Expected Fantasy Points: Running Back Usage & Efficiency (Fantasy Football)

Not every opportunity is created equal, which is why a running back’s value will vary depending on their unique usage. Are they leveraged in the red zone? Are they used as a receiver? Do they only take the field in short-yardage situations? Answering some of these questions will give us a better idea of which running backs are most valuable for fantasy managers. To do so, we will leverage a metric called Expected Fantasy Points, which will help assess each player’s usage and efficiency last season. In this piece we will discuss:

• Running Back Usage
• Running Back Leaders in Expected Fantasy Points
• Most/Least Efficient Running Backs
• Efficiency Regression

Running Back Usage And Their Expected Fantasy Value

There are a variety of ways to calculate a running back’s estimated value for fantasy. And if you read, my Expected Fantasy Points series from the last off-season, you might already be familiar with this concept. The premise is that every target or rush attempt has its own unique value for fantasy purposes, and will also vary depending on the position that we are analyzing. Focusing on running backs, the chart below should give us an idea of just how different each opportunity truly is.

Imagine that the chart above is a replica of a football field. The possession team starts on the left side, with the goal of scoring in their opponent’s end-zone on the far right. The x-axis represents the distance to the goal starting at 99 yards all the way to the 1-yard line. As you can see, the value of rushing and receiving opportunities significantly increases the closer you get into the red zone. A few observations:

• Average Value of an RB Rush Attempt: 0.60 PPR points
• Average Value of an RB Target: 1.57 PPR points
• An RB target is 2.62x more valuable than a rush attempt in PPR
• The gap shrinks slightly inside the 10 as a target is only 1.79x more valuable than a rush attempt

Naturally, we want our running backs heavily involved in the receiving game and inside the red zone where we see the highest expected value for fantasy. With this information in mind, here are 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: For receiving opportunities, the deeper targets have a much higher expected PPR value

Once we total the expected value for 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.

For example, let’s take a look at Jonathan Taylor’s numbers:

• Expected PPR value: 19.69 per game
• Actual PPR points: 21.95 per game
• FPOE: +2.26 per game

In short, not only was Jonathan Taylor one of the most valuable players for fantasy (as evidenced by his Expected PPR value), but he was also very efficient with his opportunities scoring 2.26 points above average!

Let’s dive into the rest of the data!

Fantasy Usage Leaders

Above are the top-24 running backs in Expected Fantasy Points per game from this past season based on down, distance, and yards to goal. In other words, these are the RBs that would have finished as RB1s and RB2s had they performed up to their expected value. A few observations:

Derrick Henry was truly dominant for fantasy managers (albeit for only 8 games) as he led all running backs in Expected PPR points with 21.75. This should not necessarily come as a surprise as he averaged an absurd 29.9 opportunities on an impressive 46.4% opportunity share. In other words, Henry accounted for nearly half of the Tennessee Titans’ opportunities on a per-game basis! More impressively, the majority of that usage was on the ground as his rushing opportunities accounted for 80.5% of his expected PPR points

Leonard Fournette is the perfect example of why “quality over quantity” matters for RB opportunities. While he was only the RB15 in opportunity share at 28.9%, Fournette finished as the RB3 in Expected Fantasy Points per game with 20.24. What’s especially unique with Fournette’s usage is that it was heavily driven by his work as a pass-catcher, with 11.2 (or 55.4%) of his xFP coming from the receiving game. He also finished the season as the RB6 in target share at 14%. With this in mind, it will be interesting to see how much of his receiving work will be siphoned by the rookie Rachaad White, who was an excellent pass catcher at Arizona State. And if Fournette receives fewer high-value touches, we could be looking at a decline in fantasy usage in 2022.

While it may have seemed like a slightly disappointing season for Antonio Gibson, his fantasy usage actually came in within the top-12 last season at 16.11 per game. In addition, he was the RB9 in opportunity share accounting for 32.4% of Washington’s rush attempts and targets. Keep in mind that this included multiple games prior to their bye week in which he was managing a shin injury while playing on only 38% of the offensive snaps. If he never got injured, his final usage numbers would have likely finished above RB12. Unfortunately, we may never see Gibson fully unleashed as the Commanders recently added 3rd-round pick, Brian Robinson. And while he was not the most productive prospect at Alabama, Robinson will likely steal a few opportunities from Gibson, capping his overall upside.

Ezekiel Elliott has been trending in the wrong direction as he set career lows in expected PPR points (15.3) and opportunity share (27.2%) in 2021. In addition, Elliott also saw the lowest target share of his career since his rookie season, averaging only 10.2% this past year. On the flip side, his running mate Tony Pollard set career highs in each of those metrics in 2021, adding to the concern that Elliott’s time as an RB1 could be coming to a close. Per multiple reports, however, Elliott suffered a torn PCL early in the season, which could explain the decline in usage. In fact, his pre and post-bye week split stand out as he was the RB8 in Expected PPR points (18) until Week 6. In the final 11 games, however, his usage dropped to RB17 averaging 13.8 Expected PPR points per game. If the injury truly contributed to the drastic decline in usage, Elliott could be a value at his current ADP of RB18 heading into 2022.

