After the much-watched 2021 quarterback, at least a year ago, experts have been singing the downside of the 2022 quarterback, thinking that this is the ironclad quarterback year, but after the 2021 NCAA, the original champions such as Oklahoma's Spencer Ruttler and USC's Kadon Slovis performed on the street, gave up running and transferred from college; the emerging sleepers such as Pittsburgh's Kenny Pickett and Nevada's Carson Strong can only say that the standard is mediocre, Coupled with the only remaining draft favorite Matt Corral suffered an ankle injury in the sugar bowl, the difference between the level of quarterbacks and the immediate combat power in 2022 is outrageous, which is rare in history, comparable to the 2013 class.
PFF's overall draft player list has at least two quarterbacks in the top ten since 2018, but this year's highest is corral before injury, only 16th.
Although the quality of this year's quarterbacks is oddly poor, but that doesn't mean they won't produce future NFL starts, this article lists the best six quarterbacks of this year, according to PFF's K-Means clustering algorithm to classify the quarterback's offensive plans, punches and passing types, count the different category clusters, see whose game style is more suitable for the professional system, and who has the opportunity to blossom in the ruins.
Sam Howell, University of North Carolina (20th overall PFF draft)
Offensive plan: short passes mainly
Punch Output: Punch Threat
Pass output: King of short passes
North Carolina reduced the burden on Howell through a large number of RPOs, screen short passes and fake running real passes, so from a macro point of view, Howell is in a similar system to Corral. However, Howell's accuracy is more like an FBS-level quarterback. Due to the large number of RPO passes, Howell's accuracy ranks in the top 25% of this cluster.
After outside receivers Daz Newthom and Diamy Brown and running backs Jeffent Williams and McCar Carter collectively entered the professional world at last year's draft, Howell's passing to other areas of the pitch was moderately or below average.
His production on the road this season has been surprisingly outstanding, with each punching 3.34 yards above expectations, the third-highest for a quarterback in the group, behind Mariotta and Lamar Jackson. Future physical test data will reflect Howell's true athletic talent, and it is no surprise that Howell's punching threat will also be an important weight for him to enter the NFL.
Interestingly, in addition to his sheer athletic talent, Howell's data cluster is remarkably similar to Lamar-Jackson's in college.
Malik-Willis, Liberty University (PFF 22nd)
Offensive Plan: Heavy RPO
Pass output: Gamblers
With nearly a third of the time dominating RPO, Willis's job isn't a hassle either. However, he did not play too many fake run real passes and screen short passes, so he was divided into different clusters. And even in a system that values RPO, Willis's performance is mixed. He has super high CPOE data for short-range passes, but like other RPO quarterbacks, the CPOE in other dimensions is far below average.
In addition, holding the ball for a long time without a shot is also a problem, which can lead to pressure and passing the ball to a narrow space target, ultimately leading to a potentially missed pass. However, this shows that he believes in his athletic talent, but it will also bring a lot of trouble.
Willis is undoubtedly the most powerful quarterback in this year's rushing ability, the only problem is that there are 30% of the passing offense and finally choose to run away with the ball, is it a little too high.
His data clustering is most closely related to the university performance of Josh Allen and Jaylen Hertz.
Desmond-Reed, University of Cincinnati (PFF 32nd)
Punch Output: Movers
Pass output: Fast Gunners
Similar to Corral and Howell, the offensive system around Reid allows him to play with ease. His passing accuracy is as good as Howell's. Reid's CPOE at short passes close to the starting line is very high, which may be due to a large number of RPOs, but passing in other areas of the pitch, the CPOE is either moderate or below average.
As a passer, his most notable feature is his low rate of stress. Usually, this is characteristic of the fast gunner, who always makes the right decision when retreating. It's worth noting, however, that Reid's receiving group is the most talented of the five, and the offensive front line in front of him is taller than his opponents.
Reid's road offensive efficiency is also good, implementing a lot of set quarterback rushes, and there are also many large-size punches. However, there are not many samples that break through the grappling.
Drew Locke's data clustering was similar to Reid's when he was in Missouri, although Reed was much less capable of extending the court than Locke.
Matt Coral, University of Mississippi (PFF 34)
Pass output: Accuracy is in doubt
Wren Kiffen's coached offense benefited Corral a lot, giving him plenty of easy shots with a large number of RPOs, short passes on screens and fake runs. This is similar to the successful quarterbacks in college in recent years, including Mayfield, Full Class and Trevo Lawrence.
Unfortunately, his accuracy is very problematic. In every dimension of the stats, his CPOE is in the top 20 to the bottom of the college arena. Of course, part of the reason is because 52% of his shots are short passes within 5 yards of the starting line, and the high expected value of the hit rate leads to the CPOE not meeting the standard. Even so, the question of his accuracy is still worth paying attention to and will be the focus of scouting reports.
Punching is where he deserves to be confident because he is one of the best dashers in college in recent years. Lacking more data to back it up, there doesn't seem to be much evidence that he can reach lamar jackson or Justin Fields, but his dashing threat still works in the professional arena.
Interestingly, his data cluster is very similar to Justin Herbert's, despite the vastly different arm talents.
Kenny Pickett, University of Pittsburgh (PFF 47th)
Offensive Plan: Modern Air Raids
Punch output: Almost no punch
Pass output: Trumpet game manager
The main tactic of Pittsburgh's offense was a short pass from Biletnikov Prize winner and star outsider Jordan Edison. While what their offense calls "modern airstrikes" will be questioned, there are some similarities: plenty of five-man protection, a lot of short passes, and a focus on 11 and 12 configurations.
Although the team's offense is in the same cluster as the 2019 LSU, Pickett's accuracy is much higher than the average of this cluster. Thanks to a large number of short passes, he can also handle the problem of pressured passes, but it does show his ability to make quick decisions. But it's also true that the tough Edison helped him improve his accuracy.
Although he has a fair number of set-up punches and a top 15 runaway dash rate, Pickett doesn't have much of a threat on the road. There were concerns about the size of his palms, but the average level of missing ball errors reduced some concerns.
His data cluster is similar to that of Dwayne Haskins before the draft.
Carson-Strong, University of Nevada (PFF 65th)
Punch output: almost no punch (no dropped ball)
Strong's offense is closer to a "modern air strike" than Pickett's, but the overall concept is somewhat similar. Strong is the most accurate quarterback of the year. He and Howell are grouped into the same group because his short-pass CPOE ranks seventh high this year, but unlike Howell, the shooting percentage of other dimensions is basically in the top 20. The only exception was his shooting percentage from 6-10 yards, although this area also accounted for less than 20% of all his passes.
Strong basically did not contribute in the rushing attack, but the biggest advantage was that there were not too many drops. His data cluster is similar to That's Kody Kessler's, but his vertical passes are much better than Kessler's, so it's not a very accurate comparison.