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Labyrinthian: Truth, Facts, and Data in Daily Fantasy Sports

“Beauty is truth, truth beauty, — that is all
Ye know on earth, and all ye need to know.”
— John Keats, “Ode on a Grecian Urn”

Truthiness

According to the Oxford English Dictionary, a.k.a. “word porn digest,” the word “truthiness” has existed for centuries as a derivative of “truthy.” Before Stephen Colbert popularized and appropriated the term on The Colbert Report in 2005, the word was a rarely-used locution conveying something like “truthfulness” or simply “truth.” Of course, now the word means something like “(not) truth (?).”

At the moment there’s a lot of attention in society and/or social media and/or the real media being paid to truthiness, truth, facts, #alternativefacts, falsehood, and lies. And of course fake news. Always fake news.

Sometimes it’s hard to know what’s the truth.

The Truth is Irrelevant

BOOM! The truth is irrelevant.

Although I’m something of a postmodernist — almost everything I experience is nostalgically belated, and my favorite show (which I haven’t watched in maybe five years) is Seinfeld — the truth fact is that I’m not an absolute relativist. I believe that (what we believe to be) knowledge, morality, and truth are determined in part by our cultural and historical contexts. We are our parents’ children. We are formed by the prior information we’ve been given and by the thoughts and words surrounding us always.

But not everything is relative. There may be no universal truths, but there are universal facts — like gravity and other scientific laws that have to do with the physical world.

There are also everyday boring facts. That I’m writing this article — even this sentence — is a fact. I’m not boring enough to plagiarize this article from someone else. Also, no one else on the planet is boring enough to write this article for me to plagiarize (except for me).

More importantly, that I’m the author of this article could be established through evidence. We could put a program on my computer that would record what I type. We could live stream me as I write this article. We could have a cohort of notaries public who witness me write this article and authenticate what I typed and when I typed it. In short, we could establish the facticity of my authorship through the systematic accumulation of data.

Facts and Data

The difference between truth and fact is that truth is the result of interpretation while fact is the outcome of verification. In other words, truth is nothing other than opinion masquerading as fact.

Truth might be built upon fact. In a perfect world, it is. For instance, my belief that Joel Embiid is a good player could be based on the fact that he leads all starting power forwards this season with 43.1 DraftKings points per game. In this instance, there would probably be strong correlation between what I viewed as truth and what is actually real — assuming that Embiid’s daily fantasy dominance in limited action means that he’s a good player.

But some truth is not built on fact — or at least unequivocal or representative fact. This doesn’t mean that it’s untrue. It just means that it’s not fully supported by data. For instance, I could believe that if Stephen Curry or Kevin Durant were to miss a game this season then the Warriors would be negatively impacted. But (per our On/Off tool) I see that neither Curry nor Durant has missed a game this year, so I have no data from the present year on which I can base my belief. I can look at relative performances and data from previous seasons. I can form educated beliefs based on somewhat relevant information. But my belief — my truth — will be based on facts that are imperfect because the data on which I would want to base my beliefs doesn’t exist.

Sometimes facts do exist — and people ignore them. In this instance, people either don’t care what the facts are or don’t want the facts to be what they are. They’re peddling in either bullsh*t or lies. Neither of those options is enticing.

To What End?

I prefer facts to truth. Facts are less subjective and slippery. I’m reminded of the saying that Mark Twain popularized in the early 1900s:

There are three kinds of lies: lies, damned lies, and statistics.

There are several ironies here. First of all, most people believe that Twain originated that phrase. He didn’t. Additionally, Twain himself believed that British Prime Minister Benjamin Disraeli originated the phrase. He didn’t. Statistics wouldn’t have the power to correct these false beliefs, but numerical data might: Publication dates, page numbers, individual identification codes for archived texts, etc.

Statistics might tell lies, but data can also speak facts and sometimes even hidden truths.

But, as it is, I don’t think statistics lie. People lie or misrepresent using statistics, but statistics themselves don’t lie. Also, if it sounds like I’m borrowing the logic of the familiar pro-gun argument I am — but statistics aren’t like guns. If dropped, statistics can’t inadvertently fire bullets.

