World Cup Preview – How to use freely-available data to profit

In my last article about the upcoming World Cup, we explored how using even relatively crude and questionable rating systems, like the FIFA/Coca-Cola World Rankings, enabled us to identify discrepancies in the Betfair markets between the odds available for teams playing in Russia – most notably African teams – and the actual chance that those teams have of being successful.

This article examines how using other freely available data – World Football Elo Ratings – allows us more analytical betting opportunities than ever before, even for those punters who might not be professed football experts.

As a life-long club-level chess player, I was familiar with Elo ratings long before I started using them to assess betting opportunities.  Since the 1960s, when they were developed by the American chess-master Arpad Elo, they have been the favoured system of assessing the relative strengths of chess players.  Today, they are also central to many analytical models used by winning punters, including those who make long-term profits from soccer.

At their simplest, Elo systems work as follows.  Two teams have a number of points (their rating) – say 1,000 – and put a percentage of those points into a “pot” before a match.  Whoever wins the match takes the points in the “pot” and adds them back to their rating, with the points split equally between both teams in the event of a draw.  In this way, the ratings are constantly adjusted to reflect the form of a team.

Given how easy it is to access international football results, it takes only a basic knowledge of spreadsheets and a few hours work to experiment with your own Elo rating system.  However, when it comes to international soccer, at least, there are several websites who have already done the work for us.


Research is key

Since the late 1990s, World Football Elo Ratings have done exactly this, operating a more sophisticated Elo system than that outlined above which includes an adjustment for goal superiority and for the level of competition involved.  Some criticisms can be levied against their approach (it is different to the one I use), but, for the time being, it’s a brilliant, free resource that can help us immediately identify some odds discrepancies in the upcoming World Cup.

For example, in Group A, despite facing three of the weakest five teams in the competition, Uruguay are $2.10 shots to win the group, only slightly shorter than the odds of host-nation, Russia.  The compressed price of Russia is partially defendable based on home-advantage, but not to the extent that Russia should be $2.90.  To illustrate this, if Uruguay and Russia were to play on a neutral ground, ratings suggest Uruguay would be $1.60 shots to win.

Elsewhere, Peru ($3.20) should be shorter than Denmark ($1.69) to qualify from Group C, where Australia face a difficult challenge if they are to qualify; and South Korea – rightful outsiders in Group F – should nonetheless be shorter than $5.00 to progress.  They may be the statistically weakest-team in the group, but not by as significant a margin as the odds suggest.


Use what's available 

For the upcoming World Cup, I would encourage you to use these freely-available ratings to make more analytical betting choices.  They allow you to rise above the hype and hyperbole of ill-informed commentators, and instead make rational decisions based on sound data.

The easiest way to do this is to convert Elo ratings in each match to odds, to see if the market is where it should be.  If you identify a discrepancy, it’s always worth being cautious, as there are sometimes reasons why a team’s odds are longer than they should be, but a quick search on Google News will soon tell you if there are some off-pitch reasons why a team is in disarray, and most of the time the ratings give you all you need to know.

Accurately converting Elo ratings to odds is not straightforward – it requires a fair bit of work and a decent spreadsheet to create a reliable approach – but the following short-cut will give you a quick-and-dirty appraisal of what those odds should be:

  1. Find the difference in the Elo rating between the two teams.
  2. Assume the strongest team to have a 35% chance of winning, and then add 10% to that figure for every 100 Elo points they are superior (170=17%, 268=27%).
  3. Convert that into their odds of winning by dividing 1 by their chance of winning (e.g. 1/0.56).  You now have an idea of what price they should be to win the match.
  4. Now assume 30% as the chance for a draw.  Take away 3% for every 100 Elo points that the better team is superior.
  5. Convert that into odds of a draw in the same way as described in 3, above.

In a worked example, Australia’s opening match in the World Cup is against France, who are superior by 270 Elo points.  Using the formula above, we assume France to have a 35% chance of winning.  We then add their rating superiority (35+27), which gives us 62%.  We convert this into odds by dividing 1 by the total (1÷0.62), which tells us that France should be $1.61 shots to win.

Now, assuming 30% for the draw, we subtract 7% to account for France’s rating superiority.  We divide 1 by this number to give us odds for the draw of $4.34 (1÷0.23).

Finally, we now know that Australia has around a 15% chance of winning, because that is the difference between 100, and the chance of a France win and draw combined.  Converting 15% into odds (1÷0.15) tells us that Australia should be $6.67 shots.

The early market exchanges on Betfair clash with this assessment, with France too short at $1.24 and both the draw ($6.80) and an Australian win ($16.50) looking like attractive betting propositions.

There is obviously a margin of error in this method, as the relationship between Elo ratings and odds is not linear, as this method suggests, but, for the armchair World Cup fan, it is a sound and reliable-enough starting place, and one that points to the Socceroos delivering some early tournament value, even if they face an uphill challenge in qualifying for the final stages.


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