Expected Fantasy Points: Wide Receiver Usage & Efficiency (Fantasy Football)

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In the second installment of our Expected Fantasy Points (xFP) off-season series, we shift our focus to the wide receiver position. Unlike with running backs, we will primarily focus on receiving opportunities in this article, as receivers are very rarely heavily involved in the running game. The exception is, of course, Deebo Samuel, who set a new trend as a dual-threat weapon in Kyle Shanahan’s offense. More on his unique usage later in the article! 

In this piece we will discuss:

  • Wide Receiver Usage
  • Wide Receiver Leaders in Expected Fantasy Points
  • Most/Least Efficient Wide Receiver
  • Efficiency Regression

Wide Receiver Usage And Their Expected Fantasy Value

As I mentioned in my Running Back xFP article, there are a variety of methods to assess a player’s expected value for fantasy. Naturally, it will vary depending on where the play occurs and the type of opportunity that they receive. That brings us to the chart below!

Once again, this chart is meant to replicate a football field. The possession team starts on the left side of the x-axis, with the goal of scoring in their opponent’s end-zone on the far right. The distance to the goal begins at 99 yards all the way to the 1-yard line. If you read my first article in the series, this should not come as a surprise: a rush attempt is valued significantly less than a target. The value of an opportunity also drastically increases the closer we are to the end zone. A few more observations:

  • Average Value of a WR Rush Attempt: 0.84 PPR points
  • Average Value of a WR Target: 1.81 PPR points
  • A WR target is 2.16x more valuable than a rush attempt in PPR
  • The gap shrinks slightly inside the 10 as a target is only 1.54x more valuable than a rush attempt
  • Interestingly, a WR rushing opportunity has historically generated more fantasy points than an RB rush attempt (0.84 vs 0.60)

Keep in mind that the value of a receiving opportunity is heavily driven by the depth of target (or ADOT). For the data above, I assumed an ADOT of 10.98, which is the average for a WR target since 2013. The higher the depth of the target, the more fantasy points we should expect from that opportunity.

With this information in mind, here are some of the details on how my Expected Points model works:

  • Each opportunity is evaluated separately as a Rush Attempt, Target, or Pass Attempt
  • Down and Distance: The lower the down and distance, the higher the expected value will be
  • Yard Line: The closer we are to the end-zone, the more points we can expect
  • Depth of Target: As mentioned before, deeper targets equal higher expected fantasy points. Depth of target is also known as Air Yards.

Once we total the expected value of a player’s opportunities, we arrive at Expected Fantasy Points (or xFP). This is essentially a usage metric that highlights the most valuable players for fantasy. The difference between xFP and their actual PPR score is known as Fantasy Points Over Expected (or FPOE), highlighting a player’s efficiency compared to the average player.

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For example, let’s take a look at Justin Jefferson’s numbers:

  • Expected PPR value: 17.24 per game
  • Actual PPR points: 19.44 per game
  • FPOE: 2.20 per game

Jefferson ranked within the top-13 in both xFP and FPOE, which signifies that he was one of the most heavily utilized and efficient receivers for fantasy last season.

Let’s dive into the rest of the data!

Fantasy Usage Leaders

Charted above the top-24 wide receivers in expected fantasy points. In other words, these players would have finished as WR1s and WR2s had they performed up to their expected value. 

We have to start this segment by discussing Cooper Kupp and the historic season that he just put together, averaging the 3rd highest PPR points per game in the Super Bowl Era behind only Wes Chandler and Jerry Rice. From a usage standpoint, he was far and away the WR1 in xFP as the only receiver to average over 19 expected PPR points per game in 2021. And while he only averaged 32.1% of the Los Angeles Rams’ total air yards per game (WR19), Kupp was the most productive receiver after catch leading the league in YAC share per game at 39.6%. As a result, it should not come as a surprise that Kupp also graded as my WR1 in FPOE per game, scoring 6.11 PPR points above average. With Robert Woods no longer on the team and the already established connection with Stafford, I fully expect Kupp to remain productive in 2022, even if his efficiency regresses slightly to the mean.

One of the most unexpected results coming out of my xFP model was how highly Diontae Johnson ranked in usage, slotting in as the WR3 with 17.95 expected PPR points per game. In a very productive year, he essentially set career-highs in every opportunity metric while leading the Steelers in target share (28.4%), air yards share (35.2%), and YAC share (28.3%). From an efficiency standpoint, Johnson finished with a disappointing -0.80 FPOE. That is likely driven by Ben Roethlisberger’s subpar efficiency, as every Steelers wide receiver finished below their expected receiving value in 2021. With rookie QB Kenny Pickett likely leading this offense going forward, Johnson’s value is somewhat in flux. But as long as he continues to dominate their targets, he will continue to have low-end WR1 upside in 2022. 

Perhaps one of the most surprising developments this past season was having a Ravens wide receiver finish within the top-10 in expected PPR points, despite their run-heavy offense and the dominating presence of Mark Andrews. Yet that’s exactly what happened as Marquise Brown finished the year as the WR9 in xFP with 15.64 expected points per game. Hollywood will obviously be in a much more pass-friendly offense next season after being traded to the Cardinals. However, Brown’s usage should not be dismissed as this could be a preview of Rashod Bateman’s potential breakout campaign. If he can receive the same volume operating as Lamar Jackson’s WR1, it would not surprise me to see Bateman finish as a WR2 or better this upcoming season.

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Lastly, I wanted to highlight a player who I believe could be of tremendous value in 2022: Bears WR Darnell Mooney. Finishing the year as the WR14 in expected PPR value at 14.22 per game, Mooney already took a significant step forward by improving his target share by nearly 10 percentage points at 26.7%. And with the departure of Allen Robinson, Mooney might have a path to even more volume in 2022, with rookie Velus Jones Jr. as the only significant addition to their WR corps (sorry, Dante Pettis). At his current ADP of WR31, Mooney could be a value in the middle rounds of drafts this season.

