Projecting Week 2's Top Fantasy Football Scorers

There is a time and a place to discuss players like Stephen Hill and Alfred Morris, two excellent waiver prospects for this week. There's also a time and a place to discuss Tony Romo or Andre Johnson, two solid fantasy talents who should be starting in every league.

This is not that place.

I'm here today to discuss only the best of the best, the top players at each position this week in fantasy football. I'm only looking at the projections for this week, which is why you'll see Eli Manning (playing the Bucs) jumping over Aaron Rodgers (playing the Bears) this time around. Does this mean you should trade Aaron Rodgers? Of course, and you should send me $100 while you're at it. But for the non-gullible among us, this article should simply give an indication of which players will help you win your fantasy matchup in Week 2.

All projections in this article are courtesy of the lovable stat-nerds at numberFire.com, who also help make projections for ESPN Insider and SI, among other places. Before you ask, yes, I'm aware that you can't have two-fifths of a completion, but the stats here are based off of averages run by the numberFire simulations. You're welcome to disagree with these rankings, but just know that you're not just disagreeing with me, you're disagreeing with math. The point totals given here are based off of a standard non-PPR league.

And with that explanation, we're off!

QBs: Drew Brees, New Orleans Saints

Week 2 Projected Stats: 23.7 completions on 34.5 attempts, 304.92 passing yards, 2.48 TDs, 0.65 INTs

Projected Point Total: 21.58

Week 2 Opponent: Carolina Panthers

I'm well aware that the Saints were a disappointment in Week 1, falling to the RGIII monster down in the Big Easy. So what went wrong?

To answer, we look at the Net Expected Points (NEP) value for Brees last weekend. On each play, a team can be expected to score a certain number of points. For instance, on a 3rd-and-2 at the 50, the number a team can be "expected" to score is the average of all points resulting from a drive that had 3rd-and-2 at the 50. A player's NEP measures exactly how many expected points they increased or decreased their team's total on a play as compared to the average player.

Brees's NEP value in Week 1 was one of the lowest you'll ever see from him at +0.04 NEP per passing play. By comparison, RGIII finished Week 1 with a +0.74 NEP per play value; Joe Flacco came in at +0.57. Drew Brees' value meant that he played somewhere roughly equivalent to Josh Freeman (+0.07) or Ryan Fitzpatrick (+0.01). With all due respect to Kansas State or Harvard QB enthusiasts, that hurts.

But that's not Drew Brees football. In 2011, Brees finished with an average of +0.38 NEP per pass, the highest among all NFL QBs. Especially against a Carolina defense numberFire has ranked No. 30 in the league, Brees could take a nap in the second quarter and still finish with 300 yards as long as he approaches that +0.38 NEP rating once again. And I trust him to do it.

The Best of the Rest

2. Cam Newton (vs. New Orleans): 20.01 Fantasy Points (FP)

3. Tom Brady (vs. Arizona): 19.47 FP

4. Eli Manning (vs. Tampa Bay): 17.25 FP

5. Matt Ryan (vs. Denver): 16.79 FP

RBs: Adrian Peterson, Minnesota Vikings

Week 2 Projected Stats: 18.47 rush attempts, 95.55 rushing yards, 1.04 rush TDs, 2.76 receptions, 20.28 receiving yards, 0.02 receiving TDs

Projected Point Total: 17.62

Week 2 Opponent: Indianapolis Colts

Seen enough of AP yet to be a believer? I have. numberFire called him the No. 5 overall RB this season from the very start, and he proved why last week with his two-TD, 20-fantasy-point performance against a not-half-bad Jacksonville defense.

Just how much of a dent did he make? His +0.12 NEP per rush value was fourth among all backs with at least 10 carries, which put him behind only Stevan Ridley, Frank Gore and Matt Forte. And you probably had him on your bench, didn't you? For shame.

With a week under AP's belt, I expect to see Toby Gerhart receive even less than the six carries he had versus the Jags (numberFire projects 3.38 rush attempts). And that's a good thing for Peterson owners, especially when you look at the Colts defense he'll be facing.

