Analysing statistics to create a winning team
EDMONTON, AB, Apr. 23, 2012/ Troy Media/ – Moneyball isn’t just for pro baseball players and Brad Pitt anymore.
Executives in virtually every professional sports league, from the NHL to the NFL, are finding ways to incorporate analytics – the actual term used to describe the techniques popularized in the recent hit movie – into their particular game.
The recent film, based on the best-selling 2003 non-fiction book by Michael Lewis, has helped demonstrate just how important the role of statistical analysis can be in sports. The smart use of data analysis helped the Oakland A’s, a subpar and struggling baseball team, win a record 20 consecutive games and their division championship while competing with teams that have as much as three times their payroll.
Skeptics became true believers
The A’s success using analytics converted skeptics everywhere into new believers.
The Boston Red Sox went on to win two World Series after adopting the same data analysis methods. And baseball isn’t the only sport where the edge gained by the use of analytics is spreading.
Marc Appleby with Powerscout, a hockey analytics company, is part of the movement on the ice. There are lots of performance statistics that are available in hockey, but determining what those statistics mean is the hard part, he said.
Knowing how many goals a team averages is good, but, Appleby explains, “There are other aspects besides goals and assists that are important. PowerScout has researched key statistics from over 14,000 NHL games over a 13 year period where we’ve discovered winning trends that can be modeled today to help build a winning team. Ultimately, our mission is to help teams maximize their strengths and minimize their weaknesses, which is of growing interest to hockey teams at every level.”
“When building a team we know what components provide you the best probability of winning based on key findings uncovered in our extensive research. That is what we do at PowerScout,” he said. “Often teams are looking at small situations but not the whole picture. Many times they are looking at player performance on a game by game basis but Powerscout tracks how each player is contributing to help his team win based on his position and his skills.”
Companies like Powerscout are giving coaches and front-office executives a better look at the complete picture when they are assembling their teams during the off-season. Instead of just focusing on one specific player, analytics helps determine which types of players work best together.
Engineers with Formula 1 racing teams are even finding ways to apply analytics to gain an advantage over the competition during an event.
Formula 1 racing team Lotus F1 collects data as a race progresses. The information about the car, the weather, and the competitors is sent in real time to teammates on and off the track, reports Kevin Casey of InformationWeek. A mobile app is used for the driver and information that can give a competitive edge is streamed real-time.
This gives an exclusive edge and could possibly be used in a number of other sports. For instance, a football coach using analytics software streaming to a handheld device during game play could help him determine what plays have the highest statistical edge.
Football teams are presently using analytics in the same way hockey teams are. Robert Bedetti, a blogger for the Harvard Sports Analysis Collective, recently employed analytics to help determine which draft picks are the riskiest.
“When evaluating first-round draft picks, history can tell us a lot about how different positions are valued and how they tend to live up to (or fall short of) expectations,” he said. “The data from past drafts can be invaluable to the evaluation and selection process that no team has yet to master.”
Through Bedetti’s analysis, he found that the quarterback position is one of the riskiest early-round picks. If you pick a quarterback in the first or second round you were more likely to end up disappointed, whereas, a linebacker in the first or second round is shown to be a relatively safe pick.
Analytics is also used by the sports fan. Fantasy football players are relying on data gleaned from statisticians to get the upper edge.
In Papa Chakravarthy’s research, “Optimizing Draft Strategies in Fantasy Football,” data was collected from ESPN and Pro Football Reference’s websites to determine the best auction draft strategy that relies on accurate risk estimation in a fantasy football league.
Analytics determines risk level
The study considers several draft styles including points-based drafting, value-based drafting, risk-averse drafting, and risk-neutral drafting. It attempts to determine the risk level that provides risk-neutral drafting, as well as the ways risk neutrality can increase a team owner’s utility, where utility is directly related to the fantasy point output of a team.
Regardless of if you are a team manager looking to draft the best possible team combination, a sports enthusiast building a fantasy football team, or a team looking to use real-time analytics, we can expect to see a lot more from the sports analytics field in the coming years.
Or, as Pitt’s character in “Moneyball” puts it, “We’ll change the game. That’s what I want. I want it to mean something.”
Learn more about how analytics is transforming the health care industry at Canada’s largest analytics conference. Dan Haight will be speaking at Analytics, Big Data and the Cloud will be held April 23rd-25th in Edmonton, Alberta.
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