NFL 2023 – Wide Receiver & Tight End Ratings & Rankings

Next job, Rating & Ranking NFL Wide Receivers & Tight Ends through week 11.  The 32 quarterbacks were graded with QB Score.  We graded the 32 offensive lines & defensive lines. So onto ranking the wide receivers and tight ends.

88 wide receivers & 30 tight ends qualified for rankings, so let’s get right to it, starting with methodology.  The unusual team abbreviation in some charts come from pro-football-reference.com where the statistics are drawn from.  You will find PDF links for all the receiver & tight ends rankings & ratings.

NFL Wide Receiver & Tight End Ratings & Rankings

The chart below shows the NFL top 20 receivers & tight ends through 11 weeks. One list is from ESPN, the other list are these rankings.  The players the two lists agree on are color coded.  The receiver ranking lists agree on 11 players: Brown, Aiyuk, Lamb, Moore, Kittle(TE), Allen, Collins, Dell, Hill, Evans, Metcalf.

Let’s set them aside for a moment and look at who they disagree on for Top 20 rankings.

The  9 players from the left list are: Thielen, Beckham, Bourne, Raymond, Flowers, Downs, Meyers, Andrews(TE), McBride(TE).

The 9 players from the right list are: Jefferson, St. Brown, Chase, Kelce(TE), Waddle, Nacua, Diggs, Shaheed, Samuel.

Which ranking list do you think is a more accurate, or more flawed?  It is fine to think they are equally accurate, or equally flawed.

Top 20 NFL Wide Receivers & Tight Ends Through Week 11

The Receivers & Tight End Rankings Quiz Answer

The list on the left is the ESPN Analytics Receiver Rankings.  The list on the right are the ratings and ranking you will read about here.

Ranking & Rating Wide Receivers & Tight Ends

Ok, let’s link right to https://espnanalytics.com/rtm/ where you can find, play with, and sort the updated ESPN Receiver Tracking Metrics. They are also posted below.  ESPN scores receivers in 3 categories:

• Open – assesses the likelihood a receiver would be able to complete a catch, conditional on if he were targeted.
• Catch – the model estimates the probability of a completion. If a completion occurs, the receiver is credited with the marginal difference.
• YAC –  looks at the tracking data at the time of catch and makes a prediction of how many additional yards a receiver will typically make, based on the locations, directions and speeds of all 22 players
• QB Factor -Quarterbacks are clearly an essential factor in whether a receiver makes catches and gains yards. RTMs account for who’s throwing the pass in two ways:
  • ESPN adjusts the Catch Score and the part of the Open Score that assesses openness at pass arrival based on the quarterback.
  • ESPN uses pass accuracy data from ESPN’s video analysis tracking to adjust both the Catch Score and YAC Score based on the accuracy (high, low, ahead, behind) and intent of the throw.

This sounds great and I like it.  But, it is proprietary(Only ESPN knows how it is calculated and has access to the data used), and it just has some really strange scores in certain places.  Overall, Tyreek Hill is 11th just below Odell Beckham Jr in 10th…I’m not sure which NFL GM is making that trade.

I like Kalif Raymond(Overall 68), but I do not believe he is tied for 12th best receiver in the NFL with 282 yards receiving and a yards/rt of 2.1.  Maybe one day he will be, but not in 2023. I think Mike Evans, ranked below him, would agree.  You can read about RTM here: Explaining ESPN Analytics RTM

PDF: ESPN Analytics Receiver Tracking Metrics Rankings

ESPN Receiver Tight End Metrics Scores

Statistical Metrics Used By ESPN Analytics RTM

If you read the entire RTM article, you will see ESPN is using computer models, video models, and the player tracking data(speed/direction).  Much of this data is not public, so we need to try to figure out what kind of statistical metrics we could use, and find on pro-football-reference.com, that could replace the models, staff, and technology ESPN has spent millions on.

The models, most likely, have all the statistics we could use available to them.  Whether or not any individual statistic is used is something only ESPN knows. Let’s see if we can come up with a list of statistics we could easily grab and use that would help rate wide receivers and tight ends in a way similar to the way ESPN Analytics does it.

Open Score

OPEN is probably some mix of receiver/cb separation(a metric pfr doesn’t have), target%, & passer rating.  I would love to be able to tell you, but ESPN doesn’t want to share.  I can’t even tell you whether this is an objective(a literal measurement), or subjective(someone’s opinion or rating) measure.  If you want my best guess, I’d say Passer Rating is a major factor.

