Posts Tagged ‘ Statiction ’

Want To Win The Lottery?

The random winning numbers on lottery tickets aren’t exactly random at all.  Mohan Srivastava is the man who figured out how to beat a scratch lottery game — and he has no desire to profit from it.  Srivastava, who was featured in this month’s Wired magazine, is a geological statistician by trade and is naturally adept at analyzing numbers and realizing patterns. His day job involves scoping out potential gold mines and determining the how much gold they might contain.  Cracking the lottery wasn’t all that different. Srivastava, using the same math, was able to predict winning tickets for a Canadian Tic-Tac-Toe scratch lottery game 9 out of 10 times.

The method is surprisingly simple but his road to discovery involved a bit of chance.  Holding degrees from MIT and Stanford, Srivastava was never drawn to the allure of the lottery — given the inherent propensity to lose long term. When a friend gave him a couple of cheap scratch games as a joke, he didn’t think much of it. But one of the tickets turned out to be a winner. Srivastava was intrigued.

As a trained statistician with degrees from MIT and Stanford University, Srivastava was intrigued by the technical problem posed by the lottery ticket. In fact, it reminded him a lot of his day job, which involves consulting for mining and oil companies. A typical assignment for Srivastava goes like this: A mining company has multiple samples from a potential gold mine. Each sample gives a different estimate of the amount of mineral underground. “My job is to make sense of those results,” he says. “The numbers might seem random, as if the gold has just been scattered, but they’re actually not random at all. There are fundamental geologic forces that created those numbers. If I know the forces, I can decipher the samples. I can figure out how much gold is underground.”

Srivastava realized that the same logic could be applied to the lottery. The apparent randomness of the scratch ticket was just a facade, a mathematical lie. And this meant that the lottery system might actually be solvable, just like those mining samples. “At the time, I had no intention of cracking the tickets,” he says. He was just curious about the algorithm that produced the numbers. Walking back from the gas station with the chips and coffee he’d bought with his winnings, he turned the problem over in his mind. By the time he reached the office, he was confident that he knew how the software might work, how it could precisely control the number of winners while still appearing random. “It wasn’t that hard,” Srivastava says. “I do the same kind of math all day long.”

Srivastava had been hooked by a different sort of lure—that spooky voice, whispering to him about a flaw in the game. At first, he tried to brush it aside. “Like everyone else, I assumed that the lottery was unbreakable,” he says. “There’s no way there could be a flaw, and there’s no way I just happened to discover the flaw on my walk home.”