The Utilization Score: Understanding Player Roles to Forecast Future Performance

The Utilization Score represents the strength of a player's role and performance relative to their peers. It is a weighted calculation incorporating the most predictive data points associated with scoring future points at the RB, WR, and TE positions since 2020.

Why should I care about the Utilization Score?

When evaluating weekly and rolling four-week performance, the Utilization Score is more stable and predictive than fantasy points per game. It is stronger than industry standards like snaps, attempts, targets, and air yards.

How do I use the Utilization Score?

As a fantasy player or bettor, you can use the Utilization Score to help identify over- or underperforming players. In fantasy, this means focusing on the best waiver wire pickups and buy-low or sell-high candidates. It can also be helpful when making tough start-sit decisions.

How do I interpret the Utilization Score?

The highest possible Utilization Score is 100, and the lowest is 0. There is a range of outcomes in fantasy production for each Utilization Score. But at the 30,000-foot level, the higher the score, the better for fantasy and vice versa.

Below is a position-by-position breakdown, providing the average fantasy points per game (PPG) and a range of outcomes for season-long finishes. For example, RBs with a score between 60 and 69 averaged 12.2 points, with the majority of finishes (~70%-plus) landing between an RB2 and RB3 campaign.

Running Backs

Wide Receivers

Tight Ends

What data points make up the Utilization Score?

Most of the Utilization Score is forged from data points such as snaps, rush share, route participation, target share, catchable targets, and catchable air yards. However, fantasy points per game also get some weight to help account for a player's offensive environment and ability to convert opportunities into production.

Why isn't there a Utilization Score for QBs?

We tested every QB data point we could obtain, but ultimately didn't find anything more substantial than fantasy points per game, which was our benchmark. We assess new data points and approaches each offseason, so this could change in future seasons.

How stable and predictive were the Utilization Scores?

The Utilization Score outperformed fantasy points per game at every position when testing week-over-week (WoW) and rolling-four-over-rolling-four (FoF) outcomes. Below is a table with R-squared values for each period, including year-over-year (YoY).

Stability represents how stable the Utilization Score was across time periods, while N+1 represents its predictiveness to PPR fantasy points in the next period.

Category	WoW	FoF	YoY
RB Stability	0.57	0.71	0.32
RB N+1 PPR	0.37	0.57	0.31
WR Stability	0.45	0.68	0.61
WR N+1 PPR	0.29	0.54	0.57
TE Stability	0.54	0.74	0.71
TE N+1 PPR	0.34	0.61	0.66

We could have weighted the Utilization Scores in a way that would have been even more predictive, but we wanted to maintain robustness and stability. We aim to build a solution that can withstand the test of time.

How is the Utilization Score different than expected fantasy points?

Expected fantasy points and the Utilization Score are different but complementary. While expected fantasy points are based on opportunity (attempts or targets) and field position (i.e., from the five-yard line), the Utilization Score differs in a few key ways.

The Utilization Score is based on a weighted blend of raw stats (i.e., attempts and targets) and shares (i.e., attempt and target share). Expected fantasy points are based purely on raw stats.
The Utilization Score gives a player credit for being on the field in high-leverage situations based on snaps (i.e., short yardage) and route participation.
The Utilization Score adds context to the equation by factoring in catchable targets and air yards. Expected fantasy points are based on raw targets and air yards.

They capture many of the same data points, but the Utilization Score goes further by evaluating snaps and routes. This distinction is important because one metric compares a player's performance vs. their peers based on raw opportunities. The other metric looks more holistically at the player's availability to make an impact in addition to their actual opportunities.