Sports analytics: How 'Moneyball' meets big data (gallery)

More and more, sports teams around the globe are turning to big data to better evaluate players and plan new strategies to keep them ahead of the competiton. The 2013 MIT Sloan Sports Analytics Conference held recently at the Massachusetts Institute of Technology in Cambridge, Mass. gave advocates the opportunity to share their findings.

Analytics is fairly new to sports but is nothing new to business. With today's technology, vast amounts of data is analyzed by increasingly more powerful computers to predict success rates for game strategies, a player's potential for success, betting, or marketing a team. It's all there right in front of you. The field, made popular in sports by statistician Bill James and Oakland A's general manager Billy Bean, the focus of the book and movie Moneyball, is based on crunching numbers and data over watching an athlete's or team's actual performance. Both men have been featured guests at this conference.

The goal is to make a team better while using fewer resources. It helps a team pick important role players at a lower cost while avoiding the ones who demand higher salaries but may provide a low return on a team's investment. Even small market teams can be competitive — case in point the Oakland A's.

We'll check out strategies put forward by sports management and researchers that are based on cold numbers, not hunches or out-of-date game plans.

A paper presented at this conference tackles when and where and when an NFL coach should send out his field goal unit. Here's the analytical analysis presented by three students from MIT's Aueronautics and Astonics Department — Torin Clark, a PhD candidate, and two graduate students, Aaron Johnson and Alexander J. Stimpson. Their study is one of one of eight finalists in the research-paper competition at this year’s Sloan conference.

Based on their examination of 11,896 NFL field goal attempts, they've determined that environmental factors are much more important than psychological factors in the success of a field goal attempt. Calling a timeout to ice a kicker has little value while factoring weather conditions such as wind velocity or temperature are much more critical.


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Brian Burke who authors a blog, Advanced NFL Stats, produced detailed analysis, "Fourth Downs in the New Overtime: First Possession." In an NFL overtime game, the team that possesses the ball first can only win the game with a touchdown or safety. After that possession, any score will win the game.

The numbers show the team which has the ball first in overtime has a better chance of winning if, on fourth down deep in its own territory, it tries for a first down instead of punting. The deeper the team is in its own territory, the chances are better that that the team will make a first down rather than give the ball to the opposing team which should have great field position and is likely to score. Over the long run, this strategy may win more games on average but an NFL coach is looking at losing his job if it doesn't work just once.

Another finding is that long field goals should not be attempted on a team's first possession in overtime. Their projected success rate is overshadowed by the loss of field position if it is missed and even if it is good, the opposition still has a chance to win.

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Why do the best football (soccer) players appear to have better field vision than others? To answer that question, Geir Jorde of the Norweigan Sports Institute, Jonathan Bloomfield of Hull University, and Johan Heijmerikx of the University of Groningen, Netherlands examined 1,279 close-up videos of more than 118 midfielders and forwards in the Barclay's Premier League.

The study focused on how the players use head and body movements to help them see the field better and make better split-second decisions. The most important finding was that players, especially midfielders, who better explore the field will make more accurate passes — something that managers, scouts, and fans usually overlook. Here's the full study.

In his new book, Sports Analytics: A Guide for Coaches, Managers, and Other Decision Makers, Benjamin Alamar says that sports analytics is in its infancy and teams can gain a significant advantage by using it. He cites a recent survey which showed that while 37 percent of teams have easy access to one another's data, 37 percent of them do not employ a database programmer.

Alamar says that sports and business need analytic tools and computer power to sift through massive amounts of data to produce reports that can be used to develop a competitive edge. He refers to how small market teams such as the Oakland A's have used sports analytics to successfully compete with the larger, better financed organizations.

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Chad Millman, Editor in Chief of ESPN The Magazine, tells how sports analyst Mike Wahl has examined sports betting from many angles and found an almost sure winner in college football. Typical of many current sports gurus, Wahl earned an MBA and then worked in business as a financial analyst before switching to sports.

