The 2026 NFL Draft is over, which means it’s time to talk about the 2026 NFL Draft.

We have a bunch of data on incoming rookies and we can use it to figure out how teams have done when acquiring those rookies. No approach is perfect of course, but we can at least use our collective wisdom to figure out which teams have best pushed the odds in their favor given what we know.

Table of Contents:

• Is the Consensus Board “Groupthink?”

• Can the Consensus Board Grade Picks?

• What About Steals and Reaches?

• Is This Any Good for Judging Teams?

• 2026 Consensus Big Board Draft Grades

  • Winners

  • Losers

  • Position-Blind Grades

If you want to see the ranks themselves, we’ve got this (free) piece that lists the Top 300 players.

The benefit to a project like the Consensus Big Board is that we can look back on previous classes and see if we were any good at figuring out good draft classes from bad.

The Consensus Big Board project was started with the idea that there is value in bringing together intellectually diverse approaches to evaluating college players and that we’d learn a great deal by casting a wide net when it came to the extraordinary amount of information produced about the NFL draft.

Paul Noonan at Acme Packing Company did an excellent job capturing my thought process in his piece on the subject.

One of the best books ever written on aggregating data in order to make better decisions and predictions is The Wisdom of Crowds by James Suroweicki, and the consensus draft boards are almost textbook examples of smart data aggregation. The board concept itself is built on a simple but effective aggregation method, and it relies on contributors who are independent, who have a fierce diversity of opinion, and who bring specialized, local knowledge to the task.

This year, no player who was drafted by the NFL was unranked by the Consensus Big Board. Two years ago, no player who was drafted was outside of the top 550, a record.

The first player outside of the Top 300 drafted this year was Max Bredson, fullback for Michigan — drafted by the Minnesota Vikings 159th overall and ranked 317th on the Consensus Big Board. This ties the latest we’ve ever seen a player picked that was off the Top 300 board, which was in 2020 when the Patriots selected kicker Justin Rohrwasser 159th overall.

Rorhwasser ranked 796th on the larger board, and the Patriots cut him in camp shortly after a cycle of news focused on his white supremacist tattoo, which had been discovered by Justis Mosqueda of Acme Packing Company during the draft and had been removed by Rohrwasser a few months later.

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Last year, Ruben Hyppolite II was drafted 132nd overall by the Chicago Bears. In 2024, it was the Detroit Lions drafting Givanni Manu 126th overall. It might be an NFC North thing at this point.

This year also ties the fewest number of players drafted who were outside the Top 300 — 20, tying the 2024 NFL draft.

This could mean either that NFL teams are becoming more efficient at drafting or that analysts are becoming more efficient at identifying prospects worth drafting.

For what it’s worth, feedback from NFL scouting personnel tells Wide Left that it’s most likely a mix of both. NFL teams have confirmed with Wide Left that they use some version of a Consensus Board in their draft planning. None of the teams that have contacted Wide Left have indicated they use the Consensus Board to alter their opinions of players, but they will use the board in order to get an understanding of where players will be drafted.

At least two teams Wide Left has talked to about the Consensus Big Board have mentioned that they use a combination of a Consensus Board, mock drafts and their own team grades to project where players will go in the NFL draft.

That last element is important, of course, because teams have unique and proprietary information on those players; only they could evaluate the injury concerns for Jermod McCoy or any off-field concerns they discovered in the process of scouting players.

Let’s engage in discourse, then talk about data validation for why it makes sense to at least absorb the Consensus Board grades.

Is the Consensus Board “Groupthink”?

Like with any academic term that has entered the broader social sphere, “groupthink” has lost a lot of its original meaning. Groupthink is not the concept of a large number of people having opinions.

It had primarily been used to describe the notion that people would, through social pressure, be forced into a narrow range of irrational opinions. It is an iterative process, where people with opinions outside of that range are either socially excluded or coerced somehow into changing their opinion.

One element that characterizes “groupthink” is the lack of innovation, independence or creativity in the so-called “group” being coerced into one strain of thought. This was initially used to describe policymaking, with one of the most famous case studies involving the policy process behind the Bay of Pigs invasion.

The issue is not that a group of people made a decision — that is inevitable in any policy outcome. If that were the issue, then groupthink would lose all meaning because any collective activity would be called groupthink. Instead, it was used to describe the internal social process among those making the decision to quash disagreement and data that contradicted their desired outcome.

This often requires value-setting priorities that place group cohesiveness ahead of independent thought, insulation from the group, and a leadership mechanism that isn’t impartial.

None of this applies to the Consensus Board, which does not operate with a leader, does not isolate its contributors and does not punish people with independent thought. In fact, many of the people whose boards contribute to the Consensus Board project are delighted to receive a version of the below message from me when I incorporate their board:

Many draft analysts who receive this message use it to explain who “their guys” are and why they love or don’t love a prospect. This is not a mechanism for getting them to conform to the consensus but to celebrate their perspective on how it differentiates from the consensus.

This independence is important — studies on the idea of “wisdom of the crowds” have found that it works best when the contributing members do not confer on their agreed-upon conclusions. This independence was one of the four essential pillars when the concept was introduced into the public sphere.

Anyone calling this exercise groupthink does not understand the concept of groupthink or the nature of the Consensus Big Board project.

Can the Consensus Board Grade Picks?

In a sense, anything can grade picks. Why not?

But for the purposes of this piece, we want to ask if it’s providing any information worth digesting. The evidence suggests it does. First, we can talk about people who are not affiliated with Wide Left and what they’ve found about using the Board for evaluation purposes.

Timo Riske at PFF performed an analysis of how the Consensus Big Board performed when compared to NFL draft order when predicting player performance, as measured by PFF Wins Above Replacement.

His research found that the Consensus Board was nearly as good as the NFL, despite a few significant disadvantages.

The first disadvantage is pretty obvious: the NFL has control over player outcomes, and the board does not.

The NFL knows how they plan to use players and has an incentive to develop players they draft. Scheme fit is big, and a generic board can’t accommodate all of the synergies of specific teams, coaches and teammates. A team prioritizing outside-zone-style blocking will place athletic guards higher on its board and eliminate slow-footed blockers from consideration.

Even if the Consensus Board nearly perfectly identified talent, one would expect to see higher snap counts for higher draft picks early in their rookie contracts just because of these elements — scheme fit and investment cost. And snap count helps contribute to measures like WAR.

But that’s a small reason. Because PFF’s data relies on WAR, a statistic that depends on a player’s contributions to winning, the measure — and the NFL — overindex on quarterbacks compared to the board. Correcting for that might eliminate the NFL selection process's advantage in WAR-dependent metrics entirely.

Note that this doesn’t necessarily mean that the public is bad at evaluating quarterbacks, it just means that the big boards are not necessarily designed with the intention of maximizing wins, as they are supposed to rank players by talent. The NFL draft, however, has only that one goal: maximizing wins. And that’s why quarterbacks are drafted at the very top.

Another big reason the NFL should have a larger advantage than it seemingly does has to do with the intangibles or invisible elements of a player evaluation. That can be something as minor as locker room leadership or as major as a degenerative medical condition that limits the career lifespan of a prospect.

The evaluators building the boards that end up contributing to the consensus generally don’t know if the stinger a player suffered their sophomore year contributed to a long-term nerve condition or was a minor nothing injury. The NFL does.

Without medical information or other factors like work ethic and practice habits, draft analysts who rely on publicly reported player information — all without access to character profiles, psychological data or player interviews — are at the mercy of players who may not even like playing football.

In addition to all of that, NFL teams have more time and resources — they invest in training their scouting staff, sending them to games across the country and spend more than 40 hours a week per person nailing down their process. Many of the analysts who contribute to the board have a keen eye but are fighting an uphill battle to reach the level of expertise that time and training can provide.

Riske’s approach isn’t the only one that has confirmed the value of the big board in these applications. One may argue with PFF grades – fairly so – but even if we can all agree that they are directionally correct, they aren’t gospel. The thing is, nothing really is and we can all disagree on player performance and value.

One alternative perspective is to see how the NFL itself handles these draft picks. That’s why Jason Fitzgerald’s study into second contract value for draftees is so valuable here. He also found that the Consensus Big Board was about as good as the NFL itself at rank-ordering players.

On our end, we published a deep dive two years ago that looked at every analyst we had data for and at the Consensus Big Board, comparing their rankings and the NFL draft to player outcomes.

Last year, we added 2022 data to that work, and it, unsurprisingly, continued the trend.

What About “Steals” and “Reaches”?

The data analysis performed for the 2024 grading piece tells us that NFL performs a little bit better than the Consensus Big Board when looking at all 700 or so picks in the first three rounds of the NFL draft from 2016 to 2021.

But that advantage comes almost entirely from small gains made on even value picks – things we wouldn’t call steals or reaches, like when the Bengals drafted the number two player overall at number one when they took Joe Burrow. That’s not really a reach, and we can craft our analysis to exclude those cases.

The NFL achieves tons of tiny wins by being a little closer to the correct rank-order value for picks where the board and the NFL don’t really disagree. The math I performed last year came to the conclusion that the NFL won about 52 percent of those even-ranked matchups when it came to assessing player value.

The picks with substantial disagreements were more interesting. Over the past two years, we’ve been adding data to this exercise.

In 2023, the biggest misses by the consensus board don’t actually seem like huge misses; the Consensus Big Board regarded Jalen Carter as the third-best prospect in that draft when his actual draft position of ninth seems closer to his actual value. Dawand Jones (40th) and Kelee Ringo (38th) were pretty big misses. The draft was also correct to value Jack Campbell (ranked 45th, drafted 18th), Darnell Wright (ranked 24th, drafted 10th) and Jahmyr Gibbs (ranked 26th, drafted 12th).

On the other hand, the board seemed more correct on Darnell Washington (ranked 31st, drafted 93rd), Brian Branch (ranked 16th, drafted 45th) and Joey Porter Jr. (ranked 12th, drafted 32nd). It identified the draft overvaluing Anthony Richardson (13th vs 4th), Juice Scruggs (175th vs 62nd) and Brodric Martin (260th vs 96th).

Let’s first take a look at the results in the first round, when the Consensus Big Board either identifies a big steal or a big reach, ignoring those picks where the value is within 15 percent of the pick capital.

80 percent of reaches in the first round fail to meet their pick slot value, which is astounding. In a surprising reciprocity, nearly 20 percent of steals fail to meet their board rank value. So this tells us we should pay much more attention to reaches than to steals.

