NFL

# Which Wide Receivers Will Score More Touchdowns in 2018?

Math can help us find players who should improve their scoring. These wide receivers make the cut for 2018.

Regression isn't always a bad thing.

The word generally comes with a negative connotation, and it's usually used to describe someone who has been outperforming expectation. (Kind of like wide receivers who should have scored fewer touchdowns in 2017.)

But regression in the positive sense can also imply returning to an expected state. And with how weird the NFL can get over a 16-game season, regression can really help us anticipate what will or should happen over a larger sample.

For that reason, just like we saw which receivers should expect negative touchdown regression in 2018, we can try to pinpoint which wideouts should score more easily in 2018 than they did in 2017.

### The Process

At numberFire, we have a metric called Net Expected Points (NEP), which indicates how a player impacts his team's chance of scoring. A 10-yard catch from inside your own territory is generally good, but when it comes on 3rd-and-12, it's not as good as when it comes on 3rd-and-8. One increases expected scoring by extending the drive. The other won't because it'll lead to a punt.

During the year, those plays add up, and NEP helps give weight to plays during which a player gets close to the end zone but doesn't score. Over the long haul, a receiver's Reception NEP and touchdown total should mostly fall in line.

The math shows that.

A Reception NEP of 100.00 should be tied to a touchdown total of about 7.5, so if we see a receiver with a high Reception NEP like that (100.00 Reception NEP is roughly top eight each year) with a low touchdown total, we can expect positive regression.

### Backtesting: 2017 Positive Regression Candidates

When we looked at the 20 receivers who scored at least 1.5 more times in 2016 than their Reception NEP suggested they should've, we saw that 19 of them regressed in terms of receptions per touchdown in 2017. The only one who improved was Odell Beckham, who had a short season and was the 20th player on the list (with a difference between his expected and actual touchdowns of just 1.54).

If we look at the 19 receivers who should've scored at least 1.5 more times in 2016, we see that 15 of them improved their catches per touchdown number. (This list includes only receivers with at least 25 catches in 2017.)

Player Rec NEP 2016 TD Rec/TD 2017 TD Rec/TD
Pierre Garcon 95.23 3 26.3 0 -
TY Hilton 129.84 6 15.2 4 14.3
Alshon Jeffery 70.90 2 26.0 9 6.3
Stefon Diggs 78.90 3 28.0 8 8.0
Julio Jones 115.11 6 13.8 3 29.3
DeAndre Hopkins 90.71 4 19.5 13 7.4
Robert Woods 51.85 1 51.0 5 11.2
Jarvis Landry 83.96 4 23.5 9 12.4
Marqise Lee 71.27 3 21.0 3 18.7
Tyler Lockett 46.88 1 41.0 2 22.5
Jordan Matthews 70.01 3 24.3 1 25.0
Jermaine Kearse 43.52 1 41.0 5 13.0
Marvin Jones 79.95 4 13.8 9 6.8
Golden Tate 79.54 4 22.8 5 18.4
Mike Wallace 78.65 4 18.0 4 13.0
Demaryius Thomas 89.01 5 18.0 5 16.6
Amari Cooper 88.99 5 16.4 7 6.9
DeSean Jackson 76.28 4 14.0 3 16.7
AJ Green 75.72 4 16.5 8 9.4

The primary regression candidate, Pierre Garcon, failed to reach the end zone on his 40 catches with the San Francisco 49ers in 2017. That's a miss.

Julio Jones' 3 touchdowns (down from 6 in 2016) also was a miss by our standards, and he scored once every 13.8 catches in 2016 but just once every 29.3 catches in 2017.

Jordan Matthews changed teams in 2017, and his catch-per-touchdown rate was nearly identical (24.3 in 2016 and 25.0 in 2017), but we'll count that as a miss, too. And then there's DeSean Jackson, who also had a similar catch-per-touchdown rate (14.0 and 16.7).

