With apologies to Gil Scott-Heron, the data revolution that is currently happening in football will not be televised. Instead, it is taking place in the cramped back offices of clubs where scouts are now as likely to be hunched over a computer to check a player's performance indicators as they are to be swapping stories of watching a young Algerian striker on a rainy night in Copenhagen. Instead, the data revolution is taking place online - on blogs and fan websites, but also on the screens of the most powerful and most watched sports network in the history of humankind, the Entertainment and Sports Programming Network, aka ESPN. With a few clicks, fans of any sport that matters can find all the data they want to become literate in stats or confirm their hunches that their favorite team really is as good as they think (hopefully).
I am currently in London on my way to Manchester, tracking down and talking to some of the people interested in football's evolving relationship with numbers from one of hostility to one of friendly co-existence and perhaps mutual admiration. But before I left to probe English football's affinity with evidence-based decision making, I had a chance to interview a couple of fellow data revolutionaries back in the U.S., Paul Carr and Albert Larcada.
Paul and Albert are the two guys responsible for what ESPN does in the areas of soccer analytics. They work for and with ESPN's Stats & Information Group, which consists of four departments: Production Research, Statistics & Analysis, BottomLine and Analytics. Together they provide accurate and up-to-
date information for all aspects of ESPN, including studio shows, game broadcasts and digital media.
Paul Carr is the lead soccer researcher for ESPN’s Stats & Information group. He covered the 2010 FIFA World Cup from Johannesburg and now runs the Five Aside blog on ESPN.com. You can also follow him on Twitter at @PCarrESPN.
Albert Larcada is an Analytics Specialist in ESPN's Stats & Information group. He conducts advanced statistical research with the intention of better modeling and forecasting sporting events and leagues. You can see all of his written ESPN work here, and you can also follow him on Twitter at @adlarcada_ESPN.
SBTN: Thanks for you time. So let me get right to it. You get to work with and inform fans about soccer stats and other soccer-related stuff for a living. I suspect lots of my readers are jealous and dream of getting paid for the time they spend on soccer. So how’d you get into this racket?
SBTN: Since you started analyzing soccer data systematically, have you changed how you think about the game or how you watch a match?
SBTN: Does watching a match in a stadium affect how you look at the data or which data to look at? Can you think of an example?
SBTN: Where do you get your ideas for what to write about or analyze? Can readers suggest analysis projects?
SBTN: While ESPN is based in the U.S., top-level soccer is based in Europe. Does it affect how you do your job, what you write about or analyze, and how you communicate it?
SBTN: Do you think North American fans are just more statistics-minded than, say, British or Scandinavian fans? What kinds of differences do you across countries in readers’ interest in what you produce?
SBTN: Lots of folks working in sports are former athletes. Do you think it’s important to have played the game, or played it well to analyze soccer with basic and advanced statistical techniques?
SBTN: What do you think is the biggest disconnect between people working in the game as coaches or players and how you think about what happens in a soccer match and on the field?
SBTN: What do you think are some (say your Top 3) of the biggest misconceptions about statistics in soccer?
SBTN: Will soccer follow the Moneyball template with respect to analytics? If not, why not, and what do you think the major differences will be?
I am currently in London on my way to Manchester, tracking down and talking to some of the people interested in football's evolving relationship with numbers from one of hostility to one of friendly co-existence and perhaps mutual admiration. But before I left to probe English football's affinity with evidence-based decision making, I had a chance to interview a couple of fellow data revolutionaries back in the U.S., Paul Carr and Albert Larcada.
Paul and Albert are the two guys responsible for what ESPN does in the areas of soccer analytics. They work for and with ESPN's Stats & Information Group, which consists of four departments: Production Research, Statistics & Analysis, BottomLine and Analytics. Together they provide accurate and up-to-
date information for all aspects of ESPN, including studio shows, game broadcasts and digital media.
