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How to Utilize the Power of the FantasyLabs Trends Tool for DFS

Why the Trends Tool is the Best Part of FantasyLabs

If you’ve read any of my DFS Breakdowns, you know how heavily I rely on our Trends tool. With all due respect to our Lineup Optimizer, the Trends tool is the most valuable part of your FantasyLabs subscription.

In this article, I will go over what the Trends tool is, what it isn’t, and how to get the most out of it.

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Lineup builder and optimizer

Real-time DFS models

Data-driven analysis & tutorials

What it Does

For those of you who are unfamiliar with our Trends tool, our Trends tool allows you to look at the past performance of players who meet certain criteria. You can select specific players, or have the tool list out all players who meet the criteria for the trend you’re creating.

As an example, there are over 100 different potential inputs for wide receivers.

After you select your choices, for example: “home underdog wide receivers with a game total of at least 50,” it will give you every player’s fantasy performance in that situation (dating back to 2015):

You then can see average scoring, average Plus/Minus (a proprietary measure of how well a player performs compared to their salary), average ownership, and consistency of that group. It also shows all players for the current slate that meet that criteria.

Our Player Models also come pre-loaded with “Pro Trends” built by some of the best DFS players in the game. These show you the average Plus/Minus of players who fit the trend in the past. Our pros have identified specific trends as being especially predictive, and our models allow you to sort players by the number of these trends they fit on a given slate.


What it isn’t

I shouldn’t speak for everyone else here, but my initial use of the Trends tool wasn’t very productive. I tried to emulate the Pro Trends, and build a system of trends that allowed me to easily identify the best plays on the slate. Here’s the problem with that: the Pro Trends have already done it.

While it’s certainly possible, you’d be hard-pressed to break new ground yourself, especially without “double-counting” or making trends that combine multiple Pro Trends into one.

An example of this given the McCaffrey Pro Trends above: it would be redundant to create a trend for “projected over 16 points” and “ceiling over 22 points” since both are accounted for already. Even though that trend would be very powerful, boasting a +1.66 Plus/Minus on average.


The Breakthrough

Here’s the realization I had. The Trends tool is the single most powerful “question answering” system available. Want to know which Browns running back to play when Cleveland is an underdog? The Trends tool can tell you.

Do tight ends perform better against bad defenses? Make a trend. To phrase that another way, are defensive points allowed to tight ends a predictive measure, or simply descriptive?

As an experiment, try to go back on your own and see how tight ends have performed against bottom-three defenses over the last six seasons. Remember, you have to figure out which defenses were bottom three versus the position at the time.

Looking backward at points allowed by defenses that finished the worst against the position is descriptive; it tells us what happened. Without looking up where they were ranked at the time the game was played, we have no way of knowing if that information predicts fantasy success in the future.

OK, how long did that take you? You didn’t really do it, did you? Thought so… it took me about 30 seconds:

Note: The Trends tool allows you to sort by defensive percentile, the 90th percentile includes the bottom-three NFL teams.

For someone like me, who plays primarily cash games and smaller field tournaments, these questions come up all the time. I don’t go hunting for a valuable trend, I’m looking for the best plays and trying to use this tool to help me identify them. It would take hours to answer these questions myself if I could even find the data, and Trends tool does it in seconds.


Tips and Tricks

First and foremost, familiarize yourself with the Pro Trends. If a player has a lot of those, they’re likely to be a solid play. We conveniently give the players with five or more Pro Trends a blue background.

Next, when building your own trend, the first step is to make sure the question you’re asking is a good one. Here’s what I mean: Is it relevant how well tight ends with a wind speed of exactly 7.0 MPH have performed in the past? Even though we have a decent sample size (293), it’s unlikely that there’s anything important here.

If you go hunting for enough specific situations like this, you’ll probably find one that appears hugely profitable. However, it’s almost certainly just noise. You need to ask yourself, is there any reason that “situation x” should lead to more or less fantasy scoring? If there isn’t, it’s likely not a good Trend.

As I alluded to above, sample size matters as well. You could ask a good question, but if your situation has only occurred twice in the past, it’s hard to be confident that it’s telling you anything important. This was my biggest mistake when I started playing with the tool.

When you’re using the Trends tool for slate-specific research, think about the player(s) you’re trying to research first. Then build the Trend. To use the example from my introduction, using the Trends tool to decide between Browns running backs on a given slate is very helpful.

You can sort by specific players and teams, which makes this easy. Did you know Kareem Hunt outscores Nick Chubb when the Browns are underdogs (in raw scoring, not just salary-based)?

Now you do:

Finally, be careful not to overfit your model. Is there a game expected to have high winds this weekend? It’s far more valuable to look at how quarterbacks have done in the past when wind speeds are at least 15 MPH than it is to examine games with 18 MPH winds, specifically, even if that’s the situation this weekend.

This takes some finesse, but I try to use a range of around 10% (of the available options) above or below the specific situation I’m looking into. It’s unlikely that a 0.2 or 0.3 difference in running back attempts really tells us much.


Conclusion

Hopefully, this article gives you a better understanding of one of the most valuable tools FantasyLabs has to offer. What’s so great about it is the versatility.

While I used the NFL as an example, we have the tool for MLB, NBA, NHL, and golf. If you have enough time to dig around for the best plays, it helps you do that. If you just want an at-a-glance view? Use the Pro Trends. I didn’t come anywhere near discussing all the potential uses of this tool, but take some time to dig around for yourself. I think you’ll be happy with what you find.

