Bargain Rating
Our Bargain Rating is a historical percentile rank representing how much of a bargain a player is on one daily fantasy site versus the other. We look at the typical difference in site salaries at a position and then rank a player based on how much of a bargain he is in a particular game relative to the historical data.
If a batter costs the same on DraftKings as he does on FanDuel, for example, he will have an extremely high Bargain Rating for DraftKings and a very low Bargain Rating for FanDuel since the latter site has a smaller salary cap and thus prices their batters much lower, on average.
Best Use
The Bargain Rating stat is extremely powerful and useful in a number of ways. First, there’s a strong link between Bargain Rating and player value (Plus/Minus). That shouldn’t be surprising since Plus/Minus is determined based on price; the cheaper a player, the more potential value he can offer (assuming the same skill level). It is smart to use Bargain Rating in your player models, especially in a sport like basketball in which it pays to be price-sensitive.
Second, Bargain Rating is an excellent way to determine where to get exposure to certain players. If you play daily fantasy sports on both DraftKings and FanDuel, you should get exposure to the players you like where they’re the cheapest. A big part of finding value is leaving yourself a cushion to soften the negative impact of assessment errors, and Bargain Rating does that better than any other stat.
Consistency
Also known as ‘X1,’ our Consistency figures show the percentage of games in which a player has reached his salary-based expectation. Instead of assessing players in an arbitrary and artificial way, we look at how production on each site is historically been connected to pricing to determine a more natural expected point total. All players are placed on an even playing field; it is just as easy for a $5,000 player to reach X consistency as it is for a $3,000 player, for example.
Best Use
To identify high-floor players for cash games
Breakout/Upside
Also known as ‘X2,’ our Breakout/Upside figures show the percentage of games in which a player has reached twice his salary-based expectation.
Best Use
To identify high-upside players for tournaments
Duds
Our Dud stat calculates the percentage of games in which a player has scored fewer than half his salary-based expectation.
Best Use
To identify low-floor players to avoid in cash games
Trends/Pro Trends
Our Trends product lets you leverage our massive database of historical salaries and fantasy performances to determine in which situations players traditionally offer value. You can create your own trends or utilize our DFS-pro-created ‘Pro Trends,’ which already show up in models and player cards.
Best Use
Our Pro Trends are very strongly linked to value, especially for pitchers. Most of the best pitcher models heavily weigh Pro Trends.
ML%
Moneyline percentage, or the percentage of bets coming in on each team in a game. We aggregate all our Vegas data from seven different sportsbooks.
Best Use
In baseball, there’s a positive correlation between public betting trends and player value. You can also use public betting trends to help predict player/team ownership in tournaments.
Salary Change
A player’s change in salary over a given period of time
Best Use
To help identify players whose price might be artificially inflated/deflated due to variance
