Florida Gators Blog

Breaking down the 2020 recruiting class

Now that 2019 is in the books, let’s take a look at how 2020 is shaping up. Obviously, class metrics will change considerably. The benefit to charting how things are looking now versus how they shape up a year from now will provide insight as to how much fluctuation occurs, and maybe provide some relief for fans experiencing angst over their school’s recruiting efforts before the classes are signed. I expect lots of change between now and this time next year, but here is how things are shaping up for next year’s class at the moment.

Overall Summary:

TOTAL N 5-stars N 4-stars N 3-stars
1000 34 309 657
Tot Leaning home 5-star leaning home 4-star leaning home 3-star leaning away
257 15 129 113
Tot Leaning away 5-star leaning away 4-star leaning away 3-star leaning home
211 17 119 75
% Leaning Home % 5-star leaning home % 4-star leaning home %3-star leaning home
26% 44% 42% 17%
% Leaning Away % 5-star leaning away % 4-star leaning away %3-star leaning away
21% 50% 39% 11%

The above chart shows the breakdown of how the top 1000 recruits (247 Composite) are leaning. Many aren’t leaning toward a school yet. Out of the 34 five-star recruits, 15 are leaning toward an in-state school while 17 are leaning toward an out-of-state school. The 2019 class saw 65% of the five-stars leave their home state. Right now, that figure is at 50%.

By Team:

College lean No. of leans No. 5-star No. 4-star No. 3-star Avg. Rate of lean
UCLA 3 1 2 0 0.9568
Georgia 12 3 7 2 0.9458
Ohio State 27 6 18 3 0.9441
Clemson 17 3 13 1 0.9437
USC 13 3 9 1 0.9368
Notre Dame 12 0 11 1 0.9365
LSU 23 2 19 2 0.9360
Penn State 14 3 9 2 0.9356
Alabama 15 2 10 3 0.9338
Oklahoma 14 1 10 3 0.9298
Stanford 9 1 7 1 0.9289
Florida 18 1 13 4 0.9282
Miami 18 0 14 4 0.9220
Washington 7 1 3 3 0.9219
Texas 15 0 10 5 0.9213
N.C. State 7 1 4 2 0.9185
West Virginia 1 0 1 0 0.9149
Louisville 3 0 2 1 0.9143
Tennessee 8 0 5 3 0.9117
Arizona 2 0 1 1 0.9090
Texas A&M 22 3 8 11 0.9076
Florida State 16 1 9 6 0.9074
South Carolina 12 0 8 4 0.9056
Auburn 10 0 7 3 0.9055
Oregon 11 0 8 3 0.9041
Ole Miss 7 0 4 3 0.9041
UTSA 1 0 1 0 0.9020
Michigan 15 0 10 5 0.8963
Arizona State 2 0 1 1 0.8943
North Carolina 4 0 3 1 0.8921
Wisconsin 7 0 2 5 0.8866
Nebraska 2 0 1 1 0.8863
Mississippi State 8 0 4 4 0.8835
Virginia Tech 5 0 2 3 0.8832
California 4 0 1 3 0.8818
Minnesota 5 0 1 4 0.8795
Fresno State 1 0 0 1 0.8789
Arkansas 10 0 1 9 0.8785
TCU 2 0 1 1 0.8781
Michigan State 10 0 2 8 0.8743
Kentucky 4 0 0 4 0.8736
Duke 3 0 0 3 0.8703
Purdue 3 0 1 2 0.8670
Oregon State 3 0 1 2 0.8668
Maryland 2 0 0 2 0.8667
Northwestern 4 0 0 4 0.8663
Iowa 8 0 1 7 0.8634
Utah 3 0 0 3 0.8626
Oklahoma State 4 0 1 3 0.8608
N/A 532 2 61 469 0.8605
Brigham Young 5 0 1 4 0.8596
Missouri 5 0 0 5 0.8576
Baylor 5 0 0 5 0.8569
Iowa State 5 0 0 5 0.8561
Boston College 6 0 1 5 0.8527
Rutgers 1 0 0 1 0.8527
Texas Tech 3 0 0 3 0.8520
Cincinnati 2 0 0 2 0.8477
Tulsa 1 0 0 1 0.8477
Virginia 2 0 0 2 0.8445
Colorado 1 0 0 1 0.8427
Vanderbilt 2 0 0 2 0.8366
UAB 1 0 0 1 0.8366
UCF 1 0 0 1 0.8333
Wake Forest 1 0 0 1 0.8333
Indiana 1 0 0 1 0.8316

The above table is a breakdown of how each school is doing in recruiting among the top 1000 players currently. Florida currently is 16th in terms of average talent rating for recruits committed/leaning toward them with a score of .9282. UCLA has the highest average, but they only have 3 leans.

