This is an interactive value chart for Yahoo! using projections by Maurile Tremblay ("MT") and David Dodds ("DD"). Choose whether you want to view projected points, projected value, or H-value. Projected value is equal to projected points divided by salary (and then multiplied by ten). H-value is equal to projected points raised to the square root of three, divided by salary (and then multiplied by two). H-value, a measure inspired by Dan Hindery, is often a better indicator of true value than points per dollar. Click on the column headings to sort by that column. For example, if you want to sort by Dodds' projected value, first you'd click on "Value" at the top, and then click on the "DD" column heading. (Projections are current as of 1/17/2017 at 10:19 pm (EST).)
When you click on a player's name, the player is added to your lineup over at the right. Projected total points for your lineup are displayed for each set of projections. Click on a player in your lineup to remove him.
If you fill in a partial lineup with no more than six open spaces, you can have the remaining spaces filled in automatically, based on the set of projections you choose, by clicking on the green "MT", "DD", or "AV". To exclude a player from consideration by this feature, click on the green "o" to the right of his name. (Click again to undo.)
Strategy Guide: |
General |
Cash Games |
Tournaments |
Top 20 Stacks |
How to use the value charts
Daily fantasy football contests can be loosely divided into cash games and tournaments. Cash games comprise contests in which roughly half of the field finishes in the money. Tournaments comprise contests in which a much smaller percentage of the field -- generally between 10% and 20% -- finish in the money. Tournaments are often referred to as "GPPs," which stands for Guaranteed Prize Pools. I prefer the term tournaments to minimize ambiguity because a lot of 50/50s and Double-Ups also have guaranteed prize pools.
(Head-to-head contests are cash games. Strictly speaking, they are very small 50/50s. Some contests fall in between cash games and tournaments, such as Triple-Ups, or five-person contests that pay the top two spots.)
Any lineup is capable of scoring a wide range of points. The top end of that range is often referred to as the ceiling, while the bottom end is referred to as the floor. Your primary concerns in putting together either a tournament lineup or a cash-game lineup are (a) to select players who present great value as measured by expected points per dollar, and (b) to spend most or all of the salary cap. Follow those rules, and your team will be expected to score a lot of points, which is how you win both cash games and tournaments (and anything in between).
There are some differences between lineups best suited for cash games and those best suited for tournaments, however. You are invited to click on the "Cash Games" and "Tournaments" links for advice concerning each type of contest, but the basic idea is that, in cash games, you are more concerned with achieving a high floor, while in tournaments you are more concerned with achieving a high ceiling.
In general, a lineup expected to score significantly more points than a competing lineup will have both the higher floor and the higher ceiling; so putting together a lineup with an above-average expected score is the first order of business in either type of contest. That's what we'll focus on here.
We will want to concentrate on value rather than raw points, so the first step is to click on "Value" from among the options below in blue. Then we'll sort the player pool from highest value to lowest using whichever set of projections you prefer. To do so, click on the appropriate initials in the table header.
Click on the various positional tabs and look for players near the top of the list who stand out as having large salaries. Those are the players we're most interested in because they'll help us achieve both of our goals at once -- finding great values and using up our cap space.
Once you've inserted a few such players into your lineup, let the app fill in the remaining spots. Its suggestions will maximize total expected points, but sometimes you won't be happy with its choices for whatever reason. Remove any players you're not comfortable with, exclude them from consideration (by clicking on the green "o" next to their names in the player pool), and let the app do its thing again. Repeat until you're happy with the results.
If you are entering multiple contests, you will likely want to diversify your lineups rather than choosing the same players over and over again. The multiple sets of projections come in handy here. You may, for example, want to choose some RBs based on Maurile Tremblay's projections, choose a quarterback based on David Dodds' projections, and then fill in the remaining spots using Sigmund Bloom's projections. To find a second lineup with different players, select a QB using Sigmund's projections, some WRs using the average projections, then fill in the remaining spots using David's projections. For your next lineup, try a different combination.
Cash games
We stated in the general strategy section that the first order of business, whether in a cash game or in a tournament, is to construct a roster that is expected to score a lot of points; but that in a cash game, we are more concerned with our team's floor than with its ceiling.
There are a few ways to increase our team's floor.
