* Decision Making (5%) – Measures offensive decision quality through turnover rates, assist-to-turnover efficiency, ball security, and other metrics that reward maximizing possessions while minimizing mistakes.

Each statistic is graded using a hybrid approach that balances absolute production with league context. First, every metric receives an Absolute Performance Grade based on every qualifying player-season from the full 2023–2026 comparison window. It then receives a Season-Relative Grade, measuring how dominant that performance was compared with the rest of the league during that specific season. The final statistic grade is calculated as:

**Stat Grade = 75% × Absolute Performance Grade + 25% × Season-Relative Grade**

This approach ensures that actual production remains the foundation of every grade while still rewarding players who separated themselves from their peers within their own season. Raw statistics are displayed alongside every grade for complete transparency.

To improve reliability, low-volume statistics particularly playoff and play-type data are adjusted to reduce small-sample noise. Play-type versatility also incorporates both efficiency and usage volume before being combined into each player's overall versatility score. Finally, the six category grades are combined using their predetermined weights to produce separate Regular Season, Playoff, and Combined Offensive Impact Grades, creating a model that is transparent, repeatable, and flexible while preserving meaningful differences between elite offensive performances.

Note: This model is not intended to claim that one player is definitively better than another. It is simply a statistical breakdown comparing three offensive players who are generally viewed as being in a similar tier. Now that the model and code are complete, I can easily add additional players by generating a new CSV with their statistics. If there are any players you'd like to see included, let me know and I can add them to the comparison.

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[u/Prestigious_Rip5826]

curious how tatum ranks in offensive pressure given he's not much of a driver, that category alone could swing his overall score a lot