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// PUBLIC GAMING INTERNATIONAL // November/December 2015
cumstance that would not change the outcome of the game. As
a side-bar, Palansky does not contend that sports associations
shouldn’t support the legalization and regulation of DFS and
FS. He just thinks they should not equivocate by claiming that
DFS is not gambling. Instead, they should get in front of the
issue, acknowledge the fault lines, and take action to ensure
the integrity of sports. “The NFL has smart people,” he wrote.
“The NFL can lead here. Put your smart people on it, figure out
partnerships that give you access to the data and make it a win-
win. Waiting is just going to increase the chances of something
unintended happening.” Taking no action on the basis that
DFS is not gambling is delusional and increases the likelihood
that the integrity of the games may be compromised.
IS THE RECREATIONAL ONLINE SPORTS-
BETTOR AT A DISADVANTAGE?
If skill is involved in sports betting or Daily Fantasy Sports,
wouldn’t that put the less skilled player at a disadvantage over the
skilled player? Now, take that a step further. What if sophisticated
data-crunching, computer-generated algorithmic modeling were
applied to the economic activity of sports-betting? Profession-
ally managed funds are now being created that invite us to think
of sports-betting as an investment. One website explains “Bettor
Investments, LLC uses mathematical probability calculations and
statistical analysis to determine on a daily basis which bets are
profitable. Over time, we will show conservative growth, profit
and stability for our investors. The state of Nevada has now legal-
ized sports betting “pools” which are similar to investment clubs
or mutual fund groups. I welcome you to connect with us to
reconsider your view of traditional sports betting and embrace
the opportunities of sports investing.”
One indication that the answer to that question is “YES”:
In the big picture, artificial intelligence has been disrupting one
industry after another. But since we are talking about betting,
sports betting in particular, exhibit A might be the success of
Microsoft’s AI engine, Bing Predicts, at predicting outcomes. It
has correctly predicted the outcomes of all 15 games in the 2014
Brazil World Cup knockout round and almost all the results of
the 2015 Academy Awards, including the winners of best pic-
ture, best director, best actor, and best actress. It recently beat the
Las Vegas odds-makers in predicting winners for week one of the
NFL season. If Microsoft’s AI is already that good at predicting
outcomes, how might a well-funded investment consortium fine-
tune even more sophisticated algorithmic models to apply to the
economic activity of sports-betting? And where does that leave
the casual recreational gambler?
We are talking about Big-Data—very big data and very so-
phisticated tools to glean the relevant information from Big
Data. The basic principle driving the success of Microsoft AI
is based on the “wisdom of the crowd.” In regards to predict-
ing NFL winners, for instance, not only does the AI algorithm
take into account such diverse variables as a team’s previous
margins of victory, player statistics (rushing yards and passing
yards, etc.), stadium surfaces, weather conditions, and so on,
the secret sauce that seems to give it an edge over the other ex-
perts is the ability to quantify aggregate sentiments and biases
mined on internet social networks. By tapping into social media
and digesting the opinions of millions of Twitter and Facebook
users, the AI can pick up intangibles that defy even the most
hardcore of human statisticians. For instance, the model might
detect a rumor among Twitter users that the Patriots starting
quarterback just had a fight with his wife in the wee hours be-
fore Sunday’s game and hence is less likely to be at the top
of his form. While such rumors may prove to be unfounded,
they have a semblance of truth enough of the time that they
give the model a statistical advantage. And even if there is no
truth, AI algorithmic models can infer and measure the impact
of untrue rumors on the betting bias of the crowd. Specifically,
these “wisdom of the crowd” analyses are estimated to increase
the accuracy of their predictions by 5%. Not much of an edge,
but that’s more than enough to enable an well-conceived invest-
ment strategy to garner huge profits.
The implications of this are profound, not just for sports-bet-
ting, but for a wide variety of industries which depend on an
even playing field as regards to the prediction of future outcomes.
As the understanding of AI increases, and the ways that it can
be applied to predict the future build out, the disruptive impact
will likely increase as well. It’s hard to imagine that the pace and
magnitude of disruptive change could increase over what we’ve
been experiencing for the last ten years. Will the world (or the
economic sector of gambling) become dominated by capital-in-
tensive enterprises focused on developing the best AI prediction
models? I guess we will just have to wait for the wisdom of the
crowd to weigh in on that question.
Is Fantasy Sports a rigged a rigged game?
A FanDuel em-
ployee recently won $350,000, leading some to conclude that
players were victimized by insider trading. FanDuel has since
banned its employees from playing. But how will that prevent
insiders from directing the bets of friends who are not employ-
ees? FanDuel contends that the betting was conducted with pub-
licly available information. Questions remain about exactly how
the FanDuel employee’s betting yielded such a big payoff. And
whether the methods can be repeated.
Two weeks after the insider betting scandal, DraftKings and
FanDuel saw a record 7.52 million entries into their NFL tourna-