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| Paul Carr |
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| Albert Larcada |
SBTN: Thanks for you time. So let me get right to it. You get to work with and inform fans about soccer stats and other soccer-related stuff for a living. I suspect lots of my readers are jealous and dream of getting paid for the time they spend on soccer. So how’d you get into this racket?
Carr: I grew to love soccer while I attended Wheaton College (IL). When I started as a researcher at ESPN in February 2008, I quickly realized that we were carrying Euro 2008, and that there was no soccer researcher in the department. I jumped on that opportunity and progressed from there, eventually covering the 2010 World Cup and the 2011 Women’s World Cup on site, and now coordinating the majority of the soccer coverage for ESPN Stats & Information.
Larcada: My background is completely in numbers and statistics. I attended the University of Central Florida for undergraduate (Economics) and graduate (Statistical Computing) school. Similarly to Paul, when I came to ESPN in 2009 I realized there was a niche for advanced statistical analysis in soccer at the company. Given ESPN’s strong prioritization for soccer and its vast data resources it was an obvious choice to start studying, analyzing, and producing more advanced statistical content on all of our platforms.
SBTN: Since you started analyzing soccer data systematically, have you changed how you think about the game or how you watch a match?
Larcada: By not growing up a huge soccer fan I wasn’t necessarily influenced by some of the beliefs “traditional” soccer fans have. I actually think this plays to my advantage as I can attack an idea or project without any preconceived notion of what I should find. I let the numbers guide me into most, if not all, of my results.
SBTN: Does watching a match in a stadium affect how you look at the data or which data to look at? Can you think of an example?
Carr: Whenever I attend a game, I always relish the ability to see the entire field, not just where the ball is. It’s much easier to notice positioning and how players move off the ball, which makes me think about things like heat maps and average positions. When I was at the USA-Slovenia match in Johannesburg last year, I noticed how aggressively Steve Cherundolo pushed down the right flank, and I’m sure a positional study of that game would have backed that up.
SBTN: Where do you get your ideas for what to write about or analyze? Can readers suggest analysis projects?
Carr: For historical-type information, it’s simply digging around in the numbers until I find good ones. By looking for trends in results, goalscorers, and the like, I can almost always find something. From an analytical standpoint, nothing beats what you observe while simply watching games. Reading recaps, particularly the operatic reviews from Europe, also frequently helps trigger ideas.
Larcada: I like to read what others are saying on Twitter, message boards, etc. to see what the general sentiment is on a particular juicy storyline. I then try to back up or refute what they say by taking a deeper dive into the numbers. I let the data, stats and trends decide what angle I am going to take for a story.
Of course your readers can suggest projects! The easiest way to get us is to send potential story ideas to our twitters which you can find above. We are always looking for new ways to analyze the sport.
SBTN: While ESPN is based in the U.S., top-level soccer is based in Europe. Does it affect how you do your job, what you write about or analyze, and how you communicate it?
Carr: Since only the most notable teams and/or games tend to get coverage on shows like SportsCenter, we focus more on the biggest clubs and matchups. We could write a fascinating breakdown of Norwich City, but realistically it wouldn’t get any play from most of our domestic coverage. So the top few teams in the top few European leagues get the bulk of our attention.
Larcada: I completely agree. Often the most interesting breakdowns come from lower-tiered squads (as an aside: did you know Swansea’s right back Angel Rangel leads the EPL in completed passes this season!?). However, our coverage tends to focus on the United’s, Arsenal’s and Chelsea’s of the world because those are the clubs that generate the most interest. In a way this is good because it forces me to dig deeper into these teams to find trends most wouldn’t see, including those at the clubs themselves!
SBTN: Do you think North American fans are just more statistics-minded than, say, British or Scandinavian fans? What kinds of differences do you across countries in readers’ interest in what you produce?
Carr: I think so. Since stats are so much more prevalent in the major North American sports, it’s easier for fans here to apply that statistical interest to a sport like soccer.
