How SSAT Rankings Work
The Standardized Statistical Assessment Tool (SSAT) creates fair, comparable rankings across all NFL positions using statistical normalization and position-specific evaluation criteria. Rankings are calculated from full regular season data (Weeks 1-18).
The Core Methodology: Z-Score Normalization
At the heart of SSAT is the z-score, a statistical measure that tells us how far a player's performance deviates from the average. This allows us to compare players fairly, even when raw statistics have vastly different scales.
x = player's raw statistic
μ = mean (average) across all players at that position
σ = standard deviation (spread of the data)
A z-score of +1 means the player is one standard deviation above average. A z-score of -1 means one standard deviation below. This normalization is applied to every statistic we track.
Position-Specific Categories
Each position is evaluated using categories tailored to their role. This ensures quarterbacks are judged on passing efficiency, running backs on rushing production, and so on.
Category-Based Scoring
Within each category, we average the z-scores of all relevant statistics to produce a single category score. Then, categories are combined using weights to create an overall score.
Weights (w) can be adjusted to emphasize different aspects of performance. By default, all categories are weighted equally.
Final Score: The 60-100 Scale
Raw z-scores are transformed to an intuitive 60-100 scale using linear interpolation. This makes scores easy to interpret at a glance.
raw = player's weighted composite z-score
min, max = lowest and highest composite scores among all players
Why SSAT Works
Z-scores normalize across different stat scales. Whether it's passing yards (thousands) or touchdowns (dozens), every stat is converted to a common scale.
Each position has its own relevant categories and weights. A quarterback's value isn't measured the same way as a linebacker's.
For statistics with extreme outliers (like touchdowns), we apply log-scaling before z-score calculation to prevent a single stat from dominating.
No black box. Every step of the methodology is documented here. You can see exactly how scores are calculated and why players rank where they do.
Example: From Raw Stats to Final Score
32 TD
8 INT
+0.8
-0.3
This simplified example shows how a QB's passing stats flow through the SSAT pipeline.