Passer rating when targeted next to them: Allen 117.5, Aiyuk 121.1, Wilson 64.8, Brown 112.9, Lamb 128.6, Dell 112.7, Raymond 114.4, Evans 113.9, Andrews 133.5.  To make sense of Garrett Wilson, it could be that the metric is PR when target relative to the QBs base PR.  In other words, how much higher is the QBs PR when throwing to this receiver compared to any of his receivers.  Not sure, maybe ESPN is just tossing the poor suffering Jets fans a bone, but it does appear as if PR correlates fairly well with ESPN YAC score.

Fun Note:  Van Jefferson apparently couldn’t get open if he was a swinging door.  ESPN gives him an OPEN rating of 15, the lowest value of any rating on the chart.

Catch Score

CATCH has to include Drop% somehow.  After that I would be guessing, but contested catch% would be a logical choice(another stat pfd doesn’t offer).  Maybe something like catch probability could be in there.  I can tell you it is not solely Drop%, and that Drop% does not seem to correlate well with CATCH score.

AJ Brown has 8 drops and a 7.4% drop% which puts him in the 11th pecentile.  CeeDee Lamb has 1 drop for a 1.1% Drop%.  Brown is #1 for catch at 99, Lamb is #2 at 96.  Michael Pittman has 66 reception with 0 drops.  He is ranked 26th in CATCH by ESPN with a score of 59.

Fun Note: Chris Olave may want to talk to Lester Hayes about some leftover Stickum.  ESPN gives Olave a CATCH score of 26.

YAC Score

YACatch would seem to be a  meaningful stat for both WR and TE.  The average YACatch for wide receivers is 4.1 and the average YACatch for tight ends is 4.5.  Rashee Rice leads this metric at 8.1, Deebo Samuel  7.8, Nico Collins 7.1.  For tight ends, Njoku leads at 7.8, Jonnu Smith 7.5, & Kittle at 6.4.

Look at the ESPNAnalytics list sorted by YAC.  I gave you the top 3 for YAC/reception for wide receivers and tight ends.  All 6 names are in the top 9 for YAC by ESPNAnalytics. The other three:  DJ Moore 6.2, Bourne 5.5, Wicks 6.1. It’s not perfect but it’s close.  So we have one of the 3 sub scores demystified a bit.

Fun Note:  Apparently Courtland Sutton instantly turns into a extremely fragile tortoise whenever he catches the ball.  ESPN gives Sutton a YAC score of 19, the 2nd lowest value on the chart.

With YAC kind of sorted, if ESPN told us how they calculated the OPEN, CATCH & OVERALL Metrics, we could see why they come up with nonsense sometimes much like QBR.  But I guess billion dollar companies need their secrets.  So let’s see what one dude with Google sheets can do compared to the ESPN juggernaut.

The Comparative WR/TE Receiving Metrics

Here is the list of metrics I chose to use for rating the wide receivers and tight ends.

• 1st Downs / Game
• Yards Before Catch / Reception
• Yards After Catch / Reception
• Average Depth of Target
• Drop % (inverse – lower drop % score higher)
• Passer Rating when Targeted
• Target % (Targets/Routes)
• Reception % (Receptions/Targets)
• Receiving Yards / Route

Now you may have read the other ratings articles I’ve done and noted how ratings are often done by Standard Deviation(StDev in sheets) Units.  Let’s do something a little different and use Normal Distribution(normdist in sheets) instead of StDev. Just remember, like all of the ratings done here, the wide receiver & tight end ratings are COMPARATIVE. 

In comparative ratings, scores are generated by the performance of one receiver against all receivers, and same for tight ends.  Basically, each receiver reeieves a score between 0 – 0.999 for each metric, based on their position in that metric compared to their peers.  The player with the highest score in a metric may get 0.98 score, while the lowest may get a score of 0.02.  This is quite different from almost all other NFL ratings and rankings, but useful in that it shows who is the best among the position groups when compared to each other, not some standard or formula.

What is Normal Distribution?

Remember on the SAT or ACT tests you would being given the percentile you scored in for Math & English.  For example, you scored 570 on the Math SAT which was the 77th pct for Math(I am making this up).  Changing the the result from a standard numerical score to a percentile is Normal Distribution.  It’s our old friend the Bell Curve.

And guess what it uses to do it…StDev.  All normal distribution is doing is converting StDev units into a percentile.  If you look at QB Score you will see each quaterback is given a StDev score, almost always between -3 and +3 for each metric.  All normal distribution does is change that -3 to +3 StDev score into a score between 0 and 1.