Larcada: You definitely have to alter your approach depending on your target audience. If I am helping with an article for ESPN the Magazine I would use a different style than I would if I was pitching an idea to ESPN Deportes. As is true with any presentation, you have to be aware of your audience and what their particular interests are.
That being said I actually love the challenge of explaining data-driven analysis to a European audience. There is no doubt it is easier to write an analytics-based piece to an American audience, but I don’t believe Europeans are against it either. You just have to make the analysis more results-based as that is what they generally care about. If it works, they will buy it. If it doesn’t, they won’t. Americans prefer to know the ins and outs of the analysis much more than Europeans do.
SBTN: Lots of folks working in sports are former athletes. Do you think it’s important to have played the game, or played it well to analyze soccer with basic and advanced statistical techniques?
Carr: The most important thing that former athletes have is experience. From interacting with people like Alexi Lalas, they provide the most help when they offer their thoughts on what they see on the field and what the keys to the game are. From there, we can frequently take their ideas and analyze them from a numerical standpoint. Those athletes can then use our numbers to support (or perhaps create) their opinions. We’re most able to make an impact when we can back up a key thought or storyline.
Larcada: I think it is nice to have both when analyzing a particular subject. Former athletes can see things that an analytics person cannot see and an analytics person can see things that a former athlete most likely does not. I don’t believe one is necessarily wrong without the other, but only together can you have the most complete analysis.
SBTN: What do you think is the biggest disconnect between people working in the game as coaches or players and how you think about what happens in a soccer match and on the field?
Carr: There’s simply a depth of knowledge that is unobtainable without having played or coached the game. Part of it’s physical. Part of it’s emotional. This may be a strange comparison, but I think it’s somewhat like being in love. People can study it and think about it and hear about it, but until you experience it, you really don’t know what it’s like.
Larcada: Paul is such a romantic.
SBTN: What do you think are some (say your Top 3) of the biggest misconceptions about statistics in soccer?
Carr: I think the two biggest misconceptions are that stats can tell you everything and that stats can tell you nothing. There’s obviously something to stats like chances created and passes completed in the final third of the field. Just look at the leaders for a given league. They’ll inevitably contain many of the obvious names, and there are usually a few surprises mixed in. That’s where the stats can teach you something. But everything isn’t measurable. As advanced as soccer stats may get, they’ll never get to a baseball level. The game is too fluid to ever be boiled down to numbers.
Larcada: I would say... 1) Goals scored is the most important player statistics. It is likely the most visible stat in soccer, but might be one of the most deceiving. We need to start looking beyond goals scored on a more mainstream level. 2) Winning teams do not use statistics to make decisions. While analytics is in its infantile stages in soccer, a look at other sports shows that teams who use advanced statistics outperform those who do not all other things being equal. This will be the case in soccer in the very near future, which brings me to number three… 3) Soccer will never be as analytics-based as other sports. Once squads realize the return on investment is there (which I have no doubt they will), clubs will need to invest in analytics to stay competitively balanced with others squads.
SBTN: Will soccer follow the Moneyball template with respect to analytics? If not, why not, and what do you think the major differences will be?
Carr: I think it could, and I’ll be interested to see how a club like Liverpool, which seems to be on the forefront of analytics, can use that advantage over the next few years. But I don’t think that edge will last long. Most of the biggest clubs already have analytics people on staff, and that trend appears to be growing rapidly.
Larcada: I absolutely believe soccer clubs will be investing heavily on analytics in the near future, particularly in the big leagues. One additional win in the EPL is worth so much money to these clubs that once it is determined a “quant guy” can deliver at least this much all teams will want to get this upper hand.
This is the way it happened in baseball after Billy Beane and his Moneyball philosophy caught fire. Since that time just about every MLB team has employed a statistical analyst to find new ways to maximize winning. I see this happening in leagues like the EPL very soon.