Statistics aren’t dangerous unless they’re dangerously used. Like almost anything else — especially that one guy at the gym — data is a tool. It can be used malevolently, incompetently, or wisely.

Without numbers, facts do not exist. Everything considered, data is a virtue. And a necessity.

The Facts About Daily Fantasy Sports

Our game is one of numbers. It’s not just scoring systems and fantasy points based on the accumulation of baskets, touchdowns, goals, birdies, yards, assists, etc. It’s not just salaries and ownership percentages. It’s also the quantification of what happens on the field of play. Everything to do with sports can be quantified. Everything to do with anything can be quantified.

For people wanting to improve at DFS, nothing is more important than immersing themselves in the data.

Scroll through our Player Models. Experiment with various settings. Create hundreds of models and see what their backtested Plus/Minus values are. Attach properly contextualized numbers to your assumptions. Examine the extent to which your truths align with the data.

Construct thousands of rosters with our Lineup Builder. You don’t need to enter all of them into contests — in fact, you almost certainly shouldn’t — but build them, and then analyze them later. Look for patterns in your performance. Calculate the profitability of the various ideas you have.

Play around with our Lineup Optimizer. Learn how it tends to put lineups together based on the Ratings of various players and the salary dynamics of big and small slates.

Peruse our Vegas tool. Pay attention to movements of lines, percentages of the betting public, and team-specific implications. Think about what those numbers might mean for the games on which they’re based.

Use our Trends tool religiously. Quickly sort through tens of thousands of past performances to find combinations of filters that yield high-scoring cohorts. Discover the unknown facts of DFS.

Basically, allow our suite of Tools to turn you into a Team FantasyLabs-esque full-on degenerate. That is, change yourself into someone who is even more obsessed with data. Become someone who attaches numbers to probabilistic thoughts: “There’s about a 59 percent chance of X happening.” It’s not enough to be the type of person who says simply, “X is likely to happen.” Quantify your conjectures.

And it also won’t hurt to read our content. When we’re not writing psuedo-philosophical pieces on truth, we tend to be highly focused on data. Our slate breakdowns are exquisitely full of actionable metrics as are our DFS scouting reports. We appreciate the differential nuances of accuracy and precision, averages and frequencies, and Black Swans and White Swans. We always think in terms of numbers: That’s why we put our Coors Lite where our mouths are.

Just think of data like DFS water. If you go three days without saturating yourself with it, you’re probably dead.

“When Old Age Shall This Generation Waste”

When I was a junior in college, I was majoring in biology, chemistry, and literature. I vacillated between wanting to go to medical school, law school, business school, or graduate school for a Ph.D. in English. One day I asked my advisor for guidance. She asked me if I was good with numbers. I said that I liked math. She said this:

I don’t mean math or accounting or anything like that. I’m talking about numbers. Are you good at seeing trends and patterns and manipulating numbers?

I said yes — because I have no humility. She told me to be a consultant. She mentioned a friend of hers from college who was a consultant. She described what he did. His life sounded pretty cool.

Looking back, I realize that the guy she talked about was very similar to FantasyLabs co-founder Jonathan Bales — except with fewer tank tops.

If DFS had existed back then, I think there’s about a 39 percent chance she would’ve told me to look into a career in DFS. She was a wonderful advisor.

I didn’t follow her advice. Instead, I went into a Ph.D. program in English. One summer, I did almost nothing besides read as much Romantic poetry as I could. Of the Romantic poets, John Keats was my favorite. He should be everyone’s favorite. That’s not a fact, but it’s true.

I’m not anti-truth. Truth can have utility and beauty. Truth can sometimes be the same as reality.

Occasionally the truth can set you free — but facts can keep you from needing to be freed in the first place.

———

The Labyrinthian: 2017.7, 102

This is the 102nd installment of The Labyrinthian, a series dedicated to exploring random fields of knowledge in order to give you unordinary theoretical, philosophical, strategic, and/or often rambling guidance on daily fantasy sports. Consult the introductory piece to the series for further explanation. Previous installments of The Labyrinthian can be accessed via my author page.