That makes sense — it takes just one team to misevaluate and reach for a player. But a steal requires multiple teams to come to the same conclusion, making it less likely that someone made a mistake.

But there was a very small sample of steals and a very large sample of reaches. That’s what we would expect; there are very few players to “steal” in the first round because high-ranking players are supposed to be selected there.

What happens in the second and third rounds? Adding in 2023 data made the consensus board worse than the 2016-2022 results, but not enormously so.

It seems as if both the Consensus Big Board and the NFL are “overconfident” when they determine they know a player is substantially more talented than where the other has ranked them. And the NFL’s advantage in tailoring their schemes, isolating team needs and fit, allows them to win at the margins when differences in evaluation don’t really matter.

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The fanatics who dig deep into draft analysis — those dedicated enough to follow the Consensus Big Board — often find that Day 2 is as exciting as Day 1. Teams pounce on the astounding value left on the board at the top of the second round and define their draft classes.

The headlines of draft classes are built on the first round, but the strength of classes are created in the second and third rounds. People remember the Vikings’ 2015 class not for Trae Waynes, but for Waynes, Eric Kendricks, Danielle Hunter and Stefon Diggs.

The Eagles built their 2024 Super Bowl team off of falling value. Landon Dickerson, Nakobe Dean and Cooper DeJean were all considered first-round talents who were drafted in Day 2, while other key players represented falling value — Dallas Goedert, Moro Ojomo and Josh Sweat all were rated as significant steals by the Consensus Big Board.

The 2017 New Orleans Saints draft class is remembered not for Marshon Lattimore but for Lattimore alongside Alvin Kamara, Marcus Williams, Ryan Ramczyk and Trey Hendrickson.

Conversely, the Chiefs’ 2017 class was outstanding in terms of total value because of Patrick Mahomes (and Kareem Hunt), but no one really calls it a good draft class so much as an outstanding pick.

So as teams turn draft classes from good picks into good hauls, who are the best candidates to do so? And can we always identify them?

Top Remaining Day 2 Players

Some of the top remaining players who were projected to go in the first round are easy to explain. Both Jermod McCoy and Avieon Terrell have injury concerns.

McCoy missed the 2025 season because of a torn ACL. Players who miss their final college season because of an ACL tear but are ranked in the mid-teens tend to go in the first round regardless — Todd Gurley, Kyle Fuller and Dominique Easley are good recent examples. In a way, Jeffery Simmons, who tore his ACL after the college season, would also count.

Instead, there are deeper concerns about McCoy. The need for a second surgery that would take him out of the 2026 season and a “cartilage defect” make his injury issues more serious — a problem genuinely different and distinct from his ACL tear, possibly a degenerative cartilage issue.

On top of that, his recovery timeline could have put him in play near the end of the season, but he still didn’t play in late November or early December, which warrants some caution.

Terrell, ranked slightly lower than McCoy, is a more interesting case. He has an ankle injury concern from 2024 (during the spring) and a quadriceps injury that forced him to miss a game in 2025, but was regarded as “durable” by Brugler in his draft guide. His size (5’10”) on top of his injury reaggravation — a hamstring injury that delayed his workouts with NFL teams — could have put some NFL teams off.

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Notably, Tyleik Williams injured his hamstring in the pre-draft process and was still drafted in the first round by the Detroit Lions.

Players like Emmanuel McNeil-Warren and Kayden McDonald are not particularly difficult to explain at this point; neither is considered an outstanding athletic performer at their position, and there usually needs to be some kind of athletic standout for a safety or nose tackle ranked in the mid-20s by the Consensus Board to go in the first round.

Examples include Budda Baker, Grant Delpit, Trevon Moehrig, Brian Branch, Landon Collins, Andrew Billings, A’Shawn Robinson and Eddie Goldman. These kinds of falls happen within the first round, too. Safeties Malik Hooker, Kyle Hamilton, Minka Fitzpatrick and Derwin James all fell substantially further in the draft than their Consensus Board rank would have suggested.

Denzel Boston was probably the victim of a relatively stacked receiver group; it is unlikely that many draft analysts would refer to this as a “strong” receiver class because the top-end talent doesn’t match the pre-draft evaluations we’ve seen for other receiver classes.

Those top-end receivers included (for better or worse) Corey Davis, Sammy Watkins, Odell Beckham Jr., Mike Evans, Ja’Marr Chase, Jaylen Waddle, DeVonta Smith, CeeDee Lamb, Garrett Wilson, Jerry Jeudy. This draft doesn’t seem to have any players who meet those lofty, top-ten ratings from experts. But they did have a lot of Top-32 receivers.

For Boston to have gone in the first round, he’d have needed to have been the sixth receiver off the board. Since the historic 2014 receiver class (only five were drafted in the first round then, too), we’ve only seen six or more receivers drafted four times out of 12, or 33 percent.

It would be difficult to make the argument that this class had the same regard as the meteoric 2020 class, the 2022 class or the 2024 class, which saw an astounding seven receivers drafted in the first round. You would be hard-pressed to find an analyst that favorably compared Carnell Tate, the top receiver off the board this year, to Marvin Harrison Jr., Malik Nabers or Rome Odunze.

There probably does not need to be much ink spilled over the first-round absences T.J. Parker or Colton Hood, who were just barely in the cut as Top-32 players on the Consensus Big Board. Parker’s 2024 was more productive than his 2025 (19.5 tackles for loss and 11.0 sacks, compared to 9.5 TFLs and 5.0 sacks) while Hood was just a one-year starter.

Refer a friend

Of these players and those at the top of the “second-round” grade group, the most interesting could be Terrell, Parker, C.J. Allen, Zion Young and D’Angelo Ponds. Terrell and Parker already have reasonably large variances in their rankings (generally, Terrell has ranked from 19th to 35th while Parker has ranked 25th to 39th) but so do Young and Ponds.

Young has off-field concerns. Brugler noted a DWI charge in December of 2025 (along with other vehicle violations) and an assault charge in 2023 for a post-game altercation with seven other Michigan State players.

Ponds is 5’8”.

Well, 5’8 5/8”. The shortest cornerbacks who have most recently logged at least ten starts are Darious Williams (5’9 5/8”), D.J. Reed (5’9 1/8”), Tavon Young (5’9 1/8”), Duke Shelley (5’8 5/8”) and Amik Robertson (5’8 3/8”). None of these players were drafted before Day 3, if they were drafted at all.

Ponds is a truly impressive player, but traits win the day in the NFL. Robertson generated 16 pass deflections and five interceptions in his final year of college, including two interceptions returned for a touchdown, and still couldn’t get drafted in Day 2. This was despite Robertson shutting down third-round pick Devin Duvernay and a few tall receivers, like 6’3” Obi Obialo, 6’3” De’Corian Clark and 6’5” Collin Johnson.

Nevertheless, Ponds’ performance was good enough for at least five analysts to rank him inside the top ten.

Does any of this matter?

How Often Do Day 2 “Steals” Become Good Players?

We know that the Consensus Board is generally pretty good at identifying talent and that it can compete with the NFL over a long time span when it comes to finding players that will make an impact.

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It is 1am on Wednesday morning, and I have just completed making the picks for my only mock draft of the cycle after three hours of manic research that has overwritten a fair amount of my eight months of slightly less manic theorizing.

It is now 11am on Wednesday morning. I fell asleep writing the blurbs for these picks, and naturally, I have been exposed to even more information that forced me to change a handful of picks.

But, considering I tied for 65th of 174 mock drafts submitted to The Huddle Report in 2025, my first year invited to the competition, such a cram session was necessary to inform some of the bigger swings I’ve taken in this mock.

If I look stupid on Thursday, that’s cool with me. It’s part of the fun of the cycle — which is important, because the lack of obvious top-end talent in this draft has mostly resulted in it feeling like the longest year of most analysts’ lives. But given most mock drafts are exercises in educated guessing anyhow, I feel as confident as one can feel roughly 30 hours before the draft begins on Thursday.

Note that all trades are based on the Rich Hill chart, which is what the mock draft simulator operated by Underdog uses.

Here are the picks.

1.1 Las Vegas Raiders: Indiana QB Fernando Mendoza

Thank you to the Raiders, Mendoza, and Tom Brady for making this by far the easiest selection of the night. Mendoza was really only challenged for QB1 by Oregon’s Dante Moore, who decided to head back to school and try his luck in 2027. Las Vegas will milk the new 8-minute timer, because the NFL tells them to, so don’t worry if you show up to your buddy’s draft party 10-15 minutes late on Thursday.

1.2 New York Jets: Ohio State EDGE Arvell Reese

Basically everyone on the national insider circuit has hammered David Bailey as the pick here under the pretense that Bailey is a safer player for a head coach that is surely on the hot seat after a disastrous first season. But almost every local reporter has remained steadfast that the pick is Reese, who does not have the low floor people seem to be making him out to have. It’s worth noting that the national media struggled to pin GM Darren Mougey down this time last year: most national reporters had the Jets selecting Tyler Warren rather than Armand Membou a season ago.

1.3 Arizona Cardinals: Texas Tech EDGE David Bailey

Rumors of a trade here have been centered around the Saints at 8 and Chiefs at 9, and I do believe that Arizona would love to trade out of this pick and collect an offensive lineman at more commensurate value a bit later. But Jeff Duncan of Nola.com, one of the Saints’ preeminent reporters, has said that a trade up seems unlikely. Sources connected to the Chiefs have suggested that a trade to 3 would be for Reese if the Jets select Bailey. I’m willing to buy that owner Michael Bidwill wants to take Jeremiyah Love to put butts in seats, but GM Monti Ossenfort has drafted a premium position with all 7 top 50 picks during his tenure with the Cardinals. Bailey is on the older side of those 7 players at 22.65 years old, but with no trade materializing here, I think Arizona would rather take Bailey than reach for Miami offensive lineman Francis Mauigoa or swerve off tendency and take Love.

1.4 Tennessee Titans: Notre Dame RB Jeremiyah Love

Tennessee seems to be hoping and praying that Arizona will take Love so that they can have whichever defensive player falls to 4. Recent smoke about Ohio State linebacker Sonny Styles and receiver Carnell Tate feel like complicating the picture for the sake of doing so more than legitimate interest. Getting what some see as the best player in the draft at a position that moves uniforms when you just did a brand refresh will surely be appealing to all parties involved in Nashville.

