Understanding Touchdown Regression: Why Touchdown Totals Don't Predict Future Scoring
Why touchdowns are the most misleading stat in fantasy: touchdowns are worth a lot of fantasy points, so a player’s touchdown total heavily drives his scoring — and that is exactly why touchdowns are so misleading. Touchdowns are volatile and partly luck-driven: they depend on goal-line opportunities, game scripts, and the bounce of close plays, none of which a player fully controls and many of which do not repeat. As a result, a player’s touchdown total over a stretch is a poor predictor of his future scoring. Players who have scored at an unusually high rate tend to regress down toward their expected rate, while players scoring at an unusually low rate tend to regress up. Understanding touchdown regression lets you see past the noise — to sell players whose value is inflated by unsustainable touchdowns, and buy players whose production is depressed by bad touchdown luck.
Understanding Touchdown Regression
Why touchdowns regress:
The volatility of scoring: (1) touchdowns are partly luck — they hinge on goal-line chances, game scripts, and close-play bounces that a player does not fully control and that do not reliably repeat, so touchdown rate fluctuates more than the underlying skill; (2) expected touchdowns set the baseline — based on a player’s opportunities (yardage, targets, carries, especially near the goal line), there is an expected touchdown rate, and actual touchdowns tend to drift back toward it; (3) high and low scorers both regress — a player scoring well above his expected rate is likely to score less going forward, while one below it is likely to score more, which is regression toward the mean; (4) the opportunity is what predicts, since a player’s volume and role (the opportunity and goal-line work) forecast future touchdowns far better than his recent touchdown total.
How to spot regression candidates:
Reading the signals: (1) negative regression candidate — a player scoring far more touchdowns than his opportunities support (few goal-line touches but lots of long scores, or an unsustainable touchdown rate) is likely to score less going forward, inflating his current value; (2) positive regression candidate — a player with strong opportunities but few touchdowns (heavy goal-line role, lots of yardage, but bad touchdown luck) is likely to score more going forward, with his value depressed now; (3) compare touchdowns to the underlying usage — the gap between a player’s actual touchdowns and what his role (especially goal-line work) should produce is the regression signal; (4) bigger samples and bigger gaps are more reliable, since a large divergence over a meaningful stretch is more likely to regress than a small one over a few games.
How to use touchdown regression:
Putting it to work: (1) sell high on negative-regression players — a player whose value is inflated by unsustainable touchdowns is a sell-high candidate before the scoring drops, so move him while the market prices the touchdowns as real; (2) buy low on positive-regression players — a player with strong usage but bad touchdown luck is a buy-low candidate, since his scoring should rebound toward his opportunity (the buy-low/sell-high application); (3) project from opportunity, not recent touchdowns — when forecasting a player’s future scoring, lean on his role and goal-line usage rather than his recent touchdown total, which is noisy; (4) treat it as one input among several, since touchdown regression sharpens your read on a player’s sustainable scoring, which you combine with the rest of his profile, the disciplined multi-metric approach of our advanced analytics toolkit.
For how touchdown regression fits a broader approach, see our advanced analytics guide and fantasy football tips hub. Start at the learn hub for the full fundamentals library.