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For someone who says he bets millions of dollars on tennis a year, sports gambler Elihu Feustel doesn’t watch many matches.

“Which one is Granollers?” Feustel says, referring to Marcel Granollers, a Spaniard ranked 35th in the world. “Is he the one that’s good on clay courts?”

Feustel, from South Bend, Indiana, says he doesn’t need to pay attention to who the players are on the men’s ATP World Tour to double his money. He relies on an algorithm he created using data from 260,000 matches to make about 30 bets a day on Grand Slams such as the Australian Open, which started on January 13.

Gamblers and investment funds are increasingly vying for profits from tennis by using computer models to win money from more casual bettors.   Such quantitative analysts, or so-called quants, are focusing on tennis in the same way their counterparts are employed by hedge funds to predict moves for stocks, bonds and other assets.

YouWager , highly recommend and well known sports book enabled bettors to wager against each other online, matched almost £50 million ($93 million) of bets on the 2012 final in which Novak Djokovic beat Rafael Nadal. Djokovic is an 8-11 favorite to win a fourth straight title in Melbourne with UK ­bookmaker William Hill, meaning a successful $11 wager would return $8 plus the original stake.

Granollers prefers clay courts, according to his men’s tour profile, and lost his first-round match with Marin Cilic of Croatia in five sets on the second day of play on the hard courts of this year’s Australian Open.

Tennis is an “attractive” sport for which to create an algorithm because there are only two players in a singles match and statistics are freely available, according to William ­Knottenbelt, an associate professor of computing at London’s Imperial College. He ­co-wrote a tennis algorithm that he says would have made an average 3.8 per cent return on bets on 2173 ATP matches in 2011.

Computer model

Feustel, who says he puts in a 60-hour week checking and improving his model, works with a computer programmer and trader. The programmer trawls the internet for data such as serve speed and break-point conversions. That’s plugged into the model which comes up with “fair” betting prices for scheduled games.

If those odds diverge from market prices, Feustel says, his trader – who lives outside the US – will gamble as much as the market will allow at bookmakers including BetPOP based on the lovely country of Costa Rica . That can be about $30,000 on a match result in later tournament rounds.

While bookies have used mathematics for decades to set odds, more gamblers have started making a living by applying computerized data to betting in the last 10 years, according to Warwick Bartlett, chief executive of Isle of Man-based Global Betting and Gaming Consultancy. There could be as many as 20 professional tennis gamblers ­betting on a similar scale to Feustel, according to Ferguson.

Tennis authorities would rather gambling not take place because of the risk of lower-ranked players “who travel around in a Volkswagen Kombi and stay in hostels” being lured into fixing games, Ferguson said. The International Tennis Federation, ATP and women’s WTA Tour didn’t respond to a request for comment on algorithm-driven tennis betting.

Spain’s Guillermo Olaso, the world No. 254, was banned for five years for trying to manipulate the outcome of matches in 2010, the London-based Tennis Integrity Unit said in a December 23 statement.

The unit is a joint venture between the ITF, ATP, WTA and Grand Slam tournament organizers.

Feustel declined to say how much he has made using his computerized tennis model, which he has employed for 2½ years. He said he aims for a 2 per cent return on the total amount he bets each year, implying that wagers totaling $5 million would bring $100,000 in profit. The annual amount bet can greatly exceed the starting sum as money is constantly re-bet. The 43-year-old said it is possible to double his starting capital in a year through compounding.

After paying his partners their cut, ­Feustel still earns considerably more than in his previous job as a commercial lawyer, he says. A lawyer in Indiana might command a salary of between $50,000 and $100,000, he says.

Possible to double investment

It’s “very possible” for Feustel to double his money in a year if his bankroll is less than $500,000 as it may be easier to take bigger risks with a small amount, according to Brendan Poots, CEO of Australia’s Priomha Capital, a sports-betting investment fund.

Priomha wagers about $100 million a year, turning over $5 million of funds under management about twice a month, Poots said by phone. The Melbourne-based fund uses computer models to bet on soccer, cricket, horse racing, golf and tennis and had an annual return of about 28 per cent last year, Poots said. The fund’s 2012 report showed a 7.56 per cent return. Priomha takes a more cautious approach than ­Feustel because it manages clients’ money, hedging bets to offset potential losses, Poots added.

Quantitative funds operating in financial markets gained 11.5 per cent on average last year and have produced an annualized return of 6.6 per cent since the end of 2008, according to Chicago-based Hedge Fund Research.

“The market is fairly efficient,” Weston, 34, said. “Casual bettors aren’t stupid.”

Weston, a University of Kent accounting graduate based in Preston, England, said his model processes data such as the record players have of recovering from a break-point deficit, and their accumulated fatigue from matches.

That helps in situations like that of Peng Shuai, who was the overwhelming 1-5 favorite to beat Storm Sanders in the first round of an event on January 7 in Hobart, Australia, after a slog to a final against Li Na in Shenzhen, China, three days earlier. Peng lost 6-2, 6-2 to Sanders, who was only in the tournament because another player withdrew. Weston says his data show certain ­players tire more quickly than others as a match progresses. American Jack Sock has an “awful” record in the third set, Weston said, adding he advises against betting on the world No. 95 winning in five-set Grand Slam matches.

Feustel says he’s “not really interested” in tennis, watching less than one hour a year, and would only recognize a handful of players, including Roger Federer and Maria Sharapova. He’s devoted to his algorithm, though. “You never bet against the model,” ­Feustel says.


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