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1.5 New York Giants: Ohio State LB Sonny Styles

The Athletic beat reporter Dan Duggan has gotten 3 of the Giants’ first 4 picks correct in back-to-back years and has stayed on Styles despite recent movement towards his teammate, safety Caleb Downs. GM Joe Schoen, who admittedly has a questionable amount of power remaining after the team hired John Harbaugh as head coach, gravitates more towards elite athletes in the first round and Downs is usually described as a good-not-great athlete. Styles, on the other hand, was the fourth-most athletic linebacker in the RAS database.

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Welcome to the landing page for the Consensus Big Board for the 2026 NFL Draft. As often as possible, I’ve tried to provide it free, without subscription, to as many people as possible.

To that end, this piece is free to everyone, as is the data.

The insights generated from the board, which include analyses such as who the most polarizing players are in the draft, the difference between evaluators and forecasters, and post-draft team grades, will continue to be subscriber exclusives. This page will serve as a hub for those pieces, so you can find them if you feel the need.

• Why Use This Consensus Board?

• Using the Consensus Board to Find the Most Polarizing Players in the 2026 NFL Draft

• Forecasters and Evaluators: What’s the Difference and Why Does it Matter?

• The Consensus Big Board Grades the 2026 NFL Draft

• Ranking the 2026 UDFA Classes with the Consensus Big Board

From two years ago:

• Which Draft Analysts Predict the Draft the Best? Who’s Right on Players? And is the Consensus Board any Good?

Even if those pieces don’t strike you as appealing, I would urge a subscription to keep efforts like this running; this project takes dozens of hours every year and many of the boards in use are proprietary and behind paywalls.

What Makes This Consensus Board Different?

There are, by now, a half-dozen or so consensus boards out there. In some respects, they are more useful than this one – many of them have been running throughout the season, giving us a good barometer for a player’s stock and giving fans a genuine look at the players they might want to pay attention to during bowl games.

They also happen to be more focused, with particular emphasis on big-media boards, preventing unorthodox and uninformed rankings from polluting the system.

But I believe there’s a lot of value in this board, too. Every year, I’ve been able to gather anywhere between 50 and 90 big boards to provide a larger survey on the industry’s feelings about prospects in the draft.

For more on that topic, check out the piece below.

This year, we’ve gathered over 100 boards and anticipate having at least 115 by the time the draft rolls around.

We’ve been able to use the size of that data to leverage unique insights, like the ones described above. Using just ten boards wouldn’t give us a meaningful understanding of variance in player rankings and they don’t have the ability to split boards by type.

The boards used in this ranking are all updated in the month of April — some consensus boards take the average of all boards, including ones from the same analyst multiple times over many months — something I try to avoid.

On top of that, there’s also value in the approach I take to the board, which isn’t to average out the ranks across the industry but to average out the implied player values. There is admittedly more transparency in the approach that averages out player ranks across big boards, but it has the unfortunate side effect of suggesting that the difference between 145th and 147th is the same as the difference between 1st and 3rd.

In the NFL draft, that’s not how player ranks or player value works – the decision to rank a player first is a big decision; it signifies that teams should be willing to move heaven and earth to acquire that kind of player. That’s not the case at 145th.

Often, players ranked between 145th and 147th aren’t all that different. But the differences between the two are treated as the same in most consensus methods.

There’s also typically no accounting for player absences in boards. We can demonstrate this using an example, assuming we have 100 analysts ranking players 1 to 100. Not every analyst will rank the same 100 players and most leave players on the cutting room floor that others have decided to put in their top 100.

In this example, Player A is ranked by 50 boards as the 75th-best player in the draft and unranked on the other 50. Player B is ranked by all 100 boards as the 76th-best player. Most approaches to consensus boards will rank Player A as the better player, even though the average opinion on that player is that he is worse than Player B, not better.

This particular board, with its points-based averaging approach and varying penalties for absences on different-sized boards, avoids that problem, at least partially.

The data below is downloadable using a link at the bottom (labeled “Get the data”) and the 300 players are separated into three 100-player pages; an arrow in the upper-right can help you navigate between them. The table is also searchable and sortable.

Over the next week, the table will be updated to include ranks from two different groups of analysts (“Forecasters” and “Evaluators”) as well as the overall rank by consensus. At the moment, it only shows the consensus rank. It will also be updated in the coming days to include rank-adjusted variance, a score that tells us how polarizing the players in the draft are.

If you want a printable Google Sheet, click here (this will also be updated until the day of the draft).

Data Visualizations

Below we have a few data visualizations of the Consensus Big Board. Hopefully, these will help you understand some of the concepts we’ve been discussing, especially regarding variance. The first chart is a rank-adjusted variance chart, plotting players by their Consensus Big Board rank and their rank-adjusted variance, so you get a sense for how much disagreement the player drew relative to where they are on the big board.

The rank variance between Fernando Mendoza and Peter Woods is comparable when accounting for the fact that Mendoza ranks first and Woods ranks 26th, but the absolute range of rankings on Mendoza (generally first through seventh, with the outliers hitting 35th) is much narrower than the absolute range of rankings for Woods (generally 21st through 36th, though outliers hit between 3rd and 95th).

There’s another way to visualize the distribution of ranks, and this one makes no adjustment for rank. In order to prevent ourselves from focusing on outliers, we’ll use a box-and-whiskers plot; the middle line of the box is the median and the outside edges of the box are the 25th and 75th percentile values. The “whiskers” of the plot will give us the complete range of typical outcomes, with some dots representing extreme values outside of the typical range.

Below covers the top 100 players in the draft.

What if you wanted to know where positions might be scarce or abundant in the draft? We also have a positional distribution chart.

The Consensus Big Board project includes over 120 analysts in its annual player-ranking survey. With that, we can not only find out what the aggregate opinion the players in the 2026 NFL Draft, but also which players are most polarizing or how different approaches to NFL draft analysis produce different player rankings.

The broad disagreement about players is pretty easy to understand, and we've already broken this down.

But “different approach” might be tough to quantify. In this case, we mean that there are broadly two types of player rankings to explore. The decade-long experience we have in collating boards has led us to conclude that the two “types” of big boards can yield different insights into player evaluation.

The shorthand we’ve used is “forecaster” versus “evaluator” boards, though, like many things, the distinctions are a bit arbitrary, and there’s always been a fair degree of evaluating done by “forecasters” and a good amount of “forecasting” done by “evaluators.”

The Difference Between Forecasters and Evaluators?

The two categories have been characterized by others as “big media” versus “bloggers,” though that’s a bit antiquated. Certainly, there are independent media analysts with large audiences, but the “us vs. them” mentality is appealing.

It’s not entirely accurate, but it does carry some essential truths. Evaluators — “the little guys” — are draft analysts who primarily rely on publicly available information to craft their rankings and produce their analysis.

That doesn’t mean they’re incorporating public opinion into their rankings, but rather that they might use broadcast footage, college All-22 film, media reports on player character and injury flags and so on. The NFL Combine and public pro day reporting also provide them with useful data.

Forecasters — those employed by legacy media or with the kinds of resources afforded to legacy institutions — might be characterized as analysts who not only use public data but also difficult-to-access data, sometimes data meant to be reserved exclusively for NFL teams. That comes not just from sources inside front offices and agents but also through a network of relationships with scouts and college coaches across the country.

That means access not just to unique injury information and deeper character data but quite possibly tests like the psychological exams that teams conduct, cognitive assessments like the S2, as well as other physical checks, like conditioning, flexibility and VO2 max scores.

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As an example, there have been reports about Caleb Downs’ knee that have been publicly debated and refuted by Downs and his team, yet have persisted in the background of his evaluation. Less contentiously, there have been late-breaking reports that Jermod McCoy has injury concerns that could keep him out of the 2026 NFL season.

The degree to which these concerns might impact their NFL careers is unknown to everyone, but the best guesses belong to NFL teams that have had the ability to directly evaluate both players and have discussions with the medical and training personnel who worked with them.

Forecasters are generally analysts who might have access to the NFL’s information on those players and can use that to order their boards. This is true for injury information we have access to, like Downs and McCoy, as well as for players who might have injury concerns we don’t know about.

In addition, they may have more complete “character” information, such as how players are perceived by teammates, their leadership skills and the risk factors that might affect their locker-room presence or availability and so on.

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This is a double-edged sword, of course. Teams or agents may feed them this information for a particular reason or exaggerate the degree to which these concerns are legitimate. Forecasters need to be careful when assessing privately held knowledge, as they may be subject to draft-day smokescreens and the like.

They have to make judgment calls about what information is genuinely important and what might be a red herring. And they’re not always right.

The history of Consensus Big Boards has shown this distinction to be valid. Boards tagged as Forecaster boards have a very tight spread, and there’s a low variance in the rankings of players across that group year over year. Typically, when a player slides in the draft, Forecaster boards have that player lower than Evaluator boards — though that’s not always the case; last year, Forecasters were substantially higher on Shedeur Sanders than Evaluators were.

What Happens When They Disagree?

Surprisingly, we found that disagreement between the two boards is not particularly meaningful, even though one board is better at predicting the draft order — typically a quite powerful signal of player talent.

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In 2016, then-Washington State head coach Mike Leach simplified his approach to quarterback development for media members following a practice. As the co-founder of the Air Raid offense believed, accuracy was the most important trait a quarterback could possess.

“All of high school, he’s not accurate, now all of a sudden, you’re special, you’re going to make him accurate. After all of college, he isn’t accurate; you’re going to make him accurate. I haven’t seen that happen,” Leach said. “I’ve seen guys improve, but they just don’t become accurate. … You can go get the shortstop and teach him to play quarterback easier than you can make someone accurate.”

While Leach does have a point, he is partially responsible for some of the biggest reasons why quarterback evaluation in the NFL Draft process is a mixed bag.

In college football, the wild diversity of schemes makes it difficult to pinpoint what quarterbacks can actually do in pro-style offenses. While most NFL offenses will operate under center, college offenses are the byproduct of what a quarterback likes to do. As a result, offenses that run Air Raid concepts, like Leach, will have no issue spamming their core concepts, like Y-Cross, until the game is over.

While evaluating a quarterback based only on those concepts isn’t the best way to find your favorite team’s next franchise quarterback, there is often additional insight available from which routes or concepts quarterbacks pick as their favorite or believe they struggle with.

Take Y-Cross, for example. The concept prides itself on quick progressions, but the combination of a deep over and post on the playside means there are NFL throws against certain coverages. If a quarterback likes throwing the concept and can showcase a mastery of working through it with accuracy, there will be translatable traits throughout the play.

During the pre-draft cycle, Wide Left spoke to multiple top quarterbacks to find out which routes they enjoyed throwing and which concepts they believed they needed to work on heading into the NFL.