The most obvious is to select individual players with high floors. That is to say, we will eschew boom-or-bust players and focus instead on more reliable players. This is more of an art than a science, but there are some decent indicators of reliability. First, we will prefer a player if we are confident that we know his health status, and the health statuses of his teammates. (We don't want a player who might be a late scratch or whose role might be limited; we also don't want a WR on a team whose QB is ailing; and finally, we don't want a player who will get significant playing time only if his teammate, who is currently listed as questionable, sits out.) Second, we will prefer a player if his involvement in the offense is durable. A one-dimensional runner, for example, can be taken out of the game plan if his team gets behind early; while a running back who is also heavily involved in the passing game should get touches no matter the score. We will prefer a player whose fantasy production depends more on yards than on touchdowns, and we will prefer a player who steadily gets yards in small chunks over a home-run hitter who depends on the big play.
Another way to reduce a team's volatility (and thus increase its floor) is to avoid QB-receiver combinations from the same NFL team. If a team's QB has a poor game, most likely his receivers will, too. Avoiding such QB-receiver combos is a form of insurance: if our fantasy QB has a poor game, our fantasy receivers may bail us out by having good games. That possibility is slim if our QB and receivers come from the same NFL offense.
While pairing players who score fantasy points together (such as a QB and receiver from the same NFL team) will increase volatility, pairing players who generally compete for fantasy points can reduce volatility, and therefore makes sense in a cash game. The classic examples are pairing either a QB or RB with the team defense that will be opposing him. This works as a hedge: If your quarterback or running back has a bad game, at least you should get points from your defense (and vice versa).
Other combinations of players who generally compete for points (and whose collective output is therefore relatively stable) include RB-RB, RB-WR, RB-TE and WR-TE combos from the same team. (It is difficult, however, to find two RBBC-members who are both good values, so the RB-RB combo will be rare.)
All of these factors should be considered tie-breakers more than anything else. When you're choosing among players with significantly different values (as measured in expected points per dollar), the player with the highest value is almost always the best choice. That's true in any type of contest, but especially in cash games. Only when choosing among players with similar values should these additional considerations come into play.
Tournaments
Whenever your team is expected to score more points than its target, volatility is your enemy. But when your team is expected to score fewer points than its target, volatility is your friend.
In a cash game, your target is the score earned by the median entrant in your contest -- and if you can't beat that more often than not, you shouldn't be playing. But in a tournament, your target will often be somewhere in the top 10% to 20% of the field. Nobody can expect to finish there most of the time. The goal is to finish there more than your fair share of the time, and a boost from volatility (which amplifies both your good results and your bad ones) can be rather helpful.
One way to increase the volatility of your roster is to load it with high-risk, high-reward players -- players with great upside potential relative to their projections. Look for players whose number of rushes or targets is inconsistent from week to week. Look for home-run hitters who can score bunches of points on relatively few opportunities. Look for players, other than quarterbacks, on offenses that are expected to score a lot of points. (The qualifier "other than quarterbacks" may strike you as odd. Quarterbacks on high-scoring offenses will be projected to score a lot of points, and will be valuable in any format. But they are not particularly likely to greatly outscore their lofty projections, so they are not especially valuable in tournaments compared to cash games. On the other hand, moderate differences in how looks are distributed among runners and receivers in a given week will have proportionately larger effects on their fantasy output if they are in higher-scoring offenses, making those players more volatile.)
Another common way to increase volatility is by "stacking" your lineup with a quarterback and receiver from the same NFL team. By doing so, you are increasing your chances of having a very high or very low score from that combination of players instead of a medium score. This makes sense in tournaments because a very high score is the goal, while a very low score is generally no worse than a medium score: you're out of the money either way.
Let's say you've got Jeremy Maclin at WR, and now you're choosing between Alex Smith or Matt Ryan at QB. If you select Ryan, the QB-WR combination could be great-great, medium-medium, horrible-horrible, great-horrible, horrible-great, medium-great, and so on. All possible combinations are on the table because the QB's performance and the WR's performance are uncorrelated.
But if you select Smith, now certain possibilities that lead to an overall medium score (like horrible-great) are much less likely. The odds of great-great and horrible-horrible are increased, while the odds of great-horrible and horrible-great are decreased, and the overall effect is to make the combined score more volatile. Compared to the Ryan-Maclin combo, the Smith-Maclin combo is more likely to be very high or very low, and less likely to be medium. That's an advantage in tournaments, where medium scores are useless.