Fantasy Efficiency Leaders

Next up, let’s take a look at the most efficient running backs who performed above their expected PPR value:

If you were holding on to Rashaad Penny in your dynasty leagues over the last four years, you were finally rewarded with a league-winning performance to close out the season. Interestingly, Penny was only the RB24 in Expected PPR points (13.26) in the final 5 weeks. However, his efficiency is what propelled him to top-tier production, averaging an elite 8.78 points above expected in that timespan. So despite only starting in half of his games, Penny’s dominant end to the year allowed him to finish as the RB1 in FPOE per game (+3.67).

Jonathan Taylor has had a historic start to his career, heavily driven by a dominant 2021 season. In fact, Taylor and Derrick Henry are the only two running backs last year to rank in the top-5 in both Expected PPR points and Fantasy Points Over Expected per game. In other words, Taylor was one of the most heavily utilized running backs in the league while also performing at a very efficient rate. As a result, it should not come as a surprise that he finished as the RB2 last season in actual PPR points per game at 21.9. And while efficiency regression is certainly within the realm of possibilities for Taylor, his high usage within the Colts’ offense should keep him in the conversation to finish as a top-3 RB in 2022.

It truly is unfair that the Cleveland Browns have two of the most efficient running backs in the league in Kareem Hunt & Nick Chubb, as both finished in the top-7 in Fantasy Points Over Expected in my model. It does make you wonder how dominant both could be if they were given the opportunity to command their own backfield. From a usage standpoint, Hunt continues to hold Chubb back as they both ranked within the top-30 in expected fantasy points, with Chubb ranking the highest at RB19. Since Hunt is in the final year of his contract, we could finally see Chubb unleashed after 2022.

Fantasy Inefficiency Leaders

Lastly, above are the most inefficient running backs from the 2021 season, finishing with the lowest FPOE per game:

Among running backs who received at least 100 opportunities last year, David Montgomery stands out as the most inefficient of the group averaging -3.83 FPOE per game. Interestingly, Montgomery has never averaged a positive FPOE in any of his first three seasons in the league, with 2021 being the most inefficient of his career. However, volume remains king for fantasy running backs, and Montgomery has ranked within the top-7 in expected fantasy points in each of the last two years. With not much competition in that backfield, I fully expect him to remain the lead RB for the Bears. And if this offense can take the next step with Justin Fields, Montgomery’s FPOE could regress to the mean, potentially raising his upside in 2022.

In his first season without Drew Brees as his quarterback, Alvin Kamara was heavily relied upon by the New Orleans Saints. Not only did he finish as the RB2 in expected PPR points per game (20.87), but he also set a career-high in rushing xFP at 11.84. In fact, this was the first season in his career in which he averaged a higher rushing xFP than receiving xFP, signaling a massive change in his usage. But despite receiving more opportunities on the ground, he averaged a career-low -3.09 rushing FPOE in 2021. Ideally, we see his efficiency improve with Jameis Winston returning healthy and the addition of Chris Olave potentially elevating this offense. Regardless, as long as Kamara continues to receive top-5 usage with the Saints, I fully expect him to be an RB1 once again this upcoming season.

Najee Harris had an impactful rookie season for fantasy managers, finishing the year as the RB4 in xFP (19.49). But while his usage was one of the highest in the league, he only finished as the RB86 in FPOE per game with -2.10. In fact, both his rushing and receiving FPOE were in the negative this past season. Part of that is driven by the Steelers’ below-average offensive line, which ranked 28th in the league in adjusted line yards (3.84). The good news is that Pittsburgh did address their front line by signing Mason Cole and James Daniels in free agency, which will hopefully boost their running game. And with Kenny Pickett likely leading this offense in 2022, I expect Mike Tomlin to rely even more on Harris to alleviate the pressure for the rookie QB.

FPOE Regression

Since 2013, among running backs who averaged a positive FPOE, 85.7% experienced regression year over year. That does not necessarily signify their efficiency will regress all the way to the mean (or to zero); however, it does imply that running backs do not generally improve on their positive FPOE the following season. The average decline in FPOE for those RBs is -1.67 per game. On the other hand, among the RBs who finished the year with a negative FPOE, 61.7% experienced regression, performing much more efficiently the following season. The average improvement in FPOE for that group is +0.64 per game.

What does this tell us? In short, be wary of players who relied heavily on their efficiency since that is likely unsustainable year over year. This includes players such as James Conner and Nick Chubb, two RB1s who ranked outside of the top-15 in expected PPR points. And unless their xFP or usage improves to offset the inevitable regression, they will likely score fewer points next season. On the other hand, target players whose production was rooted in volume despite their inefficiencies as they could regress to the mean and perform closer to their expected value. Players who fit that mold include David Montgomery, Josh Jacobs, and Alvin Kamara.

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

xFP and FPOE Summary