Texas Tech QB Behren Morton

Between his time at Eastland (TX) High School and Texas Tech, Behren Morton has spent more time in the Air Raid than any quarterback in this year’s draft.

Even with four offensive coordinators at Texas Tech, Morton hasn’t deviated from Air Raid concepts, with the Red Raiders running their entire offense out of shotgun under head coach Joey McGuire. Unsurprisingly, Morton’s favorite route concept to throw is a staple in any offense that runs concepts from the pass-heavy scheme.

“Y-Cross kind of beats everything. You can beat man; it can beat cover 2, cover 3, and cover 4. You can beat all-out blitz,” Morton said. “When I hear Y-Cross in the playbook, I’m fired up.”

While Pro Football Focus does not have Y-Cross as an available passing concept, it does credit Morton as 14-of-20 for 305 yards and two touchdowns on crossing routes in 2025.

Since Morton had full control of what’s called at the line of scrimmage, he doesn’t believe there was a route concept that gave him trouble. However, at the East-West Shrine Bowl, Morton had to adjust to playing at a slower pace than he was used to in college.

“I’ve never huddled in my career. In high school, I ran the Air Raid. I’ve had four different coordinators at Texas Tech; we were all in Air Raid, taking victory formation [as] shotgun snaps, never under center,” Morton told Wide Left during Shrine Bowl. “This week has been awesome as far as getting to go under center and getting to know we don’t have to play at a two-minute pace, we can slow things down, and we can really operate.”

Texas Tech LB Jacob Rodriguez (former Virginia quarterback)

Before he switched to defense, Rodriguez was a standout quarterback at Rider High School in Wichita Falls, TX, impressing even his future college teammates with his ability to throw the ball.

“He really threw the deep ball well. He was really powerful, obviously, as you know, but he could really spin it. He was a dual-threat kind of guy,” said Morton. “My roommate at Texas Tech was his tight end, so I went to watch him in the fourth round when they were playing in the playoffs. I was like, ‘This dude is legit.’ He can spin it, and he can get the ball out quick, but he can also put his face to your chest and run you over.”

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One of the wonderful elements of aggregating over 100 big boards is the ability to figure out which players are drawing the biggest disagreements across all of the analysts, not something that is as easy to figure out with 10-12 player rankings. The backlog — over a decade — of data allows us to also perform some contextual calculations that can smooth out our process and give us more granular results.

Because we have this treasure trove of data, I’ve been able to modify the approach to our “polarizing players” calculation that makes the tuning process a bit more accurate.

Often, players who provoke the most discussion can seem like the most polarizing prospect in the draft, but are not. This year, for example, the most polemic discussions seem to surround Ruben Bain Jr., Makai Lemon and Blake Miller. But analysts generally don’t disagree all that much about where those players should slot on their boards.

As an example, an early version of the Consensus Big Board in 2014 found that Jadeveon Clowney, who was subject to constant questions about his work ethic and production, was near-universally considered the top prospect in the draft. He was divisive in discourse, but analysts ultimately did not care about narrative fodder – he was one of the least polarizing players in the draft.

This has been the case for a number of top prospects over the years, though not quite as emphatically so as with the Clowney example. Divisive conversations surrounding Ed Oliver, Jamal Adams, Jerry Jeudy, Will Fuller and DJ Moore didn’t materialize into a real divergence in rankings.

On the other hand, some players drew dramatic disagreements between analysts without much hot-take style press on how they’d fail or succeed. These include players like Jonathan Allen, Keanu Neal, John Ross, Austin Jackson, Jamin Davis and Charles Harris.

Last year, we had an unusually polarizing top-32, with Cam Ward, Tyler Warren, Will Johnson, Tetairoa McMillan, Jalon Walker, Malakai Starks, Mykel Williams, Shedeur Sanders and Nick Emmanwori appearing as polarizing members of the class — in a typical class, we see four players from the top 32 hit the most polarizing players list, not nine.

Many of those players were the ones we saw leading discussions about their true talent level, meaning the discourse matched the reality of analyst rankings. But players like Will Campbell — despite endless conversation about their NFL role and fit — didn’t actually draw too much analyst disagreement. So too with Travis Hunter, who was a near universally ranked number one player despite conversation about his best NFL position.

Does It Matter if a Player is Polarizing?

Two years ago, we evaluated whether more polarizing players were set up to succeed or fail more often than their less-polarizing peers with similar consensus ranks.

We’re reworking that list with our new historically-adjusted formula and adding players form the 2022 and 2023 NFL drafts to get a better sense of what it means when a player is more polarizing than their peers.

The first step, of course, is to figure out the variance in rankings across analysts. But there’s a bit of an issue. Players ranked in the 80s or 120s are more similar in value than players ranked in the top five or top 30.

Small differences in evaluation will result in larger differences in rank for players further down the board.

Analysts know that they are disagreeing sharply with one another when they say a player is not worthy of a top-five pick and instead worth a top-ten pick — but not when they say that a Day 3 player should be just barely in or out of the Top 100.

So, we introduce a modifier to the initially calculated variance that, over multiple drafts, functionally reduces the correlation of “rank” and raw variance to zero.

The output number is basically meaningless, so I wanted to transform it into something pretty recognizable. As always, I’ve been inspired by the analysts at Pro-Football-Reference, who themselves took inspiration from baseball.

In their era-adjusted “index” scores for variance statistics, they reproduce the method that we get for OPS+ and other “plus”-type stats from baseball. Essentially, 100 is average, while every 15 “points” is one standard deviation.

Those unfortunately familiar with IQ scores might recognize this system – it’s essentially the same.

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The Most Polarizing Players of Past Drafts

With all of that context in mind, we can check out the most polarizing players from the 2016 to 2023 drafts.

There are a few observations we can make from this list. The first is that reaches seem much more likely with extremely polarizing players, as one might expect. It also seems that, with these polarizing players, the NFL does a better job of assessing overall talent than the consensus board.

For players where disagreement was substantial (Josh Allen, Carson Wentz, A’Shawn Robinson, Dalvin Cook, Daniel Jones, Anthony Richardson and Sam Darnold), teams generally reached on the player, though it should be noted that the vast majority of these players were quarterbacks, which teams are generally justified reaching on versus the consensus board.

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Wide Left will be publishing its Consensus Big Board soon, aggregating data from over 100 analysts. That piece, like this one, will be free to all readers.

Back in 2015, when I started the Consensus Big Board project, there weren’t many resources that gathered together the accumulated wisdom from draft watchers. Over ten years later, that’s changed.

There are about a dozen places to find a consensus board, including multiple former employers of mine, as well as more open fora like Reddit or social media platforms. On top of that, we have access to other methods for aggregating opinions on player prospects in the draft, including the aggregated mock positions from GrindingTheMocks and the NFL Mock Draft Database.

Is there any serious difference between them?

To some extent, we explored this two years ago when discussing the different consensus boards.

Why come to Wide Left when all of these other options are available?

I wanted to answer that question with some rigor, so I contacted Benjamin Robinson, who runs Grinding the Mocks, and we worked together to test the boards. What I found might not be surprising. But first, a primer on how these boards are constructed.

Why Are These Rankings Different?

There are essentially four categories of player rankings I’ll be looking at: the limited-rank-average model employed by most consensus boards across the web, the mock draft aggregation produced by Robinson, the expanded-value-average model for Wide Left’s board, and the blended board/mock model employed by the NFL Mock Draft Database.

Most consensus boards take rankings from 10 to 16 or so analysts and average the ranks. So, Fernando Mendoza might be ranked {1, 1, 1, 1, 1, 2, 2, 3, 3, 4, 4, 5, 6, 7 and 8} by 15 boards, his average rank would be 3.27. Arvell Reese might be ranked {1, 1, 1, 1, 1, 2, 2, 2, 3, 3, 4, 4, 4, 4 and 5} for an average rank of 2.53, so he would be ahead of Mendoza. In this exercise, Jeremiyah Love ranks {1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 4, 4, 4, 5 and 6} with an average of 2.80.

So, an averaging approach would have those players rank Reese first, Love second and Mendoza third. Easy to understand, intuitive, and gets the broad picture across easily.

That might tell us who experts think are the best players in the draft, but it doesn’t tell us very much about where those players might go.

Grinding the Mocks focuses primarily on mock draft data (with a small amount of big board data) to construct a regression model that is tuned to better reflect expected player position. As the model gets more robust, it can be used to construct probability ranges for players.

This year, Robinson’s data projects Mendoza to go first (an “expected draft position” of 1.3), Reese to go (generally) second (EDP of 3.0) and Love to go fourth (EDP of 4.7).

Robinson’s model weighs more recent and more accurate mock drafts heavily, a method meant to take advantage of the most up-to-date information we’ve learned about teams or prospects, which may better tell us what might happen on draft day.

NFL Mock Draft Database’s “Consensus Board” also focuses on grabbing data from mock drafts as well as big boards, using over 1,000 mocks and nearly 150 big boards gathered throughout the year to produce a composite ranking that blends the two approaches.

There is also a decay function in the NFL MDDB, with no boards over four months old included in the calculation at any time and with recency weighting, as with Robinson’s approach.

Wide Left’s approach ignores mock drafts and assigns values to each player based on their rank from each analyst. Some consensus boards (like the Athletic’s) do the same, assigning 100 points for the top-ranked player on a board, 99 points for the second-ranked player and so on.

The value calculation Wide Left uses is modeled after various trade charts (such as the Jimmy Johnson, Rich Hill, Fitzgerald-Spielberger, and Chase Stuart charts), assigning significant value to the first overall rank and much less to the 100th-ranked player.

This way, the differences between players are better captured; assigning a player a top-ten rank suggests that the player is much more talented than the 32nd-ranked player, but assigning a player a rank of 101st is not that different from designating them as the 132nd-ranked player.

A logarithmic decline in value can capture changes in rank differences in a way that the average rank value cannot. In order to reduce the impact of outliers, Wide Left also uses the “interquartile mean” of all the values assigned by each analyst.

That means tossing out the values in the top and bottom 25 percent of the range and averaging the middle 50 percent. Then, to break ties, the outliers are reintroduced with a much lower weight.

In the above example, with Reese, Love and Mendoza — where Reese ranks first, Love second and Mendoza third by a simple average — Mendoza finds himself second, not third, because his outlier ranks of 7 and 8 are thrown out.

Not only that, the value of having that many first-overall ranks exceeds the value of the number of second-overall ranks Love receives.

