GWTTKB Research · Player Study

Should you draft Gunnar Helm in 2026?

The volume held. The finishing did not. Whether 2025 was the player breaking or the situation breaking decides what he is worth at 201.4 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 201.4 overall.

The week it changed

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 offense around him got sharply better. He also missed Weeks 10, 18.

What actually happened in 2025

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 traveled, what was that usage worth? For 2025 the answer was 99.9 points — 6.2 per game. He scored 8.2 FEWER than that, an 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.

010201DEN2LA3IND4HOU5ARI6LV7NE8IND9LAC11HOU12SEA13JAX14CLE15SF16KC17NO
ExpectedBeat itMissed it
Every week of 2025, what he was worth against what he scored. Expected points come from the volume he actually earned — targets, air yards, and where on the field they came. He cleared it in 5 of 16 games.

There were no spike weeks

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.

This has happened before

05102025TEN · 55 tgt
Expected /gActual — ran hotActual — in line
1 season, actual against expected. None came in meaningfully above what the volume justified.

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.

So the risk is not efficiency. It is targets.

Carnell Tate18.3%Calvin Ridley18.3%Wan'Dale Robinson15.5%Elic Ayomanor11.2%Chimere Dike9.1%Tyjae Spears8.9%
Projected 2026 target share. Pale bar is the p10–p90 range. Built from comparable receivers at the same age, share and offensive continuity — not from a depth chart.

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 offense 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%. The biggest competing claim on that pie is Carnell Tate at 18.3%, 14.8 points ahead of him.

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%. One held, 2 did not.

The numbers that carry, and the ones that do not

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, a 52.6% snap share. He averaged 2.55 yards of separation, with -2.2 YAC over expected.

The offense he plays in

Vegas sets an implied total for every team every week, and some offenses 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 offense 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.

What we project for 2026

4.9 floor 7.1 ppg 12.7 ceiling bust 32% boom 79%
The 2026 range, not the point estimate. 7.1 is the middle. The spread from 4.9 to 12.7 is the actual bet.

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, 171 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.

Where to draft him

The books do not agree on him. Gunnar Helm is a board split: ESPN takes him ~170, Sleeper lets him slide to ~233 (62.4-pick gap). That 62.4-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 201.4 overall on consensus, and the books are far apart — 62.4 picks between cheapest and priciest, which is a real value window. He is latest on sleeper and earliest on espn: sleeper 232.6, espn 170.2, underdog 187.

He goes at 201.4 and our board has him 171. That is 30.4 picks of discount on a TE5 projection — you are getting the TE5 outcome at a price the room has set below it.

The case for: a 79% boom rate.

The case against: a 32% bust rate.

The call: take him at his ADP and do not talk yourself out of it.

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 realized 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.

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