A further strategy that can be helpful in tournaments is to seek out uncommonly owned players. Your primary goal at each roster position is to earn more points per dollar than your opponents. You can't win a tournament without being successful in that respect at most positions. Taking it for granted that you'll have to outscore the bulk of your opponents at a given position, you'd prefer to do so with a player owned by 5% of the field rather than with a player owned by 40% of the field. To win cash in a tournament, you may need to beat 90% of your opponents. If you get a great performance from a player who is 40% owned, you just passed 60% of the field. That's nice, but if you get a great performance from a player who is only 5% owned, you just passed 95% of the field. That brings you significantly closer to your ultimate goal.
None of this is absolutely essential. You can have a successful tournament lineup without boom-or-bust players, without stacking, and without sparsely owned players. But at the margin, among many factors to consider, those things are generally points in favor of a tournament lineup.
Name | | | Pos | Game | Salary | MT | DD | SB | Avg | MT | DD | SB | Avg | MT | DD | SB | Avg |
Aaron Rodgers |
o |
0 |
QB |
GB@ATL |
41 |
22.9 |
24.1 |
0.0 |
23.5 |
5.6 |
5.9 |
0.0 |
5.7 |
11.1 |
12.1 |
0.0 |
11.6 |
Matt Ryan |
o |
0 |
QB |
GB@ATL |
38 |
20.1 |
21.8 |
0.0 |
21.0 |
5.3 |
5.7 |
0.0 |
5.5 |
9.5 |
11.0 |
0.0 |
10.3 |
Tom Brady |
o |
0 |
QB |
PIT@NE |
35 |
18.7 |
19.5 |
0.0 |
19.1 |
5.3 |
5.6 |
0.0 |
5.5 |
9.1 |
9.8 |
0.0 |
9.5 |
Ben Roethlisberger |
o |
0 |
QB |
PIT@NE |
30 |
17.2 |
17.0 |
0.0 |
17.1 |
5.7 |
5.7 |
0.0 |
5.7 |
9.2 |
9.0 |
0.0 |
9.1 |
LeVeon Bell |
o |
0 |
RB |
PIT@NE |
39 |
19.5 |
20.4 |
0.0 |
20.0 |
5.0 |
5.2 |
0.0 |
5.1 |
8.8 |
9.5 |
0.0 |
9.2 |
Devonta Freeman |
o |
0 |
RB |
GB@ATL |
27 |
15.2 |
16.1 |
0.0 |
15.6 |
5.6 |
6.0 |
0.0 |
5.8 |
8.3 |
9.1 |
0.0 |
8.6 |
LeGarrette Blount |
o |
0 |
RB |
PIT@NE |
22 |
7.7 |
8.5 |
0.0 |
8.1 |
3.5 |
3.9 |
0.0 |
3.7 |
3.1 |
3.7 |
0.0 |
3.4 |
Ty Montgomery |
o |
0 |
RB |
GB@ATL |
20 |
12.1 |
12.7 |
0.0 |
12.4 |
6.0 |
6.4 |
0.0 |
6.2 |
7.5 |
8.2 |
0.0 |
7.8 |
Dion Lewis |
o |
0 |
RB |
PIT@NE |
19 |
10.4 |
11.9 |
0.0 |
11.2 |
5.5 |
6.3 |
0.0 |
5.9 |
6.1 |
7.7 |