Later in the draft, we find quite a few players ranked by some boards and not others. How consensus approaches deal with absent players in the rankings matters.

Different top 100s will have a different spread of players, typically encompassing a universe of 120-140 players.

A good way to understand the impact of failing to account for player absences in boards is a simple example. Let’s assume we have 100 analysts ranking players 1 to 100. We know that not every analyst will rank the same 100 players; most leave players on the cutting room floor who others have included in their top 100.

In this example, Player A is ranked by 30 boards as the 75th-best player in the draft and is unranked on the other 70 boards. Player B is ranked by all 100 boards as the 76th-best player. Most approaches to consensus boards will rank Player A as the better player, even though the average opinion on that player is that he is worse than Player B, not better.

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Wide Left’s consensus board, with its points-based averaging approach and varying penalties for absences on different-sized boards, avoids that problem (at least partially). There is a bigger penalty to a player left off of a 500-player board than off of a 100-player board, and the value calculations reflect that clearly expressed preference from the analysts.

There is also a sample advantage when using 80-plus boards over 12-16 boards and it seems to play out when we look at outcomes.

OK, So Which Board is Better?

Trying to determine which board is better depends on what you’re trying to accomplish. In general, we rank players for two reasons: 1) to figure out where they’ll go in the draft or when they will no longer be available and 2) to figure out which players in the draft are most likely to succeed.

Predicting the Draft

For that first exercise, we can determine the average pick distance each board has from the NFL’s actual selections. For the averaging consensus board, I used the rankings I’ve gathered from legacy media and well-read draft analysts over the years, picking between 12 and 16 boards, depending on which ones were available. This meant grabbing the rankings from CBS Sports, The Athletic, various NFL.com boards, ESPN and so on.

Grinding the Mocks does the best job of giving us insight into where a player will fall in the draft. Using that as a guide to determine whether a team was right to trade up or to take a shot and reach instead of trading down seems like an appropriate use case.

The NFL Mock Draft Database, despite using a very similar dataset, is an entire pick or more off from the Grinding the Mock’s approach throughout the top 100, which is a bit of a surprise. Nevertheless, it significantly outperforms Wide Left’s consensus board and the typical average-rank consensus board we see on the web.

The fact that the Wide Left consensus board outperforms the typical consensus board in the first round by a good margin is an interesting insight, though that advantage disappears heading into the second round or the top 100.

Predicting Player Outcomes

But, which should we use if we want to figure out which players are best. Given how good the NFL is at rank-ordering players through the draft selection process, wouldn’t the board best at predicting how the draft will fall be the board we want to use for that exercise?

Not necessarily.

The NFL draft market isn’t very liquid; teams don’t organize optimally to make sure that player value, need, and resources all line up. A team that needs a quarterback is going to reach, and trades are pretty rare. Teams, who are risk averse, would rather stay put and make a selection than move up or down the draft until there’s significant reason to move.

Using a combination of player grades, postseason honors, production and contract value, I’ve put together a crude ranking system to order the players from each draft class. It works alright; Dak Prescott ranks first from the 2016 draft class, followed by Jared Goff, Carson Wentz and then Jalen Ramsey – in part because quarterbacks are worth so much more than other positions.

Following that are Joe Thuney, Tyreek Hill and Hunter Henry. In 2017, the highest-ranked players are Patrick Mahomes, Deshaun Watson, George Kittle and Marlon Humphrey. In 2018, it’s Josh Allen, Lamar Jackson, Baker Mayfield, Mark Andrews, Quenton Nelson, Dallas Goedert and Jaire Alexander.

These rankings are by no means perfect, but they’re close enough to perform an analysis on how rank-ordering worked for boards and the NFL. Because we don’t have as much information on the performance of players from the 2024 and 2025 draft classes, they’ve been excluded.

Draft values and contract values both tend to organize themselves with exponentially increasing or decreasing values, so after broadly rank-ordering the players from the drafts, we can assign draft value to them.

That way, we can compare the implied value from the big boards against the produced value of the players who were selected and treat them like the logarithmic trade values used in the Wide Left consensus board rankings.

From there, we can see how close each board approach was to determining a player’s long-term outcome value.

In terms of projecting player outcomes, it doesn’t look particularly close; the Wide Left Consensus Big Board vastly outperforms the mock draft database and the average ranking approach in the first round, second round and beyond. The Grinding the Mocks database, perhaps by virtue of getting closer to NFL draft selections, comes in second in each of those value buckets.

The expansive nature of the Wide Left Consensus Board really shines on Day 3, where having data on over 800 players organized by perceived talent allows for more granular grading on players who end up going on Day 3.

Which aggregate board should you choose? It depends on what you’re looking for.

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[Editor’s Note: We asked James Foster to produce a mock draft with the draft just around the corner. In this draft, Foster projects five trades and eight defensive backs to go in the first round. Wide Left will have some of the most unique draft coverage in the NFL media world this year and Foster’s incredible, in-depth insights will be part of it]

With ten days left until the draft, these are my final predictions for the first round.

1. Las Vegas Raiders — QB Fernando Mendoza, Indiana

There haven’t been any indications that the Raiders are considering other options here. Mendoza is a sharpshooter with prototypical size and underrated athleticism. He made smart decisions and got the ball out on time in Indiana’s RPO-heavy scheme, but is unproven attacking the middle of the field and working to his second read from within the pocket.

2. New York Jets — EDGE/LB Arvell Reese, Ohio State

David Bailey currently seems like the chalk pick, but his questionable run support and redundancy with Will McDonald IV makes Arvell Reese a better fit.

I have Reese graded as an off-ball linebacker, but it’s much more likely that he plays edge in the NFL. In just 960 career snaps, Reese showed enough to earn first round grades at two positions. He’s an explosive athlete with a shredded physique - he looks like he was built in a lab to set the edge, take on pullers, or flatten blockers with speed-to-power.

In a very limited sample of pass-rushing snaps, he won with a long arm (3), cross-chop (2), bull rush (1), and power-to-speed (1), but 22/27 of his pressures and all eight of his sacks came within the first eight games of the year. While his resume is sparse compared to most first-round edge defenders, he wasn’t even practicing at that position in college. In a recent interview with ESPN’s Benjamin Solak, Reese revealed that he didn’t know the name of a cross-chop he won with in Week 10. It’s easy to imagine him improving dramatically with a single offseason of technical work.

3. Arizona Cardinals — EDGE David Bailey, Texas Tech

The Cardinals are in a tough spot and should be looking to trade down, but I couldn’t find any partners that made sense.

David Bailey is a top-tier linear athlete with the first step, arc speed, and hand usage to dominate the outside track. His success rate plummets when he doesn’t win immediately, however, as he struggles to bend through contact and lacks the upper-body strength and torque to break his opponent’s grip and transition to counters. Bailey’s fastball is overwhelming, but he’ll need to continue to develop his long-arm to maintain his snap-to-snap impact vs. NFL tackles.

4. Tennessee Titans — RB Jeremiyah Love, Notre Dame

Tennessee had just 35 explosive (1+ EPA) runs last year, which ranked 31st in the NFL. With the top two edge rushers off the board, they take Jeremiyah Love, upgrading the offense and avoiding the steep dropoff between RB1 and RB2.

Love has the patience, elusiveness, and breakaway speed to flip the field in one play. His average power through contact might reduce his efficiency as a singles and doubles hitter, but we haven’t seen a homerun threat of this caliber since Jahmyr Gibbs. In 2025, Love expanded his route tree and showed more composure and physicality in pass protection, proving himself as a three-down back.

5. New York Giants — LB Sonny Styles, Ohio State

The Giants take Sonny Styles, my highest-graded player in the 2026 class. Styles has the range and coverage versatility of a converted safety, and the instincts and block-shedding ability of a lifelong linebacker. He rarely misses tackles or run fits and processes at remarkable speeds for a two-year starter.

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The college pro day circuit has essentially concluded; by the end of March, 1700 players had completed at least one pro day workout, with more adding their pro days to the mix in early April. With that, we have more data on previously undiscovered gems.

The problem is that pro day workouts are often difficult to parse — not just because the workouts offer variable benefits depending on context, but also because pro days themselves have been mystified by the NFL's characteristically opaque nature.

Last year, Wide Left’s Alex Katson broke down how pro days actually operate and debunked a number of myths and misconceptions about them.

For this piece, I wanted to work with the research I had done several years ago about which workouts matter the most for individual positions instead of using composite athletic measures.

I have issues with measures like Relative Athletic Score, which I outlined two years ago. In that piece, I discussed preferring position-specific measures, disliked the compressing nature of eliteness (or lack-of-eliteness) in RAS, how size is accounted for and more.

I’ve done some back-of-the-envelope modeling to work on producing a position-specific measure, and though it isn’t perfect, it might be more helpful. From that piece:

Over the past 15 years, I’ve maintained a database of workout scores from pro days and the NFL Combine and have tested them against NFL outcomes. These are tested both in raw form and in size-adjusted form – it turns out that the raw 40-yard dash matters at cornerback, but size-adjusted 40-yard dash matters at tight end.

The testing hasn’t been updated in the past several years, so while it might over-index for cornerbacks with length or trend towards other NFL fads from a few years ago, it still represents something a bit more precise than composite athletic scores.

I’ve also been able to control for role a little bit. There are two sets of athletic scores at defensive tackle – one for larger DTs, presumed to be nose tackles and one for smaller DTs, presumed to be three-techniques – three sets of tests for receivers that depend on height and separate tests at center, guard and tackle.

This way, we can avoid being impressed by athletes who specialize in skills that have little to do with their projected NFL job. RAS stars like Damiere Byrd and Dri Archer didn’t test well in position-specific scoring while average RAS athletes like Sidney Rice and Malcolm Jenkins are recognized for the high-level positional athletes they are.

Terence Steele had a high RAS but low position scoring while Cordy Glenn was the opposite.

So, with that in mind, and about 2,000 player workouts to account for after ingesting April data and the NFL Combine, who stood out?

Table of Contents:

• Offense

  • Quarterback

  • Wide Receiver

  • Running Back

  • Tight End

  • Offensive Tackle

  • Guard

  • Center

• Defense

  • Defensive Tackle

  • Edge Rusher

  • Linebacker

  • Cornerback

  • Safety

Offense

Quarterback

I’ve not done any testing for the relationship between athleticism and performance at quarterback, so there’s no model to go off of. Instead, we can identify the most impressive all-around athlete at the position based on pro day testing. That happened to be Jeff Sims from Arizona State (628^th on the Consensus Big Board). His uncle, Mike Sims-Walker, was a receiver for the Jacksonville Jaguars.