The Bears did not need to rush the ball much against them in Week 1, but Forte still managed a 5.0 yards-per-carry average on 16 attempts. Not only is Peterson a must-start this week, but he's likely to win a few matchups by himself with his performance.

The Best of the Rest

2. Jamaal Charles (vs. Buffalo): 20.01 Fantasy Points (FP)

3. Arian Foster (vs. Jacksonville): 16.22 FP

4. Lesean McCoy (vs. Baltimore): 15.40 FP

5. Matt Forte (vs. Green Bay): 14.97 FP

WRs: Victor Cruz, New York Giants

Week 2 Projected Stats: 5.13 receptions, 83.72 receiving yards, 0.79 receiving TDs

Projected Point Total: 12.98

Week 2 Opponent: Tampa Bay Buccaneers

Some may look at Victor Cruz's season opener against the Cowboys and see his hands of stone; he only caught six of 11 passes thrown his way by Eli Manning for a below-average 54.5 percent catch rate. I look at it the opposite way: Those 11 targets were five more than any teammate, including fellow top-flight receiver Hakeem Nicks (who had six).

Eli Manning has clearly established a connection with Cruz, especially evident in the fact that Manning continued to go back to him after those drops. And that catch rate is likely to get closer to the league average of 60 percent as well—Cruz was slightly above it at 62.9 percent last season.

What takes Cruz's Week 2 fantasy projections from "Very Good" to "Supernova-Large" though is the matchup. Cam Newton may have struggled at times against the Tampa D, but his receivers did just fine. Steve Smith hit the century mark in yards with a 64 percent catch rate; Brandon LaFell went for 65 yards and a TD by catching three of Newton's five targets.

This is still the same Bucs defense that numberFire has ranked dead last, No. 32 overall, and two costly Newton interceptions aren't going to change that. Cruz projects to be a better receiver than either of those two Panthers this season, and given the same 11 targets Smith had against these Bucs, the Giants wideout should go off.

The Best of the Rest

2. Wes Welker (vs. Arizona): 12.56 Fantasy Points (FP)

3. Calvin Johnson (vs. San Francisco): 11.82 FP

4. Larry Fitzgerald (vs. New England): 11.56 FP

5. Marques Colston (vs. Carolina): 11.13 FP

TEs: Rob Gronkowski, New England Patriots

Week 2 Projected Stats: 5.59 receptions, 73.15 receiving yards, 0.62 receiving TDs

Projected Point Total: 11.08

Week 2 Opponent: Arizona Cardinals

Pick a random week out of a hat (preferably a sombrero after a Gronk fiesta), and chances are Rob Gronkowski will be the No. 1 receiver on numberFire's projections. He's just that good, and he proved again why on Sunday with his 60-yard, one-touchdown effort against the Titans.

The six targets from Brady versus Tennessee were actually slightly less than usual, putting him at third behind Brandon Lloyd (eight targets) and Aaron Hernandez (seven targets). That better not happen too often—you do not want to make the Gronk angry.

What really sets Rob Gronkowski apart, however, is how he is able to convert those targets into receptions. Gronkowski was a perfect six-for-six on Sunday. The man has hands of tape.

That catch rate falls right in line with his 2011 72.6 percent clip, where he finished just behind Antonio Gates among tight ends with a significant number of receptions.

Does numberFire think that Gronkowski will average over a touchdown a game as he did last season? No. But with his sure-handed abilities, he's likely continue to see the majority of the Patriots' (numerous) red-zone targets.

The Best of the Rest

2. Jimmy Graham (vs. Carolina): 9.04 Fantasy Points (FP)

3. Aaron Hernandez (vs. Arizona): 8.65 FP

4. Antonio Gates (vs. Tennessee): 8.11 FP

5. Jermichael Finley (vs. Chicago): 7.41 FP

Zach Warren is a writer and editor for numberFire.com as well as Bleacher Report. And he's here to bring the Fire to your fantasy team. NumberFire.com specializes in predicting stats for players and teams through their prediction models.