Fantasy Football Week 7: Wide Receiver Touchdown Regression Update
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.