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The start to the world’s biggest sporting event, the FIFA World Cup 2010, is a lesson in poor risk management.

No, it’s not the political risks of South Africa: The country has managed the event spectacularly. The flop is an over-engineered ball, the Jabulani.

The ball flew over the goalie’s nest…

In every match that I have watched, the vast majority of free-kicks have sailed over the goal. Most corner kicks and other set pieces have overshot their targets. Many long passes have bounced over the heads of the recipients.

Those shots that make it to the goal are harder to predict and grasp. Many top goalies, including Italy’s Gianluigi Buffon, Spain’s Iker Casillas, Brazil’s Julio Cesar, Australia’s Mark Schwarzer, and England’s David James, have sharply criticized the ball.

As I see it, the strategies of FIFA, football’s international governing body, and Adidas, creator of the official ball, might have been overtaken by a marketing obsession that was not grounded in proper risk analysis.

The lure of reward

Adidas wanted to create a ball that’s fast. FIFA wanted to increase pace in an already fast-paced game, a game without the type of “time-out” interruptions you see in typical American sports.

Adidas claims the ball is the roundest and speediest yet. The speed and flight would translate into more goals. More goals = more viewer excitement, especially in the world’s biggest underdeveloped football market, the United States. The hope is that millions of soccer fans, fueled by goals galore in the World Cup, will shell out $150 to buy this sophisticated ball, generating a nice chunk of cash for Adidas and corresponding royalties for FIFA.

The neglected risks

1. Altitude. Adidas blames the ball’s strange movement to altitude. It’s surprising that Adidas marketers and designers did not take this adequately into account. Most places in the world, and especially South Africa, require balls that would behave predictably in different playing conditions. People play football on grass and sand and dirt and streets, and in different altitudes, not inside a lab.

2. Lab-idealism. Which brings me to the second point. Adidas claims that the ball reacts the exact same way each time a robot kicks it. But on the field, human players kick it, and the ball behaves to the unpredictable twitches and curls of each individual foot in ways that surprise the players. The ball’s “Grip N’ groove” technology makes its movement closer to “true flight.” Well, Adidas, this is a football, something you kick around, not launch into space from NASA’s Kennedy Center.

3. Strike Rate. Adidas and FIFA knew the ball would be difficult for goalkeepers to handle, especially in the air, resulting in more goals. But did they count the risk of strikers not being able to predict the ball’s movement?No wonder then, that Brazil’s main striker Fabiano called the ball “supernatural,” before adding, “it’s very bad.” The chart above  shows the reality: scoring is at a historic low.

4. Aesthetics. The aesthetics of the “beautiful game” is important. It’s not just that set plays were overshot. Some of the goals ascribed–fairly or unfairly–to the ball’s unpredictability were downright ugly to watch. Even the Slovenian striker who scored a goal against Algeria said the goal was helped by a ball “really difficult to control.”

5. Goodwill. People are questioning if Adidas is really working for the good of the game. Why fix something that already works very well? Adidas’s strategy and glitzy ads are proving a bit static against the torrent of criticism that the ball is generating. Players have called the ball “a disaster” and even “the worst ball ever.” People are talking about boycotting Adidas products. Adidas has hinted that mainly teams sponsored by rival companies are criticizing the ball. But we fans are watching the World Cup, aren’t we? And the ball’s strange movement is clear. In the days of networked consumers, bad word travels real fast.

6. Revenues. Will all these affect the bottom-line? All else equal, yes. If professional football players are unable to predict how the ball will behave, why would ordinary people buy this expensive object to replace their trusted leather footballs? However, Adidas’s Jabulani sales have been good in the US, but it’d be interesting to watch Adidas’s share price here as the competition progresses.

The need for risk analysis

This fiasco, from both a product and public relations standpoint, could have been avoided if Adidas and FIFA had properly conducted risk analysis as part of their lofty marketing plans, and gave such analysis importance. They would have known then that the risks of spoiling the quality of the world’s greatest spectator event by introducing an untested, unpredictable product is unjustifiable, even from the bottom-line perspective.

The World Cup is not the stage for these experiments. Yes, the Bundesliga and MLS used the ball, but most leagues in the world did not. As Italy’s goalkeeper Buffon said, “The World Cup brings together the best players in the world and to those players you must provide something decent. The new ball is not decent.”

Football is the world’s most popular sport partly because the game is beautifully simple. All you really need is a ball. The whole game revolves around this round thing. But Adidas and FIFA may have taken their eyes off it.

