WR · NYG · GWTTKB

Calvin Austin III — fantasy football 2026

Every game, every stat category, and what the board says. 6.16 points per game in 2025, an ADP of 169.9, usage worth 6.9.

Updated 2026-08-16 · free, no account, no paywall
Every figure below comes from our database. Where a stat is not held, the row is absent rather than zero.
ADP 169.9
Consensus across 1 books, 0 picks between cheapest and priciest. Cheapest on underdog, priciest on espn.
ESPN169.9
UNDERDOG216
FFA341

Draft-room facts

Goes aroundRound 15, pick 2 in a 12-team draft
Positional rankWR79

What we project for 2026

Our board has him at 41 points, 2.5 per game — 15.3 catches, 200 yards, 0.7 TDs. That is WR6, 293 overall.

The range runs from a floor of 0.1 points per game to a ceiling of 4.9, with the median at 2.5. Boom rate 97%, bust rate 94%. The spread is the actual bet, not the middle number.

He goes at 169.9 on consensus and our board has him 293. We rank him 123.1 picks worse than the room drafts him. At that distance it is a fade: we do not want him anywhere near his ADP.

The offense he plays in, 2026

New York Giants returns 2 of 6 continuity slots, replacing qb1, te1, hc, oc. Jaxson Dart at quarterback, Jim Harbaugh as head coach, Matt Nagy calling it. The offense projects to 30.3 pass attempts a game at low confidence and 27.7 rushes.

In: Darnell Mooney (wr2), Malachi Fields (wr4), Calvin Austin III (wr5), Isaiah Likely (te1). Out: Jaxon Dart (qb), Russell Wilson (qb), Wan'Dale Robinson (wr2), Gunner Olszewski (wr4), Daniel Bellinger (te2).

His own projected target share for 2026 is 6.4%, with a bear case of 4.2% and a bull case of 7.6% and a full range of 3.2% to 8.9%. That comes from 29 historical comparables, not from a depth chart.

The projected target split across the offense:

Malik Nabers25.9%
Darius Slayton11.2%
Darnell Mooney10.4%
Malachi Fields8.6%
Theo Johnson8.2%
Cam Skattebo7.5%

Our written view on this offense in 2026

What the offense looks like: NY still reamins a question mark but there is a lot of potential in this offense if Jaxson Dart turns into the franchise QB. He has a strong arm, is mobile, and plays with a certain type of swagger not all QBs play with. Despite what Ravens fans say, bringing Harbaugh & Nagy into NY is a very good thing. A future HOF coach that is putting his reputation on the line for this team to succeed. Harbaugh has mainly focused on the defense so far, which could imply he thinks the offense is in a good spot, but we will have to see.

Key additions: Darnell Mooney WR from ATL, Calvin Austin III WR from Steelers, Drafted WR Malachi Fields 3rd round, signed TE Isaiah Likely in free agency, New Coach Jim Harbaugh & new OC Matt Nagy.

Key departures: Russell Wilson left to free agency. Won'Dale Robinson left in free agency to the Tennessee Titans (opens up significant amount of targets)

Notes: Giants fired Daboll & brought in Harbaugh. Harbaugh should revamp offense. Brought it Isaiah Likely from Baltimore who seriously hurts Theo Johnson dynasty value (likely should be good). NY did not draft RB & Skattebo will be the starter week 1 of 2026 unless they add someone. He could have a monster season with his Jaxson Dart connection growing. Jaxson Dart gets to play with Malik Nabers for the first time & connection should be electric. Darnell Mooney is a great signing & is on a 1 year prove it deal in NY. If Dart play continues, Mooney will have value.

How the volume number was reached: New QB Jaxson Dart, avg 24.2 att/g over 2025; Regressed 65% toward league mean 33.5, floored at 30 → 30.2 att/g; New OC Matt Nagy — pass rate and tempo may shift; New HC Jim Harbaugh.

