Everyone's an Expert

A regular reader alerted me to this fine piece highlighting a bogus analysis of what the keys are to winning the World Cup. The author dissects this post by Henry Fetter. In it, Fetter argues:

What does it take to win the World Cup? Past results suggest that going through a period of dictatorial government is almost a sine qua non for a nation to be a champion.

Indeed, soccer prowess proved a national morale builder for the dictatorships of the last century. This was particularly true of Italy under Mussolini who believed -- wrongly as it turned out -- that victory on the playing field would instill the martial virtues that would carry the day on the battlefield.

Brian Phillips then proceeds to destroy this line of thinking, making the "correlation does not equal causation" argument and then proceeding with this statistical observation.

Six of the seven past World Cup winners were governed by dictators in the last 80 years, England being the exception. That means around 86% of World Cup winners have had dictators during the World Cup’s eight-decade run. Fine. But that number is only interesting if it’s significantly higher than the percentage of all competing countries to have had dictators during the same period; otherwise it’s just an artifact of the historical reality that most countries have had dictators in the last 80 years. By my count, in the current World Cup, 25 of the 32 countries have undergone periods of dictatorship since 1930. That’s 78%, and that number treats South Africa, despite apartheid and everything else, as a consistent democracy.

I can assure you that there is no statistically significant difference in the percentage of World Cup winners who happen to come from dictatorships versus those who make up the overall World Cup finals team population. This is shear statistical idiocy on the part of Henry Fetter, who seems content to represent the "lies" and "damn lies" in that classic quote about statistics.

I've touched on this theme before. I began this blog with the following commitment because it is what every good statistician does.

I plan on approaching statistics as a tool to answer questions that I have already asked myself. I will not search for random patterns, but instead pose hypotheses based upon reasonably expected potential behavior and seek to prove or disprove those hypotheses via statistical analysis.

I've followed up with posts where I virtually agree with Brian Phillips' contention that these models are all backwards looking and must be used cautiously

Thus, we are limited to using historical data and the assumption that future behavior will follow a similar pattern. We use averages and distributions to talk about the most likely outcome of an event. If the last few years of economic turmoil taught us anything, it's that putting too much faith in the statistics and models such that the whole market buys into them produces disastrous results when the whole thing comes tumbling down quickly.

And I've argued that all of these models we make can't account for the human factor.

The challenge comes in building a blog around soccer statistics when my stated goal is to not be in search of patterns that don't actually exist. To me, this blog is a journey in understanding the many facets of the world's most popular sport. Statistics will greatly aid in that journey - to make sense of some larger truths in the sport. However, statistics often only describe the most likely outcome of an average event and not the actual outcome of a specific one, which is why we play each and every match to determine the actual outcome. In the same manner, I see statistics only being part of my journey through the world of soccer. Statistics related to the latest happenings in the soccer world will make up the bulk of my posts, but I also don't want to lose touch with the human element of the game. Soccer shapes our human experience, and to a greater degree our human experience shapes the game of soccer. I want to understand the humanity that produces the numbers I study.

I read The Atlantic each month because I find it to be a great crosstopic source of information with intelligent, articulate writers. The magazine is, however, in the business of making money and they have greatly expanded into the world of blogging and Twitter to keep up with the times. In doing that, they must often publish sensational, if wrong, material. Henry Fetter's piece on the Atlantic.com is the equivalent of tabloid journalism for people loosely interested in soccer statistics. He has enough of a hook (dictatorships win championships so the Dutch can't possibly win) to get people interested and make them think they now have some nugget of wisdom that few have. Because Fetter nor his readers have a basic understanding of statistics, they won't pick up on the statistical error that Brian Phillips points out.

The sad fact is that there is great commentary on the role of dictatorships in soccer. The challenge is that it takes a ton of original research to document - it can't be cranked out in a few paragraphs in a blog post using bogus statistics. If you're interested in such good research, I'd highly recommend Chapter 7 of Soccernomics which gives a good treatment of authoritarianism, the roll of factory towns, and possible future trends of democratic national capital teams winning the UEFA Champions League sometime soon. Another great discussion on the roll of a dictator in soccer is Chapter 8 of How Soccer Explains the World which gives a good bit of background on Barca as a symbol of resistance to Franco's rule.

Philips's gripe about every person with a calculator becoming a "soccer oracle" at this World Cup is valid. He does, however, seem to get lost in his hatred for garbage like the stuff spewed from Fetter's Atlantic article. I am sure that Szymanski and Kuper would be the first ones to tell you that some of their models are long-term averages, just as I said in my last post, and should be used very sparingly to predict the specific outcome of a match. Just because their model is being misused doesn't mean they don't have a valid point. The gripe shouldn't be with the authors, who are properly trained in the techniques they deploy. The gripe should instead rest on the untrained who speak of that which they know nothing about simply because they read a book. Conversely, researchers who develop match specific metrics should be lauded for using their skills to help us better understand individual contributions to teams' success. None of the authors of these papers or books claim that their methods have allowed them to discover the secret to assembling a great soccer team or develop the best strategy for defeating a specific opponent. Only Henry Fetter did that. Most researchers just help provide data-driven insight to balance our emotional love of the game and team.

I try to keep my blog positive, and not indulge in attacking others. I've toyed with the idea of having a re-occurring "BS stat of the day" to highlight the garbage that passes for statistics in newspapers, blogs, and magazines. I've resisted that temptation so far, reminding myself that my goal is not to be an elitist but to hopefully raise the level of soccer statistics discourse. Nonetheless, there's plenty of Henry Fetters out there producing statistically incorrect analysis and making money doing so. My hope is to periodically expose such material without resorting to the cheap shot of a regularly negative blog post.