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Touchdown Regression: Why Last Year's TD Leaders Disappoint

March 17, 2026Analytics7 min read
Hand tossing a large black die into the air
Photo by Erik Mclean on Unsplash

The Most Predictable Disappointment in Fantasy

Every August, drafters pay premium picks for last season's touchdown leaders — and every season, most of those players score less. This isn't cynicism; it's arithmetic. Fantasy Points' expected-touchdown study tracked players who dramatically outscored their touchdown expectation and found that in 137 of 151 cases — 90.7% — the player scored fewer touchdowns the following season. Of the decade's top-25 seasons by positive touchdown differential, exactly one player improved on his total the next year, and on average the group's touchdowns fell by 52%. A stat that halves on schedule is not a skill you're buying — it's a coin flip you're paying retail for.

What happened to 151 big touchdown overperformers the next season

Scored fewer touchdowns
137 (90.7%)
Matched or beat their total
14 (9.3%)

Source: Fantasy Points xTD study

Fantasy Points tracked 151 major touchdown overperformers: 137 scored fewer the next season. Betting on repeat TD luck is a 9% proposition.

Why Touchdowns Lie

Touchdowns are enormous in fantasy scoring and tiny in sample size. A wide receiver sees maybe 120 targets a season, of which perhaps a dozen are genuine scoring opportunities — so three bounces (a tipped ball, a goal-line vulture, a blown coverage) can swing his fantasy finish by twenty ranks. As FanDuel Research's regression primer explains, a high or low touchdown total simply isn't predictive of the next one; players drift back toward the average implied by their opportunity. The yardage stats around touchdowns — targets, carries, snap and target share — are stable, decision-driven volume. The touchdowns sprinkled on top are weather.

Expected Touchdowns: Measuring the Luck

The tool that separates skill from weather is expected touchdowns (xTD). The method, used in FantasyPros' touchdown regression reports, weighs every carry and target by where it happened — a target at the 2-yard line is worth a large fraction of a touchdown, a catch at midfield almost none — and sums a league-average conversion rate over each player's actual opportunities. The result: how many touchdowns an average player would have scored with this exact usage. A player who scored 13 on 8.1 expected is a regression candidate no matter how good he looked doing it; a player who scored 4 on 8 expected is the discount aisle. The beauty of xTD is that it doesn't ask you to doubt talent — it asks whether the opportunity supports the output.

Drafting Against the Crowd

Regression cuts both ways, and both edges are tradable. The overperformers get drafted at their ceiling: analysts flag them every summer — ESPN's 2026 projections piece named a dozen players, headlined by Jonathan Taylor, projected to score fewer touchdowns this season — yet ADP barely budges, because the market anchors on last year's point totals. The underperformers are the actual buys: players whose yardage and usage held elite while the touchdowns went missing. Positional analyses like 4for4's touchdown trend series walk through both lists each preseason. The discipline is mechanical: fade the player whose ranking requires last year's touchdown rate to repeat, and buy the one whose ranking assumes his bad luck was skill.

  • Check the gap: actual touchdowns minus expected touchdowns is the luck component — big positive gaps regress ~90% of the time
  • Re-rank TD outliers on yardage and usage alone, then let touchdowns be the tiebreaker, not the thesis
  • Buy the unlucky: elite volume with a low TD total is the cheapest way to acquire this year's leap
  • Remember it's regression, not collapse: overperformers usually stay good — they just stop being historic, and their price doesn't know that

The In-Season Version of the Same Edge

Regression thinking isn't just a draft-day tool — it's a weekly waiver filter. When a running back scores three times on eleven touches, your league's FAAB market prices the touchdowns; the xTD lens prices the eleven touches, which is the number that will still be there next Sunday. The same logic protects you from panic-dropping: a starter mired in a "touchdown drought" while his snap share and red-zone usage hold steady isn't broken, he's owed. Volume tells you who to hold and who to chase; touchdowns mostly tell you who just got expensive. In both directions, the manager who prices the opportunity instead of the outcome is trading against a market that keeps making the same mistake.

💡 Tip:One question exposes most regression traps: "if this player had scored a league-average number of touchdowns on his opportunities, would I still draft him here?" If the answer is no, the touchdowns are doing the ranking — and touchdowns don't repeat.

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