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Using the Range of Outcomes App to Find a Cheaper WR With a Better Range of Outcomes Than T.Y. Hilton

The latest in a long line of new and beefed-up RotoViz apps has arrived — Dave Caban’s Range of Outcomes App.

You might remember this as the Sim Scores App, which gathers the most comparable seasons for a player, and based on that, assigns them a range of outcomes for the coming season.

I prefer considering a player’s range of outcomes, as they provide a more rounded picture compared to straight black-and-white projections, which tend to just be the median outcome. This gives us a more complete picture of the risk/reward we’re getting with each selection.

Dave gave me the keys to the new tool to test it out. I wanted to use it to highlight one wide receiver who has a similar range of outcomes to some pricier players like T.Y. Hilton.

DownHilton?

Let’s first look at Hilton’s historical projection.

Based on players who’ve had similar seasons, the app projects him for an average per-game line of 8-5-67-0.3TDs, or 13.7 points per game in PPR.

The “Change” column shows how Hilton’s comparable players did in the following (N+1) season. So in this case, his cohort of comps dropped off by an average of three points per game the next year — a suggestion at what we might expect from Hilton in 2019.

The chart on the bottom shows how those results are distributed — with Hilton we see that the majority of the results land in that median range, while there are just a couple of high-end outliers.

Who are they? We can easily find out with this app with the click of a tab.

Now let’s look at a player who has a similar range of outcomes to Hilton according to our new app. This one is no stretch, given he outscored Hilton last year.

And yet he’s going about 15 picks later in the high-leverage, rounds.

What About Bob?

Robert Woods is coming off a 261.1-point, WR8 season in which he outscored Mike EvansKeenan Allen, and Stefon Diggs, all of whom are again being drafted ahead of Woods this summer.

Both his median and high projections are better than Hilton’s.

  • Woods’ comps averaged 13.2 points the following year, but their median score was considerably higher at 14.1
  • We can see from the distribution that Woods has a lower floor, with several of his cohorts falling below 10 PPG the following year.
  • Still, on average, this group’s N+1 dropped off by just -2 points, better than Hilton’s -3.

There are other factors not being accounted for here that make Woods an even better play than Hilton. The app doesn’t know that Andrew Luck has a “small, little bone” injury. Hilton was a WR3 with 11.4 PPG the last time Luck missed significant time.

It also doesn’t know that Woods benefited by Cooper Kupp missing half the season. Then again, did he? Woods was doing just fine with Kupp in the lineup — better, even.

It appears that Kupp’s presence may actually make the entire offense more efficient. At the risk of oversimplifying things:

  • Jared Goff went from 53 fantasy points above expectation (paFPOE) in eight games with Kupp to 17.2 in eight games without.
  • Meanwhile, as a group, the Rams receivers went from 92.4 receiving points over expectation (reFPOE) with Kupp to 23.8 without.

Maybe that sample is too small to mean anything, but then again, the difference in offensive efficiency is wild. Either way, Woods will be just fine with Kupp back in the lineup.

Conclusion

This is not a hit job on Hilton. He’s demonstrated his upside and is fairly priced.

The discount on Woods is too much to resist, however, and he’s one of my most owned players this year.

Stay tuned for the release of the new app and more range-of-outcome analysis on players who may be mispriced.

Image Credit: Jeffrey Brown/Icon Sportswire. Pictured: T.Y. Hilton.

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