Staring into the Chasm

I’m sure you’ve heard it quite often in DFS analysis: “Player A is a cash-game play, while Player B is more suited for tournaments.” There’s nothing innately wrong with that type of analysis. However, sometimes we stare too far into the chasm of the “cash games versus tournaments” mindset and consequently miss the bridge of players right next us: The players who are both cash-game and tournament plays.

What do we mean when we call a player a “cash-game play” and another player a “tournament option”? We are suggesting that one player’s primary characteristic is consistency and the other’s is upside. Of course, what do we mean by “consistency” and “upside”? At FantasyLabs, we have quantified these concepts and formalized them into unique stats: Consistency and Upside. Here are quick definitions if you need them:

Consistency: The percentage of games in which a player has reached his salary-based expectation

Upside: The percentage of games in which a player has reached twice his salary-based expectation

In general, in cash games you want to find players with high Consistency (or safety). In tournaments, you want players with high Upside. Here’s the thing: Many people assume that these terms are antonymous, and that’s not true. They’re by no means synonymous, but nowhere in the definitions above do we see anything necessitating mutual exclusivity.

The Mythology of Mutual Exclusivity

Mutually exclusive outcomes are ones that can never happen together. The easiest example of this is flipping a coin: You can flip a head or a tail, but you cannot flip both in a single toss.

When we analyze players as either “cash-game plays” or “tournament plays,” we’re inferring mutual exclusivity when there isn’t any. And we’re likely losing profitability along the way.

Thankfully, because of our Consistency and Upside metrics, we can easily measure the relationship between cash-game and tournament players. To do this, I used our FREE Trends tool to look at all batters who A) have played at least 100 games total in the last three seasons and B) have a Consistency of at least 40 percent. I found 127 such batters. Next, I looked at those same batters’ Upside values.

For an unparalleled DFS edge, try our free Trends tool, through which you can access our massive database of advanced data and leverage our premium exclusive metrics, such as Upside, Consistency, and Plus/Minus.

If Consistency and Upside were mutually exclusive, we might expect to see negative correlation between the two. In theory, as a player’s Consistency would decrease, his Upside would increase, and vice versa. When graphing one against the other, we would expect to see a downward-trending line.

Here’s what our graph actually looks like:


In looking at the graph, we can see that a negative correlation does not exist. In fact, a slight positive correlation exists, although it might just be safer to say that no strong and/or definitive correlation exists at all, especially given that our sample is only 127 batters.

Stacking Consistency and Upside

So can Consistency and Upside be mutually exclusive? Maybe on a player-by-player basis. Take Todd Frazier: His 41-percent Consistency in the last three seasons is the lowest of our studied players, but his 20-percent Upside is very high.

Of course, there are other players for whom the two metrics are strongly correlated. For instance, Jason Kipnis has a sample-low 41-percent Consistency and the second-lowest Upside at 11 percent.

For DFS, players shoudn’t be considered in terms of mutual exclusion. Some players have both Consistency and Upside. Others have one or the other. And still others have neither.

Applications Are Not Mutually Exclusive

This knowledge is applicable in a variety of ways and is perhaps most useful for cash games and MLB DFS, which is very volatile. In such a sport, why would you focus only on Consistency when constructing cash-game lineups? Consistency is important, but it’s just one part of the puzzle. Why take a player with only high Consistency when you can take one with both high Consistency and high Upside? — especially when the volatility of the sport suggests that your cash-game lineups might need the benefit of Upside?

And in head-to-head contests it especially makes sense to consider both metrics. If playing H2Hs, you will win 80 percent of your contests over a large sample if your cash-game lineup is in the 80th percentile. And you’ll win only 20 percent of your H2H contests if your lineup is in the 20th percentile. In 50/50s, as long as the lineup is better than half the field, it’s sufficient. But in H2Hs, you would be silly not to target players that have both Consistency and Upside.

The two metrics are not mutually exclusive. Stop treating them that way.