Sims ran a 4.50 40-yard dash and complemented that with a 10’11” broad jump, demonstrating his explosiveness. Doing so at 6’4” and 222 pounds is impressive, though it would have been nice to get agility measurements, too. In his final year at Arizona State, he only started in the second half of the season after starter Sam Leavitt suffered a season-ending foot injury. But in those seven games, he earned over 500 yards rushing.

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He’s not had meaningful snaps in college football, so he’s not going to be a quarterback at the next level. But it wouldn’t be surprising if an NFL team looked at him as a receiver or tight end.

Honorable Mention: Gavin Wimsatt, Jacksonville State

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Mason Reiger’s second pinned post on Instagram is captioned “Day 281: My story.”

The minute-long video captures the Wisconsin edge rusher’s journey from a walk-on at Louisville in 2020 to an impact player with the Badgers, with the caption ending: “Let me be an example of light being at the end of the tunnel!!!”

In 2006, Tajikistan opened the Iranian-built Anzob Tunnel, constructed to connect the two largest cities in the country — Dushanbe, the nation’s capital, and Khujand. The two cities had been cut off from each other for most of the previous winter due to harsh conditions across the Hisar mountain range and the closure of the original path between the cities, built through Uzbekistan during the Soviet era. But it was part of the larger Tajik-Uzbek border tensions after the Soviet Union collapsed.

The tunnel was dangerous — until 2017, it was not paved, lit or ventilated, and it remains unclear whether or not it is ventilated as of this writing. Locals told stories of people dying of carbon monoxide poisoning due to traffic jams away from the only fan, located somewhere in the middle of the tunnel. Until the tunnel was closed in June 2015 for repairs and improvements, travelers had to sign a waiver acknowledging hazards such as flooding and smog inside the tunnel.

A 2007 article by David Trilling of Eurasianet notes water jetting from the sides of the rock walls and from ceiling stalactites, and reaffirms the tales of deaths from carbon monoxide poisoning. Trilling notes that “if falling rocks were the only problem, the tunnel would be in good shape.”

When the tunnel opened in 2006, however, Tajikistan Deputy Prime Minister Asadullo Gulomov said at the ceremony that President Emomali Rahmon had once stated the Tajiks would build the tunnel “with our hands and teeth” if they did not have the requisite equipment.

“Good intentions are half the battle,” Rahmon said, according to Gulomov.

Hands and Teeth

Reiger begins the story of his six-year college career by saying that “it’s been quite a ride, and I’ve loved every bit of it.” A Division II prospect coming out of Conant High School in River Grove, Illinois, Reiger told Wide Left that “if I was going to play college football, I was going to play at the highest level. I didn’t want to look back one day when I’m 40, 50 years old with my kids and be like, ‘I wonder if I could have played at [the] Power 5 level.’”

Conant has produced four NFL players to date: 1984 UDFA wide receiver Tim Tyrrell, 1986 UDFA safety Creig Federico, 2004 UDFA quarterback Russ Michna and 2011 UDFA wide receiver Andre Holmes. None played major college football — Tyrrell played at Northern Illinois, Federico at Illinois State, Michna at Western Illinois and Holmes at Hillsdale.

Reiger came into Louisville knowing he was perceived to be a better fit for that lower caliber of school, telling Wide Left that “I saw some guys that play my position, play other positions, that I’m just like, ‘Wow, I am not ready for this level of football yet.’”

After two seasons and a third offseason program, the Illinois native found himself on scholarship at Louisville. His strong 2023 campaign, during which he had five sacks and a forced fumble, drew the attention of Wide Left draft analyst Devin Jackson:

A few of the reps highlighted by Jackson came in Louisville’s 2023 matchup against Notre Dame, which featured 2024 No. 5 overall pick Joe Alt at left tackle and second-rounder Blake Fisher at right tackle. Reiger had two sacks and a forced fumble in that game, a 33-20 upset win that proved to be one of the highlights of the Cardinals’ ACC Championship runner-up season.

“That was, on paper, my highest graded game of my career,” Reiger told Wide Left. “I think [that] goes hand in hand with that confidence, because at the time, I knew I was a good player, but I didn’t know how good I could really be and how I could take my game to the next level. A couple of those plays, I realized I could do this at a high level.”

Reiger missed the 2024 season after an offseason knee injury sidelined him for the year. By the time he suited up again, this time in Madison, in a different shade of red, the pass rusher had undergone six operations on the same right knee to get himself back into playing condition.

Louisville told Reiger to medically retire after the injury, but he wasn’t ready to give up on the chase just yet.

“At any given point, none of these players, me included, knows when our last snap of football is going to be. Having it taken away from me against my will just really puts it in perspective. Imagine your last play ever, and you weren’t giving 100% of your effort, and now you have to live with that for the rest of your life, the game that you say you loved,” Reiger told Wide Left. “I really do, I love football, since I was five years old, the first year I put pads on. For me to just have another opportunity to play, I’m going to give it everything I have, because one day when I don’t have football, I’m gonna look back and I’m gonna know that I was able to give everything that I have.”

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Wisconsin took a flier on Reiger in the transfer portal after he decided to pursue other opportunities, but the Badgers still had to wait for their new pass rusher to undergo a few more cleanup procedures on his knee before they could see what he could do. Once they did, head coach Luke Fickell told Wisconsin media that Reiger was a player the coaching staff had to “save from himself” sometimes — he was so relentless in practice that Wisconsin was worried he’d overextend himself.

“I definitely can say it comes from my parents, two of the hardest-working people I know to date,” Reiger told Wide Left of his work ethic. “I always tell people I had the privilege of growing up in a two-parent household. [My older brother and I] always pushed each other, and now I’m doing the same thing for my younger brother as well, and just to have a support system like that that’s always demanding the most out of you and you to become the best version of yourself, I think that was just a little bit of the spark to what I was going to do.”

Wisconsin drew the best version out of him. Reiger logged another five sacks and 11 more total tackles than he had in 2023 during his senior season with the Badgers, despite a nearly 20-month layover between his last game at Louisville and his first game in Madison.

“[Wisconsin] absolutely [demanded] a leadership role from me, and also myself, demanding that from me as well, to just really maximize my abilities as a player. You go out there, and you’re more vocal, and you push other guys, “Reiger told Wide Left when asked how playing for the Badgers elevated his game.

“In turn, you feel that pressure on you, but pressure is a privilege, and to have that confidence in yourself, to be able to help other guys out, get them lined up, and know that you’ve prepared enough to be confident and comfortable in your role as well is something that’s pushed me. I believe that a confident player is a better player at the end of the day. You go through a series, and you’re playing with confidence, you get into that flow state, and you’re finding more success, you’re making more plays.”

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This year’s NFL Combine purports to be the fastest combine in NFL history. In addition to record-breaking performances from Kenyon Sadiq, Lorenzo Styles Jr. and Sonny Styles, we’ve seen overall performances at the NFL Combine jump ahead of what we’ve seen historically. To the best of our verification ability, this is the fastest NFL Combine class of all time.

While that might not be a perfect indicator of talent, it certainly is exciting; we could be watching historic moments in a historic class that may or may not pan out but certainly has the juice to alter the geometry of football.

But something feels off.

While some elements of this class — like linebacker — are considered to be strong relative to the past few years, the way draft experts have talked about the class has been pessimistic. In fact, many scouts and draft analysts Wide Left spoke to in Indianapolis regard this as the worst draft class in over a decade, with some saying it’s the worst since the much-reviled 2013 draft class.

That’s not to say that we should expect that the fastest players are the best players and that the fastest classes are the highest-quality classes, but athleticism is broadly correlated to talent, even if that relationship isn’t rock solid.

Surely, if a draft class was genuinely the fastest we’ve ever seen, people would not think of it in terms of some of the worst classes the draft has ever produced. After all, scouts chase upside.

Exploring the question of whether this class was genuinely as dramatically fast as the numbers indicate doesn’t just serve as an exploration in how many different ways we can arrive at particular types of data, but also how difficult it can be to make sure one is acquiring the correct data in the first place.

Are Players Getting Faster?

First, we should validate these findings. Are players at the NFL Combine posting faster times?

Yes.

This is a general trend we have seen since 2006, but the changes in speed were gradual and uneven across groups. It’s easier to identify when we move from overall 40 time (by combine-designated position group) to 40 time against positional average.

And then it becomes even easier when we average across positions (choosing to treat each position as one unit rather than being subject to the problems of uneven distribution of player invites across positions).

This makes it clear that, before ever including the 2026 data, there was already a trend of faster 40-yard dash times over the years. But 2026 represents a meteoric leap.

That change is substantial and warrants a deeper look. NFL players didn’t just post faster times in 2026; they posted blazing times. It’s also the case that prospects posted the best vertical leaps and broad jumps in NFL Combine history, something we can validate against the prior 20 combines.

NFL players are producing historic bests in 40-yard dash times, vertical leap and broad jump… but historic worsts in the agility drills.

This could be our first clue. It may not necessarily be because NFL players are actually faster.

Data Validation

Before we dig any further, it is imperative that we learn another lesson: get the right data! It is surprisingly difficult to obtain data from the NFL combine over the years. That’s not because the NFL hasn’t been diligent about posting combine data over time as the event has gained prominence, but because the sources we generally use aren’t ensuring the results are accurate.

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Is tracking practice the future of NFL analytics?

In the past, analytics enthusiasts have talked about how the future of data analysis would come from player tracking. At the moment, we’re seeing the results of that prophecy — pass rush win rate, NGS plus/minus, receiver “open rates” and more. But in many ways, we haven’t unlocked the full potential of tracking data.

The East-West Shrine Bowl and Sumer Sports have worked on expanding what tracking data can do, hoping to find ways to use on-field data to project performance from incoming rookies into the NFL. Using numerical data to project rookies has long been a problem in analytics; traditional scouting has always taken primacy, with data-oriented approaches changing things at the margins.

Sponsored by Underdog Fantasy, organized by Sumer Sports, and put on at the Shrine Bowl, the first year of the East-West Shrine Bowl x SumerSports Analytics Competition was a moderate success.

Analysts have been using the tracking data they have access to in order to better project draft outcomes, including at the all-star games and the NFL Combine. The Next Gen Stats team, for example, has used tracking data acquired during positional drills at the NFL Combine to produce a new series of metrics.

