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2026 NFL DRAFT CHEAT SHEET 📌
For the eighth consecutive year, here’s my final look at each team’s first-round big board, built from pre-draft intel, team needs and organizational tendencies.
See more: NFL.com/IQ
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Mike Band
3.1K posts
Mike Band
@MBandNFL
NFL @NextGenStats Research & Analytics; @GatorsFB, @Vikings, @UChicago & @LanderAnalytics trained; data storyteller
Los Angeles, CA Katılım Kasım 2009
992 Takip Edilen5.4K Takipçiler
Given that the quality of a draft class is volatile year-to-year (i.e. some classes are strong than others), wouldn’t it be appropriate to use a post-model ranking algorithm to estimate draft slot within a given year? In other words, if the highest predicted pick for a WR across the full population ~ pick No. 17, but there are considerably more actual top 10 picks, then don’t you need to take the outputs within a given year and re-rank to truly estimate pick number?
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After all given number of players drafted by position signal is still sparse, so please still take it as grain of salt, but it could still be an interesting experiment to look at players n/n
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Inspired by this tweet using data provided by @CFB_Data I decided to look at draft modelling without consider mock draft/draft grade at all 1/n 🧵
Tej Seth@tejfbanalytics
think that it’s totally fine to use the consensus big board (CBB) to evaluate draft picks in the top 100. it’s really impressive the CBB can perform as well as teams do despite not being tailored to specific teams and not having the same access to medical/personality information however, would really like to see the analytics community (myself included) lean more into advanced stats when talking about why players are reaches (or steals). the NBA draft analytics community does a great job of using stats like age adjusted BPM when talking about draft prospects. the NFL draft analytics community has good stats like receiving yards per team pass attempt, first 3 years pressure rate etc and should lean more into them would like to see more of “nate boerkircher was a reach because of where he was on the CBB *and* his receiving production and blocking profile projects him to be [this type of player] in the NFL” part of this is access to advanced college football data but for those with access, think that we can take draft analysis a bit further than just the CBB
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Someone tell NFL IQ that Ryan Poles would never target Caleb Banks with that significant of an injury history.
We’ve got 4 years of draft, trade & FA decisions that Poles is notorious for passing on any player with questionable medicals that impact their *long-term* durability outlook.
(Yes, Loveland had a shoulder surgery but no impact to long-term durability & that’s exactly what proved out. He had a great rookie season)
Multiple foot injuries on the same foot qualify as such for Banks. Poles is too conservative to ever have him on his draft list
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Mike Band retweetledi
Now that the 2026 NFL Draft is in the books, what did every team’s Round 1 short list really look like?
@MBandNFL uses post-draft reporting to project who teams may have been targeting, available on NFL IQ, powered by @awscloud.
NFL.com/IQ » NFL Draft » Cheat Sheet
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@NextGenStats @awscloud The post-draft projected big boards will continue to be a work in progress as more reporting comes out on teams’ first-round plans.
If you’re aware of any reports not reflected above, please share them in the replies.
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Mike Band retweetledi
Which NFL teams had the most athletic draft classes in the 2026 NFL Draft?
The @ChicagoBears, @BuffaloBills, @Raiders, @49ers and @Saints each averaged an 80+ NGS athleticism score across their first seven picks.
See the full list at NFL.com/IQ powered by @awscloud
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Mike Band retweetledi
The Next Gen Stats analytics team used the NGS Draft Model to identify the five best value picks in Day 2 of the 2026 NFL Draft.
🔗 nfl.com/news/2026-nfl-…
Powered by @awscloud
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Mike Band retweetledi
The Next Gen Stats analytics team used the NGS Draft Model to identify the five best value picks in Round 1 of the 2026 NFL Draft, powered by @awscloud.
nfl.com/news/2026-nfl-…
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2026 NFL DRAFT CHEAT SHEET 📌
For the eighth consecutive year, here’s my final look at each team’s first-round big board, built from pre-draft intel, team needs and organizational tendencies.
See more: NFL.com/IQ
English
Mike Band retweetledi
Mike Band retweetledi
Who could your team target in Round 1?
Here are the top 5 projected first-round big boards from NFL.com/IQ powered by @awscloud.
🧵
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Mike Band retweetledi
2026 NFL Draft sleepers (via @MBandNFL): Which prospects offer immense value on Day 2? Hidden gems for Day 3?
nfl.com/news/2026-nfl-…
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@DTLB58 @NextGenStats @RosterWatch No. 9 and 40 works out in Tennessee’s favor in all three public trade charts.
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@MBandNFL @NextGenStats @RosterWatch How in the world does KC trade up from #9 to #4 and still keep their #29 pick?!?!
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My final 2026 NFL Mock Draft is live!
This is the 22nd straight year I’ve put together a first-round mock, and it’s still one of my favorite annual exercises. First-round cheat sheet drops tomorrow morning.
rosterwatch.com/mike-bands-fin…
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What did the Chiefs give up to go from 9 to 4?
Mike Band@MBandNFL
My final 2026 NFL Mock Draft is live! This is the 22nd straight year I’ve put together a first-round mock, and it’s still one of my favorite annual exercises. First-round cheat sheet drops tomorrow morning. rosterwatch.com/mike-bands-fin…
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Mike Band retweetledi
NFL Draft Day 2 Standouts & Day 3 Gems 💎
The 2026 NFL Draft marks the seventh year we've used the Next Gen Stats Draft Model to identify sleepers using data and machine learning. @MBandNFL breaks down the top prospects to target AFTER Round 1.
nfl.com/news/2026-nfl-…
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Mike Band retweetledi
Team Central is now the Draft Room in NFL IQ.
See every team’s most-likely draft targets across all seven rounds of the 2026 NFL Draft with NFL IQ, powered by @awscloud and featuring insights from @MBandNFL, @GrindingMocks & @BigBoardLab.
nfl.com/iq?tab=team-ce…
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@benj_robinson @jaredlander Unfortunately, they did not keep using it after 2015. Jared/Lander Analytics retained the rights to the code, while I was off to UChicago for grad school to learn how to do what he did myself.
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@jaredlander @MBandNFL Do you think the Vikings kept on using your model, moved on to greener pastures, or maybe something in between? A good story but just one year.
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Mike Band retweetledi
@Shauncore I just added over 1,000 words to the backend to address this issue. While it may not be perfect without an all-32 team sim, you won't find Caleb Downs as a fourth round target.
Let me know if you find anything else that fails to pass the sniff test.
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Tried having NFL IQ AI do a Brett Veach 7 round mock and yeah while this would be an incredible draft, it obviously didn't stick to the rules...
Shaun Newkirk@Shauncore
Asked the NFL IQ AI tool to describe Brett Veach's draft philosophy and history, and which players in the draft this year fit that mold.
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