Decide whether to go for it on 4th down: compare go-for-it expected points with a field goal or punt, or find the break-even conversion rate.
Fourth Down Expected-Points Formula
A fourth-down choice can be written as a small outcome tree. Going for it has one value when the offense converts and another when it is stopped. The conversion probability weights those two branches:
The expected-point values must use the same offense-relative scale. A negative value is allowed when the opponent’s resulting possession is expected to be worth more than the current team’s future scoring value.
Field-Goal Alternative
When field goal is selected, the calculator applies the same two-branch structure:
The made-field-goal value does not have to equal exactly three net points. A complete offense-relative value can subtract the opponent’s expected value after the ensuing kickoff. The missed value can reflect the opponent’s field position after the miss.
Punt Alternative
Punt mode accepts one net expected-point value after averaging the likely punt outcomes. A well-formed input can account for net distance, touchbacks, returns, penalties, and the opponent’s ensuing possession. The calculator does not infer that value from punt distance alone.
Break-Even Conversion Probability
Set the go-for-it branch equal to the selected alternative and solve for the conversion probability:
A threshold from 0% through 100% is the entered scenarioโs break-even conversion rate. An algebraic result outside that interval is reported as no threshold in 0โ100%: below 0% the go branch is higher throughout the interval; above 100% the alternative is higher throughout. Conversion EP must exceed failure EP.
Where the Inputs Come From
Public NFL models such as nflfastR and nfl4th estimate expected points, field-goal probability, fourth-down conversion probability, and win probability from play-by-play data. Their outputs depend on field position, yards to go, time, score, team strength, model version, and other features.
This calculator does not copy a partial lookup table or silently approximate a complete model. Instead, it lets an analyst enter internally consistent branch estimates from the model or scouting source they trust, then audits the arithmetic and solves the exact break-even threshold.
Example
Suppose conversion is estimated at 55% and net expected points are 3.0 after success and -1.0 after failure. Go-for-it expected points are 0.55 times 3.0 plus 0.45 times -1.0, or 1.20.
If a field goal is estimated at 80%, with net values of 2.2 when made and -1.5 when missed, field-goal expected points are 1.46. Under those illustrative inputs, the field-goal branch is higher by 0.26 expected points. The break-even conversion rate is 61.5%.
Expected Points vs. Win Probability
Expected points summarize average scoring value, but game decisions are often evaluated with win probability. Late in a game, a lower-EP option can sometimes fit the exact score and clock better, while a higher-EP option can sometimes create the needed upside. A complete decision model also accounts for remaining possessions, timeouts, overtime, opponent strength, weather, and uncertainty.
The output therefore describes which entered branch has the higher modeled expected value. It does not issue a play call or claim that one choice is universally correct.
Assumptions and Limitations
- All branch values must come from the same expected-points definition and the current offense’s perspective.
- The success and field-goal probabilities are treated as known estimates.
- One average value represents each outcome branch; the full distribution of gains, returns, penalties, and subsequent plays is compressed.
- The calculation does not model score, clock, timeouts, overtime, opponent, personnel, weather, or risk preference by itself.
- Expected-point comparisons can disagree with a complete win-probability model.
- Inputs start blank. The example numbers above are illustrative worksheet values, not league benchmarks or recommendations.
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Sources
Romer D. Do Firms Maximize? Evidence from Professional Football. Journal of Political Economy, 2006.
nflverse. nfl4th package documentation and nflfastR expected-points model documentation. Accessed 2026.
National Football League Next Gen Stats. Introducing the Next Gen Stats Decision Guide: A New Analytics Tool for Fourth Down and Two-Point Conversions. 2021.