0.0 |
6.9 |
Tevin Coleman |
o |
0 |
RB |
GB@ATL |
17 |
11.6 |
10.9 |
0.0 |
11.2 |
6.8 |
6.4 |
0.0 |
6.6 |
8.2 |
7.4 |
0.0 |
7.7 |
James White |
o |
0 |
RB |
PIT@NE |
13 |
9.1 |
7.6 |
0.0 |
8.4 |
7.0 |
5.8 |
0.0 |
6.5 |
7.1 |
5.2 |
0.0 |
6.1 |
DeAngelo Williams |
o |
0 |
RB |
PIT@NE |
12 |
1.8 |
1.2 |
0.0 |
1.5 |
1.5 |
1.0 |
0.0 |
1.2 |
0.5 |
0.2 |
0.0 |
0.3 |
Christine Michael |
o |
0 |
RB |
GB@ATL |
12 |
5.8 |
3.9 |
0.0 |
4.8 |
4.8 |
3.2 |
0.0 |
4.0 |
3.5 |
1.8 |
0.0 |
2.5 |
Aaron Ripkowski |
o |
0 |
RB |
GB@ATL |
11 |
2.5 |
2.7 |
0.0 |
2.6 |
2.3 |
2.5 |
0.0 |
2.4 |
0.9 |
1.0 |
0.0 |
1.0 |
James Develin |
o |
0 |
RB |
PIT@NE |
10 |
0.9 |
0.0 |
0.0 |
0.4 |
0.9 |
0.0 |
0.0 |
0.4 |
0.2 |
0.0 |
0.0 |
0.0 |
Patrick DiMarco |
o |
0 |
RB |
GB@ATL |
10 |
0.3 |
0.0 |
0.0 |
0.2 |
0.3 |
0.0 |
0.0 |
0.2 |
0.0 |
0.0 |
0.0 |
0.0 |
Antonio Brown |
o |
0 |
WR |
PIT@NE |
37 |
18.8 |
17.5 |
0.0 |
18.2 |
5.1 |
4.7 |
0.0 |
4.9 |
8.7 |
7.7 |
0.0 |
8.2 |
Julio Jones |
o |
0 |
WR |
GB@ATL |
32 |
13.3 |
14.6 |
0.0 |
14.0 |
4.2 |
4.6 |
0.0 |
4.4 |
5.5 |
6.5 |
0.0 |
6.0 |
Jordy Nelson |
o |
0 |
WR |
GB@ATL |
31 |
6.2 |
0.0 |
0.0 |
3.1 |
2.0 |
0.0 |
0.0 |
1.0 |
1.5 |
0.0 |
0.0 |
0.5 |
Julian Edelman |
o |
0 |
WR |
PIT@NE |
24 |
9.6 |
12.6 |
0.0 |
11.1 |
4.0 |
5.2 |
0.0 |
4.6 |
4.2 |
6.7 |
0.0 |
5.4 |
Davante Adams |
o |
0 |
WR |
GB@ATL |
24 |
13.0 |
14.6 |
0.0 |
13.8 |
5.4 |
6.1 |
0.0 |
5.8 |
7.1 |
8.7 |
0.0 |
7.9 |
Randall Cobb |
o |
0 |
WR |
GB@ATL |
23 |
8.1 |
13.4 |
0.0 |
10.8 |
3.5 |
5.8 |
0.0 |
4.7 |
3.3 |
7.8 |
0.0 |
5.4 |
Taylor Gabriel |
o |
0 |
WR |
GB@ATL |
18 |
7.8 |
8.4 |
0.0 |
8.1 |
4.3 |
4.7 |
0.0 |
4.5 |
3.9 |
4.4 |
0.0 |
4.2 |
Mohamed Sanu |
o |
0 |
WR |
GB@ATL |
15 |
5.7 |
7.9 |
0.0 |
6.8 |
3.8 |
5.3 |
0.0 |
4.5 |
2.7 |
4.8 |
0.0 |
3.7 |
Chris Hogan |
o |
0 |
WR |
PIT@NE |
14 |
8.8 |
8.5 |
0.0 |
8.6 |
6.3 |
6.1 |
0.0 |
6.1 |
6.2 |
5.8 |
0.0 |
5.9 |
Geronimo Allison |
o |
0 |
WR |
GB@ATL |
13 |
4.9 |
8.3 |
0.0 |
6.6 |
3.8 |
6.4 |
0.0 |
5.1 |
2.4 |
6.0 |
0.0 |
4.0 |
Michael Floyd |
o |
0 |
WR |
PIT@NE |
12 |
4.6 |
5.2 |
0.0 |
4.9 |
3.8 |
4.3 |
0.0 |
4.1 |
2.3 |
2.9 |
0.0 |
2.6 |
Malcolm Mitchell |
o |
0 |
WR |
PIT@NE |
12 |
2.0 |
2.2 |
0.0 |
2.1 |
1.7 |
1.8 |
0.0 |
1.8 |
0.6 |
0.7 |
0.0 |
0.6 |
Eli Rogers |
o |
0 |
WR |
PIT@NE |
11 |
7.4 |
