The volume held. The finishing did not. Whether 2025 was the player breaking or the situation breaking decides what he is worth at 185.5 overall.
Gunnar Helm scored 91.7 fantasy points in 2025. The volume he earned was worth 99.9 — he finished 8.2 points BELOW what his own usage justified. That is a different problem from losing the job, and it is the single most important thing to understand before drafting him at 185.5 overall.
Rather than reading a season average, it is worth finding the point the season actually turned. Our shift detector flags in-season changes large enough to clear a statistical threshold, then asks what moved around them.
The largest single move was Week 5: snap share went up from 38 to 57.4, a 51.1% change, at 6.49 standard deviations. The cause was structural — the offence around him got sharply better. He also missed Weeks 10, 18.
He finished 5.73 points per game on 55 targets, his first full season. Every part of that is real and none of it is in dispute.
What is worth separating is how much of it he earned. Expected points strip out the finishing and ask a narrower question: given the targets he drew, where they came from on the field, and how far downfield they travelled, what was that usage worth? For 2025 the answer was 99.9 points — 6.2 per game. He scored 8.2 FEWER than that, a 8.2% shortfall.
The expected line underneath the season was 39.7 catches for 412 yards and 3.2 touchdowns — and he came in under it.
That distinction matters more than the raw finish. A player who loses his role posts a low score and a low expected score. Gunnar Helm posted a low score on an expected total of 99.9 — 6.2 points a game of earned opportunity. The targets were still coming. What went wrong happened after the ball was in the air.
Not one of his 16 games cleared 25 points. His best was 14.9 in Week 15. For a player who had cleared it routinely before 2025, that is the clearest single symptom of the year — not a change in what he was asked to do, a change in what came of it.
A steady floor has its own value, but this was not a floor season by choice. 13 games came in under 10 points, including Week 1 against DEN (2.6) and Week 2 against LA (2.9).
The three largest overshoots — Week 15 (+7.6), Week 8 (+4.9), Week 9 (+0.7) — are the same games. The spikes were not extra volume. They were finishing.
Not one of his 1 seasons is flagged as running hot. 1 came in below what the usage justified: 2025 (-8.2%). Across all 1 he has scored 8.2 points fewer than his usage was worth.
The reflexive read on a down year is decline. But the direction of the miss matters: finishing BELOW expectation is the more correctable of the two errors, because the hard part — earning the volume — is the part that held.
But an expected-points model has a specific blind spot, and it is worth naming: it converts usage at league-average rates. A target twenty yards downfield is worth what the average receiver does with a target twenty yards downfield. If a player is reliably better than average at winning a particular kind of target, he will beat the model every single year, and calling that luck is just mislabelling a skill.
So the question is not whether he missed the number. It is whether there is a mechanism.
Across 55 targets and four seasons, he has been a fundamentally different receiver depending on what the defence played. Against man he has caught 75% for 5.69 yards per target and 0.067 expected points added per target. Against zone: 82.1%, 6.82 yards, 0.071 EPA.
That is a gap of -0.004 EPA per target on a sample of 16 man targets against 39 zone. The catch rate goes the other way — he catches more against zone — which is exactly what you would expect from a receiver whose value is in winning contested downfield throws rather than in finding soft spots underneath.
The shell detail sharpens it. Cover 3 is the look he has faced most: 16 targets, 7.56 yards per target, -0.019 EPA. His best is Cover 2 at 0.132 on 15 targets.
The weakness is specific. Against Cover 3 he has caught 81.3% for 7.56 yards a target and -0.019 EPA across 16 looks — a gap of 0.2 expected points a target between his best coverage and his worst.
This does not prove the overshoot repeats. It does mean the pattern has a stated cause rather than being a coin that keeps landing heads.
Tennessee returns 2 of 6 continuity slots — qb1, rb1 — with Cam Ward at quarterback, Robert Saleh as head coach and Brian Daboll calling it. The offence projects to 33.51 pass attempts a game at medium confidence.
The pie is stable. His slice is the question. Our share model has him at 3.5% against the 10.7% he ran, with a range of 1% to 6.1%.
That number is built from 25 comparable players — same age band, same prior share, same team, same coordinator — not from a depth chart. The closest three went Hayden Hurst 10.5% to 14.8%, Jack Doyle 10.4% to 0%, Anthony Firkser 10% to 6.1%. Two held, one fell hard.
Across 4,488 player-seasons we swept every stat for whether it predicts NEXT year's points, and kept only the ones that replicated in all five. target share (r 0.247), WOPR (r 0.218), air-yards share (r 0.142) carry. receiving EPA per game (r -0.127) and yards per target (r -0.114) and week-to-week volatility (r -0.075) run negative — a player who was hyper-efficient on low volume tends to come back down, so a gaudy per-touch number is a warning rather than a selling point.
So the figures worth weighing for him: a 10.7% target share, 8% of the air yards, a WOPR of 0.22, on the field for 52.6% of snaps. He averaged 2.55 yards of separation against 4.74 yards of cushion, and lost 2.2 yards after the catch above expectation. He finished 31 at the position — TE3.
Vegas sets an implied total for every team every week, and some offences beat theirs systematically. Over 103 games, TEN has come in -0.21 points against its own implied total, clearing it in 41% of weeks.
That is close to neutral — the offence performs about where the market expects, so there is no environment bonus or penalty to apply to him either way.
One related finding worth carrying: across 1,280 cases we measured what happens after a team's implied total slides, and the correlation is -0.37 — negative, meaning the market over-corrects. A falling team total is more often a buying window than a warning.
Our board has him at 108.4 points, 7.1 per game across 15.2 expected games — 49.5 catches, 445 yards, 2.4 touchdowns. That is TE5, 162 overall, and -46 points of value over a replacement starter.
It is a step down from 2025, and the reason is volume rather than efficiency. The projection assumes he keeps doing what he does on slightly fewer looks.
The books do not agree on him. . That 30.6-pick gap between ESPN and Sleeper is the practical thing to act on: in a Sleeper-priced room he is available later than his consensus number suggests.
He goes at 185.5 overall on consensus, and the books are far apart — 30.6 picks between cheapest and priciest, which is a real value window. He is latest on sleeper and earliest on espn: sleeper 200.8, espn 170.2, underdog 184.4.
At 185.5 you are paying a WR2 price for a player whose median outcome is a WR2 season with five weeks that win you the game outright and four that lose it. The bust rate of 32% is real and so is the 79% boom rate.
The call: fair value, not a discount. The reason to take him is the ceiling and the betting record. The reason to pass is that you are buying a profile that has beaten its expected output four years running and only needs to stop once.
Ask the Coach about Gunnar Helm Every number in this piece, plus your league's roster and scoring, in one answer.Expected points are computed from realised usage — targets, air yards and field position — against league-average conversion, not from projections. Projections are anchored to consensus with our engine applied as a capped tilt; the raw engine figure is stated where it differs. Nothing here is betting advice.