Explore NFL ACL injury episodes, recorded time missed and fantasy performance after return for quarterbacks, running backs, receivers and tight ends.
75 recorded episodes · Updated November 11, 2026 · Half-PPR fantasy scoring
How does fantasy production change after return?
| Position | Episodes | Avg games missed | Game 1 | Game 2 | Game 3 | Game 4 | Game 5 | Game 6 |
|---|---|---|---|---|---|---|---|---|
| QB | 9 | 9.9 gamesn=9 | -22.0%n=9 · small sample | +5.7%n=9 · small sample | +12.9%n=9 · small sample | -0.5%n=8 · small sample | +5.0%n=7 · small sample | -15.0%n=7 · small sample |
| RB | 20 | 15.1 gamesn=13 | -25.0%n=15 | -49.1%n=14 | -58.8%n=11 | +7.1%n=8 · small sample | +8.0%n=6 · small sample | -10.2%n=6 · small sample |
| WR | 34 | 12.0 gamesn=27 | -39.3%n=19 | -35.2%n=18 | -35.4%n=18 | -8.7%n=17 | -10.2%n=17 | -48.0%n=17 |
| TE | 12 | 14.1 gamesn=11 | -34.6%n=12 | -30.8%n=12 | -43.9%n=12 | -27.4%n=10 | -43.7%n=10 | -9.2%n=9 · small sample |
Each game has its own eligible sample. These are historical comparisons, not a prediction for an individual player.
QB: first game back
-22.0% fantasy production change across 9 eligible observations.
9.9 games missed on average across 9 recorded values.
Small sample: interpret cautiously.
RB: first game back
-25.0% fantasy production change across 15 eligible observations.
15.1 games missed on average across 13 recorded values.
WR: first game back
-39.3% fantasy production change across 19 eligible observations.
12.0 games missed on average across 27 recorded values.
TE: first game back
-34.6% fantasy production change across 12 eligible observations.
14.1 games missed on average across 11 recorded values.
What the numbers mean for fantasy football
An ACL injury can create a prolonged rehabilitation process. Restoring strength, movement control and confidence in changing direction matters beyond the return date. These records may span seasons, and associated injuries or different treatment approaches can change recovery. Do not treat the category average as an individual surgical timeline.
Role, age, workload, associated injuries and the type of treatment can all differ between episodes. Read the diagnosis and practice report alongside these data; the averages cannot confirm readiness or a return date.
Shareable first-game comparison
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Credit: Fantasy Injury Team. Link to this page when citing the chart; the chart includes the source date and sample sizes.
The people behind the percentages
Individual player episodes
Select a player to expand their injury timeline, baseline, and return-game outcomes.
Aggregate position data · ACL
| Position | Episodes | Avg games missed | Game 1 | Game 2 | Game 3 | Game 4 | Game 5 | Game 6 |
|---|---|---|---|---|---|---|---|---|
| QB | 9 | 9.9 gamesn=9 | +3.2%n=9 · small sample | +3.1%n=9 · small sample | +2.8%n=9 · small sample | -0.3%n=8 · small sample | +2.4%n=7 · small sample | +0.3%n=7 · small sample |
| RB | 20 | 15.1 gamesn=13 | -34.4%n=12 | -28.6%n=11 | -15.0%n=8 · small sample | -12.9%n=5 · small sample | +29.9%n=3 · small sample | +10.7%n=3 · small sample |
| WR | 34 | 12.0 gamesn=27 | -21.2%n=21 | -8.4%n=20 | -8.2%n=20 | -7.9%n=18 | -5.4%n=18 | -5.7%n=18 |
| TE | 12 | 14.1 gamesn=11 | -30.5%n=12 | -27.1%n=12 | -31.6%n=12 | -22.5%n=10 | -18.0%n=10 | -4.2%n=9 · small sample |
75 matching episodes · ACL · All positions.
| Player / team | Injury timing | Games missed | G1 snap Δ | G2 snap Δ | G3 snap Δ | G4 snap Δ | G5 snap Δ | G6 snap Δ |
|---|---|---|---|---|---|---|---|---|
De'Von AchaneLeft knee ACL tear | 2026 Week 3 | 5.0 | — | — | — | — | — | — |
Calvin Austin IIIRight knee ACL tear | 2026 Preseason | 8.0 | — | — | — | — | — | — |
Jayden HigginsKnee ACL tear | 2026 Preseason | 8.0 | — | — | — | — | — | — |
Michael PenixLeft knee partial ACL tear; reconstruction | 2025 Week 11 | 9.0 | +3.0% | +3.0% | -2.2% | +3.0% | +3.0% | +3.0% |
Daniel JonesACL | 2023 Week 9 | 8.0 | +9.9% | +9.9% | +9.9% | +9.9% | +9.9% | +9.9% |
Kyler MurrayACL | 2022 Week 14 | 13.0 | -1.8% | +1.2% | +0.2% | +1.2% | -1.8% | +1.2% |
