Our Blog


Fading Vegas Early in the MLB Season

If you’re anything like me, you’ve always looked at Vegas lines and will continue to do so for the rest of your life. For years, I’ve unsuccessfully tried to tinker with different systems to beat my bookie. I once manually compiled data for two whole months on second half college basketball lines because I thought I could find inefficiencies in the lines. I thought there was no way Vegas could set a line and that same line become efficient in just 15 minutes time (during halftime). Typing that, I still kind of believe it. A few thousand dollars later, I quit compiling data. Fast forward to today: courtesy of FantasyLabs, I think I can crack the Vegas code…sorta.

Last year when I started playing MLB DFS, I developed a process in picking my players. My process, like many other DFS players, involved using Vegas lines to project points for my players. I had what I thought to be a great process down. In the beginning of last year, I noticed that using Vegas in MLB yielded me selecting a lot of very high-ownership players, which you really don’t want in GPPs, which is what I mostly play.

On top of having highly-owned players, I wasn’t seeing production from the players that I was selecting. Maybe I was bad at picking players, or maybe it was something else; this is when the past demons of “are there inefficiencies with Vegas lines” started creeping into my head. I developed a hypothesis that maybe Vegas, along with the public, wasn’t as good in creating accurate lines early in the season. Maybe there wasn’t enough information about the teams early in the season to accurately price lines. Would this be the first time I could beat Vegas? Only FantasyLabs could tell … by way of the Trends tool.

Before we get into this, I’ll lay the groundwork. We are going to analyze this by the way of batters’ Plus/Minus rating relative to team totals, game totals, and heavy favorites/underdogs. For those not familiar, the Plus/Minus is the difference between actual points and expected points based on the player’s salary. If on average, $3,000 outfielders score 10 points, and a $3,000 outfield scores 11, he has a Plus/Minus of +1.0.

I’m going to take sectors of a team’s projected runs, game totals, and moneylines, and take a look at the corresponding Plus/Minus of players in those sectors on a monthly basis.  All of what I’m about to talk about applies to batters only.

Bottom of the Barrel

quaile1

quaile2

quaile3

So, what does this show?

This is flat out some of the most important data that you can use right now in your MLB DFS GPP strategy. This data jumped off the page when I saw it. Most of you might think, “OK, so you’re telling me that player’s teams with low ‘team totals’, ‘game totals’, and ‘big underdogs’ all have a negative Plus/Minus.” While that may be true, look at the trends. It’s staring us right in the face. When it comes to DFS, Vegas is very inefficient early in the season. This is evidenced by the monthly regression of the Plus/Minus relative to these Vegas inputs. Look at the difference in how these “bottom of the barrel” Vegas plays perform in April compared to the rest of the year.

Intuitively, one would think that the Plus/Minus of players on teams like this would perform poorly all year, but this is not necessarily true. In April, players on teams with low team totals, game totals, and big underdogs don’t perform nearly as bad as they do as the year goes on. Why is this? My guess is that these totals/lines become more efficient as the year goes on. An easy way to put it: A player on a team with a low team total has way less value in August than they do in April. We will talk more about this later.

That Was Cool, but What About the Crème de la Crème?

vegas1

vegas2

vegas3

And again, what does this show?

Again, I believe this is one of the more important pieces of data to look at early in the baseball season. To summarize, players on teams with high run totals, high game totals, and heavy favorites really do not perform as well as they do early in the season as they do in the later months of the season. It should be a surprise to no one that these are all positive Plus/Minus plays. What stands out to me the most is that the players in these situations seem to perform to their Vegas prices as the season goes on – as Vegas gets better at pricing games. To summarize: A player on a team with a high total has less value in April than they do in August.

How Can We Trade This?

Early in the article I pointed out how Vegas is a big part of my process in DFS, especially for baseball. Most of the DFS world looks at Vegas; it is silly not to. This is where we get to take advantage. Favorites and high-Vegas totals are a big driver of ownership in MLB DFS. There is a correlation of ownership and all of these factors that I have shown above – i.e., a higher team total = higher ownership for players on that team.

Now that we know that Vegas doesn’t entirely get it right early in the season, we can really exploit it in DFS, and especially in GPPs. We know that players on teams that have low projected team totals, game totals, and heavy underdogs do not really perform as bad as Vegas thinks early on in the season. We also know that players on these teams are going to come with low ownership. The inverse is also true – players with favorable Vegas numbers do not perform as well as we think early in the season, and this comes with higher ownership. That’s GIGANTIC for GPPs. Early in the season, I believe it’s a very +EV play to target players on teams with unfavorable Vegas numbers. It’s actually the perfect storm for MLB DFS in the early months of the season.

Warning, MLB DFS is really, really hard. If you think that you’ll just be able to target teams with low totals and win a GPP tonight, you’re wrong. Not only do you have to pick the right team/game/players to target, but you also have to build the players around those lower team total/game total/underdog players. I’ll use myself as an example because I have no shame.

I started using this data during this season. I’ve been really good at finding these low-total gems. I think I stacked the highest-scoring teams the first four days of the season, and all had low ownership and low totals. So how much have I won? ZERO. You still need to be able to pick the right games, then teams, then players. And then, you need to build around that. So why am I throwing myself under the bus here? It is because that using this strategy is probably not going to win you a tournament tonight, or even tomorrow; after all, we are targeting guys on teams that Vegas thinks will be duds. Vegas is going to be correct sometimes.

However, this data reveals that there is more of a chance to target these lower-total teams early in the season. If executed properly, and given the right amount of time, this is a strategy that can win you a lot of money. You just have to have the stomach for losing before that big hit – that pretty much applies to MLB DFS GPPs in general. Good luck.