By Position:

Position Offense Defense Skill Pos Total 5-stars 4-stars 3-stars Avg. rating
SDE No Yes No 54 3 16 35 0.8803
RB Yes No Yes 73 5 24 44 0.8895
ILB No Yes No 35 2 8 25 0.8765
OLB No Yes No 75 2 27 46 0.8824
WR Yes No Yes 162 5 61 96 0.8895
OT Yes No No 98 3 33 62 0.8870
PRO Yes No Yes 46 1 12 33 0.8798
ATH Yes No Yes 85 1 23 61 0.8788
CB No Yes Yes 78 4 21 53 0.8814
OG Yes No No 43 1 11 31 0.8759
DT No Yes No 66 1 28 37 0.8908
WDE No Yes No 38 3 11 24 0.8864
APB Yes No Yes 13 1 3 9 0.8829
DUAL Yes No Yes 33 1 6 26 0.8718
TE Yes No No 34 1 5 28 0.8692
OC Yes No No 10 0 1 9 0.8688
S No Yes Yes 57 0 19 38 0.8766

This table breaks down the class by position. There are 73 running backs in the top 1000 players, 5 of which are 5-stars, 24 are 4-stars, and 44 are 3-stars. The overall average rating for the position group is .8895. The skill position designation is subjective. Feel free to let me know if you disagree and why. I will gladly take input on that.

The University of Florida Gators:

future gators

This table depicts how Florida’s class is looking now. So far, so good.

By State:

2020collegestate

This map shows how many recruits from this sample are leaning/committed to schools in various states. 53 of them are leaning toward Florida teams, with Florida and Miami each having 18, FSU having 16, and UCF having 1.

By Home State:

2020homestate

This map depicts where the top 1000 recruits for 2020 are from. Of note, 3 are from Canada and not depicted here. Florida and Texas are doing a lot of the heavy lifting, however, Georgia is producing some great players. Here is how the per capita breakdown looks:

State 2018 Population Players produced Per Capita lean (by 10,000)
Hawaii 1420491 18 78.9
Georgia 10519475 105 100.2
Alabama 4887871 45 108.6
Louisiana 4659978 39 119.5
Tennessee 6770010 41 165.1
Florida 21299325 117 182.0
Wisconsin 1805832 9 200.6
Texas 28701845 139 206.5
Nevada 3034392 11 275.9
Missouri 6126452 22 278.5
Kentucky 4468402 16 279.3
Arizona 7171646 25 286.9
Maryland 6042718 19 318.0
Michigan 9995915 30 333.2
Ohio 11689442 33 354.2
South Carolina 5084127 13 391.1
Oklahoma 3943079 10 394.3
Utah 3161105 8 395.1
Virginia 8517685 21 405.6
California 39557045 88 449.5
North Carolina 10383620 23 451.5
Nebraska 1929268 4 482.3
Washington 7535591 15 502.4
Iowa 3156145 6 526.0
Kansas 2911505 5 582.3
Arkansas 3013825 5 602.8
Indiana 6691878 10 669.2
Pennsylvania 12807060 16 800.4
Minnesota 5611179 7 801.6
Colorado 5695564 7 813.7
Oregon 4190713 5 838.1
Illinois 12741080 15 849.4
Massachusetts 6902149 7 986.0
Connecticut 3572665 3 1190.9

What about the 3-stars? Let’s give them some attention.

Every year college football fans go bananas over blue-chip recruits (guilty). However, it isn’t uncommon for those unheralded three-star recruits to turn into a special player. For us Florida fans, we have had a bunch- Antonio Callaway, Jarrad Davis, etc. That aside, the reality is that blue-chip recruits are fairly rare. In 2019 there were a total of 383 blue-chips, that ultimately ended up at 54 different colleges. I took an in-depth look at those, and those findings will be finished sometime soon. But in the middle of that study, I got curious about the three-stars.

I took a sample of 1,225 three-star recruits from the 2019 class. There were more, but that was enough. They were the top-rated group that had committed to a school according to the 247 Composite website. In my blue-chip study, I was looking at overall migration patterns- where do the BCs come from and where do they go, etc. I started by doing the same thing for the 3s. Here is a map of where this sample came from (of note, 5 of them came from Canada, not depicted):

3star home state

This is a map of where these recruits ended up. This gives you a general idea of where they end up going to school.

3star destination

As you can see, a lot of Florida’s 3-stars leave the state. 165 (first map) are from Florida, but only 75 (second map) committed to schools in Florida, about 45%. This is a net loss of 3-stars of 55%. Keep in mind those that committed aren’t necessarily from Florida- that is just the gross number.

The overall average for recruits to leave their home state is 66%. 2019 5-stars left their home state 65% of the time, 4-stars 67%, and 3-stars left 67% of the time as well.  However, for the state of Florida, 118 of their 165 3-stars committed to schools out of state- 72%. A bit higher than average. In this metric, Florida ranked number one:

departure chart

The average rating for the group is .8490. These players committed to 163 different schools. I was also curious as to how good Florida’s 3s rated compared to everyone else. I took the average rating and then standardized each school’s 3s ratings compared to the other schools in the sample. I then removed schools that have 2 or fewer three-stars; schools like Monmouth, Prairie View A&M, Alabama, and Stony Brook. Because they have so few of the 3s, their averages wouldn’t really change, and I wanted to rank the teams by average rating. Here are the top 20 teams for best 3-star recruits:

3s Class Rk School N 3 stars Avg Rating Std. score
1 Oregon 12 0.8792 2.370
2 Auburn 6 0.8760 2.121
3 Clemson 14 0.8749 2.031
4 LSU 7 0.8748 2.027
5 Oklahoma 5 0.8742 1.978
6 Florida 8 0.8736 1.935
7 Georgia 3 0.8723 1.833
8 Michigan 10 0.8722 1.819
9 Nebraska 19 0.8716 1.778
10 Texas 7 0.8696 1.621
11 Washington 7 0.8696 1.619
12 South Carolina 15 0.8673 1.441
13 Tennessee 9 0.8673 1.440
14 Notre Dame 6 0.8667 1.388
15 Florida State 10 0.8660 1.336
16 Arkansas 14 0.8659 1.327
17 Wisconsin 17 0.8651 1.268
18 TCU 18 0.8645 1.221
19 Ohio State 5 0.8640 1.179
20 Texas A&M 11 0.8627 1.079