Percentile Scoring Made Simple

That’s it.  By doing it, you create a percentile(0.77 or 77th percentile).  So a score of 1.95 StDev units is probably going to score right around 97% percentile by very nature of standard deviation which tries to keep all the data between -3 and +3 StDev units.  A score of -1.50 StDev is probably down in the 7%-8% perecentile.

It is simply a different way of showing the same thing.  You can see percential relative to standard deviation in the chart above.  The percentile rank is shown on the orange line at the bottom.

So take a look at these charts.  One is ranking the wide receivers, the other is ranking the tight ends.  Here is the important info:

• Next to each metric is the normalized score for that stat.
• Add up the scores for each of the 9 metrics to get a final score.
• Normal Distribution is used on the Final Scores to generated a percentile for each receiver & tight end.
• Receivers are measured against receivers, & tight ends are measured against tight ends.
• Thus the percentile score of a wide receiver is the percentile of wide receivers they fall into, and same for tight ends.
• The last 4 columns are ESPN Analytics scores and rankings for comparison.
• There will be PDFs available as some images don’t scall well, particularly on mobile devices.

PDF  NFL 2023 Wide Receiver Ratings

PDF  NFL 2023 Tight End Ratings

Measuring & Ranking the Wide Receiver Units by Team

Let’s try to go one step further and estimate the quality of each team’s wide receiver unit.  To do so we are going to simply average out their wide receiver scores and compare those averages.  It would be better to try to do weighted averages that take into account share of targets or completions in some way, but it would be much more difficult and would require determining the best way to weigh each receiver’s input.  So let’s cheat a bit and just look at simple averages and see how accurate they are.

In this pivot table you will see each teams rated receivers, along with the team average.  I also included a table showing each team’s receiver ratings based on those averages.  In this ultra simple look at it, the best receiving units are San Francisco, Miami, & Philadelphia.  The worst are the Jets 3rd from bottom, Washington, & Carolina is last.

Adding In The Tight Ends

Now that we have the receivers all sorted by team, let’s add in the tight ends.  Some teams did not have a qualified tight end.  If this happened, then it is shown as N/A.  Other teams had 2 tight ends who qualified for rankings.  If this was the case, both are included.

To makes things easy for you to find your team and ratings, the info has be broken down by conference, by division, and by team.  This should make comparing and contrasting easy and allow you to focus on your team, division or conference as you see fit.

Changing Receiver & Tight End Scores Into Percentiles

Now let’s simply change the scores into percentiles by multiplying by 100 so you can see where each receiver ranks against other receivers, and where each tight ranks against their fellow peers.  Again it is broken down into conferences, divisions, and teams to make it easy to read and digest.  And if we simply round the %, we get the second chart.

Best & Worst Receiving & Tight End Units

Using the final rounded percentiles, we can see that the San Francisco 49ers have the best combination of receivers & tight end.  Aiyuk is the #1 rated WR in the 99%, Samuel is a very strong 76% and Kittle is #1 Tight End at 98%.

Other teams with strong receiving units:

• Houston: Collins 96%, Dell 86%, Schultz 81%
• Miami: Hill 96%, Waddle 80%
• Minnesota: Jefferson 98%, Addison 69%, Hockenson 87%
• Baltimore: Beckham 66%, Flower 60%, Edwards 94%
• Philadelphia: Brown 97%, Smith 69%, Goedert 62%
• Detroit: St. Brown 89%, Reynolds 54%, LaPorte 75%

The Bears are quite good with 2 of 3 places set in Moore 96% & Kmet 76% but Mooney 31% is a weak link.

Team with weak receiving units:

• Carolina: Thielen 66%, Chark 14%, Hurst 8%
• Washington: McLaurin 40%, Samuel 30%, Thomas 46%
• NY Jets: Wilson 43%, Lazard 7%, Conklin 56%
• NY Giants: Slayton 37%, Robinson 32%, Waller 70%

The Chiefs are ranked between the Jets & Giants overall but they have Kelce 93% and Rice 63% so they are thin but not hopeless.

Comparing Wide Receivers & Tight Ends – Everyone in the Pool

So we have our comparative wide receiver rankings & our comparative tight end rankings, but what if we looked at all of them as “receivers”?  Before we compared a wide receiver to all wide receivers, and likewise for tight ends, but what if we compared them all to each other regardless of position.

The first thing we have to realize is that since we are doing comparative ratings, this may change the order of individual receivers and tight ends relative to their peers.  Why?  Because now each player is slotted somewhere between 1 -118, instead of 1 – 88 or 1 -30.