How that share projection was built

29 historical comps for WRs age ~25, prior share 12.5%, team change, OC change, QB change. Distribution: median 8.2%, p25-p75 [2.6%, 11.5%], tails [0.0%, 14.8%]. Closest comps: Julio Jones 2022→2023 (TB→PHI: 13.3%→8.2%); Nelson Agholor 2022→2023 (NE→BAL: 13.8%→10.1%); Olamide Zaccheaus 2022→2023 (ATL→PHI: 14.8%→5.6%).

arrival self-anchored 41% to own 12.5% role (3yr)

The named comps are the closest historical matches and the arrow is what their share actually did the following season. That is the working, not a summary of it — if you disagree with the projection, this is the part to argue with.

Offensive environment: NYG rates 21.8 against a league average of 23, 1.1 below it on opponent-adjusted least squares (multi-capture merge).

2026 schedule

Opponent-adjusted pass defense faced, against 2025 ratings. Positive is an easier slate.

Full season+4.4 · easier
Weeks 1–6+8.3 · easier
Weeks 12–17+5.7 · easier
Fantasy playoffs (15–17)+7.9 · easier

Read this narrowly. Our own testing found that season-long strength of schedule does not survive as a draft input — defensive quality is among the least stable team properties year to year, and a preseason slate is built on last year's identities. The playoff-weeks column is the only one we would let break a tie, and even then it is a tiebreaker rather than a reason. The finding.

What happened when he missed time

From the absence record rather than a depth chart — who actually gained when he was out.

SeasonGames missedMain beneficiaryTheir PPR gain
20252Scott Miller+1.1

Dynasty context not redraft

Everything in this section is about his dynasty trade value — what he is worth as a long-term asset in the trade market. It is not a forecast of his 2026 fantasy scoring. A player can be a fine redraft pick while his dynasty value falls, and the reverse. The redraft read is above; this is a different question with a different answer.

Where he sits in the dynasty value cycle

His dynasty value has moved -27.4% over the last twelve months. The market cycle classifies him as post-crash. The base rate that applies: after a -25% crash, WRs recover only 15% of the time (keep falling 85%).

For context on how long this lasts at the position: the average career at his position produces 2.1 elite seasons and 2.6 startable seasons.

The five most similar seasons, and what their dynasty value did next

Matched on production profile — production-driven (pedigree ignored). The last column is how that player’s dynasty value moved the following year — a market outcome, not a scoring one.

PlayerSeasonTheir PPGSimilarityNext year
Jalen Guyton20233.680%-62.1%
Lil'Jordan Humphrey20244.676%+27.6%
Olamide Zaccheaus20233.576%+246.6%
Marquez Callaway20223.874%-19.2%
Hunter Renfrow20227.972%-32.4%

Of the 5 with a following season on record, 2 gained value, 3 lost it and 0 held roughly flat.

Four years of dynasty value

02,0002023202420252026
Monthly superflex value, 2022-03 to 2026-07. Down 0% across the series, peaking at 2,285.

The player

Draft capital and athletic profile

Drafted2022, round 4, pick 138 by PIT
CollegeMemphis
Age at draft23
Height5′8″
Weight170 lb
40-yard dash4.32s
Vertical39″
Broad jump135″
3-cone6.65s
Shuttle4.07s

Availability and volatility

Career PPR per game4.7
Week-to-week variation1.1
Boom rate10.5%
Bust rate42.1%
Games missed per season0.7
Injury historyShoulder, Hamstring
Correlation between his posted line and his actual score-0.22

That correlation is how closely the books’ posted line tracked what he actually scored, week to week. A higher number means the market has him figured out and there is less to exploit; a lower one means his weeks are harder to price.

Injury type matters more than games missed. Measured across our injury database, knee and foot returns stay below a player’s pre-injury baseline for all three of the first games back, while hamstring returns over-recover by the third.