The Gators sit at 6th overall. Their 3-star recruits are almost 2 full standard deviations above the mean (“Std. score”). If you’re going to get some three stars, might as well be good ones. Florida’s success recruiting good 3-stars is not an indicator (to me) of recruiting failure. Mullen is doing an excellent job of stocking the roster with blue-chip talent, especially compared to his predecessors:

mullenUF

With Florida landing a top 10 class this year and on track to have an even better class next year, Florida will be just fine on talent. Go Gators.

An in-depth statistical look at the 2019 Blue Chip high school recruits.

In this analysis, I was curious about the migratory patterns of the modern blue-chip high school football recruit. Blue-chip is defined as a 4 or 5-star recruit. Using 247 Composite ratings, I analyzed every BC in the 2019 class across several dimensions. It ended up being a large data set because I got carried away. The factors reviewed were:

  1. 5-star vs 4-star status
  2. Home state
  3. State of school committed to
  4. School committed to

Then I looked at how many recruits stayed in their home state versus leaving for another state, and each school’s role in that migration. The chart below shows the overall breakdown.

migchart1

I then looked at how each school contributed to its states’ level of migration. For example, the state of Georgia produced 40 blue-chip recruits (Seven 5-stars and thirty-three 4-stars). 34 of those committed to schools not in Georgia, so they lost 85% of their home state talent. The Georgia Bulldogs, however, have 18 blue-chip high school recruits committed as of this writing. 13 of those come from other states. Their blue-chip poaching percentage is 72%. The chart below shows the findings for every school that has a BC committed.

chart2

An important note here. For BCs that are still unsigned, the Crystal Ball percentages were used to include them. So, if a recruit was 51% to University 1 and 49% to University 2, that recruit is included in the data for University 1. I will update after all are signed.

chart3

Migration is not just a Florida issue.

Out of the 383 blue-chip recruits for the 2019 class, 255 have committed to or are favored to go to out of state schools, which is 67%. Florida makes up a chunk of that date, with 28 out of 46 (61%) leaving. California (35 out of 47 -74%), Georgia (34 out of 40- 85%), Texas (25 out of 47- 53%), Louisiana (8 out of 15- 53%), and Alabama (9 out of 14- 64%) all have similar issues.

Both 5-stars and 4-stars are equal in terms of migrating away from home, 68% and 66%, respectively.

I won’t disagree with anyone who thinks winning state recruiting battles isn’t important but keeping talent in-state isn’t a common thing in modern times.

Teams with top 20 recruiting classes for 2019 who have the highest poach percentage (number of blue-chip recruits committed who come from out of state relative to BCs from in-state) are:

school heat map

Schools with the most BC recruits from Florida (either committed or favored by Crystal Ball):

chartFL

There is a lot more I’m looking at here, and this will be updated after NSD. Check back with me to see what the final numbers look like.

Did Florida upgrade when they acquired Gray after Warren went to Georgia? A statistical breakdown.

A hot topic on Twitter, at least for a few minutes, was Georgia’s poaching of Florida cornerbacks coach Charleton Warren. Florida coach Dan Mullen responded by bringing back one defensive backs coach Torrian Gray. The general consensus was that Florida upgraded. Taking a look at the numbers from each coach’s one year spent in Gainesville, it appears as if Florida did indeed come out ahead in this series of transactions.

Taking each coach’s statistics at Florida (Gray in 2016, Warren in 2018), I analyzed opponent QB ratings. There are several other metrics that could be included, but I chose this one because I thought it provided a good overall view of how the defensive backs performed. I analyzed how the team performed relative to the previous year. So for Gray, I used 2015 and 2016 statistics. For Warren, I used 2017 and 2018.

I was generally looking to see how much improvement each team showed under the coach compared to the previous year. I then compared the raw data to the national average and to how they stacked up compared to the rest of the SEC. Here’s how it played out:

warren ranks

Coach Warren saw his unit improve from an average opponent passer rating of 130.9 in 2017 to 122.9 in 2018. Overall, Florida ranked 38th in the nation in 2018 (way up from 68th in 2017). When standardized against the rest of the SEC, Florida showed the 3rd best improvement from the previous year. Not at all a bad job by coach Warren.

gray ranks

In coach Gray’s only year in Gainesville, he saw his defensive backs move from 11th best in the nation in terms of opposing QB rating all the way to number 1. Relative to the rest of the SEC that year, Florida had the second-best improvement behind Arkansas. The Razorbacks, however, had been so horribly horrendous the previous year that even with the excellent improvement, they were still worse than average. Florida, under gray, went from very excellent to the best.

What the numbers in the charts mean:

In columns 3 and 4 (from left), this is the overall opponent QB rating for that year. The columns marked with a ‘z’ is the standardized score for the SEC. The lower the score the better. The improvement score shows the difference from the year the coach was there compared to the previous year. Again, the lower the number, the better. When you look at the two charts, you can see that Florida improved -0.948 standard deviations better under Gray in his one year than they did under Warren in his year with the Gators. Given the findings, I believe the Gators upgraded after all is said and done.

