Weighted Opportunity


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Weighted Opportunity

There are a lot of bad, worthless, noisy, and overused stats in fantasy football. “Touches,” for running backs, might not be at the top of the list … but it’s close.

Why? Because not all touches are created equal. A running back can touch the ball as a runner (rushing attempt) or as a receiver (reception). Rushing attempts are far more common, but receptions are far more valuable. Over the past four seasons, rushing attempts have comprised 81% of all running back touches, though 45% of all running back fantasy points scored have come through the air. How can that be true? Because a reception is worth 3.40 times as much as a rushing attempt in PPR leagues.

Why is “touches” such a bad stat? Because I’ve come up with something much better.

Volume is far more important than efficiency for fantasy running backs, and far more important for running backs than for any other position in fantasy. But “raw touches” doesn't do a good job of measuring volume. “Raw touches” is inferior to raw opportunities (carries + targets), and raw opportunities is inferior to our stat: weighted opportunity.

Weighted opportunity is what it sounds like. It measures a running back’s opportunity, weighted appropriately for the worth of each unit of opportunity (a carry or a target).

On average (over the past four seasons), a single rushing attempt has been worth about 0.61 fantasy points. A target has been worth roughly 1.61 fantasy points. So, broadly speaking, a target is worth 2.64 times as much as a carry in PPR leagues.

The methodology to calculate this was simple. In each year we totaled running back rushing fantasy points and then divided that number by total carries. For targets, we totaled all running back receiving fantasy points and then divided that number by total targets.

However, we can improve upon this further by incorporating red-zone usage. (For simplicity, we’re using PPR points in the next two charts.)


With this knowledge at our disposal, we can better approximate the value of a player’s role than through raw touches. By multiplying a running back’s red-zone carries by 1.32, red-zone targets by 2.32, outside-the-red-zone carries by 0.48, and outside-the-red-zone targets by 1.51, we can sum up these numbers to create what I’ve been calling a running back’s “weighted opportunity.”

Using the methodology I outlined above, here are 2020’s top-30 running backs by weighted opportunity per game:

What does the differential represent?

Should we be avoiding players with a negative differential (assuming this represents a measure of efficiency) or should we be targeting these players (assuming this is a number that tends to regress to the mean)? This isn’t an easy question to answer, but it’s mostly the latter, while still being some of the former.

Last season, Alvin Kamara averaged 19.9 weighted opportunity points per game. By scoring 25.2 fantasy points per game, he produced a +5.3-point differential. It’s not surprising Kamara scored more fantasy points than his weighted opportunity would suggest, just like it’s not surprising Kamara ranked highly in yards-per-carry and yards-per-target average – Kamara is really freaking good. A player’s weighted opportunity is based on the average of all running backs over the past four seasons, and Kamara is much better than a perfectly average running back.

This being said, a differential of +5.3 is very likely to regress to the mean. This doesn’t mean that he’ll necessarily regress in fantasy points per game or weighted opportunity points per game, only that the differential between those two numbers is very likely to be much closer to zero (though still likely well above average) next season. Kamara outscored his weighted opportunity by 79.9 points in 2020, which ranks second-best over the past 10 seasons, behind only… Kamara’s 2017 season (82.8).

Okay, again, Kamara is a true freak outlier. But, typically, we should expect a heavy regression to the mean. Of the top 40 seasons this past decade (by positive differential), 38 regressed the following year. On average the fall was from a differential of +3.37 to +0.27. Of the bottom 40 seasons this past decade, 38 regressed (positively) in efficiency the following year. On average the climb was from -2.82 to -0.50.

Player Analysis

In 2019, Christian McCaffrey set an all-decade record in weighted opportunity points per game (25.6) and was hyper-efficient with that good volume (his +3.9-point differential ranks 17th-best over the past decade). He only played in three games in 2020, but his 23.2 weighted opportunity points per game would have ranked fifth-most and his +6.9-point differential would have ranked best over the past decade.

Dalvin Cook averaged 20.1 weighted opportunity points per game in 2020, which ranks 23rd-most over the past 10 seasons. Alvin Kamara’s 2020 season ranks right behind him (19.9, 24th-most).