So when everyone is in the pool, there may be extra players in between when each metric is scored. This means slightly different scores for each metric and as a result, a slightly different final score.  It won’t be a huge swing for any individual player, but two receivers who were close in the receiver only comparison may swap places when the tight ends are added in.

You can see an example of this right at the tip of the next chart.  A.J. Brown who was ranked #4 in the wide receivers rankings has now dropped to #6 behind Tyreek Hill and Nico Collins.  Brown & Hill have normalized scores of 0.965 and Collins 0.960 when just looking at receivers.  When the tight ends are thrown in the pool the new scores are Hill 0.974, Collins 0.972, Brown 0.971.  Multiplying by 100 would give us  the standard 1-99 grades.

So we are literally splitting hairs out in the 1/1000ths area, but the ratings are slightly different.  When we round, Brown & Hill were originally 97 and Collins a 96 when comparing wide receivers to only other wide receivers.  When we put the tight ends into the mix, all three score a 97 when rounded so it all came out in the wash.

Wide Receivers & Tight Ends Metrics Chart

PDF:   NFL 2023 Tight End Wide Receiver Metrics

Now let’s just hide all the metrics so we can see the grades.  Again the last four columns show the ESPNAnalytics scores for comparison.  Now we are looking at grades for “receivers”; wide receivers and tight ends compared to each other.  This might be looked at as a Fantasy Football ratings for receivers and tight ends since it is mixing them together and treating them as a single group.

Wide Receivers & Tight Ends Ratings & Rankings – Single Pool

PDF: NFL 2023 Tight End Wide Receiver Scores

Creating Sub-scores for Open Catch & YAC

What if we wanted to be cool like ESPN, and create sub scores for OPEN, CATCH & YAC?  First we have to decide which metrics to use for each sub score.  I am using the same 9 metrics we used for the ratings.  I realize this may not be the ideal way to calculate the sub scores(we should bring other metrics in for each sub score), but we don’t have the vast resources ESPN does, so let’s wing it.

I am going to assign 3 metrics to each sub score, using all 9 metrics in the process.  I won’t make the argument as to why each was assigned where it was, but hopefully you will see some logic in it.

OPEN = YBR / Rec + Passer Rating + Target %

CATCH = Drop % + 1st Downs / Game + Reception %

YAC = YAC / Rec + ADOT + Yards / Route

Now all we have to do is treat the sub score sums as a metric, use the same normal distribution, and we create the sub score for OPEN CATCH & YAC.

Let’s look at the wide receiver ratings with our ESPN like sub scores.  The ESPN Analytics ratings are still in red, while the new subscore we create are in blue.

PDF  NFL 2023 Wide Receiver Ratings Open Catch YAC
PDF NFL 2023 Tight End Ratings Open Catch YAC

Creating the False Bottom Scores

Ok this isn’t too bad.  The sub scores we created, because they are comparative, go all the way down to 1, while the ESPN subscores and ratings have a minimum score, seemingly around 25 or 30(there are a couple scores below 20, and a handful below 30).  My guess is this is simply done not to embarrass any players by scoring them a 1 in CATCH, OPEN, YAC or OVERALL.  Someone, or someone(s), is going to be the lowest whether the score is a 25, a 30 or a 1.  But 25 or 30 is probably more palatable then seeing yourself rated a 1, so it spares some feelings.  And ESPN has to ask these guys for interviews so…..

Well that is an easy fix.  We can be as polite as ESPN.  With a simple IF statement and choosing a bottom score, we can easily mimic ESPN and spare the feelings of the slow, unopen, or stone-handed.  I decided to set a minimum score of 30 just to be extra nice to everyone.

NFL 2023 Wide Receiver & Tight Ends Grade Scores

PDF NFL 2023 Wide Receiver Ratings Open Catch YAC with min
PDF NFL 2023 Tight End Ratings Open Catch YAC with min

Ranking the Wide Receivers & Tight Ends with OPEN CATCH YAC & Grade

Now if we throw all the wide receivers and Tight Ends back into one pool, we get the final list of ratings along with sub scores.  PDF:  NFL 2023 Tight End Wide Receiver Scores Mins

NFL 2023 Wide Receiver & Tight End Ratings

So there you have it.  A non proprietary comparative ranking of NFL wide receivers & tight ends through week 12.  I am sure there will be questions and criticisms, but that is part of the fun.  It may not be better than ESPN Analytics but it isn’t too bad for one guy with Google Sheets.  Now I just need to work on that floating heads chart thing they have…..

As with all the ratings and analysis, feel free to chime in via the post on Reddit/r/nfl, Practicalist on Reddit, or by sending an email.  Until next week, enjoy the football and best of luck to your team.