If you’re anything like me, you’ve always looked at Vegas lines and will continue to do so for the rest of your life. For years, I’ve unsuccessfully tried to tinker with different systems to beat my bookie. I once manually compiled data for two whole months on second half college basketball lines because I thought I could find inefficiencies in the lines. I thought there was no way Vegas could set a line and that same line become efficient in just 15 minutes time (during halftime). Typing that, I still kind of believe it. A few thousand dollars later, I quit compiling data. Fast forward to today: courtesy of FantasyLabs, I think I can crack the Vegas code…sorta.

Last year when I started playing MLB DFS, I developed a process in picking my players. My process, like many other DFS players, involved using Vegas lines to project points for my players. I had what I thought to be a great process down. In the beginning of last year, I noticed that using Vegas in MLB yielded me selecting a lot of very high-ownership players, which you really don’t want in GPPs, which is what I mostly play.

On top of having highly-owned players, I wasn’t seeing production from the players that I was selecting. Maybe I was bad at picking players, or maybe it was something else; this is when the past demons of “are there inefficiencies with Vegas lines” started creeping into my head. I developed a hypothesis that maybe Vegas, along with the public, wasn’t as good in creating accurate lines early in the season. Maybe there wasn’t enough information about the teams early in the season to accurately price lines. Would this be the first time I could beat Vegas? Only FantasyLabs could tell … by way of the Trends tool.

Before we get into this, I’ll lay the groundwork. We are going to analyze this by the way of batters’ Plus/Minus rating relative to team totals, game totals, and heavy favorites/underdogs. For those not familiar, the Plus/Minus is the difference between actual points and expected points based on the player’s salary. If on average, $3,000 outfielders score 10 points, and a $3,000 outfield scores 11, he has a Plus/Minus of +1.0.

I’m going to take sectors of a team’s projected runs, game totals, and moneylines, and take a look at the corresponding Plus/Minus of players in those sectors on a monthly basis.  All of what I’m about to talk about applies to batters only.

Bottom of the Barrel

quaile1

quaile2

quaile3

So, what does this show?

This is flat out some of the most important data that you can use right now in your MLB DFS GPP strategy. This data jumped off the page when I saw it. Most of you might think, “OK, so you’re telling me that player’s teams with low ‘team totals’, ‘game totals’, and ‘big underdogs’ all have a negative Plus/Minus.” While that may be true, look at the trends. It’s staring us right in the face. When it comes to DFS, Vegas is very inefficient early in the season. This is evidenced by the monthly regression of the Plus/Minus relative to these Vegas inputs. Look at the difference in how these “bottom of the barrel” Vegas plays perform in April compared to the rest of the year.

Intuitively, one would think that the Plus/Minus of players on teams like this would perform poorly all year, but this is not necessarily true. In April, players on teams with low team totals, game totals, and big underdogs don’t perform nearly as bad as they do as the year goes on. Why is this? My guess is that these totals/lines become more efficient as the year goes on. An easy way to put it: A player on a team with a low team total has way less value in August than they do in April. We will talk more about this later.

That Was Cool, but What About the Crème de la Crème?

vegas1

vegas2

vegas3

And again, what does this show?

Again, I believe this is one of the more important pieces of data to look at early in the baseball season. To summarize, players on teams with high run totals, high game totals, and heavy favorites really do not perform as well as they do early in the season as they do in the later months of the season. It should be a surprise to no one that these are all positive Plus/Minus plays. What stands out to me the most is that the players in these situations seem to perform to their Vegas prices as the season goes on – as Vegas gets better at pricing games. To summarize: A player on a team with a high total has less value in April than they do in August.

How Can We Trade This?

Early in the article I pointed out how Vegas is a big part of my process in DFS, especially for baseball. Most of the DFS world looks at Vegas; it is silly not to. This is where we get to take advantage. Favorites and high-Vegas totals are a big driver of ownership in MLB DFS. There is a correlation of ownership and all of these factors that I have shown above – i.e., a higher team total = higher ownership for players on that team.

Now that we know that Vegas doesn’t entirely get it right early in the season, we can really exploit it in DFS, and especially in GPPs. We know that players on teams that have low projected team totals, game totals, and heavy underdogs do not really perform as bad as Vegas thinks early on in the season. We also know that players on these teams are going to come with low ownership. The inverse is also true – players with favorable Vegas numbers do not perform as well as we think early in the season, and this comes with higher ownership. That’s GIGANTIC for GPPs. Early in the season, I believe it’s a very +EV play to target players on teams with unfavorable Vegas numbers. It’s actually the perfect storm for MLB DFS in the early months of the season.

Warning, MLB DFS is really, really hard. If you think that you’ll just be able to target teams with low totals and win a GPP tonight, you’re wrong. Not only do you have to pick the right team/game/players to target, but you also have to build the players around those lower team total/game total/underdog players. I’ll use myself as an example because I have no shame.

I started using this data during this season. I’ve been really good at finding these low-total gems. I think I stacked the highest-scoring teams the first four days of the season, and all had low ownership and low totals. So how much have I won? ZERO. You still need to be able to pick the right games, then teams, then players. And then, you need to build around that. So why am I throwing myself under the bus here? It is because that using this strategy is probably not going to win you a tournament tonight, or even tomorrow; after all, we are targeting guys on teams that Vegas thinks will be duds. Vegas is going to be correct sometimes.

However, this data reveals that there is more of a chance to target these lower-total teams early in the season. If executed properly, and given the right amount of time, this is a strategy that can win you a lot of money. You just have to have the stomach for losing before that big hit – that pretty much applies to MLB DFS GPPs in general. Good luck.