Independent Math Worksheet Undated Bo Nix / KC fixture

Rushing Yard Score & Density Explorer

Four assumed inputs; fixed 18-yard example threshold
Exported!
Illustrative Presets Quick scenarios
Assumed Inputs
Assumed Scrambles 4
Chosen count; no observed matchup sample
Yards per Scramble 5.2
Example yield, not sourced historical efficiency
Assumed Designed Runs 1.0
Each expected run adds a fixed 3.7 example yards
Illustrative Pressure Input 7.4%
Each point above 7.4 adds 0.25 example yards
What this worksheet knows

The Bo Nix / Kansas City names provide an undated example. Run counts, yields, pressure input and coefficients are authored assumptions. No verified analyst quote, paid partnership, current line or held-out forecast validation is supplied.

Use the controls to study sensitivity. Export records the assumptions and both model definitions.

Over 18 Yards Favored
Bands classify this authored score. No odds or calibration establish market value.
Favorable Matchup
Example Mean Yardage
24.5
Mean minus 18-yard threshold
Logistic Score
71.4%
Authored sigmoid; not a game-win probability
Fixed Example Threshold
18.0
Chosen illustration, not a verified market
Assumed Total Runs
4.8
Scrambles + Designed
Separate Gaussian Density Fixed spread: 9.5 yards
Density at 18+ yards
Density below 18
18-yard split
A dated fact is different from a forecast

Denver’s official player biography records 42 rushing yards on nine attempts at Kansas City on December 25, 2025. That single result does not validate these coefficients or the former unsourced 92-yard career claim. Read the Broncos biography.

One mean, two different model outputs

Why is the score not the green area of the chart?

The percentage uses an authored logistic transformation of mean minus 18. The bars use a separate normal density with a 9.5-yard spread. These are different mathematical choices, and neither has been fitted or validated against a documented game sample.

No event date, efficiency sample, pressure measurement, verified analyst transcript, commercial relationship, offered odds or settlement rule supports the original matchup verdict. The dated Broncos result provides historical context only.

Try a worked example

The baseline mean is 4 × 5.2 + 1 × 3.7 + (7.4 − 7.4) × 0.25 = 24.5 example yards. The fixture stores a 71.4% score, matching the rounded sigmoid 100 / (1 + exp(−0.1407 × 6.5)). A normal curve with mean 24.5 and spread 9.5 instead has about 75.3% of its area above 18. The bars do not reproduce the displayed score.

Read the score and density separately

R’s statistical documentation defines the logistic cumulative function. This page applies its sigmoid shape to a chosen yardage gap with slope 0.1407; the slope is an authored parameter, not a learned football coefficient. Nonbaseline scores are rounded to one decimal and limited to 2–99%. R stats: Logistic distribution

NIST distinguishes a normal density from cumulative area. Here each bar is the density at a two-yard-spaced sample, multiplied by 100. Bar height is not the probability of an exact integer outcome or a two-yard bin. There are no random trials or fitted kernel estimates. NIST: Normal distribution

The chart shows only 0–50 yards. Joint maximum inputs yield 124.1 example yards, outside that window; bars can become nearly zero while the score reaches its 99% cap. The normal distribution itself extends beyond the visible window, including negative values. NIST: Normal distribution

Test assumptions before drawing a football conclusion

Heavy Blitz is only a stored scenario: 6 × 6 + 0.5 × 3.7 + (12 − 7.4) × 0.25 = 39.0 example yards. The pressure term always adds yardage when its input rises; no source establishes that causal direction. Fractional designed-run counts represent hypothetical expected counts.

The Broncos biography records 42 yards on nine rushing attempts at Kansas City on December 25, 2025. It supports that dated observation, not the original cumulative claim, a pressure-to-scramble rule, or this worksheet’s percentage. Denver Broncos: Bo Nix biography

Manual changes clear the preset highlight. Reset restores all four baseline inputs. JSON includes the selected values, hidden coefficients, baseline override, score clamp and separate density definition. If the chart library is unavailable, the canvas supplies a text summary rather than a curve.

Sources and further reading
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