To find the right winning bet, Wahl searched through six years of college football games (376) when a team was favored by 20-25 points. To bet on an outright game winner is supposed to be evened out by having the wager on the favorite cost more than the one on the underdog. He found that if you bet the same amount on the favorite as an outright winner, you'd have won overall for six years in a row and your return would have been 12.24 percent. But I'm sure this loophole will be closed very soon.

Billy Beane changed the face of baseball by using new statistics, such as on-base percentage and slugging average, as a better indication of a player's vaue than traditional baseball measurements — batting average, stolen bases, and RBI. An even newer analysis of a baseball player's value is called WAR (wins above replacement) which attempts to indicate how much a player contributes to his team. One major leaguer who stands out is Atlanta Braves outfielder Jason Heyward. His three-year WAR rating is the sixth highest for outfielders under 22 since 1961.

For more read:  ESPN Stats and Info. There are a lot of interesting blogs on the site. The Atlanta Braves analysis is third on the list.

Kevin Mongeon is the principal owner at The Sports Analytics Institute and shows how sports analytics can impact on winning and losing in his blog, "More Hockey Data"? Unlike baseball where specific actions show measureable results, hockey is played in a continous flow making the game more difficult to put into an analysis on paper.

Mongeon says additional data is needed to discover a statistical path to a winning season. He needs statistical models that can examine a player's abilities even under different scenerios.

An NBA study by Jenna Wiens, Guha Balakrishnan, Joel Brooks, and John Guttag from MIT examines the offensive/defensive strategy about whether it's better to crash the boards for an offensive rebound or lay back and play defense.

This detailed analysis developed the Crash Index and Retreat Index to determine which philosophy gives a team the opportunity to score more points. The study found that when a team made a big effort for the offensive rebound, it gained more than passivly staying back on defense. The study does note that it does not take player personel into account.

John Parolin, Statistics Analyst, ESPN Stats and Analysis is part of a team that recorded every single play in the NFL 2012 regular season and playoffs. For this year's Super Bowl, the easy finding was that major mid-season changes, offensive coordinator for the Ravens and quarterback for the 49ers, led both teams through the playoffs. The Ravens rush/pass ratio turned from 40 percent to 49 percent after the change, while the 49ers new quarterback, Colin Kaepernick, experienced great success with the zone-read option where he determined the play based on the actions of an unblocked linebacker.

ESPN found that the one team, Atlanta Falcons, had overplayed Kapernick's running ability in the zone-read option, and held him to just 21-yards rushing — and almost led them to an upset of the 49ers. The Ravens successful defense of the zone-read option, in the first half anyway, was one of the keys to their victory.

Damien Demaj, Geospatial Product Engineer at ESRI analyzed the Olympic Gold Medal tennis match between Roger Federer and Andy Murray. He studied "the spatial variation of serve patterns" in his project, "Using Spatial Analytics to Study Spatio-temporal Patterns in Sport."

Demaj's analysis focused on the placement and bounces of each serve in the match. He found that the location where the server was standing, the service patterns, and the importance of that particular point in the match were keys to understanding the game. For example, in the ad court Federer's spacial service cluster went left most of the time with a wide spread while in the deuce court he was more accurate. Murray's clusters were more focused and favored the right side of the court. Murray won the match: 6-2, 6-1, 6-4.

Talk about detailed analysis, here's one of the tools he designed, "The sequence of bounces then allowed us to create Euclidean lines between p1 (x1,y1) and p2 (x2,y2), p2 (x2,y2) and p3 (x3,y3), p3 (x3,y3) and p4 (x4,y4) etc in each court location."  

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Ed Feng, founder of ThePowerRank.com, tells how to make it in the sports analytics world. Any number of people can sift through data on their own computers but few are able to go to the next step and find a full-time job in sports analytics.

While expertise in numbers crunching and being adept with the use of social media will help, Feng says that there's no substitute for "real human interaction." That means being able to shake someone's hand or looking at them straight in the eye, according to Feng. He suggests attending conferences such as the Sloan Sports Analytics Conference where you can show off your stuff.

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