This article will give you the critical tools to wide receiver PPR scoring. This is a helpful guide to the position and explains why D.J. Moore is destined for disappointment in Chicago.

Target Volume is King

The most important factor in wide receiver scoring is target volume. With more volume comes more points.

Plotted on the graph below are player targets (horizontal axis) and PPR points (vertical axis) for wide receivers with more than 50 targets in a season since 2017. As you can see in the graph below, there is a strong correlation between targets and points.

Overall, there is an r-squared of 0.855, which means targets explain 85.5% of PPR scoring. This is as big of a correlation you will find between a player’s stats and the points the player will score.

Since 2017, wide receivers with more than 50 targets averaged 1.83 PPR points per target. Those wide receivers with 100 over more targeted averaged 1.89 PPR points per target. This stat is highly variable from year to year, as you can see in the graph below which has points per target (horizontal axis) along with the following season’s points per target (vertical axis).

Of wide receivers with 50 targets in back-to-back seasons, the r-squared between points per target in the two seasons is 0.07. In other words, a wide receiver’s performance in points per target only explains 7% of the player’s performance the following year.

One of the keys to understanding the wide receiver position is understanding the variability of scoring per target by year. Much of wide receiver scoring depends on touchdown scoring, which can be fluky from year to year. A good thing to remember is high per-target efficiency is not predictive of high future per-target efficiency. Likewise, a low per-target efficiency does not predict high future per-target efficiency.

More Durable Metrics

While wide receiving points-per-target is highly variable from year to year, other metrics are more durable.

Targets Per Route Run

For example, the percentage of routes a wide receiver (TPRR) is targeted on significantly correlates year to year. In the graph below, the TPRR of wide receiver (horizontal axis) is compared against the following season’s TPRR (vertical axis).

There is an r-squared of 0.42, meaning 42% of a wide receiver’s TPRR is explained by his prior season’s TPRR. This is a much strong correlation than points per target.

Simply put, when they are on the field, wide receivers maintain a similar share of the offense from year to year. Good wide receivers are targeted on a high share of their routes and tend to maintain that job.

Yards Per Route Run

Other metrics are also more predictive than points per target. Yards per route run (YPRR) is a similar metric that measures a player's productivity when he runs a route on a passing dropback. Below is a graph showing the YPRR (horizontal axis) with the following season’s YPRR (vertical axis).

This has a smaller r-squared (0.266) than TPRR but is still significantly more predictive than points per target.

Target Share

The YPRR correlation is similar to target share, or the percentage of a team’s targets a wide receiver will receive in a season. The graph below compares target share (horizontal axis) to the following season’s target share (vertical axis) for wide receivers that had at least 50 targets each season.

When evaluating wide receivers with at least 50 targets in consecutive years, target share explains 26.7% of the following season’s target share.

The big takeaway is targets are a skill, but what happens on the targets is highly variable. Once you determine the targets of a wide receiver, the way they score on the targets is the variance that is difficult to predict. For fantasy football, accumulate as many targets as possible, and let the chips fall where they may.