Our Blog


The FantasyLabs Friday Recap: 6/3/16

This week, we published a lot of content that will be applicable for a while. Within this FantasyLabs Friday Recap, you can find links to all of that content, for your weekend reading pleasure.

General

Asset Allocation: The Secret of Bankroll Management, by Matthew Freedman

In a perfect cash-game world, you would be able to build a lineup with projectable players competing in a larger, consistent slate in a DFS sport that is relatively nonvolatile. Based on past experience, you would determine that your lineup has a high probability of beating maybe two-thirds of the cash-game field. You would then allocate the entire 80 percent of your cash-game portion to 50/50s. And then you would cash in 100 percent of contests. And then you would repeat the process forever.

FantasyLabs Podcast: How to Transition From Cash Games to Tournaments in DFS

Bryan Mears is joined by guest Max Steinberg to talk about how to transition from cash games to tournaments in daily fantasy sports.

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

NBA

The Bayesian Prior, GS-OKC, and the 2016 NBA Finals, by Matthew Freedman

Why, after only four games, did people act as if the Warriors were destined to lose? People bought into the myth of momentum. They allowed their judgment to be clouded by recency bias. They placed too much significance on a four-game sample (and really just the two-game sample of Games 3-4). They got caught up in the noise and lost the signal. They forgot about the primacy of the Bayesian prior.

Golf

Video: Memorial Tournament Model Preview

Peter Jennings (CSURAM88) breaks down his personal model for the 2016 Memorial Tournament.

Video: PGA Lineup Review for the 2016 DEAN & DELUCA Invitational

Peter Jennings (CSURAM88) breaks down his Golf DFS lineup for the 2016 DEAN & DELUCA Invitational.

Why Stars-And-Scrubs Is The Way to Go in DFS Golf, by Bryan Mears

The Vegas Bargain Ratings for the top golfers are incredibly high compared to those of the rest of the field. This is something I’ve been noticing for a while and want to discuss further: The top golfers, in terms of implied upside, are drastically underpriced on DraftKings.

Quantifying Course History’s Effect, by Colin Davy

First, it’s liberating knowing that you don’t necessarily have to know what you’re not picking up, as long as you can quantify it and fold it back in. Second, blending in empirical errors on a player-level basis is probably something every DFS Golf model should have. That’s what course history is in a nutshell: A correction factor for when you’re empirically off.

MLB

The Daily Fantasy Flex, MLB: 6/3/16 Main Slate

Jay Persson and Peter Jennings (CSURAM88) break down the 6/3/16 MLB DFS main slate.

MLB Plays of the Day: 6/3/16, Main Slate

J.D. Martinez is a clear anti-Carlos Rodon stacking candidate, as he boasts an impressive .310 Isolated Power and .395 Weighted On-Base Average against opposing left-handed pitchers. Additionally, Martinez can be had fairly reasonably on DraftKings tonight, where he carries a Bargain Rating of 70 percent.

MLB DFS 6/3/16 Slate Breakdown, by John Daigle

Ortiz is now slugging .692 versus right-handed pitching and has recorded the most DraftKings points among first basemen over the last month. What’s more astonishing is that he has met or exceeded salary-based expectations with 65-percent Consistency over that span. As for tonight, note that he’s the only player at his position with double-digit Pro Trends.

Video: Introducing the Sports Geek MLB Pro Model

We’ve added a new Pro Model in our MLB Player Models, built around Kevin The Sports Geek.

A Study on Fastball Velocity, Part II, by Bill Monighetti

While my assumption was that a higher velocity would lead to harder contact (which would be especially bad for fly-ball pitchers), it looks like the opposite is true. A lower velocity likely makes the pitches more hittable, which is especially bad for fly-ball pitchers. I’ll keep mentioning the small samples that we are working with, but when there is nearly a five-point swing per-player, per-game, it’s pretty hard to ignore.

MLB DFS: The Most Powerful Advanced Stats of All, by Mitchell Block

We’ve established which recent advanced stats provide the most value for both hitters and pitchers. But what do we do with this information? Personally, I try to incorporate a good amount of this data into our Trends tool. Much of this data isn’t being incorporated into pricing at the DFS sites or utilized in the research by non-FantasyLabs DFS players. Take advantage of this edge as often as possible. 