“Beauty is truth, truth beauty, — that is all
Ye know on earth, and all ye need to know.”
— John Keats, “Ode on a Grecian Urn”

Truthiness

According to the Oxford English Dictionary, a.k.a. “word porn digest,” the word “truthiness” has existed for centuries as a derivative of “truthy.” Before Stephen Colbert popularized and appropriated the term on The Colbert Report in 2005, the word was a rarely-used locution conveying something like “truthfulness” or simply “truth.” Of course, now the word means something like “(not) truth (?).”

At the moment there’s a lot of attention in society and/or social media and/or the real media being paid to truthiness, truth, facts, #alternativefacts, falsehood, and lies. And of course fake news. Always fake news.

Sometimes it’s hard to know what’s the truth.

The Truth is Irrelevant

BOOM! The truth is irrelevant.

Although I’m something of a postmodernist — almost everything I experience is nostalgically belated, and my favorite show (which I haven’t watched in maybe five years) is Seinfeld — the truth fact is that I’m not an absolute relativist. I believe that (what we believe to be) knowledge, morality, and truth are determined in part by our cultural and historical contexts. We are our parents’ children. We are formed by the prior information we’ve been given and by the thoughts and words surrounding us always.

But not everything is relative. There may be no universal truths, but there are universal facts — like gravity and other scientific laws that have to do with the physical world.

There are also everyday boring facts. That I’m writing this article — even this sentence — is a fact. I’m not boring enough to plagiarize this article from someone else. Also, no one else on the planet is boring enough to write this article for me to plagiarize (except for me).

More importantly, that I’m the author of this article could be established through evidence. We could put a program on my computer that would record what I type. We could live stream me as I write this article. We could have a cohort of notaries public who witness me write this article and authenticate what I typed and when I typed it. In short, we could establish the facticity of my authorship through the systematic accumulation of data.

Facts and Data

The difference between truth and fact is that truth is the result of interpretation while fact is the outcome of verification. In other words, truth is nothing other than opinion masquerading as fact.

Truth might be built upon fact. In a perfect world, it is. For instance, my belief that Joel Embiid is a good player could be based on the fact that he leads all starting power forwards this season with 43.1 DraftKings points per game. In this instance, there would probably be strong correlation between what I viewed as truth and what is actually real — assuming that Embiid’s daily fantasy dominance in limited action means that he’s a good player.

But some truth is not built on fact — or at least unequivocal or representative fact. This doesn’t mean that it’s untrue. It just means that it’s not fully supported by data. For instance, I could believe that if Stephen Curry or Kevin Durant were to miss a game this season then the Warriors would be negatively impacted. But (per our On/Off tool) I see that neither Curry nor Durant has missed a game this year, so I have no data from the present year on which I can base my belief. I can look at relative performances and data from previous seasons. I can form educated beliefs based on somewhat relevant information. But my belief — my truth — will be based on facts that are imperfect because the data on which I would want to base my beliefs doesn’t exist.

Sometimes facts do exist — and people ignore them. In this instance, people either don’t care what the facts are or don’t want the facts to be what they are. They’re peddling in either bullsh*t or lies. Neither of those options is enticing.

To What End?

I prefer facts to truth. Facts are less subjective and slippery. I’m reminded of the saying that Mark Twain popularized in the early 1900s:

There are three kinds of lies: lies, damned lies, and statistics.

There are several ironies here. First of all, most people believe that Twain originated that phrase. He didn’t. Additionally, Twain himself believed that British Prime Minister Benjamin Disraeli originated the phrase. He didn’t. Statistics wouldn’t have the power to correct these false beliefs, but numerical data might: Publication dates, page numbers, individual identification codes for archived texts, etc.

Statistics might tell lies, but data can also speak facts and sometimes even hidden truths.

But, as it is, I don’t think statistics lie. People lie or misrepresent using statistics, but statistics themselves don’t lie. Also, if it sounds like I’m borrowing the logic of the familiar pro-gun argument I am — but statistics aren’t like guns. If dropped, statistics can’t inadvertently fire bullets.

