Just in Time for the NFL Draft...
Hello all. It's been a while since the last update but here is the final list of 2021-22 FBS receivers with their Dominator Rating and my own Return on Investment efficiency metric.
First, the table below looks at Dominator Ratings of qualifying players (starting with the top 150 WR in terms of reception yards, I then exclude those more than one standard deviation below the group average of receptions).
- Dominator Rating, or "DR" measures a player’s percentage of team receiving yards plus percentage of team receiving touchdowns.
- This concept was brought to the internet mainstream by the guys at Rotoviz.com.
- They admit the Dominator moniker is not a promise the player will dominate at the next level, but an apt description of how the player dominated his college team's passing game.
- A DR > 50% would suggest NFL superstar potential (top 10 draft pick) for a prospect, 40%-50% would suggest a player worthy of a top 20 pick, 35%-40% indicates late first round/early second, and so on.
Based on 2021-22 FBS stats provided by NCAA.com, here is the Top DR list based on my calculations:
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| Standard Deviation Color Code: Purple >= 3 St Devs above the mean; Blue < 2 above; Green > 1; Yellow Bold < 1; Yellow =< 0; Orange < -1; Red < -2 |
You see a lot of household names in the top half section of the table with Jameson Williams, Drake London, Calvin Austin III, Jahan Dotson, Tyquan Thornton and Treylon Burks which reflects above average Dominator Ratings.
While it is helpful to see how much "market share" a player receives, as an evaluator, it helps to understand how they players got there. Return on Investment (ROI) attempts to help fine tune results to find overlooked prospects.
The Z-Score for each of the following is calculated:
Tgt% = percentage of targets to team passing attempts
Rec% = percentage of receptions to team receptions
Yard%= percentage of yards to team total passing yards
Improvement attempts to show the improvement players gain based on the changes in Yard% over Rec% and Rec% over Tgt%.
Notes:
- Of the highest DR players, Tolbert, Sorenson, Burks, Brownlee, Shakir and Flowers also had ROI > 1 standard deviation above the mean. Solid.
- Players who have the biggest jump from DR to ROI were Singleton from FIU, Pierce from Vandy, Robinson, Jr from Northwestern, Gray from SMU and Bell from Purdue, all of whom will be available in this coming NFL Player Draft. These are guys we would want to take a closer look at to see if there is something we are missing here in terms of the evaluation.
- Players with high DR falling the most in terms of ROI include Robinson and Phillips, both with DR of at least 35% but falling below average in terms of ROI. What does this mean?
- In Robinson's case, he had a high percentage of his teams targets, reception and yards, but his efficiency in comparing yards to receptions and receptions to targets were all decreasing, naturally leading to negative ROI. Here we would want to watch game footage to review the possibility the high DR may be a function of high volume which he will not get in the NFL. Of course, the inefficiency here may be caused by the offensive coordinator's play calling but we won't be able to make a determination until we watch. But what can't be lost here is Robinson was responsible for a huge amount of the Kentucky passing attack regardless of the efficiency decline (lowest metric is at 2.44, so it may be reasonable to deem it nearly impossible to maintain a positive Improvement trend at those levels) and is a top flight prospect.
- In Philips' case it's a declining trend of metrics that are unfortunately not top tier like Robinson, with two of three components being below average. Again, this isn't a "cut and dried" tool to just take the guys with the highest scores, so we have to take a closer look at what is driving this with Phillips who, by many accounts, is seen as a highly desirable prospect for the upcoming NFL Player Draft.
Once again, ROI is a tool to screen out potential players who are sneakily efficient for value that may be overlooked due to numerous reasons each draft season. The numbers make it pretty plain if the metric is "high" or "low" however, following up with game footage review to make sense of the numbers would be the best way to use this data.
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If you can stomach the poor commentating, go back and check out The Trouble with Sam, my review of former NY Jets QB Sam Darnold's game play vs. the Chiefs two years ago that pinpointed why it was clear his time in NY had to come to an end.