The record, season by season

2025 · PIT · 14 games

His best game was Week 1 against NYJ — 17 PPR on 6 targets and a 20.7% target share, in a game that finished 34-32. His worst was Week 15 against MIA at 0, on 1 targets, final score 28-15. Across 14 games he cleared 20 points 0 times and came in under 8 points 10 times. In the 8 games decided by 8 points or fewer he averaged 8.9; in the 6 decided by more, 2.5. He scored more when the game was live.

Earned against scored

His usage that season was worth 6.9 points per game. He scored 6.16, 13.6% below it. The engine classified the season as unlucky. On receiving touchdowns specifically he finished 2 against 0.74 expected, a gap of 1.3.

WkOppScorePPRRecTgtYdsTDTgt%Snap%
1NYJ34-32174670120.7%80%
2SEA17-313.21422012.9%92%
3NE21-1412.43534122.7%72%
4MIN24-213.3221309.1%51%
8GB25-356.84628018.8%78%
9IND27-2010.65656017.1%56%
10LAC10-253.42714025%73%
11CIN34-121.511503.4%29%
12CHI28-317.64536016.1%46%
13BUF7-26002009.1%49%
14BAL27-224.1123106.1%31%
15MIA28-15001003.7%27%
16DET29-241.811802.6%16%
18BAL26-2414.53755115.9%49%

Production

Receptions31
Targets55
Receiving yards372
Touchdowns3
Points per game6.16
Yards per target6.76
Catch rate56.36%

Role

Snap share53.5%
Target share13.09%
Air-yards share25.46%
WOPR0.374
RACR0.929

Efficiency

Receiving EPA per game-0.3

Scoring position

Red-zone targets4
Red-zone target share5.2%
End-zone target share10.7%
Expected receiving TDs0.74
Actual receiving TDs2
Receiving TD luck1.26

Who else ate

The offense threw it 550 times. He took 10.58% of the targets. 2 team-mates cleared the competing-target threshold.

DK Metcalf19.04%
Kenneth Gainwell16.35%
Calvin Austin III 10.58%
Jonnu Smith10.38%
Pat Freiermuth10.38%
Jaylen Warren8.65%

By quarterback

He caught passes from 2 quarterbacks that season, and the splits are not close.

QBGamesTargetsPPGY/TTgt%
Aaron Rodgers12496.426.7613.64%
Mason Rudolph264.556.839.75%

Blowouts against close games

2 of his 14 games were blowouts, 1.7% of his snaps coming in them. He averaged 0.75 in those and 8.91 in close games — his scoring did not depend on garbage time.

2024 · PIT · 17 games

His best game was Week 8 against NYG — 20.4 PPR on 4 targets and a 14.8% target share, in a game that finished 26-18. His worst was Week 18 against CIN at 0, on 1 targets, final score 17-19. Across 17 games he cleared 20 points 1 time and came in under 8 points 11 times. In the 10 games decided by 8 points or fewer he averaged 6.1; in the 7 decided by more, 8.6. He scored more when the game was not close.

Earned against scored

His usage that season was worth 5.9 points per game. He scored 7.11, 16.9% above it. The engine classified the season as lucky. On receiving touchdowns specifically he finished 0 against 1.22 expected, a gap of -1.2.

WkOppScorePPRRecTgtYdsTDTgt%Snap%
1ATL18-101.712709.1%41%
2DEN13-61.6126011.1%45%
3LAC20-1019.54595116.1%54%
4IND24-272.7111703.1%56%
5DAL17-201.612607.7%76%
6LV32-135.62536021.7%36%
7NYJ37-154.61436014.8%50%
8NYG26-1820.43454114.8%58%
10WAS28-2742620023.1%45%
11BAL18-160.912-106.3%33%
12CLE19-2416.83378112%58%
13CIN44-3810.9222915.6%23%
14CLE27-141.4144016.7%35%
15PHI13-2711.55565023.8%81%
16BAL17-3410.54565019.2%80%
17KC10-297.14531014.3%75%
18CIN17-19001003.4%66%