Why the Trends Tool is the Best Part of FantasyLabs

If you’ve read any of my DFS Breakdowns, you know how heavily I rely on our Trends tool. With all due respect to our Lineup Optimizer, the Trends tool is the most valuable part of your FantasyLabs subscription.

In this article, I will go over what the Trends tool is, what it isn’t, and how to get the most out of it.

Start Your PRO Trial Today

Lineup builder and optimizer

Real-time DFS models

Data-driven analysis & tutorials

What it Does

For those of you who are unfamiliar with our Trends tool, our Trends tool allows you to look at the past performance of players who meet certain criteria. You can select specific players, or have the tool list out all players who meet the criteria for the trend you’re creating.

As an example, there are over 100 different potential inputs for wide receivers.

After you select your choices, for example: “home underdog wide receivers with a game total of at least 50,” it will give you every player’s fantasy performance in that situation (dating back to 2015):

You then can see average scoring, average Plus/Minus (a proprietary measure of how well a player performs compared to their salary), average ownership, and consistency of that group. It also shows all players for the current slate that meet that criteria.

Our Player Models also come pre-loaded with “Pro Trends” built by some of the best DFS players in the game. These show you the average Plus/Minus of players who fit the trend in the past. Our pros have identified specific trends as being especially predictive, and our models allow you to sort players by the number of these trends they fit on a given slate.


What it isn’t

I shouldn’t speak for everyone else here, but my initial use of the Trends tool wasn’t very productive. I tried to emulate the Pro Trends, and build a system of trends that allowed me to easily identify the best plays on the slate. Here’s the problem with that: the Pro Trends have already done it.

While it’s certainly possible, you’d be hard-pressed to break new ground yourself, especially without “double-counting” or making trends that combine multiple Pro Trends into one.

An example of this given the McCaffrey Pro Trends above: it would be redundant to create a trend for “projected over 16 points” and “ceiling over 22 points” since both are accounted for already. Even though that trend would be very powerful, boasting a +1.66 Plus/Minus on average.


The Breakthrough

Here’s the realization I had. The Trends tool is the single most powerful “question answering” system available. Want to know which Browns running back to play when Cleveland is an underdog? The Trends tool can tell you.

Do tight ends perform better against bad defenses? Make a trend. To phrase that another way, are defensive points allowed to tight ends a predictive measure, or simply descriptive?

As an experiment, try to go back on your own and see how tight ends have performed against bottom-three defenses over the last six seasons. Remember, you have to figure out which defenses were bottom three versus the position at the time.

Looking backward at points allowed by defenses that finished the worst against the position is descriptive; it tells us what happened. Without looking up where they were ranked at the time the game was played, we have no way of knowing if that information predicts fantasy success in the future.

OK, how long did that take you? You didn’t really do it, did you? Thought so… it took me about 30 seconds:

Note: The Trends tool allows you to sort by defensive percentile, the 90th percentile includes the bottom-three NFL teams.

For someone like me, who plays primarily cash games and smaller field tournaments, these questions come up all the time. I don’t go hunting for a valuable trend, I’m looking for the best plays and trying to use this tool to help me identify them. It would take hours to answer these questions myself if I could even find the data, and Trends tool does it in seconds.


Tips and Tricks

First and foremost, familiarize yourself with the Pro Trends. If a player has a lot of those, they’re likely to be a solid play. We conveniently give the players with five or more Pro Trends a blue background.

Next, when building your own trend, the first step is to make sure the question you’re asking is a good one. Here’s what I mean: Is it relevant how well tight ends with a wind speed of exactly 7.0 MPH have performed in the past? Even though we have a decent sample size (293), it’s unlikely that there’s anything important here.

If you go hunting for enough specific situations like this, you’ll probably find one that appears hugely profitable. However, it’s almost certainly just noise. You need to ask yourself, is there any reason that “situation x” should lead to more or less fantasy scoring? If there isn’t, it’s likely not a good Trend.

As I alluded to above, sample size matters as well. You could ask a good question, but if your situation has only occurred twice in the past, it’s hard to be confident that it’s telling you anything important. This was my biggest mistake when I started playing with the tool.

When you’re using the Trends tool for slate-specific research, think about the player(s) you’re trying to research first. Then build the Trend. To use the example from my introduction, using the Trends tool to decide between Browns running backs on a given slate is very helpful.

You can sort by specific players and teams, which makes this easy. Did you know Kareem Hunt outscores Nick Chubb when the Browns are underdogs (in raw scoring, not just salary-based)?

Now you do:

Finally, be careful not to overfit your model. Is there a game expected to have high winds this weekend? It’s far more valuable to look at how quarterbacks have done in the past when wind speeds are at least 15 MPH than it is to examine games with 18 MPH winds, specifically, even if that’s the situation this weekend.

This takes some finesse, but I try to use a range of around 10% (of the available options) above or below the specific situation I’m looking into. It’s unlikely that a 0.2 or 0.3 difference in running back attempts really tells us much.


Conclusion

Hopefully, this article gives you a better understanding of one of the most valuable tools FantasyLabs has to offer. What’s so great about it is the versatility.

While I used the NFL as an example, we have the tool for MLB, NBA, NHL, and golf. If you have enough time to dig around for the best plays, it helps you do that. If you just want an at-a-glance view? Use the Pro Trends. I didn’t come anywhere near discussing all the potential uses of this tool, but take some time to dig around for yourself. I think you’ll be happy with what you find.