7.8 |
0.0 |
7.6 |
6.7 |
7.1 |
0.0 |
6.9 |
5.8 |
6.4 |
0.0 |
6.1 |
Cobi Hamilton |
o |
0 |
WR |
PIT@NE |
10 |
3.9 |
3.0 |
0.0 |
3.4 |
3.9 |
3.0 |
0.0 |
3.4 |
2.1 |
1.3 |
0.0 |
1.7 |
Sammie Coates |
o |
0 |
WR |
PIT@NE |
10 |
2.7 |
2.8 |
0.0 |
2.8 |
2.7 |
2.8 |
0.0 |
2.8 |
1.1 |
1.2 |
0.0 |
1.2 |
Danny Amendola |
o |
0 |
WR |
PIT@NE |
10 |
4.2 |
4.2 |
0.0 |
4.2 |
4.2 |
4.2 |
0.0 |
4.2 |
2.4 |
2.4 |
0.0 |
2.4 |
Jeff Janis |
o |
0 |
WR |
GB@ATL |
10 |
3.1 |
2.2 |
0.0 |
2.7 |
3.1 |
2.2 |
0.0 |
2.7 |
1.4 |
0.8 |
0.0 |
1.1 |
Aldrick Robinson |
o |
0 |
WR |
GB@ATL |
10 |
2.4 |
2.9 |
0.0 |
2.6 |
2.4 |
2.9 |
0.0 |
2.6 |
0.9 |
1.3 |
0.0 |
1.0 |
Justin Hardy |
o |
0 |
WR |
GB@ATL |
10 |
5.4 |
4.8 |
0.0 |
5.1 |
5.4 |
4.8 |
0.0 |
5.1 |
3.7 |
3.0 |
0.0 |
3.4 |
Ladarius Green |
o |
0 |
TE |
PIT@NE |
16 |
3.8 |
0.0 |
0.0 |
1.9 |
2.4 |
0.0 |
0.0 |
1.2 |
1.3 |
0.0 |
0.0 |
0.4 |
Jared Cook |
o |
0 |
TE |
GB@ATL |
15 |
7.8 |
8.7 |
0.0 |
8.2 |
5.2 |
5.8 |
0.0 |
5.5 |
4.7 |
5.7 |
0.0 |
5.1 |
Martellus Bennett |
o |
0 |
TE |
PIT@NE |
13 |
6.3 |
7.6 |
0.0 |
7.0 |
4.8 |
5.8 |
0.0 |
5.4 |
3.7 |
5.2 |
0.0 |
4.5 |
Jesse James |
o |
0 |
TE |
PIT@NE |
12 |
4.4 |
5.6 |
0.0 |
5.0 |
3.7 |
4.7 |
0.0 |
4.2 |
2.2 |
3.3 |
0.0 |
2.7 |
Xavier Grimble |
o |
0 |
TE |
PIT@NE |
10 |
0.4 |
0.0 |
0.0 |
0.2 |
0.4 |
0.0 |
0.0 |
0.2 |
0.0 |
0.0 |
0.0 |
0.0 |
Matt Lengel |
o |
0 |
TE |
PIT@NE |
10 |
0.6 |
0.0 |
0.0 |
0.3 |
0.6 |
0.0 |
0.0 |
0.3 |
0.1 |
0.0 |
0.0 |
0.0 |
Richard Rodgers |
o |
0 |
TE |
GB@ATL |
10 |
1.8 |
3.9 |
0.0 |
2.8 |
1.8 |
3.9 |
0.0 |
2.8 |
0.6 |
2.1 |
0.0 |
1.2 |
Levine Toilolo |
o |
0 |
TE |
GB@ATL |
10 |
2.6 |
2.5 |
0.0 |
2.6 |
2.6 |
2.5 |
0.0 |
2.6 |
1.0 |
1.0 |
0.0 |
1.0 |
Austin Hooper |
o |
0 |
TE |
GB@ATL |
10 |
5.8 |
5.4 |
0.0 |
5.6 |
5.8 |
5.4 |
0.0 |
5.6 |
4.2 |
3.7 |
0.0 |
4.0 |
New England Patriots |
o |
0 |
D |
PIT@NE |
17 |
10.0 |
8.7 |
0.0 |
9.4 |
5.9 |
5.1 |
0.0 |
5.5 |
6.3 |
5.0 |
0.0 |
5.7 |
Pittsburgh Steelers |
o |
0 |
D |
PIT@NE |
14 |
6.6 |
5.8 |
0.0 |
6.2 |
4.7 |
4.1 |
0.0 |
4.4 |
3.8 |
3.0 |
0.0 |
3.4 |
Atlanta Falcons |
o |
0 |
D |
GB@ATL |
13 |
6.8 |
6.1 |
0.0 |
6.4 |
5.2 |
4.7 |
0.0 |
4.9 |
4.3 |
3.5 |
0.0 |
3.8 |
Green Bay Packers |
o |
0 |
D |
GB@ATL |
12 |
4.5 |
3.9 |
0.0 |
4.2 |
3.8 |
3.2 |
0.0 |
3.5 |
2.3 |
1.8 |
0.0 |
2.0 |