The term “upside” is thrown around every draft season and is often used to describe athleticism or measurables.
But one problem with assuming upside is figuring out where to weigh it in the process. Does it matter more than the film or a player’s character evaluation? Athleticism is often used as a proxy for implying that “this guy will get better” at the next level, but is that always true?
Using only the measurables as a starting point, I’ve set out to quantify upside and downside and identify the positions with a history of improved performance based on athletic measures alone.
It’s important to note that this should never be the only way of evaluating prospects for the draft. The question to answer is, “Does this player project to improve upon his college performance when he gets to the NFL?”
Let’s take a look.
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The Process
1. Identify players who have improved or not improved from college to the NFL (using WAA and WAR percentiles and taking the top and bottom of those ranges). We'll call these players “most improved” and “least improved” players.
2. Take the average combine measurables of the most improved and least improved players.
3. Identify players who are better or worse than those averages historically and put them into either the “upside” or “downside” category (for example, edge defender Danielle Hunter would have been considered an upside player when he came out in 2015).
4. Quantify how well upside and downside players have “hit” against the historical average (Hunter is considered a hit as an upside player).
5. Identify positions where upside and downside players are significant against historical averages (i.e., upside edge defenders have hit about 18% of the time compared to just a 9% hit rate for all edge defenders).
6. Identify upside and downside 2024 draft prospects at significant positions.
Identifying the Most Improved and Least Improved Players
The priority is identifying players who have shown improvement from college to the NFL.
For this exercise, we are taking quarterbacks out of the equation. We are using NCAA WAA (wins above average) as a proxy for college production and NFL WAR (wins above replacement) as a proxy for NFL production.
Since WAA and WAR are both cumulative metrics, we’ve put both numbers on a season scale so each player has a WAA per season number and a WAR per season number for all his years in the NFL. Please note that we do not have WAA for FCS players.
Using WAA per season and WAR per season, we converted both numbers to percentiles. To identify those “most improved” players, we took the top 20% of players who saw the biggest increases in WAR compared to their college WAA production. We will call these players “most improved” players.
While identifying upside is the goal, we can also identify players who went the other way and generated lower NFL production relative to college. For these players, we took the lowest 20% of players who did not see growth at the NFL level. We will call these players “least improved” players.
Here’s an example of what the average measurables look like for a “most improved” edge defender:
| Event | “Most improved” edge defender |
| 40-yard dash | 4.65 |
| 10-yard split | 1.62 |
| Vertical Jump | 35.6 |
| Broad Jump | 121.6 |
| Three-cone | 7.14 |
| Shuttle | 4.36 |
Identifying upside and downside players
After identifying the most improved and least improved players, the next step is to look for the measurables for the two groups.
For simplicity, we took the average of all combine and pro-day measurables, taking the best-recorded number for each player without adjusting for the differences between a combine and pro days.
So, the most improved players at each position group have an average measurable set that we will test against, while the least improved players at each position group have their own average measurable set.
To classify players into historical categories of upside or downside, we look at a handful of metrics at each position and take all those who bettered the most improved numbers (upside players) and those who were worse than the average of the least improved players (downside players).
One test group looks at the 40-yard dash, 10-yard split, vertical jump, broad jump, three-cone and 20-yard shuttle. The second test group looks at the 40-yard dash, 10-yard split, vertical jump and broad jump but excludes the agility drills (three-cone, 20-yard shuttle). We’ll call those “Upside w/agility” and “Upside w/o agility.”
Here’s a look at Danielle Hunter’s measurables and why he qualifies as an “upside” player in the “upside w/agility” category.
| Event | Most improved edge defender | Danielle Hunter |
| 40-yard dash | 4.65 | 4.57 |
| 10-yard split | 1.62 | 1.57 |
| Vertical Jump | 35.6 | 36.5 |
| Broad Jump | 121.6 | 130 |
| Three-cone | 7.14 | 6.95 |
| Shuttle | 4.36 | 4.35 |
We replicate the same process for downside players, using the averages for the least improved players in the NFL. Downside players have worse measurables than the average of the least improved group at each respective position.
Now that we have a process for classifying historic players as upside or downside players, how well have those groups actually performed at the NFL level?
Evaluating hit rate for historic prospects
Using PFF WAR per season, we’ve evaluated every season for starters at each position group back to 2006 and converted those values into percentages.