Factors related to winning percentage in the top 20 most talented college football teams

The number of 4-star players on the roster are most strongly correlated with winning percentage for the 2018 teams in the top 20 talent ratings. Here are how some factors correlate to win percentage:

Five-star players: 28.1%

5star

Four-star players: 59.8%

4stars

Three-star players: negative 18.2% (the higher the number of 3-stars, the less you win).

3stars

Blue-chip percentage: 48.8%

bcp

Talent rating: 43.7%

talent

However, when you go one step further and look at the strength of schedule ratings (Sagarin), SOS takes the cake:

SOS: negative 62.8% (the weaker the schedule, the more you win)

sos

Total Blue-chips (4 and 5-stars) 54.4%:

totalbc

A complete look at how the Power 5 conferences compared in 2018.

The SEC as the dominant conference in college football is a common theme. There has been a lot of analysis attempting to prove and disprove this widespread notion. This analysis utilizes the 2018 season only, as to avoid any claims of historical biases and to make the argument about which conference is the best right now. I don’t need historical data for that.

This analysis examined each conference across several statistical dimensions, scored the conferences and then ranked them. One caveat- only teams in the top 50 talent rankings, roster-wise, were included. This was done for one primary reason: Time constraints. I have to analyze each, and every roster of every team and I already have the 2018 data for the top 50 most talented teams according to the Composite Rating website. However, there is another benefit. By excluding teams without top 50 roster talent, negative outliers are removed. The analysis is based on averages and outliers can have a heavy impact on averages. So, there’s that.

The dimensions analyzed were:

  1. Average ordinal roster ranking.
  2. Average number of 5-star recruits
  3. Average number of 4-star recruits
  4. Average number of 3-star recruits
  5. Average roster blue chip (4 & 5-star recruits) percentage.
  6. Average roster talent rating (Composite).
  7. Average winning percentage (regular season).
  8. The average number of blue-chip recruits in a conference.
  9. Percentage of teams in the conference among those with top 50 talent roster (included for analysis).
  10. S&P+ Strength of schedule average.
  11. Dispersion scores.

The dispersion scores measured the amount in variance each conference had among its sample scores. The smaller the number, the more consistent the scores. This is a way of examining the influence of potential outliers or extreme scores.

table1 conference scores

The table above shows the scores for each conference along each dimension. So, the SEC scored as follows along the 11 dimensions:

  • Averaged ranking of roster talent: 20.1
  • Average number of 5-stars per team in the sample: 2.9
  • Average number of 4-stars per team in the sample: 27.9
  • Average number of 3-stars per team in the sample: 47.2
  • Average roster blue-chip percentage: 37%
  • Average talent rating per roster: 87.9
  • Average win percentage per team: 63%
  • Average number of blue-chip players per roster: 30.8
  • Percentage of teams from conference among the top 50 talented rosters: 100%
  • The average strength of schedule (SOS) according to S&P +
  • Overall average variance of all dimensions: 5.5

The charts below depict how each of the conferences ranked among the dimensions. This clearly shows the SEC as the dominant conference in 2018. The rankings flow top to bottom, 1 to 5.

ranks1

ranks2

The SEC ranks at the top of almost every category and has all 14 teams in the sample. Each of the other conferences scores would be lowered with the inclusion of every team, thus widening the gap between those conferences and the SEC. The Big 12 has the highest winning percentage but also had the fewest teams included in the top 50. While I can’t say for sure, I suspect that if I included all of the Big 12 teams, the overall win % for that conference would go down. I might do that in the future, but until then, this gives you an idea of how 2018 went for each conference.

Statistical breakdown of the 2019 Blue Chip class

The data on the 2019 high school class Blue Chip players (4 and 5 star rated players by 247 Composite). A full chart of the players is at the bottom.

By position:

Position Count % by Pos 5 star %5 star Pos 4 star %4 star Pos
WR 48 13% 6 18% 42 12%
CB 39 10% 3 9% 36 10%
OT 33 9% 5 15% 28 8%
S 30 8% 1 3% 29 8%
SDE 28 7% 3 9% 25 7%
DT 27 7% 3 9% 24 7%
WDE 23 6% 2 6% 21 6%
RB 22 6% 2 6% 20 6%
ATH 21 6% 1 3% 20 6%
ILB 21 6% 2 6% 19 5%
OG 20 5% 2 6% 18 5%
OLB 19 5% 1 3% 18 5%
TE 15 4% 0 0% 15 4%
PRO 13 3% 1 3% 12 3%
DUAL 13 3% 0 0% 13 4%
APB 5 1% 0 0% 5 1%
OC 3 1% 2 6% 1 0%

Total BC by pos

5 star by pos

4 star by pos

By State:

State Total BC % of BC 5 star by state 4 star by state % 5 star % 4 star
 CA 47 12% 3 44 9% 13%
 FL 46 12% 5 41 15% 12%
 TX 45 12% 4 41 12% 12%
 GA 40 11% 7 33 21% 10%
 LA 16 4% 4 12 12% 3%
 MS 16 4% 1 15 3% 4%
 NC 14 4% 0 14 0% 4%
 AL 13 3% 1 12 3% 3%
 TN 13 3% 0 13 0% 4%
 OH 12 3% 1 11 3% 3%
 VA 10 3% 1 9 3% 3%
 MI 9 2% 2 7 6% 2%
 NJ 8 2% 1 7 3% 2%
 MD 8 2% 0 8 0% 2%
 KY 8 2% 0 8 0% 2%
 AZ 7 2% 1 6 3% 2%
 IN 6 2% 0 6 0% 2%
 MO 6 2% 0 6 0% 2%
 OK 5 1% 1 4 3% 1%
 HI 5 1% 0 5 0% 1%
 AR 4 1% 0 4 0% 1%
 IL 4 1% 0 4 0% 1%
 CT 4 1% 0 4 0% 1%
 PA 4 1% 0 4 0% 1%
 WV 3 1% 1 2 3% 1%
 SC 3 1% 1 2 3% 1%
 WA 3 1% 0 3 0% 1%
 DC 3 1% 0 3 0% 1%
 IA 3 1% 0 3 0% 1%
 NY 2 1% 0 2 0% 1%
 KS 2 1% 0 2 0% 1%
 MN 2 1% 0 2 0% 1%
 UT 2 1% 0 2 0% 1%
 OR 2 1% 0 2 0% 1%
 RI 1 0% 0 1 0% 0%
 NE 1 0% 0 1 0% 0%
 CO 1 0% 0 1 0% 0%
 DE 1 0% 0 1 0% 0%
 NV 1 0% 0 1 0% 0%
Total BC by state
States with fewer than 3 were omitted from graph.

5 star by state

4 star by state

All Players:

State Player Position Rating Stars
 FL Nolan Smith WDE 0.9994 5
 CA Kayvon Thibodeaux WDE 0.9976 5
 LA Derek Stingley CB 0.9973 5
 OH Zach Harrison SDE 0.9970 5
 FL Trey Sanders RB 0.9969 5
 GA Jadon Haselwood WR 0.9968 5
 CA Bru McCoy ATH 0.9954 5
 OK Daxton Hill S 0.9948 5
 LA Ishmael Sopsher DT 0.9946 5
 WV Darnell Wright OT 0.9944 5
 TX Kenyon Green OT 0.9935 5
 LA John Emery Jr. RB 0.9931 5
 GA Wanya Morris OT 0.9929 5
 MS Nakobe Dean ILB 0.9925 5
 GA Owen Pappoe OLB 0.9922 5
 TX Garrett Wilson WR 0.9922 5
 MI Logan Brown OT 0.9921 5
 SC Zacch Pickens SDE 0.9913 5
 GA Andrew Booth CB 0.9905 5
 FL Evan Neal OT 0.9904 5
 TX Theo Wease WR 0.9900 5
 AL Clay Webb OC 0.9897 5
 AZ Spencer Rattler PRO 0.9886 5
 GA Travon Walker DT 0.9886 5
 VA Brandon Smith ILB 0.9886 5
 MI Devontae Dobbs OG 0.9876 5
 FL Frank Ladson WR 0.9873 5
 NJ Antonio Alfano SDE 0.9867 5
 CA Kyle Ford WR 0.9851 5
 TX DeMarvin Leal DT 0.9850 5
 GA Harry Miller OC 0.9845 5
 LA Kardell Thomas OG 0.9844 5
 FL Akeem Dent CB 0.9842 5
 GA Dominick Blaylock WR 0.9841 5
 AL Pierce Quick OT 0.9827 4
 AL George Pickens WR 0.9825 4
 TX Tyler Johnson OT 0.9815 4
 FL Tyrique Stevenson CB 0.9810 4
 NC Quavaris Crouch ATH 0.9807 4
 CA Chris Steele CB 0.9804 4
 CA Henry To’oto’o OLB 0.9800 4
 CA Zach Charbonnet RB 0.9800 4
 CA Mykael Wright CB 0.9793 4
 TX Marcel Brooks OLB 0.9787 4
 MS Jerrion Ealy RB 0.9787 4
 HI Faatui Tuitele DT 0.9780 4
 AL Bo Nix DUAL 0.9777 4
 IN George Karlaftis SDE 0.9773 4
 GA Chris Hinton DT 0.9760 4
 CA Mase Funa ILB 0.9757 4
 CA Joe Ngata WR 0.9746 4
 AL Amari Kight OT 0.9744 4
 TX Jordan Whittington WR 0.9734 4
 CA Ryan Hilinski PRO 0.9731 4
 TX Brian Williams S 0.9723 4
 CA Sean Rhyan OT 0.9706 4
 FL Khris Bogle WDE 0.9701 4
 TX Baylor Cupp TE 0.9700 4
 TX Trejan Bridges WR 0.9699 4
 AR Hudson Henry TE 0.9692 4
 FL Kaiir Elam CB 0.9690 4
 MI Julian Barnett CB 0.9687 4
 TN Maurice Hampton CB 0.9685 4
 CA De’Gabriel Floyd ILB 0.9682 4
 MS Nathan Pickering DT 0.9679 4
 TX Lewis Cine S 0.9676 4
 TX Demani Richardson S 0.9674 4
 OH Jowon Briggs DT 0.9668 4
 FL Jeremiah Payton WR 0.9655 4
 MD Shane Lee ILB 0.9650 4
 NJ Caedan Wallace OG 0.9649 4
 TX Austin Stogner TE 0.9643 4
 CA Jacob Bandes DT 0.9638 4
 CA Jonah Tauanu’u OT 0.9638 4
 GA Justin Eboigbe SDE 0.9636 4
 MD Nick Cross S 0.9633 4
 FL Jordan Battle S 0.9629 4
 FL William Putnam OG 0.9626 4
 NY Adisa Isaac WDE 0.9625 4
 VA Devyn Ford RB 0.9624 4
 AZ Jake Smith WR 0.9620 4
 CA Jayden Daniels DUAL 0.9615 4
 FL Mark-Antony Richards ATH 0.9614 4
 TX Marquez Beason ATH 0.9613 4
 CA Mycah Pittman WR 0.9611 4
 TX Erick Young CB 0.9609 4
 NC Sam Howell PRO 0.9606 4
 MS Byron Young SDE 0.9593 4
 TX Dylan Wright WR 0.9592 4
 FL Rian Davis OLB 0.9590 4
 TX Jeffery Carter CB 0.9589 4
 WV Doug Nester OG 0.9581 4
 NC Savion Jackson SDE 0.9580 4
 MD DeMarcco Hellams S 0.9576 4
 MS Charles Cross OT 0.9574 4
 MS Jaren Handy SDE 0.9571 4
 TX Elijah Higgins WR 0.9570 4
 CA Austin Jones RB 0.9565 4
 MS Brandon Turnage CB 0.9557 4
 AR Treylon Burks WR 0.9550 4
 IN David Bell WR 0.9543 4
 KS Graham Mertz PRO 0.9535 4
 GA Kyle Hamilton S 0.9530 4
 FL Noah Cain RB 0.9529 4
 MS Charles Moore SDE 0.9526 4
 OH Cade Stover OLB 0.9517 4
 GA Ramel Keyton WR 0.9517 4
 MN Quinn Carroll OT 0.9507 4
 MO Isaiah Williams ATH 0.9502 4
 AL Taulia Tagovailoa PRO 0.9502 4
 LA Trey Palmer WR 0.9495 4
 NJ Ronnie Hickman S 0.9493 4
 GA Kevin Harris WDE 0.9492 4
 LA Donte Starks ILB 0.9492 4
 AL Christian Williams CB 0.9490 4
 FL Brendan Gant S 0.9485 4
 MS Dannis Jackson WR 0.9485 4
 FL Dontae Lucas OG 0.9478 4
 OH Zeke Correll OG 0.9477 4
 FL John Dunmore WR 0.9474 4
 VA Sheridan Jones CB 0.9470 4
 GA Trezmen Marshall ILB 0.9468 4
 GA Zion Puckett S 0.9458 4
 CA Jeremiah Criddell S 0.9454 4
 AR Stacey Wilkins OT 0.9450 4
 TX Arjei Henderson WR 0.9449 4
 LA Bryton Constantin OLB 0.9438 4
 CA Trent McDuffie CB 0.9436 4
