GWTTKB Research · Player Study

Should you draft D'Andre Swift in 2026?

What the expected-points record, the coverage data and the market say he is worth at 55.8 overall.

D'Andre Swift scored 253.4 fantasy points in 2025. The volume he earned was worth 240. That gap of 13.4 points is the single most important thing to understand before drafting him at 55.8 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 6: receptions went down from 3.3 to 1.8, a 46.2% change, at 3.35 standard deviations. The cause was structural — the play-calling changed. He also missed Weeks 5, 9.

Year over year the engine classifies 2025 as a stable year. That is the label to carry into the projection, because it separates a player who lost snaps from one who kept them and converted worse.

What actually happened in 2025

He finished 14.08 points per game on 305 touches — an 11.6% jump on his 2024 rate with CHI. 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 carries he took, where on the field they started, and the targets he drew out of the backfield, what was that usage worth? For 2025 the answer was 240 points — 13.3 per game. He scored 13.4 more than that, a 5.6% overshoot.

The expected line underneath the season was 1,113 rushing yards and 8.2 rushing touchdowns, plus 39.1 catches for 295 yards and 1.8 receiving touchdowns, and he cleared it.

Where the season actually moved

Against the expected line, he finished 1,217 rushing yards, 10 rushing touchdowns, 36 catches, 337 receiving yards, 1 receiving touchdowns — against 1,113, 8.2, 39.1, 295, 1.8 expected.

32% of the entire gain came from rushing touchdowns. He hit 122% of his expected rushing touchdowns, against 109% of his expected rushing yards and 92% of his expected catches and 114% of his expected receiving yards and 56% of his expected receiving touchdowns.

01020301MIN2DET3DAL4LV6WAS7NO8BAL10NYG11MIN12PIT13PHI14GB15CLE16GB17SF18DET
ExpectedBeat itMissed it
Every week of 2025, what he was worth against what he scored. Expected points come from the volume he actually earned — carries, where they started on the field, and the targets he drew out of the backfield. He cleared it in 7 of 16 games.

The season was one game

1 of his 16 games produced 25 or more points: Week 6 against WAS (25.5). Strip it and the remaining 15 games average 13.5.

Spike weeks win fantasy games and a player who produces them is more valuable than one who never does — he is a ceiling play with real weeks off. 5 games came in under 10 points, including Week 1 against MIN (9.5) and Week 11 against MIN (9).

The three largest overshoots — Week 6 (+11.9), Week 17 (+11.5), Week 15 (+9.7) — are the same games. The spikes were not extra volume. They were finishing.

This has happened before

051015202020DET · 171 tch2021DET · 229 tch2022DET · 169 tch2023PHI · 292 tch2024CHI · 305 tch2025CHI · 305 tch
Expected /gActual — ran hotActual — in line
6 seasons, actual against expected. 2 of the 6 came in meaningfully above what the volume justified.

2 of his 6 seasons ran hot: 2020 (+19.5%), 2022 (+14.8%). 1 came in below what the usage justified: 2024 (-11.9%). Across all 6 he has scored 23.2 points more than his usage was worth.

The reflexive read is regression. Finishing above expectation is unstable, and a player who does it repeatedly is usually one whose luck has not run out yet.

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 beat the number. It is whether there is a mechanism.

What the coverage data says

COVER 358 tgt-0.0314.91 y/tCOVER 253 tgt-0.075.58 y/tCOVER 144 tgt-0.0367.18 y/tCOVER 425 tgt+0.3327.16 y/tCOVER 624 tgt-0.124.63 y/t
What he does against each coverage, 226 targets over four seasons. Cover 1 is single-high man — the look he sees most and punishes hardest. Cover 0 and Cover 6 are the two he cannot solve.

Across 226 targets and four seasons — a back’s pass-game role rather than his primary work, so read it as a tiebreaker and not as the case for him, he has been a different pass-catcher depending on what the defense played. Against man he has caught 68.6% for 7.78 yards per target and 0.054 expected points added per target. Against zone: 76.6%, 5.36 yards, 0.008 EPA.