State of the Stacks, Vol. 6, by Mitchell Block

The Brewers will spend the majority of their week in Philadelphia, taking on a Phillies team that has been average in terms of fantasy production allowed to opposing batters this year. With Philadelphia scoring the fewest runs per game in the majors this season, and Milwaukee sitting in the middle of the pack, I would expect the majority of these games to come in with low implied Vegas totals. From an ownership arbitrage perspective, such a scenario could offer up an opportunity to exploit the low ownership often associated with such games.

MLB Trend Testing: Weak-Hitting Opponents, by Bill Monighetti

This week’s trend matches pitchers who both have a high K Prediction and are facing a lineup of batters whose collective Hard Hit Percentage is low. I think that this trend is best utilized in both cash games and tournaments. There will be really chalky qualifiers — like Scherzer — who make great cash game plays, and there will also be pitchers who appear a little riskier than they actually may be: These are the players whose matchups you will want to exploit in tournaments.

MLB Recent Form Report: 5/30/16, by Bill Monighetti

I created a pitcher trend on FanDuel and added filters that matched Matt Harvey’s recent differentials in Pitch Velocity, Distance, and Exit Velocity. So what did the Plus/Minus look like? While I would have accepted “Crying Jordan” or “Poop Emoji,” the actual Plus/Minus is -2.57.

Trends

MLB 5/30/16: High-ISO Lefties at Oriole Park, by Jonathan Cabezas

MLB 5/31/16: Pitchers with Poor WHIPs but Are Heavy Favorites, by Brandon Hopper

MLB 6/1/16: If You’re Going to Steal, Make It Worth It, by Jay Persson

– MLB 6/2/16: Bottom-Of-The-Order Rockies, by Bryan Mears

MLB 6/3/16: Power Hitters at the Top of the Lineup, by Mitchell Block

This week, we published a lot of content that will be applicable for a while. Within this FantasyLabs Friday Recap, you can find links to all of that content, for your weekend reading pleasure.

General

Asset Allocation: The Secret of Bankroll Management, by Matthew Freedman

In a perfect cash-game world, you would be able to build a lineup with projectable players competing in a larger, consistent slate in a DFS sport that is relatively nonvolatile. Based on past experience, you would determine that your lineup has a high probability of beating maybe two-thirds of the cash-game field. You would then allocate the entire 80 percent of your cash-game portion to 50/50s. And then you would cash in 100 percent of contests. And then you would repeat the process forever.

FantasyLabs Podcast: How to Transition From Cash Games to Tournaments in DFS

Bryan Mears is joined by guest Max Steinberg to talk about how to transition from cash games to tournaments in daily fantasy sports.

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

NBA

The Bayesian Prior, GS-OKC, and the 2016 NBA Finals, by Matthew Freedman

Why, after only four games, did people act as if the Warriors were destined to lose? People bought into the myth of momentum. They allowed their judgment to be clouded by recency bias. They placed too much significance on a four-game sample (and really just the two-game sample of Games 3-4). They got caught up in the noise and lost the signal. They forgot about the primacy of the Bayesian prior.

Golf

Video: Memorial Tournament Model Preview

Peter Jennings (CSURAM88) breaks down his personal model for the 2016 Memorial Tournament.

Video: PGA Lineup Review for the 2016 DEAN & DELUCA Invitational

Peter Jennings (CSURAM88) breaks down his Golf DFS lineup for the 2016 DEAN & DELUCA Invitational.

Why Stars-And-Scrubs Is The Way to Go in DFS Golf, by Bryan Mears

The Vegas Bargain Ratings for the top golfers are incredibly high compared to those of the rest of the field. This is something I’ve been noticing for a while and want to discuss further: The top golfers, in terms of implied upside, are drastically underpriced on DraftKings.