Eric Galko, the director of the East-West Shrine Game, explained why he contacted Sumer Sports to set up the analytics competition. “We used analytics when I was with the XFL, and I’ve seen the growing rise of it. [I’ve] also [seen the rise of] opportunities and the need for people to network in the industry. And then combine that with the idea that I value analytics, [but] I can’t use R or Python, so I need to have stuff dumbed down for me.”

He added, “I think a lot of NFL teams also need help in kind of translating that information too. So, I wanted to make an opportunity for those in the analyst community to show their work in front of NFL teams and present and impress NFL teams, but also meet NFL teams on their level of understanding.”

Tracking Practice

Focusing on practice metrics is relatively new in public-facing analytics. “I think there’s a larger goal with this in particular, which is like, practice is gold, and right now we’re doing very little with practice, because practice is the most confidential, secretive thing that is out there for teams, right?” said Sam Bruchhaus, lead NFL analyst and senior data scientist at Sumer. “Unless they’re doing internal stuff, which is hard to do during the season, you’re not getting a lot of analytical juice or player development tracking out of practice.”

“I think the idea,” he said, “was that these are practices that everyone gets to see and everyone wants to see and it tells us more about college.”

“First thing, first,” Bruchhaus added, “which is why I was excited, was help us break down practice more when it comes to tracking data. We saw that, I believe, or at least, started a solution to that. And then the second thing is, let’s see how much juice this has for, you know, actually getting a beat on these players in a world where the average GM hits on 45% of his picks, if we can get that number up to 47% because we’re tracking this better, that’s 2% better we got with data.”

Like anything else, there’s more at play here than simply providing a service to the NFL community and the analysts who work in it. The Shrine Bowl asked contestants to produce analyses validating data from the Shrine Bowl to demonstrate the value of Shrine Bowl play.

The more that they can prove that they provide unique value versus other all-star games, the more they can push more players to attend the Shrine Game versus other bowl events. There are multiple elements involved here; a successful analytics competition that places analysts with football teams draws general managers in and keeps them in Frisco.

Growing the Shrine Bowl

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Editor’s Note: James Foster watched all three practices for the East-West Shrine participants and followed up by watching the tape of all of their drills. For more on understanding what we can learn from bowl games, check out last year’s piece on how all-star games operate and what evaluators can learn from them.

After watching the Shrine Bowl tape, here are my winners from the week.

TE Bauer Sharp – LSU

I haven’t gotten into Bauer Sharp’s tape yet, but he’ll be one of the first players I study following his performance at the Shrine Bowl. He was uncoverable in 1-on-1 drills, setting up routes effectively and separating with quick footwork and short-area burst. Linebackers and safeties will struggle to match his twitch and salesmanship at the top of the route. He also made some tremendous contested grabs and showed the ability to track and work back to underthrown deep targets. Sharp excelled in the pass blocking drills as well.

WR/KR Kaden Wetjen – Iowa

Wetjen entered the week with draftable grades based on his kick and punt return ability. The back-to-back Jet Award winner averaged 26.8 yards per punt return in 2025.

His route tree at Iowa was extremely basic, primarily consisting of screens, flats, and hitches. Last year, 22 of his 30 targets were behind the line of scrimmage, and his average route depth of 5.1 yards ranked near the bottom of the FBS.

But Wetjen’s route-running chops were on full display at the Shrine Bowl, and it’s realistic to project him into a more traditional role. He showed the salesmanship and quick footwork necessary to separate from man coverage. At the top of routes, Wetjen used head fakes, rocker steps, and crafty hand techniques to maximize space.

He struggled to play through contact at the line of scrimmage and catch point, however. When defenders got hands on him early, they were able to smother his route. He was unable to find success in the red zone period, but is unlikely to be deployed in that role in the NFL.

TE Seydou Traore – Mississippi State

Traore is another tight end whose tape I need to catch up on. He influenced defenders with deceptive stems and snapped off routes at sharp angles. He’s a long-strider who explodes out of cuts and uses his hands effectively to escape grabby coverage at the breakpoint.

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With the 2026 NFL Draft quickly approaching, I’ve decided to start releasing individual scouting reports on players who have already declared. Today, we’re starting with Auburn EDGE Keldric Faulk, who is consistently selected at the top of mock drafts.

Does he have the skills to merit getting selected that high?

Faulk’s General Scouting Report

Draft Age: 20.6

NFL Comparisons: Andre Branch/Mykel Williams

Keldric Faulk is a prototypical DE with an imposing frame and long arms. Despite starting 32 games in three years at Auburn, he’s still one of the youngest players in the 2026 class.

Faulk is an NFL-ready run defender who should immediately find a role on early downs. He has a sturdy anchor to set the edge, powerful hands to shed blocks, and impressive pursuit range for his size. During the last two seasons, he has led SEC defensive linemen with 72 run tackles.

Faulk has an effective long-arm, which could improve from good to great with more consistent pad level. While his power profile gives him a solid floor as a pocket-pusher, I’m much more skeptical of his ability to win the outside track in the NFL.

With a mediocre first step and below-average bend and arc speed, he lacks the juice to threaten the corner vs. more athletic tackles. He showed encouraging technical development from 2024 to 2025, but must continue to improve his hand-fighting skills.

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CONSENSUS

As of Dec. 13, Faulk is the seventh-ranked player and second-ranked edge rusher on the consensus board.

STATS

Faulk had modest pass-rushing production in 2025, recording 31 pressures, two sacks, and a 9.9% pass-rush win rate. That’s a severe dropoff from his nine-sack sophomore year, but considering how many of those were unblocked, I fully expected his sack production to regress to the mean.

Faulk played multiple positions on Auburn’s defensive front, lining up at 2-4 Tech on 30.3% of snaps this year. This hybrid deployment was not conducive to pass-rushing success and is important context when comparing Faulk statistically to other edge prospects.

It’s so much easier to win off the edge than from the interior, so it would be unfair to hold Faulk to the same standard as someone like Rueben Bain Jr., who played 95.2% of his snaps at 5-9 Tech.

Last year, Faulk’s pass-rushing efficiency was directly related to his alignment width. His pressure rate was just 2.6% from the interior and 4.1% when aligned over the tackle (4-Tech). But on 179 pass rush snaps from outside the tackle, he had a 15.1% pressure rate, which ranked in the 73rd percentile for qualifying edge rushers.

Faulk has ranked near the top of the league in most run defense metrics since becoming a starter. During the last three years, he has led FBS edge defenders with 62 run stops.

ATHLETICISM

Though Faulk moves well for his size, he’s a mediocre athlete relative to most edge prospects. His stride length allows him to cover more ground with fewer steps, which offsets his lack of burst and results in a decent overall get-off.

According to in-game tracking, Faulk’s 2.8 average get-off yards ranks in the 61st percentile for edge rushers. His bend, arc-speed and lateral quickness, however, are sub-par.

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Editor’s Note: With the trade deadline behind us, we have a good idea of what teams are working with as they head into the second half of the season. James Foster has used his dozens of hours of film study of the college season to best match the top prospects to teams holding the top-32 picks in next year’s draft.

The draft order was determined by the NFL ordering process before the results of Week 10’s Thursday Night Football matchup.

2026 Post-Trade Deadline Mock Draft

1. New Orleans Saints

Despite underwhelming production, I’ve been impressed by Tyler Shough’s tape over the last two weeks. Depending on how he plays down the stretch, the Saints might still take another quarterback this April, but based on the available sample, I’m penciling Shough in as their starter for 2026. This takes New Orleans out of the quarterback market and allows Mickey Loomis to recoup some draft capital after decades of recklessly trading up at every opportunity. 10-12 teams will be competing for three first-round quarterbacks this year, so he’ll likely have multiple offers and the leverage to demand higher compensation.

TRADE

• LV gives: No. 7, No. 38, 2027 1^st, 2027 2^nd, 2028 1^st

• NO gives: No. 1

1. Las Vegas Raiders: QB Ty Simpson, Alabama

The Raiders send a pick haul to move up and take Alabama quarterback Ty Simpson. Simpson is the least-experienced quarterback in this class, and I understand having reservations about taking a one-year starter this early, but he’s one of the most refined pocket passers I’ve seen at the college level. I’m significantly more encouraged by the quality of Simpson’s tape than I am concerned by the lack of quantity.

He’s made more NFL throws in eight games than a lot of college quarterbacks make over their entire careers. His pre-snap responsibilities far exceed what is normally asked of a college quarterback, and he consistently displays his command of the offense, adjusting protections at the line or checking out of a bad look. He has fewer starts than every legitimate 2026 prospect, but is already a better anticipation thrower with advanced pocket movement and sharp coverage recognition. Considering how much he developed on the bench, I’m fascinated to see what the “battle-tested” version of Simpson looks like.

2. Tennessee Titans

Tennessee declined a massive offer for the #1 pick last year, but the roster is devoid of talent at most key positions, so they need to prioritize volume and accumulate as many top-100 picks as possible.

TRADE

• LAR gives: No. 11, No. 27, 2027 3^rd, 2028 2^nd

• TEN gives: No. 2

2. Los Angeles Rams: QB Dante Moore, Oregon

Matthew Stafford is playing like he’ll be back next year, but the Rams still have to find a long-term solution at quarterback, so they take Dante Moore. After a rough freshman season at UCLA and spending a year backing up Dillon Gabriel at Oregon, Moore took over as the Ducks’ starter in 2025. He’s been one of the more surprising breakout players this year, and with a strong finish, he can solidify himself as a top-three pick. Though he doesn’t “need” a redshirt year, sitting behind Stafford as a rookie would undoubtedly benefit his development.

Moore executes full-field reads and throws with exceptional timing and ball placement within structure. He cycles through reads efficiently and makes rapid decisions while protecting the football. He prefers to win from the pocket, but has the accuracy and playmaking instincts to create when the play breaks down (like the Penn State game). The Indiana tape exposed his average escapability, but it’s the lone blemish on Moore’s résumé

3. New York Jets: QB Fernando Mendoza, Indiana

The Jets have accumulated a war chest of draft picks and have plenty of ammunition to trade up for a quarterback, if necessary. In this scenario, they keep their picks and select Indiana quarterback Fernando Mendoza.

Mendoza is a sharpshooter with prototypical size, elite accuracy, and a good, but not great arm. Indiana’s RPO-heavy scheme and penchant for blowouts make Mendoza a tricky evaluation. While he’s shown the ability to attack tight windows and throw with anticipation, he isn’t asked to move off of his first read very frequently. He’s also usually on the sideline or running the clock out by the start of the fourth quarter, so he only gets ~75% as much tape as other quarterbacks. The lack of high-leverage throws clouds the analysis, but Mendoza’s timing and ball placement give him a high floor in multiple schemes.

