NFL

# Fantasy Football Week 7: Wide Receiver Touchdown Regression Update

Amari Cooper has been strong in fantasy football of late, but should his totals actually be better?

It's true that some players -- I'm looking at you, Dez Bryant -- are good at scoring touchdowns. But, across the entire NFL, finding the end zone is something that mostly stems from opportunity. And, of course, a little bit of luck.

Remember Calvin Johnson's historic 2012 campaign? You know, the one where he almost hit the 2,000-yard mark in receiving? That year, Megatron scored five -- that's five -- touchdowns. Despite the fact that he caught more than a mile worth of yards, he found the end zone five times. He was unlucky -- he was tackled within the five-yard line eight times that season.

It goes the other way, too. In 2013, Jerricho Cotchery scored 10 touchdowns on just 602 yards receiving. Clearly, that was an outlier -- he regressed to the mean the next season in Carolina, scoring once with just 22 fewer yards.

Math is real.

Yards are one way to normalize touchdown production, but to be more accurate, we can also use our Net Expected Points (NEP) metric, which you can read more about in our glossary. Specifically with wide receivers, Reception NEP measures the number of real points a player accumulates on all catches. Because this is fantasy football and we're only interested in cumulative volume, we'll work with that.

### The Process

I wrote about this topic over the offseason, so rather than re-writing the process of using Net Expected Points to show touchdown regression, I'll copy and paste that sucker here for you:

Charting the relationship between touchdowns and our Net Expected Points (NEP) metric -- which shows how many actual points a player adds for his team (check out more on NEP in our glossary) -- allowed for an analysis of how many touchdowns a player should have scored versus how many touchdowns a player actually scored. To put this another way, because Net Expected Points measures how many points a player actually scored for his team, it's not skewed by a counting statistic like touchdowns -- a touchdown scored from the 1-yard line isn't as impactful as a touchdown scored from the 40.

This, in turn, brought the following chart.

What we find with this trendline is the number of touchdowns a player would be expected to score based on his NEP totals. So, if a dude puts up 100 Net Expected Points, we'd generally expect him to score a little under eight touchdowns.

### Update Through Week 7

Now that that's out of the way, let's take a look at players who should have more touchdowns than they currently do through seven weeks. (Note: Data does not include Thursday night's contest.)

Player Reception NEP Touchdowns Should Have Difference
Alshon Jeffery 39.41 0 2.79 2.79
Amari Cooper 45.36 1 3.25 2.25
John Brown 27.77 0 1.90 1.90
A.J. Green 47.72 2 3.43 1.43
Julian Edelman 21.44 0 1.41 1.41
Jarvis Landry 34.18 1 2.39 1.39
Chris Conley 19.12 0 1.23 1.23
Stefon Diggs 31.85 1 2.21 1.21
Marqise Lee 18.32 0 1.17 1.17
Vincent Jackson 16.07 0 1.00 1.00
Quincy Enunwa 28.98 1 1.99 0.99
Quinton Patton 15.74 0 0.97 0.97
Adam Humphries 15.33 0 0.94 0.94
Pierre Garcon 28.31 1 1.94 0.94
Kenny Britt 39.60 2 2.81 0.81
Victor Cruz 26.36 1 1.79 0.79
Ted Ginn Jr. 13.17 0 0.77 0.77
Tajae Sharpe 13.17 0 0.77 0.77
Dorial Green-Beckham 13.14 0 0.77 0.77
Philly Brown 12.75 0 0.74 0.74

And here's a list of wide receivers who should have fewer touchdowns than they currently have:

Player Reception NEP Touchdowns Should Have Difference
Jordy Nelson 29.50 5 2.03 -2.97
Larry Fitzgerald 39.04 5 2.77 -2.23
Seth Roberts 14.41 3 0.87 -2.13
Antonio Brown 44.62 5 3.19 -1.81
Michael Crabtree 44.72 5 3.20 -1.80
Justin Hunter 6.23 2 0.24 -1.76
Andre Holmes 6.36 2 0.25 -1.75
Tyreek Hill 7.48 2 0.33 -1.67
Brice Butler 7.90 2 0.37 -1.63
Michael Floyd 21.50 3 1.41 -1.59
Justin Hardy 10.20 2 0.54 -1.46
Andre Johnson 11.39 2 0.64 -1.36
Brian Quick 24.75 3 1.66 -1.34
Torrey Smith 12.00 2 0.68 -1.32
Devin Funchess 12.45 2 0.72 -1.28
Kenny Stills 12.74 2 0.74 -1.26
Brandon LaFell 26.44 3 1.79 -1.21
Jamison Crowder 27.39 3 1.87 -1.13
Danny Amendola 14.74 2 0.89 -1.11

You can do what you want with this data -- it's here to simply show regression. But, generally speaking, the first list includes players you may want to considering buying in fantasy football, while the bottom one shows wideouts you may want to sell.