Is Adidas willing to risk a quality flop at the World Cup in order to maximize short-term revenues? Well, in a competitive market, one’s mistake is another’s opportunity. So don’t be surprised if Nike or Puma or Reebok comes up with a glitzy ad of their own that makes fun of an over-engineered ball playable only by Wall-E.

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Ok, time to take a break from the South Asia forecasts and talk about something a bit more global: The 2010 FIFA World Cup. In anticipation of the world’s greatest sporting event, three major investment banks have put their stakes  on the table. Will the quant models of JP Morgan Chase, Goldman Sachs, and UBS trump your gut feeling? Let’s take a look.

JP Morgan Chase

The JPMC report is based on “a simple Quant methodology” in which analysts looked at four categories of variables that they normally use in studying companies: Valuation, Market Sentiment, Fundamentals, and Price Trends.

Each category was broken into specific proxy metrics, and countries were ranked for those indicators. FIFA World Ranking and Bookmakers’ Odds, for example, were the two metrics for Valuation. Price Trends were estimated by looking at historic trends of those two indicators.

To come up with a composite score, the analysts weighted (admittedly arbitrarily) each category: Valuation 40%, Sentiment 15%, Fundamentals 15%, and Trend 30%. After this, the strongest teams to emerge were Brazil, Spain, Netherlands, and England.

The next step was particularly innovative. To account for penalty shootouts in tied games, the report measured “Ability to Score” (=goals scored/games played) and “Goalkeeper Ability” (=goals conceded/games played). Brazil ranked very poorly in this metric, not even in the top ten.

The analysts plugged in the model score of each team to predict the outcome of each game; in case of draws (teams of similar strength), the penalty shootout model predicted the winner. This throws out Brazil, the overall strongest team, in a quarterfinal penalty shootout against Netherlands. The other surprise is that Slovenia, on the back of recent trends, advances to the semifinals. In the final, England beats Spain on penalties based on their much better shootout record.

Goldman Sachs

In contrast to JPMC, the GS report does some macro analysis. It notes a weak relationship (-0.17) between GNP/capita and FIFA ranking. But there’s a stronger and positive correlation between improvement in FIFA ranking since 2006 and the overall economic growth environment of a country, especially if the two outliers, Brazil and Argentina, are excluded. In short, if emerging markets want to improve their chances in the World Cup, they better invest in growth and human development and improve rule of law. Equity market performance is not a good indicator of World Cup performance.

GS predicts that Brazil is going to be favorites for a long time to come. Not only is its past performance (64-14-14) better than any other country (Germany is second, at 55-19-18), but its growth environment is healthy and its demographics, esp. number of males, are stronger than European countries. It is also a large football market.

Now, the main question: Who will win? The narrative in GS’s report reads mostly like a journalistic analysis, purposely devoid of numbers. It looks through the groups, and predicts England, Argentina, Brazil, and Spain as the semi-finalists. The report then introduces a simple probability model. Like JPMC, the main inputs into the probability model are official FIFA rankings and odds from different bookmakers. (I suspect a high multicollinearity between these two variables.) Arbitrary weighting is another problem, and GS admits: “Our model-probabilities are intuitive to a large extent” (p. 65). While JPMC explains its method in detail, GS does not. The model predicts Brazil as the winner, and Spain with the next highest odds. Overall, GS opts for a more conservative outcome than JPMC.

GS’s report has a couple of other gems. One, it polls its clients (N=an astonishing 2,955) to come up with a Dream Team. It also lists odds for the golden boot award: Villa, Rooney, and Messi top the list.

UBS

Unlike GS’s global review, UBS focuses on Africa, with an eye to promoting the continent to investors and philanthropists. The report was published by its Wealth Management Research group.

Once the selling is out of the way, UBS considers three criteria in making its prediction. The first is past performance. Unlike the other two banks, UBS uses Elo ratings, a system developed by Hungarian-American Physicist Arpad Elo. This apparently determines the strengh of teams better than FIFA ranking does.

The second consideration is whether or not a team is the host nation. UBS gives home ground advantage much more prominence than does JPMC or GS. UBS notes that 63% of the time the hosts have reached semifinals. Now it’s doubtful whether South Africa can add to this trend, but most people didn’t consider South Korea in 2002 either.

The third element is — yep you guessed it — a proprietary model, described as “an objective quantitative measure that assesses the strength of each team three months before the start of the World Cup.” Fine. UBS also claims flat out that socio-economic factors and GDP growth have “no explanatory power when it comes to forecasting the performance of a specific team.” That also makes sense. But disappointingly, UBS does not reveal the workings of its model.

