The FantasyLabs Friday Recap: 2/5/16

As we’re growing and publishing more content all around (very exciting), I’ve decided to make a post every Friday afternoon of the content from the previous week, just in case you’ve missed anything.

Here we go (Mario 64 voice)…

General

– Introducing the New FantasyLabs DFS Lineup Builder Tools

The new Lineup Builder is here! Watch Jonathan Bales in five different tutorial videos walk you through exactly how to use our new features.

– FantasyLabs Lineup Tools: Export to FanDuel

FanDuel added an import function this week, so we added the ability to use it with our new Lineup Builder tool. Jonathan Bales breaks down how.

– Accounting For Error in DFS Player Models, by Bryan Mears

One of the most important pieces of advice you can give a new DFS player is this: variance happens. It’s inevitable, of course – no projections, even the best ones out there, will always be perfect. Further, not only are projections prone to error, but our lineup processes and decisions are prone to error as well, be it because of biases or whatever other reason. I’ve said this before and I still believe it’s true – I don’t think the best DFS players are the best because they’re better at being right; rather, they’re the best because they best understand and account for the fact that they will often be wrong.

– The Pharmaceutical Philosophy: The Art of Shotgunning DFS Lineups, by Matthew Freedman

Like a pharmaceutical company “designing” drugs, you should never become too focused on any given lineup when creating entries for a GPP. Instead, you should focus your attention on the types of players you want and then create, through a streamlined shotgunned process, as many distinct lineups as possible with those players.

PGA

– Sign up for a chance to be part of the BETA test!

NBA

– NBA Stacking: Chicago Bulls, by Bill Monighetti

The Chicago Bulls are a team that you really have to pay attention to in DFS because when certain players are out, there are some pretty big ramifications. Just a few short seasons ago, it seemed like Derrick Rose was destined for superstardom, but today the only time I get excited about Rose is when he is confirmed out because that means it’s Butler time. To see how the Bulls’ players work together, let’s breakdown which stats lead to fantasy production for each of their key pieces.

– True DvP: Opponent Plus/Minus, 2/1/16, by Bryan Mears

Bryan updates the True DvP data.

– The Sophistication of Simplicity: The Simpleton’s NBA Cash Game Model, by Matthew Freedman

Through approximations we can make advancements. Something akin to a successful model can be constructed with a merely a few factors. I don’t think that the ease with which the Simpleton’s Model was created should be counted as a strike against it, and the same can be said for its simplicity. Rather, I think that the model should serve as a reminder that (not only are our tools awesome but also) what is basic can often be brilliant. The menial can contain magnificence.

– The Rockets in DFS Without Dwight Howard, by Bryan Mears

Dwight Howard has been out 10 games this year and I thought it would be interesting and hopefully useful to quickly look at his teammates’ fantasy impact in those particular games. Is it a small sample size? Sure. Is it tough to 100% trust the data because the rotation has been constantly changing throughout the season? Of course. However, DFS isn’t about finding perfect data, as that doesn’t exist. DFS is about using the data you have and making the best, most-informed decisions possible.

– Starting Three Shooting Guards, Becoming the Outlier, and Practicing For 10,000 Hours, by Matthew Freedman

Trying out crazy ideas, honing your craft, committing yourself to continual practice in the name of steady improvement — that’s the point of playing small slates. If you ever want to be a DFS outlier, you need to work toward that 10,000-hour goal, even if you’re down in a hole.

– Beating NBA: Adjusting Models While Building a Lineup, by JayCabay12

My transition into beating NBA has been a learning experience. I have had mild success playing cash games and I am now attempting to figure out a profitable GPP strategy. My goal now is to find the balance between playing the more obvious cash game players and mixing them with some riskier GPP plays. I think one way to do this is going to be by utilizing more than one model when creating a lineup.

– NBA DFS: Monitoring the Minutes, Volume 10, by Mitch Block

In this week’s volume of Monitoring the Minutes I thought we’d change it up a bit. After doing my usual research for this week’s column, it became clear that there weren’t any major meaningful changes to the minute allocations of fantasy relevant players. So I figured what better time to take a broader overview of how minutes can affect a player’s potential fantasy output on a night to night basis.

– NBA Trend Testing: Monthly Plus/Minus, by Bill Monighetti

This week, I’m taking a look at players who have been the most consistent over the past month’s worth of games. Without really considering matchup, if someone’s price point does not match their recent level of production due to increased opportunity or “getting hot,” wouldn’t it make sense to just keep riding the wave? Using this trend, I have matched players who have added the most Plus/Minus value over the last 30 days.