Daily Fantasy Baseball, Part I

When playing daily fantasy baseball, the most important concept is value.  Using the restriction of a salary cap, the objective is to assemble a lineup that scores the most points.  However, the players that score the most points per game are not necessarily the best players to use in your lineup.  In general, you want to look at a player's production relative to his price when determining his actual value to your lineup.  Obviously, player salaries fluctuate based on past performance, matchup, ballpark, position in the batting order, and several other factors.  Therefore, it is not even sufficient to look at a player's average points scored (in all games) compared to his current salary.  Rather, to get a better picture, we must examine his performance in each game relative to his salary for only that game.  (As far as I can tell, no free website that I have seen keeps track of this type of data and compiles it for you.)  

I have been keeping Draft Kings point totals and salary data all season long and have written a few programs to analyze all of it.  In doing so, I have developed a few metrics to measure a player's profitability.  First, what do I mean by profit?  In economics, profit is total revenue minus total cost.  In DFS, we have an easy way to measure cost (the player's salary), but revenue requires one extra step.  In order to equate points to a dollar value, we have to know, on average, how much a single DFS point is worth.  Based on my analysis, I have concluded that:

• On average, it costs about $517 in salary per point for pitchers
• On average, it costs about $569 in salary per point for hitters

This tells us that pitchers are approximately 10% more valuable than hitters since it takes about 10% less salary on average to score 1 point.  The profit formulas then become:

• For pitchers:     (points scored) x ($517) - (salary)
• For hitters:        (points scored) x ($569) - (salary)

Using these formulas, I have created a database of every player's game logs including salary and points scored.  I calculated total profit over the course of the season, average profit per game, percent of games played in which the player returned a profit. and a metric I like to call the GPP index.  This index heavily weights performances that are outliers in the positive direction, i.e. when a player returns 2 or 3 times the point total that one would expect based on his salary.  This, in general, is what will win you GPP matchups-- outstanding performances by players who are bargains based on their price.

The top 25 hitters in profit per game are listed below:

Top Draft Kings DFS players in profit per game

This analysis shows us that the most profitable hitters are a combination of high-priced superstars (Bryce Harper, Paul Goldschmidt, Josh Donaldson), breakout players having career years (A.J. Pollock, Lorenzo Cain, Manny Machado), and undervalued, cheaper role players (Chris Colabello, Billy Burns, Eddie Rosario).  In terms of GPP value, though, the picture is somewhat different.  Joey Votto, for example, is not a great GPP play because he is consistently good without the upside.  He is only profitable in less than 40% of his games (relatively low) and rarely provides an outstanding performance, giving him a GPP rank of 119 despite being the 22nd most profitable player.  Chris Colabello, on the other hand, has returned a profit in 57% of his games and comes at a relatively cheap price.  He also often returns 2 or 3 times his salary and is the highest ranked GPP player so far this season.

I have a lot more DFS data to share (including analysis of pitchers), but I wanted to put this out there and see if there is any response for more.  Part II may be coming soon if the demand is there.