Fantasy Efficiency Leaders

Next up, let’s take a look at the most efficient wide receivers from the 2021 season. In other words, these are the receivers that performed well above their expected value.

While Kupp stole the spotlight with a historic campaign, Deebo Samuel was equally impressive in his breakout season. Two things stand out with his production. First of all, Samuel was one of the most efficient receivers with +5.89 FPOE. In fact, Samuel’s season is the 4th most efficient campaign in my xFP database that goes back to 2013. Second of all, his usage slowly shifted halfway through the season. In his first 8 games, Samuel was the WR2 in target share at 32.3%, while accounting for 19.1% of his team’s total opportunities (targets + rush attempts). In his final 8 games, his target share dropped to 18.5%, but his opportunity share remained flat (19.2%). How is that possible? He also averaged a unique 19.7% rushing share starting in week 10. So while he was less involved as a receiver, Samuel remained a focal point of the 49ers’ offense in the back half of the season.

Ja’Marr Chase had a record-setting year, averaging the most PPR points by a rookie since Odell Beckham Jr. in 2013. What stands out in his production is his elite efficiency, ranking as the WR3 in FPOE (+4.36) this past season. And while some of that is driven by the offense as a whole, as three Bengals receivers finished in the top-16 in FPOE, Chase still stands out as the most efficient of the bunch. The concern with Chase, however, is his overall volume as he only ranked as the WR18 in xFP (13.56), with both Tyler Boyd and Tee Higgins heavily involved in Zac Taylor’s offense. If he does regress to the mean and his target share remains in the 23% range, it is entirely possible that he does not live up to his WR3 ADP in 2022. 

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Lastly, Cardinals WR DeAndre Hopkins is another player to keep an eye on as he heavily relied on his efficiency to produce for fantasy. In 2021, Hopkins scored 8 times on only 42 receptions, averaging an absurd 19% touchdown rate. For reference, the average WR touchdown rate since 2013 is 7.9%. If Hopkins’ efficiency does decline, fantasy managers could be in a for a disappointing season as he was only the WR37 in xFP (11.68 per game). Thankfully, you will not have to reach for him in fantasy drafts as his ADP is currently at WR37 due to his suspension. But even then, I would not bank on the fact that Hopkins will return anywhere close to WR1 production as he did in 2020, especially with Marquise Brown joining the team and Rondale Moore potentially taking a Sophomore leap.

Fantasy Inefficiency Leaders

Finally, above are the bottom 12 wide receivers in FPOE, averaging the most points BELOW expected in 2021.

In the previous segment, we discussed a couple of players who relied heavily on their efficiency to produce for fantasy. D.J. Moore is the opposite as his volume carried his fantasy value, averaging the 7th most expected PPR points at 16.41. Unfortunately, he also finished as the WR168 (not a typo) in FPOE at -2.44 per game. Ironically, Moore started the year as one of the most efficient receivers, averaging 3.52 points above expected up until Week 4. In his final 13 games, however, he would only score one touchdown, severely hurting his FPOE. Despite that, Moore remains one of my favorite targets in dynasty and redraft as I fully expect him to maintain his volume, with the potential that his FPOE regresses into positive territory.

Unlike Moore, Allen Robinson was not only inefficient (-2.21 FPOE), but he also averaged a career-low xFP at only 9.46 per game (WR52). Naturally, this would be a sign to fully dismiss Robinson heading into 2022, except he signed with the Los Angeles Rams this offseason. With Stafford now throwing him the ball, I would not be surprised if Robinson averages a positive FPOE, similar to Cooper Kupp, Robert Woods, and Van Jefferson in 2021. And with ARob slotting in as the WR2 for the defending champions, we could see an improvement in both efficiency AND volume this season.

Similar to Robinson, Kenny Golladay was both inefficient (-3.33 FPOE) and underutilized in the Giants’ offense with only 9.69 expected PPR points (WR48). However, I have very little optimism regarding Golladay’s potential in 2022. While he did deal with multiple injuries last year, Saquon Barkley and Kadarius Toney (assuming he is not traded) are set to come back fully healthy. In addition, the Giants also added a dynamic rookie receiver in Wan’Dale Robinson, who will likely command a few opportunities even in his rookie year. So while regression could be on the horizon for Golladay’s efficiency, his usage and expected value could remain capped in a crowded WR corps.

FPOE Regression

When it comes to Fantasy Points Over Expected (FPOE), players tend to experience regression year over year. Among the WRs since 2013 to average a positive FPOE, 75.2% produced closer to the mean (or zero) the following year. The average decline in FPOE for those players is roughly 1.72 per game. 

On the other hand, of the WRs who averaged a negative FPOE, 72.9% performed more efficiently the following year. The average increase for those players is 1.61 FPOE per game. 

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Keep in mind that a player could still regress down to the mean and finish the year with positive FPOE, especially if they were significantly above average like a Deebo Samuel.

Regardless, the main takeaway should be this:

  • Volume and xFP dictate the baseline of a player’s fantasy production. Target players who relied on volume to produce and could experience an improvement in FPOE, such as D.J. Moore or Diontae Johnson
  • Be slightly cautious about players who rely on efficiency to produce, such as Adam Thielen or even Ja’Marr Chase. If their volume remains unchanged while their efficiency regresses to the mean, they will be less productive this following season

If you have any specific questions on xFP and FPOE, reach out on Twitter @FF_MarvinE.

xFP and FPOE Summary

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Comments

dirtmcgirt810 says:

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