Despite these misses, this means that 34 of the 39 receivers who were above or below their expected touchdown total by at least 1.5 in 2016 regressed in the expected sense in 2017. That's 87.2%.

Further, 6 of these 19 players -- the ones who should've improved their touchdown numbers in 2017 -- also appear on the list of receivers who scored too frequently in 2017. Jarvis Landry, Amari Cooper went from underperforming in the touchdown column to overperforming -- because touchdown numbers are pretty flukey.

I think we should keep an eye on the following players for that reason.

### 2018 Regression Candidates

These 17 receivers should have scored at least 1.5 more touchdowns than they actually did in 2017, so they make the cut as our primary positive regression candidates for 2018.

Player Reception NEP TD Expected TD Difference
Julio Jones 117.85 3 8.97 -5.97
Marquise Goodwin 78.39 2 5.72 -3.72
Keenan Allen 126.08 6 9.64 -3.64
Adam Thielen 101.65 4 7.63 -3.63
Michael Thomas 112.65 5 8.54 -3.54
Pierre Garcon 40.91 2.64 -2.64
Danny Amendola 64.97 2 4.62 -2.62
Devante Parker 52.43 1 3.58 -2.58
Terrance Williams 39.02 2.48 -2.48
Kendall Wright 51.08 1 3.47 -2.47
Adam Humphries 50.09 1 3.39 -2.39
TY Hilton 84.13 4 6.19 -2.19
Sterling Shepard 58.28 2 4.06 -2.06
Eric Decker 45.32 1 3.00 -2.00
Marqise Lee 68.23 3 4.88 -1.88
Chris Godwin 43.14 1 2.82 -1.82
Mike Evans 91.47 5 6.80 -1.80

Surprise, surprise. Julio Jones makes the list again. Jones finished fourth in Reception NEP (117.85) and had 19 red zone targets (11 from inside the 10) but hauled in just 3 touchdowns. Something has to give eventually...right?

Keenan Allen isn't a surprising name here, as he scored just six times in 2017, despite ranking third in Reception NEP. Allen also had 33.3% of the Los Angeles Chargers' red zone targets, the third-highest red zone target market share in the league.

Adam Thielen outperformed teammate Stefon Diggs in the Reception NEP category (101.65 to 79.20), but Diggs doubled him up in the touchdown column this season (8 to 4).

Michael Thomas popped as a receiver who should've seen negative touchdown regression in 2017 (and he did, dropping from 9 scores to 5), but he's back on the list for positive regression in 2018.

Let's jump down to the bottom of the list to Mike Evans, whose Reception NEP totals since entering the league have been somewhat consistent: 100.30, 102.21, 144.22, and 91.47. His touchdown tallies have been quite random: 12, 3, 12, 5. This year, he should have a better touchdown tally.

Jones, Thomas, Allen, and Evans will all cost you at least a second-round pick, via FantasyFootballCalculator, and Thielen is coming off the board in the third round. That's pricey for all, but they should have room to grow in the touchdown column this year.

We'll bop back up to the man who is second on the list: Marquise Goodwin. Goodwin actually produced a Reception NEP (78.39) right between Stefon Diggs' 79.20 and JuJu Smith-Schuster's 76.71. They scored eight and seven touchdowns, respectively, while Goodwin scored just twice.

Goodwin's teammate, Pierre Garcon, failed to score on his 40 catches -- as we already discussed -- but both look primed to post more touchdowns this season, especially when paired with 2017's most efficient quarterback by our metrics: Jimmy Garoppolo.

Danny Amendola and DeVante Parker are now teammates in Miami, a team that lost 2017's touchdown hog Jarvis Landry.

Along with Evans, Adam Humphries and Chris Godwin are flagged as positive regression candidates, though they will play the first three games without quarterback Jameis Winston.

Naturally, not all of these players will overcorrect or even improve their touchdown rates in 2018, but the model has done well to identify regression candidates in the past, and if nothing else, we should be trying to buy low on some of these options whenever possible for the 2018 season.