 TN Bill Norton SDE 0.9429 4
 LA Devonta Lee ATH 0.9428 4
 CA Jason Rodriguez OT 0.9427 4
 HI Enokk Vimahi OG 0.9427 4
 CA Laiatu Latu WDE 0.9424 4
 TN Lance Wilhoite WR 0.9422 4
 GA Kenyatta Watson II CB 0.9419 4
 FL Keon Zipperer TE 0.9410 4
 MI Mazi Smith DT 0.9407 4
 TX NaNa Osafo-Mensah WDE 0.9407 4
 RI Xavier Truss OT 0.9406 4
 MO Jameson Williams WR 0.9404 4
 NE Nick Henrich ILB 0.9399 4
 LA Tyrion Davis RB 0.9396 4
 KY Stephen Herron Jr. WDE 0.9393 4
 CA Sean Dollars APB 0.9390 4
 LA Christian Harris ILB 0.9386 4
 OH Nolan Rumler OG 0.9384 4
 TN Joseph Anderson SDE 0.9383 4
 GA Joseph Charleston S 0.9381 4
 FL Diwun Black ILB 0.9379 4
 TX Branson Bragg OC 0.9378 4
 GA Tyron Hopper OLB 0.9376 4
 CA Max Williams CB 0.9372 4
 AZ Noa Pola-Gates CB 0.9352 4
 LA Ray Parker OT 0.9352 4
 WA Dylan Morris PRO 0.9346 4
 KY Wandale Robinson APB 0.9340 4
 KY Jacob Lacey DT 0.9324 4
 GA Keiondre Jones OG 0.9318 4
 UT Siaki Ika DT 0.9315 4
 GA King Mwikuta WDE 0.9312 4
 FL Tyler Davis DT 0.9310 4
 GA Jaylen McCollough S 0.9308 4
 IL Trevor Keegan OT 0.9307 4
 GA Trente Jones OT 0.9302 4
 CA Drake Jackson SDE 0.9300 4
 TX EJ Ndoma-Ogar OG 0.9298 4
 AL Mohamoud Diabate OLB 0.9288 4
 CA Isaiah Foskey WDE 0.9285 4
 FL Jaquaze Sorrells DT 0.9284 4
 TX Isaiah Spiller APB 0.9284 4
 TN Eric Gray APB 0.9283 4
 FL Travis Jay CB 0.9278 4
 IN Sampson James RB 0.9268 4
 FL Deyavie Hammond OG 0.9262 4
 DC Joseph Weté WDE 0.9261 4
 CT Taisun Phommachanh DUAL 0.9258 4
 VA Jaden Payoute ATH 0.9253 4
 FL Ge’mon Eaford OLB 0.9252 4
 FL Kenny McIntosh RB 0.9248 4
 NJ John Olmstead OT 0.9246 4
 MS Derick Hall WDE 0.9245 4
 AZ Brayden Liebrock TE 0.9241 4
 TX Jalen Curry WR 0.9240 4
 TN Woodi Washington CB 0.9237 4
 FL Keontra Smith S 0.9235 4
 MN Bryce Benhart OT 0.9231 4
 CA Joshua Pakola SDE 0.9231 4
 TX Kam Brown WR 0.9226 4
 TX Marcus Banks CB 0.9222 4
 FL Braylen Ingraham SDE 0.9221 4
 MO Marcus Washington WR 0.9217 4
 HI Maninoa Tufono ILB 0.9212 4
 FL Anthony Solomon OLB 0.9208 4
 GA Jalen Perry CB 0.9207 4
 MI Lance Dixon OLB 0.9207 4
 GA Ryland Goede TE 0.9206 4
 TX Tyler Owens S 0.9206 4
 NC Nolan Groulx WR 0.9205 4
 MI Anthony Bradford OG 0.9203 4
 FL Jaleel McRae OLB 0.9197 4
 FL Josh Delgado WR 0.9197 4
 CA Isaiah Rutherford CB 0.9195 4
 FL Quashon Fuller SDE 0.9195 4
 MS Jonathan Mingo WR 0.9195 4
 TN Kane Patterson ILB 0.9192 4
 CA Chris Adimora S 0.9191 4
 AZ Ty Robinson SDE 0.9191 4
 NC Anthony Harris S 0.9189 4
 LA Makiya Tongue ATH 0.9186 4
 FL Chez Mellusi RB 0.9182 4
 SC Cameron Smith CB 0.9178 4
 NC C.J. Clark DT 0.9176 4
 VA Salim Turner-Muhammad CB 0.9173 4
 TX Roschon Johnson DUAL 0.9172 4
 NC Osita Ekwonu ILB 0.9171 4
 KY Milton Wright WR 0.9169 4
 UT Puka Nacua WR 0.9165 4
 NC Khafre Brown WR 0.9163 4
 MS De’Monte Russell WDE 0.9161 4
 TN Trey Knox WR 0.9159 4
 FL Avery Huff OLB 0.9155 4
 VA Litchfield Ajavon S 0.9148 4
 CA Daniel Heimuli ILB 0.9148 4
 TX Jalen Catalon S 0.9147 4
 VA Cam’Ron Kelly ATH 0.9145 4
 FL Jahfari Harvey WDE 0.9140 4
 TX Deondrick Glass RB 0.9138 4
 FL Jaden Davis CB 0.9138 4
 PA Andrew Kristofic OT 0.9138 4
 NC Tyus Fields CB 0.9136 4
 LA Lance LeGendre DUAL 0.9132 4
 MD Isaiah Hazel WR 0.9132 4
 TX Marcus Stripling SDE 0.9131 4
 GA Derrian Brown RB 0.9129 4
 GA Warren McClendon OT 0.9128 4
 KY Bryan Hudson OG 0.9127 4
 FL Lloyd Summerall WDE 0.9125 4
 NC Donavon Greene WR 0.9123 4
 OK Demariyon Houston WR 0.9120 4
 GA Steele Chambers ATH 0.9119 4
 TX Braedon Mowry WDE 0.9117 4
 CA Hank Bachmeier PRO 0.9116 4
 GA Kalen DeLoach OLB 0.9114 4
 CA Jude Wolfe TE 0.9112 4
 IL Jirehl Brock RB 0.9112 4
 OK Grayson Boomer TE 0.9108 4
 TN Jackson Lampley OG 0.9107 4
 NC Garrett Shrader DUAL 0.9106 4
 AL DJ Dale DT 0.9095 4
 MD D’Von Ellies DT 0.9092 4
 FL Josh Sanguinetti S 0.9087 4
 GA Jashawn Sheffield ATH 0.9086 4
 AL Paul Tyson PRO 0.9086 4
 CA Darren Jones WR 0.9083 4