That is a gap of 0.047 EPA per target on a sample of 51 man targets against 175 zone. The catch rate goes the other way — he catches more against zone — which is exactly what you would expect from a back used as a checkdown outlet rather than as a downfield threat.

The shell detail sharpens it. Cover 3 is the look he has faced most: 58 targets, 4.91 yards per target, -0.031 EPA. His best is Cover 4 quarters at 0.332 on 25 targets.

The weakness is specific. Against Cover 6 he has caught 62.5% for 4.63 yards a target and -0.12 EPA across 24 looks — a gap of 0.5 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.

The market has him fairly priced

Across 124 graded prop lines, he has gone over 50.8% of the time. On rushing yards specifically the number is 51.6% across 31 lines, beating the posted number by an average of 24.3%.

That is close enough to a coin flip that the market has him fairly priced on his primary market. There is no edge to claim in either direction.

Touchdowns are the control. His anytime-TD market implied a 41.9% rate and he converted at 41.9% — a gap of 0.0 points, which is noise.

So the risk is not efficiency. It is the touches.

Chicago returns 5 of 6 continuity slots — qb1, wr1, rb1, te1, hc — with Caleb Williams at quarterback, Ben Johnson as head coach and Press Taylor calling it. The offense projects to 33.59 pass attempts a game at medium confidence.

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 James Conner 10.8% to 9.4%, Todd Gurley 10% to 0%, David Montgomery 9.3% to 5.8%. One held, 2 did not.

The numbers that carry, and the ones that do not

Across 2,022 player-seasons we swept every stat for whether it predicts NEXT year's points, and kept only the ones that replicated in all five. time to the line of scrimmage (r 0.128), snap-share trend (r 0.103), recent scoring form (r 0.078) carry. week-to-week volatility (r -0.163) and receiving EPA per game (r -0.143) 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: 255 carries, 45.2% of his team’s red-zone carries, 49.2% of the goal-line work, a 57.9% snap share. His carries produced 0.049 EPA per play, and he ran a 9.1% target share out of the backfield.

The offense he plays in

Vegas sets an implied total for every team every week, and some offenses beat theirs systematically. Over 104 games, CHI has come in +0.48 points against its own implied total, clearing it in 52% 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

8.3 floor 13.2 ppg 17.1 ceiling bust 37% boom 29%
The 2026 range, not the point estimate. 13.2 is the middle. The spread from 8.3 to 17.1 is the actual bet.

Our board has him at 210.5 points, 13.2 per game across 16 expected games — 911 rushing yards, 7.5 rushing touchdowns, 33.3 catches for 274 yards. That is RB3, 39 overall, and 53 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.

What we have been saying about him

three straight 250+-touch seasons with real room for the receiving role to grow further; Chicago's brutal 2025 schedule is read as a bigger risk for Kyle Monangai's early-down role than for Swift's, since more competitive/trailing games mean more passing-down snaps for Swift specifically.

BUY · medium conviction · 2026-08 · 4 logged takes

That is the current read. It has held since 2026-06-05.

It rests on one of our draft principles:

Where to draft him

The books do not agree on him. D'Andre Swift is a board split: CBS takes him ~43, ESPN lets him slide to ~73 (30-pick gap). The market hasn't settled — room to get him below consensus if your leaguemates draft off the ESPN board. That 30-pick gap between CBS and ESPN is the practical thing to act on: in a ESPN-priced room he is available later than his consensus number suggests.

He goes at 55.8 overall on consensus, and the books are far apart — 30 picks between cheapest and priciest, which is a real value window. He is latest on espn and earliest on cbs: sleeper 58.9, espn 72.5, yahoo 49.4, underdog 48, cbs 42.5.

He goes at 55.8 and our board has him 39. That is 16.8 picks of discount on a RB3 projection — you are getting the RB3 outcome at a price the room has set below it.

The case for: 53 points of value over a replacement starter.

The case against: a 37% bust rate; 2 of 6 seasons flagged as running hot — not simply finishing above expectation, but far enough above it to classify, which is the pattern that regresses.

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

Ask the Coach about D'Andre Swift 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. Prop records cover 124 graded lines. 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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