Statistics aren’t dangerous unless they’re dangerously used. Like almost anything else — especially that one guy at the gym — data is a tool. It can be used malevolently, incompetently, or wisely.

Without numbers, facts do not exist. Everything considered, data is a virtue. And a necessity.

The Facts About Daily Fantasy Sports

Our game is one of numbers. It’s not just scoring systems and fantasy points based on the accumulation of baskets, touchdowns, goals, birdies, yards, assists, etc. It’s not just salaries and ownership percentages. It’s also the quantification of what happens on the field of play. Everything to do with sports can be quantified. Everything to do with anything can be quantified.

For people wanting to improve at DFS, nothing is more important than immersing themselves in the data.

Scroll through our Player Models. Experiment with various settings. Create hundreds of models and see what their backtested Plus/Minus values are. Attach properly contextualized numbers to your assumptions. Examine the extent to which your truths align with the data.

Construct thousands of rosters with our Lineup Builder. You don’t need to enter all of them into contests — in fact, you almost certainly shouldn’t — but build them, and then analyze them later. Look for patterns in your performance. Calculate the profitability of the various ideas you have.

Play around with our Lineup Optimizer. Learn how it tends to put lineups together based on the Ratings of various players and the salary dynamics of big and small slates.

Peruse our Vegas tool. Pay attention to movements of lines, percentages of the betting public, and team-specific implications. Think about what those numbers might mean for the games on which they’re based.

Use our Trends tool religiously. Quickly sort through tens of thousands of past performances to find combinations of filters that yield high-scoring cohorts. Discover the unknown facts of DFS.

Basically, allow our suite of Tools to turn you into a Team FantasyLabs-esque full-on degenerate. That is, change yourself into someone who is even more obsessed with data. Become someone who attaches numbers to probabilistic thoughts: “There’s about a 59 percent chance of X happening.” It’s not enough to be the type of person who says simply, “X is likely to happen.” Quantify your conjectures.

And it also won’t hurt to read our content. When we’re not writing psuedo-philosophical pieces on truth, we tend to be highly focused on data. Our slate breakdowns are exquisitely full of actionable metrics as are our DFS scouting reports. We appreciate the differential nuances of accuracy and precision, averages and frequencies, and Black Swans and White Swans. We always think in terms of numbers: That’s why we put our Coors Lite where our mouths are.

Just think of data like DFS water. If you go three days without saturating yourself with it, you’re probably dead.

“When Old Age Shall This Generation Waste”

When I was a junior in college, I was majoring in biology, chemistry, and literature. I vacillated between wanting to go to medical school, law school, business school, or graduate school for a Ph.D. in English. One day I asked my advisor for guidance. She asked me if I was good with numbers. I said that I liked math. She said this:

I don’t mean math or accounting or anything like that. I’m talking about numbers. Are you good at seeing trends and patterns and manipulating numbers?

I said yes — because I have no humility. She told me to be a consultant. She mentioned a friend of hers from college who was a consultant. She described what he did. His life sounded pretty cool.

Looking back, I realize that the guy she talked about was very similar to FantasyLabs co-founder Jonathan Bales — except with fewer tank tops.

If DFS had existed back then, I think there’s about a 39 percent chance she would’ve told me to look into a career in DFS. She was a wonderful advisor.

I didn’t follow her advice. Instead, I went into a Ph.D. program in English. One summer, I did almost nothing besides read as much Romantic poetry as I could. Of the Romantic poets, John Keats was my favorite. He should be everyone’s favorite. That’s not a fact, but it’s true.

I’m not anti-truth. Truth can have utility and beauty. Truth can sometimes be the same as reality.

Occasionally the truth can set you free — but facts can keep you from needing to be freed in the first place.

———

The Labyrinthian: 2017.7, 102

This is the 102nd installment of The Labyrinthian, a series dedicated to exploring random fields of knowledge in order to give you unordinary theoretical, philosophical, strategic, and/or often rambling guidance on daily fantasy sports. Consult the introductory piece to the series for further explanation. Previous installments of The Labyrinthian can be accessed via my author page.

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.