GWTTKB Research · Player Study

Should you draft Christian McCaffrey in 2026?

What the expected-points record, the coverage data and the market say he is worth at 6 overall.

Christian McCaffrey scored 458.4 fantasy points in 2025. The volume he earned was worth 439.3. That gap of 19.1 points is the single most important thing to understand before drafting him at 6 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 13: receiving yards went down from 65.4 to 27.8, a 57.5% change, at 5.52 standard deviations. The cause was structural — the play-calling changed. He also missed Week 14.

Year over year the engine classifies 2025 as a breakout the underlying work supports. 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 24.13 points per game on 143 touches — a 101.9% jump on his 2024 rate with SF. 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 439.3 points — 23.1 per game. He scored 19.1 more than that, a 4.3% overshoot.

The expected line underneath the season was 111.8 catches for 844 yards and 5.1 touchdowns, and he cleared it.

The miss was touchdowns, and almost nothing else

The expected line was 111.8 catches for 844 yards and 5.1 touchdowns. He finished with 113, 1029 and 9.

54% of the entire gain came from touchdowns alone. He hit 101% of his expected catches and 122% of his expected receiving yards — and 176% of his expected touchdowns.

0102030401SEA2NO3ARI4JAX5LA6TB7ATL8HOU9NYG10LA11ARI12CAR13CLE15TEN16IND17CHI18SEA
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 9 of 17 games.

The season was eight games

8 of his 17 games produced 25 or more points: Week 4 against JAX (26.1), Week 5 against LA (27.9), Week 7 against ATL (39.1), Week 9 against NYG (34.3), Week 11 against ARI (35.1), Week 12 against CAR (27.2), Week 16 against IND (32.6), Week 17 against CHI (28.1). Strip them and the remaining 9 games average 18.5.

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. 1 game came in under 10 points, including Week 8 against HOU (9.8).

The three largest overshoots — Week 11 (+17.4), Week 7 (+11.3), Week 9 (+7.1) — are the same games. The spikes were not extra volume. They were finishing.

This has happened before

0510152025302021CAR · 41 tgt2022CAR · 122 tgt2023SF · 108 tgt2024SF · 19 tgt2025SF · 143 tgt
Expected /gActual — ran hotActual — in line
Four seasons, actual against expected. Two of the four came in meaningfully above what the volume justified.

1 of his 5 seasons ran hot: 2022 (+15.6%). 1 came in below what the usage justified: 2024 (-22.7%). Across all 5 he has scored 185.6 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.

There is a mechanism, and it is man coverage

COVER 3104 tgt+0.1666.76 y/tCOVER 291 tgt-0.0745.77 y/tCOVER 181 tgt+0.3156.07 y/tCOVER 444 tgt+0.4489.25 y/tCOVER 626 tgt-0.3035.08 y/tCOVER 017 tgt+0.7879.82 y/t
What he does against each coverage, 392 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 392 targets and four seasons, he has been a fundamentally different receiver depending on what the defence played. Against man he has caught 81.3% for 7.05 yards per target and 0.401 expected points added per target. Against zone: 78.6%, 6.72 yards, 0.096 EPA.

That is a gap of 0.305 EPA per target on a sample of 107 man targets against 285 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: 104 targets, 6.76 yards per target, 0.166 EPA. His best is Cover 0, all-out pressure with no safety help at 0.787 on 17 targets.

The weakness is specific. Against Cover 6 he has caught 69.2% for 5.08 yards a target and -0.303 EPA across 26 looks — a gap of 1.1 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 been wrong about him in one direction

Across 76 graded prop lines, he has gone over 53.9% of the time. On receiving yards specifically the number is 63.2% across 19 lines, beating the posted number by an average of 29.9%.

A projection model can be wrong about conversion. A book adjusting weekly, with money on the other side, being wrong 63% of the time on the same market is a harder thing to explain away.

Touchdowns are the control. His anytime-TD market implied a 64.0% rate and he converted at 57.9% — a gap of -6.1 points, which is worth noting.

So the risk is not efficiency. It is targets.

De'Zhaun Stribling16.1%Mike Evans11.8%George Kittle11.5%Ricky Pearsall10.4%Christian Kirk9.2%Christian McCaffrey8.9%Jake Tonges7.4%Isaac Guerendo6.6%Demarcus Robinson6.5%Kaelon Black6.3%
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.

San Francisco returns 5 of 6 continuity slots — qb1, rb1, te1, hc, oc — with Brock Purdy at quarterback, Kyle Shanahan as head coach and Klay Kubiak calling it. The offence projects to 33.65 pass attempts a game at high confidence.

The pie is stable. His slice is the question. Our share model has him at 8.9% against the 22% he ran, with a range of 6.6% to 10%.

That number is built from 22 comparable players — same age band, same prior share, same team, same coordinator — not from a depth chart. The closest three went Derrick Henry 8.3% to 6.4%, Jerick McKinnon 10.3% to 7%, Rex Burkhead 11.6% to 10.3%. Two held, one fell hard.

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. f_timeToLOS (r 0.128), f_snapTrend (r 0.103), f_fantasyForm (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: a 23.5% target share, 8.2% of the air yards, a WOPR of 0.41, on the field for 83.1% of snaps. He finished 1 at the position — RB1.

The offence he plays in

Vegas sets an implied total for every team every week, and some offences beat theirs systematically. Over 112 games, SF has come in +0.57 points against its own implied total, clearing it in 48% 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.

What we project for 2026

18.1 floor 19.4 ppg 27.3 ceiling bust 7% boom 41%
The 2026 range, not the point estimate. 19.4 is the middle. The spread from 18.1 to 27.3 is the actual bet.

Our board has him at 310.7 points, 19.4 per game across 16 expected games — 70 catches, 603 yards, 4.3 touchdowns. That is RB1, 7 overall, and 155 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

the 100-reception ceiling is the whole case: strip out every rushing yard and TD and he still would've been fantasy-relevant on receiving work alone last year (would've finished as a top-20 back on catches alone). Efficiency concerns off the 413-touch, age-30 season matter much less when the receiving floor is that high regardless of rushing efficiency. The one real risk is just injury, which can't be projected.

BUY · high conviction · 2026-08 · 2 logged takes

That is the current read. It has held since 2026-06-14.

It rests on these draft principles:

Where to draft him

The books do not agree on him. Christian McCaffrey is a board split: Sleeper takes him ~5, CBS lets him slide to ~7 (1.7-pick gap). That 1.7-pick gap between Sleeper and CBS is the practical thing to act on: in a CBS-priced room he is available later than his consensus number suggests.

He goes at 6 overall on consensus, and the books are tight on him — 1.7 picks between cheapest and priciest. He is latest on cbs and earliest on sleeper: sleeper 5, espn 6.6, yahoo 5.5, underdog 6, cbs 6.7.

At 6 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 7% is real and so is the 41% 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 Christian McCaffrey 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. Prop records cover 76 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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