Historically five teams (Argentina, Brazil, France, Germany, and Italy) have accounted for 53% of all semifinal places. But UBS notes that of late, weaker teams on paper are posing more surprises, and so there will be at least one rank outsider in the semifinals. But the winner will definitely come from usual powers. And competition will be intense. Based on Elo scores, this World Cup will see “the strongest Spanish team ever to go to a World Cup, the strongest English team since 1970, the strongest Dutch team since 1978, [and] the strongest Brazilian and German teams since 1998.”

In the end, Brazil emerges on top, with 22% probabilty to win the World Cup. UBS puts Germany (this was before Ballack’s injury) at 18%. England, JPMC’s favorite, has only 4% chance of winning according to UBS. So does fancied Spain, even though if you look at bookmakers’ odds, Spain is numero uno (4/1), edging out Brazil (9/2). All the more reason to wish UBS exposed details about its model.

Who is right?

Is one prediction better than the other? Let’s just take the bankers’ playbook and do a meta-analysis using “an objective quantitative measure.” Let’s assume, with good reason, that the overall predictive power of the quant models of each bank is reflected in its relative stock price trend. After all, if their models perform consistently well, their trading desks will make more money, and investor confidence will drive up the stock price. In short, although multiple factors exist, we simply assume that relative stock price movements subsume all such factors into one neat proxy metric.

The chart below shows the relative stock price movements of JPMC, GS, and UBS for the last three years (2007=0).

Relative Stock Prices, Jun 2007 - Jun 2010

As you can see, all three ticker indices are down since 2007. But JPMC (-20% approx.) has outperformed GS (-40% approx.) and UBS (-80% approx.) pretty consistently for the last 2.5 years. Therefore, JPMC’s prediction is more reliable.

So what’s next?

Does all this mean you should get out your excel sheet and hash out some kind of model? Chances are, you already know all you need to know from just following football. So my advice: just stay put on your couch. After all, even UBS admits, “one needs to be humble about the predictive power of one’s models,” before concluding that forecasting football is more art than science. That’s good news for me, because none of these analyses made me change my mind. I’m rooting for Spain.

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This article describes step 2 of 4 of the South Asia Political Forecast project. The 4 step method is described in the previous post. In the first step, I discussed the baseline for the forecast, identifying the current state of democracy in South Asia. In this step, I draw from theory to identify factors that influence the strengthening of democracy in general.

The baseline indicated strong support for democracy despite weak performance. But we cannot assume that democracy will continue by default. A significant share of the population is open to alternatives, such as “strong leaders” or “military rule”, even while they support democracy (Ref 1). So we need to find predictors of democratic strengthening.

What strengthens democracy?

Among the many factors debated in the literature on democratic consolidation, a general consensus exists around only three:

  • Income and wealth levels are positively correlated to democratic strengthening (Income inequality, however, is negatively correlated)
  • Economic growth is positively correlated to democratic strengthening
  • Literacy rates and education level are positively correlated to democratic strengthening

The combined positive influence of these factors was theorized in a famous 1959 paper by Seymour Martin Lipset. Lipset considered these factors inter-related and termed them together as “the economic development complex.” Subsequent cross-national studies have generally held these relationships as valid. (These are cited in the full report.)

The most recent survey of South Asia, in this vein, found that formal education is the single biggest factor in determining support for democracy. “In South Asia, someone with a graduate degree is seven times more likely to support democracy than is a nonliterate person” (Ref 1, 92).

Another strain of research focuses on cultural factors: History as a former British colony (as opposed to say, French colony) and penetration of the English language have been correlated with democratic viability. Diversity may also help, especially because minorities in any given area are stronger promoters of democracy.

Forces extraneous to South Asia may constrain region-wide democratic politics. The political environment of the neighborhood (e.g., China, Iran, Southeast Asia) affects longer-term democratic consolidation, due to both geopolitics and the so-called “contagion effect”. (The most famous example of this effect was in Eastern Europe, where the fall of communism in one country affected others almost like dominoes.)

In addition, we need to consider spillovers from international terrorism, American foreign policy, and, very significantly, climate change.

Next step

All these influences on democratic strengthening are derived from theory and past data, which are predictors but do not form a forecast. The next step is to organize these predictors to form a forecast, in which variables are prioritized by risk. In doing so, the next post will introduce relative certainties and uncertainties.

Note: I’m using these posts to summarize my lengthier analysis. The references below reflect only this summary.

Ref 1. deSouza, Peter R., Suhas Palshikar, and Yogendra Yadav. “The Democracy Barometers: Surveying South Asia.” Journal of Democracy 19/1 (January 2008): 84-96.

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