For this exercise, a “hit” is considered any player who averages at least 60th-percentile WAR per season over their career.
For example, an elite edge defender averages about 0.43 WAR per season, while a “solid” edge defender averages about 0.22 WAR per season. Any edge defender who averages at least 0.22 WAR per season is considered a hit.
Since entering the league, Danielle Hunter has averaged 0.23 WAR per season, so he qualifies as a hit for this study. Each position will have a different 60th-percentile WAR threshold, but it’s all based on historical precedent from 2006.
Upside Results
Before we break down the results, here are a couple of things to remember:
1. This is not the only way to evaluate players. It’s a potential tie-breaker, pointer or eliminator.
2. The opposite of an upside player is not a downside player. There is a large group of players who qualify as neither. Upside players simply have better measurables than historical players who have improved at the NFL level, and downside players have worse measurables than historical players who have not improved at the NFL level.
With that said, since 2015, here’s a look at how upside players have performed relative to the league at each position.
| Pos. | All | Upside (w/agility) | Upside (w/o agility) |
| G/C | 16.6% | 37.5% | 40.0% |
| CB | 19.2% | 30.0% | 29.4% |
| TE | 15.3% | 30.0% | 28.6% |
| EDGE | 8.1% | 17.6% | 15.6% |
| WR | 9.5% | 18.2% | 11.4% |
| LB | 7.3% | 6.7% | 2.3% |
| T | 15.7% | 0.0% | 0.0% |
| DI | 7.3% | 0.0% | 4.7% |
| S | 5.7% | 0.0% | 3.7% |
| RB | 4.6% | 0.0% | 0.0% |
The two positions with the most significant hit-rate improvement are interior offensive line and tight end, with cornerback, edge defender and wide receiver behind them.
There was little to no difference in upside players at linebacker, offensive tackle, defensive interior, safety and running back, and it could be argued that chasing upside at those positions using this criteria is a fool’s errand.
Here are some examples of players from the upside (w/agility) group who have become hits since 2015:
Guard/Center
Tight end
Cornerback
Edge defender
This group also includes Vic Beasley Jr, Randy Gregory, Josh Sweat and Odafe Oweh, who have averaged about average WAR per season.
Wide receiver
- Tyreek Hill
- D.J. Moore
- Christian Watson (when healthy)
Downside Results
On the other end, here’s a look at how downside players have performed relative to the league average.
| Pos. | All | Downside w/agility | Downside w/o agility |
| G/C | 16.6% | 30.0% | 16.7% |
| T | 15.7% | 28.6% | 16.7% |
| LB | 7.3% | 8.0% | 9.5% |
| EDGE | 8.1% | 7.4% | 4.3% |
| CB | 19.2% | 6.3% | 10.3% |
| DI | 7.3% | 5.0% | 3.2% |
| WR | 9.5% | 0.0% | 0.0% |
| RB | 4.6% | 0.0% | 0.0% |
| TE | 15.3% | 0.0% | 0.0% |
| S | 5.7% | 0.0% | 0.0% |
The offensive line is the only position group in which taking a downside player did not lead to a wash or (more commonly) a significant disadvantage relative to the average.
It’s notable that interior offensive line is on top of both groups as far as hit rate goes, as high-end athletes have a good hit rate, but lower-end athletes are not disqualifiers for success at either offensive line position.
It does seem that positions like wide receiver, tight end and cornerback — which usually feature high-end athletes — are not producing low-end athlete outliers at a high level, so players below those various thresholds should be avoided.
Here are some notable downside players who have had NFL success:
Guard/Center
Offensive tackle
Here are some notable downside players who were drafted highly but have not lived up to their billing:
Wide receiver
Edge defender
Linebacker
The NFL generally avoids taking downside players in the top two rounds, showing how much the league values baseline athletic traits. Deviating from those baselines has proven risky at all non-offensive line positions.
What have we learned?
Before applying our results to the 2024 draft class, let's summarize what we have learned.
1. Selecting upside players at interior offensive line, tight end, wide receiver, edge and cornerback is likely helpful.
2. Selecting upside players at offensive tackle, running back, safety, linebacker and defensive interior is likely unhelpful or a wash.
3. Selecting downside players at offensive tackle or interior offensive line does not preclude players from succeeding.
4. Downside players at all other positions are less likely to have NFL success, though NFL teams usually avoid these players in the early rounds.
