The Tennis Racket

The Tennis Racket

Organisation: BuzzFeed News (United States)

Publication Date: 04/14/2016

Applicant(s)

Size of team/newsroom:large

Description

In October 2014, BuzzFeed News data reporter John Templon found the first, tantalizing clues of what would become a groundbreaking investigation: Tennis gamblers seemed to be placing bold, unorthodox bets on a small group of players. Over the course of 15 months, Templon analyzed the betting odds and outcomes of 26,000 matches spanning seven years. Using probability theory, he identified players who routinely lost matches with unusual betting patterns. He fine-tuned his approach in consultation with leading academics and analysts. Finally, after running simulations for each player one million times apiece, he found something that had previously been hidden: A small group of players were losing matches seemingly on cue. Shocking as those findings were, they were just the beginning of BuzzFeed News’ investigation. Next came months of forensic, shoe-leather reporting. Working with Templon, Heidi Blake, who leads BuzzFeed News’ UK investigative team, learned that world tennis authorities had commissioned their own inquiry into match-fixing back in 2008. She tracked down the participants, now long removed from the sport, and learned of the explosive evidence they uncovered of match-fixing on a global scale. Blake also learned what became of these findings: nothing. The leaders of the sport made a deliberate decision to shelve the evidence and abandon any further inquiries into it. Since then, betting houses and foreign police forces have repeatedly sounded alarms. But the suspicious players continue to play. And the savvy gamblers — who always seem to know exactly when a match will turn — continue to cash in. Some publications would have led with those names. But BuzzFeed News and the BBC took a different approach. Statistical anomalies, after all, are not proof, and individual names would have diverted attention from the far greater scandal of how authorities failed effectively to police their own sport. The story caused a global sensation, dominating headlines around the world. Andy Murray tweeted the BuzzFeed News story and called for greater transparency about corruption in tennis; Novak Djokovic admitted he had been offered $200,000 to fix a match; David Cameron said he was “deeply concerned” and called for an urgent independent inquiry. Within days, the world tennis authorities convened a press conference and announced that the leading British QC Adam Lewis would conduct a sweeping investigation. Separately, the House of Commons Culture, Media and Sport committee convened its own hearing at which tennis bosses admitted that the number of suspicious match reports they received has rocketed from 14 to 246 over three years. And in March, BuzzFeed News and the BBC made global headlines again, revealing that more than two dozen high-ranking tennis players are named in evidence seized from a confessed match-fixer and handed to the sport’s authorities by Italian prosecutors. The investigation is ongoing.

What makes this project innovative? What was its impact?

Unlike most traditional investigations, “The Tennis Racket” began with math. But unlike most statistical analyses, it did not end with numbers. An exhaustive data project led the way to old-fashioned spadework, whistleblowers and vast trove of documents. Templon scraped and analyzed betting data on 26,000 individual matches played between 2009 and 2015. Through months of programming, statistical analysis, consultation with former investigators, betting experts, and academic sports statistics experts, he arrived at a simulation methodology with which to see past random odds fluctuations and find legitimately suspicious patterns. His final seven-step approach used custom-built Monte Carlo simulations to identify players who regularly lost matches in which heavily lopsided betting appeared to substantially shift the odds. Four players lost almost all of these red-flag matches. Given the bookmakers’ initial odds, the chances that the players would perform that badly were less than 1 in 1,000. At least six of the 15 most suspicious players had been flagged to tennis authorities by outside sources. The same analysis showed that the players whom tennis’s first investigation flagged in 2008 had gone on to lose at least 112 highly suspicious matches. “The Tennis Racket” appears to be the first time any media outlet used this type of analysis to identify suspicious activity in sport. To explain the analysis to readers, BuzzFeed News published two methodologies. One, aimed at a general audience, used GIFs and straightforward language to broadly describe the approach. The other, aimed at a technical audience and published on GitHub, provided an in-depth description of the analysis, as well as the underlying Python code. In publishing the story and the code, in presenting the analysis along with an anonymized version of the data that enabled readers to replicate the findings, BuzzFeed struck an innovative balance between transparency and privacy.

Technologies used for this project:

Scraping: -Python -requests — Python library for HTTP requests -lxml — Python library for HTML parsing Analysis: -Python -Jupyter notebooks for structuring exploratory analysis and final presentation -pandas — Python data-analysis library Additional team member: John Templon, Data Reporter, BuzzFeed News
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