Fantasy Football Today - fantasy football rankings, cheatsheets, and information
A Fantasy Football Community!




Create An Account  |  Advertise  |  Contact      

 





Sean Holler | Archive | Email  
Contributor


DFS University: Finding Wide Receiver Value with Dollar Per Adjusted Opportunity (DPAO)
9/16/16


Finding a statistic that correlates to fantasy wide receiver success is very difficult. This is because as a receiver you can find success in three main ways: you can catch a lot of balls, you can catch fewer balls but run deeper routes, or you can catch a lot of touchdowns. Considering they all rely on targets, that is the most logical place to start.

NFL.com did a great piece on this in 2015, so I wonít steal it. But to paraphrase, of the top 24 WRs (non-ppr) in each year from 2011-2015, 26.7% finished with 150 targets or more, 45.8% finished with 120 to 149 targets, and only 27.5% finished with less than 120 targets.

Put in another way - 73% of the top 120 WRs over the past five years, received 120 targets or more. Okay, so we have our first qualifier, and itís a good one: crossing the 120 target threshold is key to fantasy/ DFS success. And when we look at the 150 target mark itís even better: only one WR since 2011 with 150 targets finished outside the top 24 (Sorry Larry Fitzgerald). So to recap, we want 150 targets for a 99% percent chance of a top 24 finish, or 120 targets for 73% chance. I like those odds.

What about those guys who received less than 120 targets and still managed to make it to the top 24? They got touchdowns. The average touchdown rate (touchdown/target) among top 24 receivers over the last five years was 6.63. Of the 33 wide receivers who finished as top 24 in that time frame despite seeing less than 120 targets, all but six of them posted a touchdown rate above 6.63.

Per NFL.com, the only wide receivers who finished inside the top-24 with less than 120 targets and a touchdown rate less than the league average of 6.63 are:

1) A.J. Green: 6.1 (2011)
2) Lance Moore: 5.8 (2012)
3) Michael Floyd: 4.5 (2013)
4) DeSean Jackson: 6.3 (2014)
5) Brandon LaFell: 5.9 (2014)
6) A.J. Green: 5.2 (2014)

That means only six of the 120 (5%) were able to produce with a less than average touchdown rate and less than 120 targets. So how did they do it? Take a look at the list - they are mostly deep threat receivers. We can analyze this not by Yards Per Reception because it is a very poor statistic, but rather by average depth per target (ADOT). YPR has a big flaw in that if you catch one bubble screen and take it to the house, your yards per reception will be high, but you arenít actually a deep threat. This can confuse your role and cause fantasy owners to over predict your value. ADOT is much more accurate. It shows us how deep the average target is and is more accurately tied to being a deep threat wide receiver. Only one receiver finished inside the top 24 over the last five years, with less than 120 targets, less than average touchdown rate (6.63), and less than a 13.8 ADOT: Brandon LaFell.

So now we have accounted for all variables. In order to finish as a fantasy top 24 WR in the modern NFL, you need to have a minimum 120 targets per season, or less than 120 but an above average touchdown rate, or some combination of those and a high ADOT, specifically above 13.8, and failing all of that you need to be Brandon LaFell in 2014.

I decided to convert these requirements into a formula: DPAO: dollar per adjusted opportunity. What we want to do is forecast the number of targets the player is likely to receive, with small adjustments made for players with an average ADOT above 14, and additional adjustments made for game flow and strong CBs. This will give us an adjusted opportunity prediction.

Predicting touchdowns is very difficult - year over year they do not correlate well and even red zone targets arenít as accurate as one would like. Therefore, I am not factoring in touchdown upside, however game flow will help us factor this in. Targets are the key, as you need the ball in your hands to score. We then take this adjusted opportunity prediction number and contrast it with a playersí DFS salary to help us find value.

Here is the DPAO formula:

Opportunity: 1 target = 1 opportunity. We want to first screen for players with a minimum of 8 targets per game to help predict with reasonable accuracy a top 24 finish. We will forecast targets using: same game last year averaged with previous year average targets, averaged with projected targets.

Adjustments:

A) ADOT Adjustment: +1 AO for players with an ADOT above 14 (they have an additional tool that can help them crack top 24 despite less than 120 targets).

B) Weather Adjustment:

+1 AO Full Sun/ Dome
-1 AO slight Rain/Wind
-2 AO weird torrential downpours/ extreme wind

C) Strong CB (top 8) Shadow Adjustment:

+15% of AO if WR2
- 25% of AO if WR1

My research shows that top CB are targeted around 25% percent less than the league average on a per-snap basis. Those targets are often displaced, not removed, so we move them to the WR2. However, they do not get moved directly onto the WR2 as there are other options in the pass game.

D) Game Flow Adjustment:

Up/Down by 0-5 -1/+1 AO
Up/Down by 5-10- -2/+2 AO
Up/Down by 10-14- -3/+3 AO
Up/Down by more than 14- -4/+4 AO

Game flow is intensely correlated to fantasy success. Here we are using the average Vegas spread to analyze game flow. If a team has to abandon the run early, this will benefit any and all receivers. Conversely, if a team is up by 21 points, it is unlikely they are going to be chucking rocks downfield, and will most often turn to their stable of running backs. Analyzing the expected game direction is necessary.

We then takethe players DFS salary and divide it by this adjusted opportunity prediction (AO) number to find the dollar per adjusted opportunity.

Finding players with DPAO values between $500-600 will allow you to build your roster with four potentially top 24 WRs and not have to make major concessions elsewhere. When we pay over $600-700 per opportunity, we risk over paying per chance to succeed and that has a ripple effect throughout the roster. WR1 often have high DPAO, this is not a bad thing as they are often safer plays, but recognizing that you might be overpaying per opportunity is key to differentiating between players in similar tiers.

Talent is obviously important, but it's not as important as you think, as noted above, you need the ball in your hands for anything to happen in the first place. We want as many chances as we can get.

Week 1 picks and results:

Julio Jones - DK Salary $9,400 / 12 AO = $783 per adjusted opportunity

Marvin Jones - DK Salary $4,600 / 8.5 AO = $541 per adjusted opportunity

Michael Crabtree - DK Salary $5,500 / 11 AO = $500 per adjusted opportunity. This value was off the charts.

Donte Moncrief - DK Salary $6,000 / 9 AO = $666 per adjusted opportunity. This valuation was a bit higher than I would have liked for him. But the game looked like a shootout from a mile away.

Using DPAO and the above players, I was able to win 97% of my cash games. I will always choose the players that I recommend, so if you fail, you can at least take comfort in knowing I went down in flames too.

Tune in tune in next week for 10 reasons why I hate Gary Barnidge, Week 2 evaluations and Week 3 DPAO picks.