Jameis WinstonACL tear + MCL damage; reconstruction | 2021 Week 8 | 10.0 | +4.3% | +1.2% | +4.3% | — | — | — |
Joe BurrowACL | 2020 Week 11 | 6.0 | +0.1% | +0.1% | +0.1% | +0.1% | +0.1% | -17.9% |
Jimmy GaroppoloACL | 2018 Week 3 | 13.0 | 0.0% | 0.0% | 0.0% | -1.0% | 0.0% | 0.0% |
Carson WentzACL + LCL | 2017 Week 14 | 5.0 | +4.1% | +4.1% | +4.1% | +4.1% | +4.1% | +4.1% |
Deshaun WatsonACL | 2017 Week 8 | 9.0 | +7.0% | +7.0% | +7.0% | +7.0% | — | — |
Ryan TannehillACL tear; reconstruction | 2017 Preseason | 16.0 | +1.8% | +1.8% | +1.8% | -26.7% | +1.8% | +1.8% |
Zach CharbonnetLeft knee ACL tear; reconstruction | 2025 Divisional round | 7.0 | -23.5% | +17.8% | — | — | — | — |
Kendre MillerKnee ACL tear | 2025 Week 7 | — | +4.8% | -31.3% | -6.0% | +12.0% | +59.0% | +41.0% |
Antonio GibsonACL | 2025 Week 5 | — | — | — | — | — | — | — |
Kenny McIntoshACL | 2025 Preseason | — | — | — | — | — | — | — |
Jonathon BrooksRight knee ACL re-tear; reconstruction | 2024 Week 14 | — | +31.0% | +106.9% | — | — | — | — |
Keaton MitchellACL | 2023 Week 15 | 12.0 | -88.8% | -88.8% | +1.3% | -21.3% | — | — |
Jonathon BrooksACL | 2023 Week ? | 16.0 | — | — | — | — | — | — |
Nick ChubbACL | 2023 Week 2 | 21.0 | -26.5% | +20.4% | -28.6% | -38.8% | +34.7% | -30.6% |
Breece HallACL | 2022 Week 7 | 10.0 | -42.8% | -37.2% | -9.5% | -18.8% | -4.0% | +21.8% |
Javonte WilliamsACL | 2022 Week 4 | 13.0 | -19.6% | -19.6% | — | — | — | — |
Gus EdwardsACL | 2021 Preseason | 23.0 | +6.1% | — | — | — | — | — |
JK DobbinsACL | 2021 Preseason | — | — | — | — | — | — | — |
Rex BurkheadACL | 2020 Week 11 | 6.0 | -69.8% | -58.1% | -65.1% | — | — | — |
Tarik CohenACL + MCL + tibial plateau fracture | 2020 Week 3 | — | — | — | — | — | — | — |
Saquon BarkleyACL | 2020 Week 2 | 14.0 | -44.8% | -3.4% | -1.1% | +2.3% | — | — |
Rashaad PennyACL | 2019 Week 14 | 16.0 | -55.4% | -75.7% | +74.3% | — | — | — |
Jay AjayiACL | 2018 Week 5 | 21.0 | -72.3% | -69.7% | -84.9% | — | — | — |
Jerick McKinnonACL | 2018 Preseason | 32.0 | — | — | — | — | — | — |
Dalvin CookACL | 2017 Week 4 | — | — | — | — | — | — | — |
Gabe DavisACL | 2025 Wild card | — | — | — | — | — | — | — |
Tyrell ShaversACL | 2025 Wild card | — | — | — | — | — | — | — |
Malik NabersACL tear | 2025 Week 4 | — | -45.3% | -22.1% | -17.9% | -20.0% | -5.3% | -9.5% |
Christian WatsonACL | 2024 Week 18 | 6.0 | -10.0% | +6.1% | +31.8% | +25.4% | +18.9% | +17.3% |
Stefon DiggsACL | 2024 Week 8 | 9.0 | -49.9% | -36.5% | -35.3% | -23.0% | -38.9% | -27.9% |
Brandon AiyukACL | 2024 Week 7 | — | — | — | — | — | — | — |
Braxton BerriosACL | 2024 Week 7 | 16.0 | +52.6% | -5.8% | -96.8% | — | — | — |
Kendrick BourneACL | 2023 Week 8 | 13.0 | -63.9% | -30.5% | -17.2% | +4.2% | +4.2% | -37.2% |
Mike WilliamsACL tear; reconstruction | 2023 Week 3 | 15.0 | -78.4% | -22.2% | -46.1% | -30.5% | -15.0% | -38.9% |
Jameson WilliamsACL tear; reconstruction | 2022 Week ? | 11.0 | — | — | — | — | — | — |
Wan'Dale RobinsonACL | 2022 Week 11 | 9.0 | -56.2% | +27.5% | +33.5% | +19.5% | +19.5% | +59.4% |
Sterling ShepardACL tear; reconstruction | 2022 Week 3 | 14.0 | -75.0% | -81.3% | -95.0% | -91.3% | -65.0% | -98.8% |
Jalen GuytonLeft ACL tear; reconstruction | 2022 Week 3 | 21.0 | +533.3% | +777.8% | +788.9% | +588.9% | +255.6% | +444.4% |
Bisi JohnsonLeft ACL tear; reconstruction | 2022 Preseason | 17.0 | — | — | — | — | — | — |
Tim PatrickRight ACL tear; reconstruction | 2022 Preseason | 17.0 | -53.4% | -40.3% | -52.2% | -47.5% | -36.7% | -8.1% |
Odell Beckham Jr.Left ACL retear; reconstruction | 2021 Super Bowl LVI | 17.0 | +28.2% | -27.6% | -26.2% | -42.9% | -20.6% | -20.6% |
Michael GallupACL tear; reconstruction | 2021 Week 17 | 4.0 | -19.2% | -30.6% | -4.1% | -15.5% | +6.0% | +4.7% |
Chris GodwinACL + MCL tear | 2021 Week 15 | 3.0 | -65.7% | -8.2% | -42.5% | -1.5% | +4.0% | -0.4% |
John MetchieACL | 2021 Week ? | — | — | — | — | — | — | — |
Snapshot updated November 11, 2026. All tables use the same 2,413-episode source snapshot. Historical comparisons are observational; they do not establish that an injury caused a particular performance change. Read the methodology and limitations.