 CA Stephon Wright SDE 0.9075 4
 CT Cornelius Johnson WR 0.9074 4
 CA Colby Bowman WR 0.9072 4
 CA Tristan Sinclair OLB 0.9072 4
 AR Darius Thomas OT 0.9071 4
 CO Luke McCaffrey ATH 0.9069 4
 MI Dwan Mathis PRO 0.9065 4
 IN Beau Robbins WDE 0.9065 4
 CT Tyler Rudolph S 0.9063 4
 FL Nay’Quan Wright RB 0.9063 4
 MS John Rhys Plumlee DUAL 0.9062 4
 MI Marvin Grant S 0.9061 4
 LA Devin Bush CB 0.9057 4
 TX David Gbenda ILB 0.9055 4
 GA Ja’Darien Boykin WDE 0.9055 4
 CA Drake London WR 0.9054 4
 OR Michael Johnson Jr. DUAL 0.9052 4
 GA Jaelin Humphries DT 0.9051 4
 AZ Jacob Conover PRO 0.9051 4
 DE Saleem Wormley OG 0.9049 4
 NV Cade McNamara PRO 0.9048 4
 AL Jaydon Hill CB 0.9048 4
 FL Derick Hunter SDE 0.9046 4
 NJ John Metchie WR 0.9045 4
 AL Vonta Bentley ILB 0.9043 4
 CA Keyon Ware-Hudson DT 0.9043 4
 FL Michael Tarquin OT 0.9042 4
 NC Joshua Harris DT 0.9039 4
 NJ Taquan Roberson DUAL 0.9039 4
 TX Daimarqua Foster RB 0.9038 4
 GA Curtis Fann SDE 0.9034 4
 KY Tanner Bowles OG 0.9033 4
 MO Jalani Williams S 0.9032 4
 MS Jarrian Jones S 0.9029 4
 TX Peyton Powell ATH 0.9029 4
 IA Ezra Miller OT 0.9029 4
 TX Hunter Spears DT 0.9028 4
 MO Shammond Cooper ILB 0.9027 4
 TX Josh Ellison DT 0.9026 4
 MD Osita Smith S 0.9025 4
 OH Ryan Jacoby OT 0.9023 4
 CA Asa Turner ATH 0.9022 4
 CA Giles Jackson WR 0.9020 4
 NC Tony Davis CB 0.9019 4
 CA Casey Kline ATH 0.9019 4
 IL Jason Bargy SDE 0.9018 4
 IA Max Duggan DUAL 0.9016 4
 FL Te’Cory Couch CB 0.9011 4
 GA K.J. Wallace CB 0.9009 4
 CA Joey Yellen PRO 0.9006 4
 GA Jaelyn Lay TE 0.9005 4
 PA Andre White Jr. ILB 0.9005 4
 MD William Harrod OT 0.9002 4
 FL Wardrick Wilson OG 0.9000 4
 PA Keaton Ellis CB 0.8999 4
 IN Cameron Williams OLB 0.8999 4
 IL Jahleel Billingsley TE 0.8998 4
 NJ David Ojabo SDE 0.8998 4
 VA Jalon Jones DUAL 0.8996 4
 VA Hakeem Beamon SDE 0.8995 4
 TN Keveon Mullins ATH 0.8990 4
 OH Jestin Jacobs OLB 0.8989 4
 FL Raymond Woodie III S 0.8984 4
 GA J.D. Bertrand OLB 0.8980 4
 NY Jason Blissett DT 0.8980 4
 OR Patrick Herbert TE 0.8978 4
 CA Joshua Calvert ILB 0.8977 4
 NC J.R. Walker ATH 0.8977 4
 PA Joey Porter Jr. CB 0.8975 4
 OH Tommy Eichenberg ILB 0.8966 4
 IN Joe Tippmann OT 0.8963 4
 MS KJ Jefferson DUAL 0.8961 4
 CA Cameron Davis RB 0.8960 4
 KY Jared Casey ILB 0.8958 4
 TX Bobby Wolfe CB 0.8958 4
 HI Julius Buelow OT 0.8958 4
 OH Noah Potter SDE 0.8958 4
 MD Darrian Dalcourt OG 0.8958 4
 OH Steven Faucheux DT 0.8958 4
 GA Jaylin Simpson CB 0.8958 4
 CT Marquis Wilson CB 0.8958 4
 NJ Howard Cross SDE 0.8958 4
 CA Braedin Huffman-Dixon WR 0.8958 4
 TX Javonne Shepherd OT 0.8958 4
 AL Peter Parrish DUAL 0.8954 4
 OK Collin Clay SDE 0.8950 4
 OK Marcus Major RB 0.8946 4
 VA Tayvion Robinson ATH 0.8943 4
 KS Marcus Hicks WDE 0.8942 4
 MI Karsen Barnhart OG 0.8942 4
 TN Zion Logue SDE 0.8941 4
 GA Jackson Lowe TE 0.8940 4
 TX Jamal Morris S 0.8940 4
 LA Reginald Johnson WR 0.8939 4
 TX Jacob Zeno PRO 0.8938 4
 GA Mataio Soli WDE 0.8937 4
 GA Colby Wooden WDE 0.8937 4
 OH Erick All TE 0.8937 4
 KY JJ Weaver SDE 0.8937 4
 WA Nathaniel Kalepo OT 0.8937 4
 CA Ethan Rae TE 0.8937 4
 TX Steven Parker WDE 0.8937 4
 CA Jordan Wilmore APB 0.8935 4
 WV Brenton Strange TE 0.8935 4
 AZ Matthew Pola-Mao DT 0.8934 4
 LA Jordan Clark CB 0.8933 4
 MS Raydarious Jones ATH 0.8932 4
 HI Sama Paama DT 0.8929 4
 SC Jamario Holley WR 0.8926 4
 FL Keshawn King RB 0.8925 4
 DC Keilan Robinson RB 0.8925 4
 CA Kamren Fabiculanan CB 0.8921 4
 GA Rashad Cheney DT 0.8920 4
 GA Jamious Griffin RB 0.8917 4
 TX Tamauzia Brown ATH 0.8917 4
 TN Kristian Williams DT 0.8910 4
 TX Isaiah Hookfin OT 0.8910 4
 DC Quinten Johnson S 0.8909 4
 TX Langston Anderson WR 0.8908 4
 OH Moses Douglass S 0.8906 4
 WA Darien Chase ATH 0.8905 4
 FL Mikel Jones OLB 0.8904 4
 FL Shamar Nash WR 0.8904 4
 IA Tyler Endres OT 0.8903 4
 TN Ani Izuchukwu WDE 0.8902 4
 MO Kyren Williams RB 0.8900 4