2024 upside players to watch
TE Theo Johnson, Penn State
There’s a lot to like about Johnson, who is one of the biggest and most athletic tight ends in the draft. He ranks in the 90th percentile in the 40-yard dash, 10-yard split, vertical jump, broad jump and 20-yard shuttle, all while carrying a massive 6-foot-6, 259-pound frame.
He already showed his potential at Senior Bowl practices, as his 93.6 receiving grade trumped all other tight ends, and he fits the profile of an NFL most-improved player.
TE Ben Sinnott, Kansas State
Sinnott technically misses the official list by a smidge due to his 4.68-second 40-yard dash (threshold is 4.65), but he’s notable because his 10-yard split (75th percentile), vertical jump (99th percentile), broad jump (96th percentile) and three-cone (97th percentile) give him an elite athletic profile.
The Kansas State tight end averaged 13.9 yards per reception in college. He quickly gets into the secondary and shows the ability to run-block or become a pass-game weapon from various alignments.
IOL Graham Barton, Duke
Already seen as one of the most versatile players in the draft, Barton’s pro-day workout may have solidified his first-round status. His 4.95-second 40, 1.68-second 10-yard split, 4.55-second shuttle and 7.31-second three-cone are among the best for any offensive line position. It’s fitting, as teams have Barton pegged as a “five-position” player who can play anywhere along the line.
Unlike others on the list, Barton also has the production to back up his athletic profile, as he earned a 90.3 PFF grade and finished as the fourth-most valuable offensive tackle in the nation in 2022. However, his grade did take a hit last season as he battled injury.
IOL Mason McCormick, South Dakota State
McCormick has the mean streak you want to see from an FCS prospect, and he showed well during East-West Shrine practices. Though he’ll be 24 at the start of the season, McCormick’s impressive testing profile includes a 5.08-second 40 (85th percentile), a 94th-percentile 10-yard split, a 99th-percentile broad jump and a 97th-percentile shuttle. Add his 6-foot-4 frame and nearly 34-inch arms, and McCormick has three-position potential at the next level.
IOL Tanor Bortolini, Wisconsin
Bortolini's college production doesn’t jump off the page, as he earned an overall grade of 76.6 in 2022 and 67.1 last year, but his strong athletic profile shows up on the field. His strong movement skills fit well in a zone-heavy scheme. There are some production/athleticism similarities to 2021 fourth-round center Drew Dalman, who was solid in college before grading at 67.2 in his first year as an NFL starter in 2022 and then breaking out with an 83.1 grade last season.
IOL Dylan McMahon, NC State
Like Bortolini, McMahon has an average production profile, topping out with a 69.7 grade last year, his fourth season as a starter. He had a high percentage of negative plays in the run game and below-average pass-blocking grades compared to recent NFL prospects, but his athletic testing is conducive to future improvement.
Eagles guard/center Cam Jurgens put up similar below-average numbers in college before emerging as a serviceable starter last season. Jurgens is primed to take over at center for the now-retired Jason Kelce. While McMahon has a different body type, his testing compares favorably to Jurgens'.
Other IOLs to watch: Brandon Coleman, TCU
Edge Dallas Turner, Alabama
This is an obvious choice and a big reason why Turner is projected to be the first defensive player off the board. Unlike recent athletic upside projections on the edge, such as Travon Walker (2022) and Tyree Wilson (2023), Turner has a stronger production profile to go with the perceived upside.
He earned an 89.3 pass-rush grade last season and has 238 career coverage snaps, showing off his athletic versatility. Turner ran a 98th-percentile 40 (4.46) to go with 98th-percentile vertical and 95th-percentile broad, all good indicators that he has more room to grow at the NFL level.
Other edge defenders to watch: Jalyx Hunt, Houston Christian; Cedric Johnson, Ole Miss
WR Roman Wilson, Michigan
The draft process has been good for Wilson, who had a strong week of Senior Bowl practice to go with one of the better combine workouts at the position. He ranks better than the average most-improved player in every key category, including a 4.39-second 40, a 91st-percentile 10-yard split, and a 93rd-percentile shuttle.
WR Ricky Pearsall, Florida
In another tick-all-the-boxes offseason, Pearsall posted the highest receiving grade at Senior Bowl practice before posting elite workout numbers. The highlight was a 6.40 three-cone, the best-ever for a receiver, to go with a 4.41-second 40, a 96th-percentile 10-yard split, a 99th-percentile vertical and a 95th-percentile shuttle.