Production

Receptions36
Targets58
Receiving yards548
Touchdowns4
Points per game7.11
Yards per target9.45
Catch rate62.07%

Role

Snap share53.65%
Target share13.11%
Air-yards share18.22%
WOPR0.325
RACR0.745

Efficiency

Receiving EPA per game1.42

Scoring position

Red-zone targets5
Red-zone target share8.2%
End-zone target share12%
Expected receiving TDs1.22
Actual receiving TDs0
Receiving TD luck-1.22

Who else ate

The offense threw it 498 times. He took 12.64% of the targets. 2 team-mates cleared the competing-target threshold.

George Pickens22.44%
Pat Freiermuth16.99%
Calvin Austin III 12.64%
Najee Harris10.46%
Jaylen Warren10.24%
Van Jefferson8.71%

By quarterback

He caught passes from 2 quarterbacks that season, and the splits are not close.

QBGamesTargetsPPGY/TTgt%
Russell Wilson11418.019.2914%
Justin Fields6175.459.8211.47%

Blowouts against close games

4 of his 17 games were blowouts, 23% of his snaps coming in them. He averaged 6.95 in those and 6.06 in close games — a meaningful share of his scoring came with the game already decided.

2023 · PIT · 16 games

His best game was Week 3 against LV — 15.2 PPR on 6 targets and a 22.2% target share, in a game that finished 23-18. His worst was Week 17 against SEA at 0, on 0 targets, final score 30-23. Across 16 games he cleared 20 points 0 times and came in under 8 points 14 times. In the 11 games decided by 8 points or fewer he averaged 2.1; in the 5 decided by more, 5.8. He scored more when the game was not close.

Earned against scored

His usage that season was worth 3.7 points per game. He scored 3.29, 9.8% above it. The engine classified the season as neutral.

WkOppScorePPRRecTgtYdsTDTgt%Snap%
1SF7-309.76637013.3%56%
2CLE26-221.81410013.8%76%
3LV23-1815.22672122.2%73%
4HOU6-305.93524018.5%90%
5BAL17-10001003.2%56%
7LA24-170.100000%12%
8JAX10-204.9221905%27%
9TEN20-16101003.4%26%
10GB23-191.911304.5%20%
11CLE10-13000000%17%
12CIN16-101.511503.1%25%
13ARI10-242111003.7%15%
14NE18-211.200000%29%
16CIN34-116.702018%19%
17SEA30-23000000%19%
18BAL17-100.800000%27%

Production

Receptions17
Targets30
Receiving yards180
Carries11
Rushing yards57
Touchdowns2
Points per game3.29
Yards per target6
Catch rate56.67%
Yards per carry5.18

Role

Snap share36.69%
Target share6.17%
Air-yards share11.42%
WOPR0.172
RACR0.444

Efficiency

Receiving EPA per game-0.2
Rushing EPA per game0.21

Scoring position

Red-zone targets1
Red-zone target share2%
End-zone target share0%
Red-zone carry share1.3%
Expected receiving TDs0.28
Actual receiving TDs1
Receiving TD luck0.72
Expected rushing TDs0.12

Who else ate

The offense threw it 506 times. 3 team-mates cleared the competing-target threshold.

George Pickens21.9%
Diontae Johnson17.98%
Jaylen Warren15.29%
Allen Robinson10.12%
Pat Freiermuth9.71%
Najee Harris7.85%

By quarterback

He caught passes from 3 quarterbacks that season, and the splits are not close.

QBGamesTargetsPPGY/TTgt%
Kenny Pickett10253.716.048.2%
Mitchell Trubisky332.79.672.9%
Mason Rudolph322.502.67%

Blowouts against close games

3 of his 16 games were blowouts, 42.3% of his snaps coming in them. He averaged 7.43 in those and 2.14 in close games — a meaningful share of his scoring came with the game already decided.

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