This is one outlet's own report from Yahoo Sports — the article as it was filed. Other outlets are covering the same event; open the full story to compare every source side by side.
See the full story · 1 sourcesThis is one outlet's own report from Yahoo Sports — the article as it was filed. Other outlets are covering the same event; open the full story to compare every source side by side.
See the full story · 1 sourcesAs training camp battles get underway, two things seem to be written in stone about the Commanders’ wide receiver group. Terry McLaurin has a lock on the WR1 position. And rookie third-round pick Antonio Williams will have every opportunity to compete for a position high on the depth chart.
After those two, most of the final positions on the depth chart are up for grabs.
The team’s two recent draft picks, Luke McCaffrey and Jaylin Lane, are virtual locks to make the final 53-man roster, if for no other reason than their value in the return game. Neither has yet proved to be a reliable second or third receiving option. They will have to compete for playing time on offense, but it would be shocking if either isn’t active on opening day.
That leaves one or two roster spots up for grabs, depending on whether the Commanders keep five or six receivers. The competition for the remaining roster spot(s) at receiver features a host of characters, including cheap 2026 free-agent additions Dyami Brown and Van Jefferson, returning veteran Treylon Burks, 2025 UDFAs Jacoby Jones and Nick Nash, and this year’s UDFA signees, Jaden Bradley and Chris Hilton Jr.
The remaining wild card in the mix is the possibility that the Commanders could sign another free agent, such as Stefon Diggs or Keenan Allen.
A quick reader poll:
Until another signing is announced, which is by no means guaranteed, there is a prime opportunity for a player currently on the margin to claim a roster spot through a standout performance in training camp and the preseason. One reason why Jaden Bradley could be that guy is his better than expected ability to catch the football.
It might seem a strange thing to say, but catching the football is an underrated skillset in wide receivers. Every NFL draft cycle, without fail, some receiver shoots up draft boards after running a fast 40-yard dash at the combine. But when was the last time that a receivers shot up boards because scouts suddenly noticed, late in the process, that he was really good at coming down with the football?
A few months after the draft, when players finally take the field, some late round pick or UDFA invariably emerges as a viable starting receiver. One thing that most of these hidden gems at receiver frequently have in common is being really good at catching the football.
The truth is, it doesn’t matter how much separation a speedy receiver can create if he doesn’t make the catch when he’s targeted. On the other hand, elite catch phase execution can make up for a lot of deficiencies in athletic testing.
The first stat that comes to mind when we think about catching ability is reception rate (Rec %). Unfortunately though, reception rate tells us very little about catching ability because that is drowned out by a major confounding variable, Average Depth of Target (ADOT). Even the most casual football fan will appreciate that it is easier to complete short passes than long passes. As a result, reception rate depends very heavily on the route tree that a receiver runs.
In order to compare two wide receivers in a meaningful way, for example Commanders’ 2026 third-round draft pick Antonio Williams (76.4% reception rate, ADOT 7.7 yds) and UDFA Jaden Bradley (61.7% reception rate, ADOT 16.3 yds), they would need to have run a similar depth of routes. In this case, they didn’t. Superficially, it might appear that Williams was better at catching the ball because his reception rate was higher. But that could just be a byproduct of his average target being less than half as deep as Bradley’s.
In fact, many previous analyses I have done have shown that ADOT explains around 40% of the variance in reception rate at both the NCAA and NFL levels. Statisticians call that level of effect a dominating influence. In order to see the effects of receiving skills, we need to have some way to factor out the confounding effect of ADOT.
My attempt to solve that problem is what first caused Jaden Bradley to cross my radar. Although I didn’t realize it at the time. To explain what I mean, let’s revisit some analysis I did for the roundup of WR draft prospects I published before the 2026 draft.
Catch Rate Over Expectation (CROE)
Two years ago, I developed a metric which I called Catch Rate Over Expectation (CROE) to adjust reception rate for ADOT. In mathematical terms, it is simply the residual of the regression of reception rate on ADOT. If you have no idea what that means, don’t worry. You don’t really need to. And I will walk through it below for those who are interested. All you really need to know is that it measures an individual receiver’s catch rate relative to the expectation for an average receiver based on ADOT alone.
There is another metric popularized in fantasy football circles called Catch Rate Over Expected, which shares the same acronym. That one is an attempt to tease out catching ability from all of the other variables which contribute to reception rate, including separation. Consequently, the fantasy football version gives the erroneous impression that receivers who excel at creating separation aren’t very good at catching the football.
My version of CROE is actually a lot simpler and makes more sense. What we want to know is how likely a receiver is to come down with the ball when targeted, no matter how he gets it done, without being fooled into thinking that receivers with shorter route trees have better ball skills. And that’s what it achieves.
To illustrate how CROE works, the following graph plots reception rate against ADOT for all the draft eligible FBS WRs in 2026 who ran 100 or more routes.
As expected, there is a strong trend for reception rate to decline as ADOT increases.
The regression line (often called the trend line), shown in blue, tracks the central tendency of the scatter of points. This essentially shows the average, or “expected”, va...
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