WR Anthony Gould, Oregon State
For the purposes of this study, we haven’t made any size adjustments, so perhaps Gould’s 5-foot-8, 180-pound frame gives him an advantage over his peers. However, he was in the 90th percentile or better in all explosive measures, including a 4.39-second 40 and 40-inch vertical. Other smaller receivers who ticked the boxes historically include Phillip Dorsett, Tyreek Hill and Damiere Byrd.
CB Max Melton, Rutgers
Melton had one of the most explosive cornerback workouts of all time, posting a 4.39-second 40, a 95th-percentile vertical and a 99th-percentile broad jump. The agility times were closer to average, but Melton’s straight-line explosion shows up in game action, as he easily runs with wide receivers down the field.
Given his career-high PFF grade of just 73.5 (2023), Melton has plenty of room to grow, but he has the athletic profile to become a better player in the NFL.
CB Elijah Jones, Boston College
A hot name as we get closer to draft day, Jones produced a monster 43-inch vertical to go with a strong 4.44-second 40 time and 1.55-second 10-yard split. He has just one year of good production (last year’s 86.9 overall PFF grade), but it came on just 524 snaps in his sixth year at Boston College. So, while Jones is a late breakout player, his movement skills make him a candidate to continue his ascent.
Other CBs to watch: Jarrian Jones, Florida State; Nehemiah Pritchett, Auburn
2024 downside players to watch
RB Bucky Irving, Oregon
It saddens me to put Irving on this list, as his college film is outstanding. However, he had a disappointing combine week in Indianapolis. He was just below the average of the “least improved” group in the 40, 10-yard split, vertical and broad.
Irving has one of the best production profiles in the draft, and he’s a jitterbug who plays much quicker than he plays explosively, but he lands on the downside list due to those sub-par testing numbers.
Edge Bralen Trice, Washington
Another player with a strong production profile and a questionable workout, Trice has two years of 88.0-plus PFF grades and 90.0-plus pass-rush grades. However, he posted mid-tier 40 and 10 times while coming in below average in vertical and broad jump. He falls into the downside bucket without agility times, a group that hits about half as often as the average edge defender since 2015.
DI T’Vondre Sweat , Texas
A recent DUI arrest has thrown Sweat’s draft projection into question, but his workout also raised some red flags. With no size adjustment for this exercise, it may be unfair to hold the 367-pound Sweat to the same standard as other interior defensive linemen. Still, there are other 340-plus-pound nose tackles with better testing numbers in recent years. Sweat is below average in the broad and vertical jump and about average in the 40 and 10 compared to recent big-bodied nose tackles.
DI McKinnley Jackson, Texas A&M
Jackson weighed in at 326 at the NFL combine, and he posted a disappointing 4th-percentile vertical to go with below-average 40, 10 and broad. His pro-day agility testing wasn’t much better, as his 4.90 shuttle (15th percentile) and three-cone (27th percentile) came in well below par.
The one outlier interior defensive lineman to overcome the downside group is Derrick Brown, who came with first-round production and carried that into the NFL to become one of the better players at the position.
S Tyler Nubin, Minnesota
One of the top safety prospects in the draft, Nubin will have to overcome sub-par agility drills (13th-percentile shuttle, 28th-percentile three-cone) to become a solid NFL player. He also posted a below-average 40-yard dash and 10-yard split, along with a 14th-percentile vertical at 32 inches. The most recent positive example coming out of the safety downside group is new Bengals safety Geno Stone, who ranked second in the league with seven interceptions last season. However, there have not been many consistent starters to come out of this group since 2015.
Putting this data to use
The NFL draft is about paring down thousands of players into a handful of draft picks for each team. Studies like this one should be used as eliminators or tie-breakers to help narrow draft boards.
This study aims to help answer the question often raised when evaluating prospects: Will this player improve in the NFL?
Rather than guessing or assuming that a “good workout” means a player has upside, we’ve attempted to quantify exactly what a good workout looks like and if that has actually led to improvement among players with similar athletic profiles in the past.
The next time the question arises about a player’s prospects for improvement at the next level or whether or not he’s maxed out, quantifying upside and downside using combine and pro-day measurables is one way to get closer to an answer.
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