RotoAcademy Preview: Essential Stats in NBA DFS
I wanted to start this lesson with a story, but I didn’t have an exciting one that had anything to do with statistics. Quoting statistics and trends used to be nerdy in sports, but the tables have turned. All of the cool kids are doing it now. If you are still making lineups based on feel and your gut, you are probably falling way behind the rest of the field.
This lesson is going to cover what I believe are the most important statistics in daily fantasy basketball. I’ve also tweaked some of the stats to make them more applicable to DFS.
Editor’s Note: This is one of the many valuable DFS lessons that can be found over at RotoAcademy. Click here to browse through all of our offerings and improve as a daily fantasy sports player!
Minutes
One of the most common ways people describe daily fantasy basketball is “predictable.” This is a big reason why it is my most profitable sport. The key difference between the NBA and the NFL or MLB is variance. Football and baseball both rely on big plays for fantasy production. Big plays are obviously few and far between, which causes player production to vary greatly on a weekly or daily basis.
A deep touchdown pass or a home run could be the bulk of a player’s fantasy production in football or baseball. In basketball, the best a player can do on a single play is to get a block, a rebound, and make a three pointer. Even if that happens, 6.2 fantasy points wouldn’t swing a player’s fantasy production unless he were having a terrible game. There are more possessions and more ways to score fantasy points, which leads to a more predictive sport on a nightly basis.
One of the most important stats is the simplest of them all: Minutes. There is a linear relationship between minutes and fantasy production in basketball, and the reason is simple. A player can score fantasy points through points, rebounds, assists, blocks, and steals. The longer a player is on the floor, the more access he will have to that potential fantasy production. This isn’t rocket science here. If you have two comparable players, the one expected to play more minutes will have the edge if everything else is equal.
Now, I want to point out quickly that all minutes are not created equal. Pace of play should always be factored in when analyzing minutes. Someone who plays 30 minutes per game for the Grizzlies isn’t going to see nearly as many possessions as someone who plays 30 minutes per game for the Warriors. However, if you are already factoring in pace and Vegas implied team totals, this will account for the difference.
The tricky part is trying to predict minutes. I use a fairly simple approach. I take a player’s average minutes over the course of the season and compare them to his average minutes over his last five games. These stats are easily pulled from the NBA.com link that I gave you in the resources section. I put the season-long minutes in one column and the five-game minutes in another column. I then create a third column where I put my minutes projections.
For actual projection, this is more of an art than a science. When you see that a player is playing more minutes recently and you know that it isn’t fluky, you want to account for that in your projection. I then adjust my projection for injuries and for potential blowouts.
Usage Rate
A player’s usage rate measures how many possessions a player uses per 40 minutes while on the floor. This is one of the most common statistics used in daily fantasy basketball. It is one of the best ways to capture how involved a player is offensively. As we know, most players rely on offensive production for the bulk of their fantasy points, especially guards.
The simple usage rate calculation is as follows:
Usage Rate =
{[FGA + (FT Att. x 0.44) + (Ast x 0.33) + TO] x 40 x League Pace} divided by (Minutes x Team Pace)
I have no qualms if you want to use this formula in your daily analysis. It’s simple and a ton of sites show each player’s usage rate, so you don’t have to do the calculation on your own. However, the formula does have its flaws. The first is that it counts turnovers as a positive. What I mean is that if a player commits a turnover, it adds to their usage rate. Obviously, turnovers are worth negative points in DFS, so ideally we don’t want to use a formula in which turnovers are good. The formula also undervalues assists and doesn’t account for three-point attempts.
To make it more applicable to DFS, I’ve created my own calculation that I call DFS-Adjusted Usage. The calculation for this is as follows:
DFS-Adjusted Usage Rate =
{[FGA + (FT Att. x 0.44) + (3PA x 0.1) + Ast – TO] x 40 x League Pace} divided by (Minutes x Team Pace)
If you use excel regularly and are already importing the stats from NBA.com, this should be a simple calculation that you can have excel do for you. The key differences between the two metrics are subtle, but ultimately DFS-Adjusted Usage Rate is more correlated with DFS production. As you can see, I’ve subtracted turnovers, added three point attempts, and increased the value of assists.
If you aren’t Excel-savvy or don’t have the time to calculate your own usage rates, there is one site that I like to use that you might find useful. This site breaks usage out into three categories: regular usage rate, play-making usage, and turnover usage. Regardless of which usage rate you decide to use, it should be included in your daily analysis. Players with low usage rates often have low ceilings because they aren’t involved offensively.
Defense vs. Position
If you have played any daily fantasy sport, then you should be familiar with the concept of DvP. It shows how many fantasy points a defense allows to each position. This is the quickest way to spot favorable matchups for players. The stat has its flaws, but it becomes more and more valuable as the season progresses. The main reason I don’t DvP metrics early in the season is the issue of sample size. An outlier will sway the data, so I generally wait a few weeks before I start using DvP stats.
Ideally, it would be beneficial to create a schedule-adjusted DvP in basketball. However, I don’t have the resources to do it. If you can find a way to take each player’s expected production and compare that to what the defense allows, you could get a plus/minus value for each position that would be a lot more indicative of a defense’s ability to stop each position.
While DvP stats are valuable, we need to adjust them when there are injuries, trades, or rotation changes on the opponent. When Marc Gasol is healthy, the Grizzlies are going to be one of the worst matchups for opposing centers. However, if he is out for a game or for an extended period of time, you don’t want to use the Grizzlies’ DvP ranking against centers.
Hopefully, you will be able to take these statistics and make them your own. A big part of being successful at daily fantasy basketball is constantly adjusting, whether it be with your stats and weightings or with your lineup construction.
In Notorious’ Ultimate Guide to Beating NBA DFS, you’ll learn:
• Which resources to use for research
• The importance of Vegas data
• How to predict pace and favorable game environments
• The essential statistics for NBA
• How to adjust for late scratches and injuries
• The nuances of salary-based expectations
• The splits that add value to your research
To read the rest of this content, you must purchase the course!