As we discussed earlier, when you see a running back wildly out-score their expectation, 29 times out of 30 you’re going to project a significant regression to the mean. But 1 time out of 30, that running back is Alvin Kamara, a true freak outlier. His mean (which you’re regressing to) is naturally going to be a lot higher than that of an average running back. That’s also going to be true for Christian McCaffrey. And I think Derrick Henry, who posted a +5.1-point differential in 2019 (fifth-most this past decade) and a +3.4-point differential in 2020 (21st-most)…

Although I do expect Henry to far exceed his weighted opportunity-based expectation again this season, just note, he’s going to need to. (And that’s still no sure thing, even for the Kamaras of the world. Kamara posted a negative differential in 2019, and Henry averaged a differential of only +1.0 prior to 2019.) But even if he is hyper-efficient again in 2020, it still might not be enough for him to return value at ADP (pick 1.04, one spot behind Kamara). Because he’s a non-factor in the passing game, Henry is at a major disadvantage to his peers — he’s never going to see the volume of the high-end bell cow running backs. Last year he ranked just 8th in weighted opportunity points per game last year (17.4), after ranking 18th in 2019 (14.5). And I think his 2020 numbers were somewhat maxed out. Tennessee posted a .688 Win% in 2020, after a Win% of .563 in 2019, but they have a projected Win% of just .529 this year. Because he doesn’t catch passes, Henry is massively gamescript-dependent — for instance, he averaged 12.8 more FPG in victories (24.8) than losses (12.0) last season. In other words, if Vegas is right, just based on a gamescript regression, Henry’s FPG should drop from 20.8 to 18.4. And that’s with an elite (unstable) differential baked in.

To me, Nick Chubb (+4.9), J.K. Dobbins (+3.1), and Jonathan Taylor (+2.7) are all on the Derrick Henry spectrum. Who is the best / most-efficient pure runner in football? It’s either Chubb or Henry. And Jonathan Taylor already might not be far behind. And, given the Lamar Jackson/Konami Code effect on running backs, J.K. Dobbins is probably the odds on favorite to lead the league in YPC again this year. All three RBs were hyper-efficient last year, and are good bets to be hyper-efficient this year, but they’re going to have to be to return value at current ADP. Why? Because all three are stuck in committee backfields. And all three have an uncertain or low-end target projection. As much as I believe in the talent of running backs like Henry, Chubb, Dobbins, and Taylor, I think all four running backs are overpriced at current ADP.

On the other end of the spectrum, Ezekiel Elliott is an obvious and glaring positive regression candidate. He was fantasy football’s least-efficient running back last year, posting a -2.9-point differential, but averaged +1.3 over his prior four seasons. There’s a legitimate risk that this is “just who he is now” and Tony Pollard will continue to steal work, but I don’t think that’s too realistic. More so, this is just an obvious outlier year for the $90M running back. For one thing, we probably shouldn’t have expected much to begin with, with opposing defenses stacking the box against Andy Dalton (5.34 ANY/A), Garrett Gilbert (4.88), and Ben DiNucci (2.92). For another, he was the league’s most unlucky running back in the touchdown-department, falling 5.4 touchdowns shy of his expectation. That would have been worth an additional 2.2 FPG. And now he gets Dak Prescott back, and, according to multiple reports, Elliott looks much “quicker” and “more elusive” this year.

Joe Mixon (-2.2), Clyde-Edwards-Helaire (-1.6), Josh Jacobs (-1.6), Cam Akers (-1.3), and Austin Ekeler (-0.9) are a few more running backs to get excited about. Frank Gore (-2.5), Kalen Ballage (-2.5), J.D. McKissic (-2.1), Devin Singletary (-1.8), and Joshua Kelley (-1.7) probably aren’t. Simply, I just don’t think Ballage, Singletary, or Kelley or any good, and Gore is cooked. But, I suppose, this could be good news for Antonio Gibson (+2.0) and Zack Moss (-0.3). McKissic saw 110 targets last season but wasn’t very efficient with that good volume. Gibson was a literal wide receiver in college, and the sky would be the limit for him if he absorbed a bulk of those targets in addition to his dozen-plus carries per game.

Scott Barrett combines a unique background in philosophy and investing alongside a lifelong love of football and spreadsheets to serve as FantasyPoints’ Director of Analytics and Lead DFS Writer.