4. Miami Dolphins: LB/EDGE Arvell Reese, Ohio State

Miami takes LB/EDGE Arvell Reese, the best and most physically imposing player in the 2026 class. Reese’s overwhelming punch and bulletproof anchor make him a force at the point of attack. Whether he’s setting an edge, stacking a guard at the second level, or using a long-arm/bull rush, he annihilates blocks with ease.

Reese has All-Pro upside as an edge defender or off-ball linebacker, and I initially didn’t have a strong opinion regarding his NFL position. But his pass-rushing tape over the last few weeks has been dominant, and I’m beginning to think he’s an edge at the next level.

5. New York Giants

Rueben Bain Jr. is the best player available, but it’s hard to see the Giants spending another top-five pick on an edge rusher. The (assumed) departure of Trey Hendrickson and lack of edge depth in the 2026 edge class create enough urgency for Cincinnati to trade up and select Bain.

TRADE

• CIN gives: No. 8, No. 72, 2027 3^rd

• NYG gives: No. 5, 2027 6^th

5. Cincinnati Bengals: ED Rueben Bain Jr., Miami

Bain is a densely built edge defender with a deadly blend of speed and power. His arm length is well below average, but he’s a great athlete for his size with surprising flexibility at the top of the arc. At 275 pounds, he bursts into contact and has natural leverage to convert speed to power effectively. But he also has a wide array of hand moves and wins the corner much more frequently than a player of his size should.

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Ross Watson can still remember it as vividly as if it happened yesterday. He was walking to the meeting room, preparing to meet with his safeties, the position he has coached at Toledo for 10 seasons.

He heard a noise and took a peek around the corner. Inside the room, he watched Tycen Anderson grill fellow safety Maxen Hook on defensive calls, assignments, jobs, among various other aspects of the Toledo defense.

Watson, who often tests the mental aptitude of his players in a defense that asks a lot of its safeties, just watched from afar as the culture that was being built in front of his eyes was manifesting. Manifesting into something special. Manifesting a standard set by the defense’s best player and special teams ace.

He told his wife this later, after reflecting on the moment: “Tycen’s changing what’s going on in there.”

“That moment to me, when I saw those two in the room, changed my mind of what was going on,” Watson, who is also Toledo’s co-defensive coordinator, said by phone last month. “This guy is controlling what’s going on. He’s setting the tone for the room, and that keeps filtering through. We’re going through this right now. Our young freshmen right now need to learn what it means to play secondary at Toledo.”

Development at the core

When you think of the best Group of Five programs, Toledo might not be among the first couple of schools named. Programs like Tulane, Boise State, UNLV lately, and even UTSA or Liberty might come to mind.

But consider this: Toledo has a 75-43 record under Jason Candle since he took over the program full-time, has won more than half of his MAC games, and now, in back-to-back years, has produced top-three round draft picks in Quinyon Mitchell (2024 first-rounder) and Darius Alexander. In each of the last four drafts, Toledo had a player drafted.

Toledo had a long drought from 2005 to 2017. No players were drafted despite the success Tim Beckman and Matt Campbell (now at Iowa State) had as head coaches for Toledo. Then Candle took the head coaching job in 2016 after spending seven seasons as an assistant, and things immediately changed. Kareem Hunt, Treyvon Hester, and Michael Roberts were drafted in 2017. Logan Woodside in 2018. Diontae Johnson and Ka’dar Hollman in 2019.

Things changed under Candle in a hurry. He won the MAC in 2017, and six of his players got drafted in his first three years. Part of his recruiting strategy, he says, is having quality high school tape, but also to “find out who the human being is and what the man, the man inside that tape, is.” And at the core of his program’s success, he says, is developing his players and not just winning “the offseason from January to August.”

“I think that development is important. It’s more important than recruiting. You don’t get developmental rankings. You get recruiting rankings,” Candle said. “We’ve had a great track record of development, our strength coaches [Brad Bichey, Christian Klinec, Devan Rogers, and Spencer Davis] are A1 in my opinion.”

“[They’ve] done a great job with our guys, getting the most out of them from the physical side of it,” he said. “We have real, honest conversations with our players here in our building. We tell each other the truth. We don’t sugarcoat anything, and we just try to stay in the fight with them, rather than fighting against them.”

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Cory Kinnan from the Daft on Draft Newsletter, a publication devoted to high-quality work covering the NFL Draft, wrote a piece for us on early entrance into the NFL Draft. For more of his content, check out his Substack.

Fresh off a Heisman Trophy-winning season in 1988, Oklahoma State running back Barry Sanders changed the fate of the NFL Draft forever. Whether he recognized it at the time or not.

At the time, the NFL had a rule that only players who had finished all four years of school or had graduated early were eligible to enter the NFL Draft. However, entering Sanders’ senior season at Oklahoma State, the football program was placed on probation due to recruiting violations. Sanders requested a special exemption to enter the NFL Draft, and as a result, was granted it.

That opened a floodgate that only took one year for NCAA underclassmen to fully realize.

In 1990, a dozen talented juniors rebelled, deciding they wouldn’t play college football for a fourth year, and there was nothing the NCAA could do to stop them. Some of these players included Florida running back Emmitt Smith, Alabama linebacker Keith McCants, Tennessee running back Reggie Cobb and Heisman Trophy-winning quarterback Andre Ware from the University of Houston.

This forced the hand of NFL Commissioner Paul Tagliabue, who altered the NFL’s policy to allow for juniors to enter the NFL Draft permanently. Over the last 35 years, the number of juniors entering the NFL Draft has skyrocketed.

Until the NCAA allowed for players to receive payment for their name, image and likeness (NIL). Since the 2022 season, when players started receiving compensation at the college level, the number of underclassmen has steadily decreased.

NIL has changed the NFL Draft since underclassmen are no longer risking development to chase life-changing money. They’re now receiving more or equal amounts of money than they would see on Day 3 and undrafted free agent contracts.

This has shifted the mindset of every non-first-round player with remaining eligibility at the college level. It will also lead to another 1990-like facelift of the NFL Draft soon.

NIL’s Role in Changing the NFL Draft

While the NFL isn’t likely overly concerned about the talent pool year in and year out, the NFL Draft’s player pool is getting older because of NIL. Players with remaining eligibility are opting for the sure thing of upfront money for another year of college football versus the risk of sliding in the draft.

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Since 2005, The Athletic’s Bruce Feldman has collected workout numbers and tracking data from college football teams across the country, highlighting the most impressive athletes in his annual article, “Feldman’s Freaks List.” It’s a valuable resource, and the most anticipated article of the year for draftniks and college football fans.

The most attention-grabbing information in Feldman’s piece is the school-reported workout results. These unverified numbers are typically recorded a year before the player performs the drill at the combine, so it’s important to take them with a grain of salt.

I’ve been fooled in the past by players like Mazi Smith, whose actual combine results were a letdown relative to the numbers Michigan invented for him, so I now make sure to read the Freaks List with healthy skepticism. But I’ve always wondered how skeptical I should be of these claims, and whether the accuracy varies by drill, team or conference.

For this article, I evaluated every Freaks List claim from 2018 to 2024 and analyzed the results by school, drill, conference, year and other factors to determine how each factor affects accuracy. This data provides insight into whether a claim should be trusted, questioned or ignored, and allows for a more critical analysis of the Freaks List.

METHODOLOGY

My first step was creating a list of claims from each article. I define a “claim” as a reported drill result that can be verified at the combine.

Looking at Aireontae Ersery’s 2024 blurb, for example, the statements highlighted in green all qualify as claims, while those in red do not. Any reported tracking data or weight-room feats (aside from 225 bench press reps) cannot be verified and aren’t considered “claims.”

I compare the reported numbers to the combine and pro day results (best of the two) and give each claim a score of 0 or 1 depending on accuracy.

Ersery’s broad (111/110) and vertical (29.5/27.5) jumps were higher than reported, so he gets full credit (1) for those claims. But his 10-yard split (1.74/1.52) and short shuttle (4.82/4.61) were worse, so those count as misses (0).

I then calculate the raw accuracy rate for each player, school and conference by averaging the scores. This process is straightforward for a player like Ersery, whose incorrect claims were all decisive misses.

His reported 10-yard split and short shuttle would have ranked in the 100th and 78th percentiles for offensive tackles, but his actual results ranked in the 78th and 39th percentiles.

But the Freaks List is ultimately designed to serve as a watchlist of elite athletes, not a cheat sheet for NFL Combine prop bets, so the accuracy rate calculation should be a bit more flexible and less punitive. While the binary scoring system provides a rough estimate, it doesn’t account for the severity of missed claims.

A player with a reported 4.35 40-time running a 4.55 at the combine would qualify as a miss and receive no credit. If that player ran a 4.36, however, the claim would still be scored as a miss, which, under a binary grading system, would have the same score (0) and the same negative impact on the overall accuracy rate.

However, a 0.01-second difference is negligible and could be attributed to an inefficient start, a false step or a slight weight change. Nobody who read and believed this player’s reported 4.35 40-time was disappointed when he ran a 4.36. For this study, that claim is fairly accurate and shouldn’t be classified as a “miss” to the same extent as a 0.2-second exaggeration.

To address this issue, I created an adjusted accuracy rate, which grades close misses and egregious whiffs differently. As with the raw accuracy rate, a player gets a 1 when they perform at or better than the reported number. Missed claims receive a score of 0.75, 0.5, 0.25 or 0, depending on how close the result is to the reported number.

The table above shows how much partial credit a claim receives based on the drill and severity of the miss. For example, if a player’s actual vertical jump is within 0.5 inches of the reported number, the score for that claim is 0.75. Misses of 1.0 and 1.5 inches are scored 0.5 and 0.25, respectively.

Darrell Baker Jr.’s section in the 2021 Freaks List exemplifies the value of adjusted accuracy. He exceeded expectations in the broad jump, which was five inches better than reported, but fell short on the other three claims.

In the binary grading system, Baker Jr. is credited with one correct claim and three misses, for a raw accuracy of 25% (1/4).

The adjusted approach still penalizes him for the short shuttle (0.07 difference) but gives partial credit for close misses. His 40-time was just 0.02 seconds slower than reported, which corresponds to a 0.5. He also gets a 0.25 for the vertical jump since the actual result was within 1.5 inches of the claim.

Baker Jr.’s adjusted accuracy = (1 + 0.5 + 0.25 + 0) / 4 = 43.8%.

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