Quantifying Course History’s Effect, by Colin Davy

First, it’s liberating knowing that you don’t necessarily have to know what you’re not picking up, as long as you can quantify it and fold it back in. Second, blending in empirical errors on a player-level basis is probably something every DFS Golf model should have. That’s what course history is in a nutshell: A correction factor for when you’re empirically off.

MLB

The Daily Fantasy Flex, MLB: 6/3/16 Main Slate

Jay Persson and Peter Jennings (CSURAM88) break down the 6/3/16 MLB DFS main slate.

MLB Plays of the Day: 6/3/16, Main Slate

J.D. Martinez is a clear anti-Carlos Rodon stacking candidate, as he boasts an impressive .310 Isolated Power and .395 Weighted On-Base Average against opposing left-handed pitchers. Additionally, Martinez can be had fairly reasonably on DraftKings tonight, where he carries a Bargain Rating of 70 percent.

MLB DFS 6/3/16 Slate Breakdown, by John Daigle

Ortiz is now slugging .692 versus right-handed pitching and has recorded the most DraftKings points among first basemen over the last month. What’s more astonishing is that he has met or exceeded salary-based expectations with 65-percent Consistency over that span. As for tonight, note that he’s the only player at his position with double-digit Pro Trends.

Video: Introducing the Sports Geek MLB Pro Model

We’ve added a new Pro Model in our MLB Player Models, built around Kevin The Sports Geek.

A Study on Fastball Velocity, Part II, by Bill Monighetti

While my assumption was that a higher velocity would lead to harder contact (which would be especially bad for fly-ball pitchers), it looks like the opposite is true. A lower velocity likely makes the pitches more hittable, which is especially bad for fly-ball pitchers. I’ll keep mentioning the small samples that we are working with, but when there is nearly a five-point swing per-player, per-game, it’s pretty hard to ignore.

MLB DFS: The Most Powerful Advanced Stats of All, by Mitchell Block

We’ve established which recent advanced stats provide the most value for both hitters and pitchers. But what do we do with this information? Personally, I try to incorporate a good amount of this data into our Trends tool. Much of this data isn’t being incorporated into pricing at the DFS sites or utilized in the research by non-FantasyLabs DFS players. Take advantage of this edge as often as possible. 

State of the Stacks, Vol. 6, by Mitchell Block

The Brewers will spend the majority of their week in Philadelphia, taking on a Phillies team that has been average in terms of fantasy production allowed to opposing batters this year. With Philadelphia scoring the fewest runs per game in the majors this season, and Milwaukee sitting in the middle of the pack, I would expect the majority of these games to come in with low implied Vegas totals. From an ownership arbitrage perspective, such a scenario could offer up an opportunity to exploit the low ownership often associated with such games.

MLB Trend Testing: Weak-Hitting Opponents, by Bill Monighetti

This week’s trend matches pitchers who both have a high K Prediction and are facing a lineup of batters whose collective Hard Hit Percentage is low. I think that this trend is best utilized in both cash games and tournaments. There will be really chalky qualifiers — like Scherzer — who make great cash game plays, and there will also be pitchers who appear a little riskier than they actually may be: These are the players whose matchups you will want to exploit in tournaments.

MLB Recent Form Report: 5/30/16, by Bill Monighetti

I created a pitcher trend on FanDuel and added filters that matched Matt Harvey’s recent differentials in Pitch Velocity, Distance, and Exit Velocity. So what did the Plus/Minus look like? While I would have accepted “Crying Jordan” or “Poop Emoji,” the actual Plus/Minus is -2.57.

Trends

MLB 5/30/16: High-ISO Lefties at Oriole Park, by Jonathan Cabezas

MLB 5/31/16: Pitchers with Poor WHIPs but Are Heavy Favorites, by Brandon Hopper

MLB 6/1/16: If You’re Going to Steal, Make It Worth It, by Jay Persson

– MLB 6/2/16: Bottom-Of-The-Order Rockies, by Bryan Mears

MLB 6/3/16: Power Hitters at the Top of the Lineup, by Mitchell Block

About the Author

Matthew Freedman is the Editor-in-Chief of FantasyLabs. The only edge he has in anything is his knowledge of '90s music.