Antony Lee, in a previous career life, ran a derivatives trading desk, where he and colleagues would buy and sell collateralized debt obligations (CDOs) and other complex financial instruments, trying to gauge risk and correlations and volatility and other fast-moving and unpredictable factors familiar to anyone in the markets.
Nowadays, he works in a similarly rough-and-tumble business – professional rugby – for the London-based Saracens. One of at least a few common denominators between the two, Lee said: Data, and the power therein.
Lee is a Data Analyst for Saracens (which is sponsored by CME Group), and his job is to gather, analyze and ultimately develop practical, understandable insights and applications his coaches and players can use to win matches. Saracens’ use of data, Lee said, has many parallels to data in trading.
“Data is all about objects and attributes,” Lee said. “In trading, the object was my profits and losses (P&L), and the attributes were the risk sensitivities that could influence the P&L.”
“Back then, I was trying to understand the behavior of the markets,” he said. “Now, I'm looking at the behavior of rugby players and teams. At the end of the day, you need to understand those relationships. And it can be difficult because markets can behave unpredictably and so can humans.”
Rugby Joins Data-Driven Revolution
Rugby, like baseball and many other sports, joined a data-driven revolution of the past two decades that’s changed the way games are played and players are evaluated, acquired and coached. Technology is fueling that revolution, with greatly enhanced computing power and analytical tools, combined with sophisticated cameras placed throughout stadiums. These help baseball teams, for example, determine “launch angle” and “exit velocity” of a batter’s hits and “spin rates” of pitches.
“Over the years, advancements in technology and data management processes in all top sports have led the way in better defining individual and team performances,” Sports Performance Analysis, a website devoted to research of “applied performance analytics” in sports, said in a 2021 post. Rugby “is no exception,”
“Coaches and other backroom staff can now be seen in the stands with a wide variety of computers and technology monitoring all aspects of the match in great detail,” Sports Performance Analysis said. “Different camera angles, data and analysis are now available to them right there and then to make instant decisions, as well as post-match reviews.”
“At the end of the day, you need to understand those relationships. And it can be difficult because markets can behave unpredictably and so can humans.”
— Antony Lee
Market Data Growth and Evolving Needs
The data revolution goes beyond sports. Global big data market revenue was valued at $163.5 billion in 2021, with expected growth to $473.6 billion by 2030, according to a report from Acumen Research. The industry with the biggest share of the market is financial services.
That growth trend is reflected in market data growth at CME Group, the world’s leading derivatives marketplace. In recent years, as the firm’s ability to collect, store and distribute data expanded, market data consumption and analysis from its clients grew along with the variety of clients needing data.
One of the biggest areas of growth has come from the cloud. In November 2021, CME Group and Google Cloud announced a 10-year strategic partnership to accelerate the move to the cloud and transform how global derivatives markets operate with technology.
“There has especially been an increased interest in our cloud native distribution of data via the Google Cloud Platform,” said Trey Berre, Managing Director and Global Head of Data Services at CME Group. “While many firms today are just beginning to set down the path of the cloud adoption journey, some have established themselves as almost entirely cloud native.”
Visitors to the CME Group Datamine hub have grown to more than 500,000 visits per year from over 160 countries. More than 11,000 users access the firm’s historical data each year.
“We have lots of different data types our customers want,” said David Gresky, Senior Director and Global Head of Data Sales at CME Group. “It’s kind of like the weather. One person might just want to know the current temperature. Someone else might want the know relative humidity. It’s the same thing with the markets.”
Data’s Ultimate Power: Telling a Story
Lee said Saracens’ data analytics efforts are applied in three primary areas: recruitment, opposition analysis and the team's analysis. The team aggregates data and tracks around 900 different metrics on every player in the league, information that can be applied to scouting and recruiting (one might infer that data analytics has been good for Saracens, which was 13-2 and sitting atop the Premiership Rugby standings as of early March).
“Our system allows me to look at the player performances match-by-match and apply various statistical analyses to understand their opposition's behavior,” Lee said. “We produce graphs, performance profiles and other visual representations that illustrate our team's performance based on certain metrics and compare that to league averages. I can put together a bullet-point narrative of the key themes. Where do we rank highly? Where do we rank poorly?”
Among in-game examples where analytics is applied, after the two teams line up, Lee tracks “gainline momentum,” or how much ball carriers are gaining past the line. There’s also “speed of ball” and certain efficiency metrics that indicate how effective a team’s attack is. Data collected on “rucks” (formed when at least one player from each team are in contact, on their feet and over the ball on the ground) “helps us determine how quickly we respond, bounce back into the game, cause turnovers and exert line speed.”
Access to more and more data can be a valuable resource, but Lee noted that it’s not just a quest for quantity – quality matters. Used properly, data should “tell a story” humans can understand and apply toward real-world action, whether the subject is a rugby team or the financial markets.
“Data is nothing without context,” Lee said. “It's a little bit like Sherlock Holmes collecting clues. You find one bit of data, then you find another bit that's related to the first one, and then another, and then you can start telling a story.”
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