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The Best Leagues for Over/Under 2.5 Goals

Since the new year I have been spending a lot of time trading and analysing the over / under 2.5 goals markets. I know a lot of traders are interested in these so I just wanted to share some facts and figures which might be of interest.

I might break this up into a few posts since I have a lot of stats to hand but today I will just post some of the more interesting stuff. As in my last post I have used my football stats database which uses data from football-data.co.uk to produce these figures.

The Best Leagues for Goals

It can be hard to see over the course of one weekend or even a few weeks how the league itself can have an impact on how many goals we might expect see. I myself have previously assumed lower leagues generally produce higher scoring games but have since found out this is not necessarily the case.

In order to see which leagues are best for O/U 2.5 trading I have taken all games over the last 10 seasons for the main European leagues (from 11th Aug 2007 to 31st Jan 2018). The table below shows the average goals per game for each of the main European leagues:

best-leagues-for-u2p5-10-year-average-table

As can be seen in the table above the German 1st Bundesliga and the Spanish La Liga 1 are among the highest scoring leagues on average and (surprisingly) the Greek Super League has the lowest scores with both French leagues not far behind!

When to Expect More (or Less) Goals in a Match

In order to be successful with the O/U 2.5 market in the long term we would need to find some kind of long-term edge. There will inevitably be fluctuations in the short term so it would be reasonable to assume 100’s of bets will be needed for an edge to show itself.

So, with all of the above considered I have made some assumptions about when we might expect to see higher or lower scoring games over the long term:

  • If a game has a clear favourite (odds under 1.51) there should be more goals
  • If a game is a close match (i.e. chance of draw above 25% / Under 4.00) there will be less goals
  • If the favourite is playing at home are there generally more goals
  • If the favourite is playing away are there generally less goals

Below I will run some analysis for each of these predictions against my database and see what 10 years of game-by-game data can tell us.

Games with a clear favourite

I have said a clear favourite is a team starting the match with odds of 1.5 or under. It is reasonable to assume that most of the time such teams will force a convincing win which in turn should mean more goals.

games-with-a-clear-favourite-uo-2p5-goals

games-with-a-clear-favourite-uo-2p5-goals-difference-chart

Looking at the data above this theory clearly stands up with all leagues showing more goals on average when there is a game with a clear favourite playing. With a percentage increase of as much as 21% this can clearly be used to help find an edge when looking at the over / under markets.

Closely matched teams

Here I am looking at teams which are closely matched (according to the odds on offer) and if they “cancel each other out” over the long run (i.e. produce a lower goal scoring rate because their abilities are so closely matched).

I have said matches with a 25% or higher chance of a draw (i.e. odds of 4.0 or less) are “closely matched” for the purposes of this example.

games-with-closely-matched-teams-uo-2p5-goals

games-with-closely-matched-teams-uo-2p5-goals-difference-chart

This looks promising! As can be seen over the long run games with closely matched teams tend to generate less goals than those with a clear favourite.

This doesn’t mean we will be profitable by blindly backing the under market on these games since the odds will probably be priced-in to reflect this! This is however promising data and could even be a good starting point for a over / under 2.5 goals trading bot!

Games with a home favourite

In this scenario I have said teams with a home favourite should have a “home advantage” and as such are more likely to score goals. So I would expect to see more goals scored in such matches versus the all games average:

games-with-a-home-favourite-uo-2p5-goals

games-with-a-home-favourite-uo-2p5-goals-difference-chart

The graph above shows that most leagues register a small or nominal increase in goals scored versus the average when we have a home favourite. The stand out exception to this is the English Premier League which shows a sizable 1.1% decrease in goals versus the all games average and the German league 2 which shows noticeably more goals.

For me this is nothing conclusive nor valuable so on to the next one…..

Games with an away favourite

Here I am suggesting that when the favourite is playing away they should, on average have a tougher time winning which should translate to fewer goals scored.

games-with-an-away-favourite-uo-2p5-goals

games-with-an-away-favourite-uo-2p5-goals-difference-chart

Again this theory is generally true albeit with notable exceptions of the English Premier League and the Italian Series A which both showing a gain in goals scored whilst the favourite is away.

Since most of the leagues show a decrease this could be of some use when combined with other indicators to help find low scoring games.

Home favourite vs away favourite (Bonus Graphs)

Just like most bookies I like to disguise the piss poor value I offer with a nice little bonus! In this case I was curious as to how the home and away metrics from above compared with each other:

home-vs-away-comparison-uo-2p5-goals

home-vs-away-comparison-uo-2p5-goals-chart

Unfortunately this doesn’t really doesn’t give us much insight other than to reaffirm that teams generally have a tougher time away when it comes to scoring than they do at home. Even though it is a small difference when combined with other metrics this could still help in devising a profitable strategy over the long run.

Conclusions

As with any data analysis different people will take away different things from this, for me these are just a few (of many) building blocks which could be used to start developing a profitable trading model.

Something key which does need to be mentioned is the exchange odds will generally reflect how highly scoring a game should be. This means making any over / under strategy successful will also involve working out implied percentages on a per-game basis and making sure we only bet when the odds offer relatively good value!

Another issue is that of exchange commission! Even if you do work out a system which can yield a few percentage points over the long term the exchange commission of 2% – 5% will potentially still make such a system unprofitable!

I hope you found this interesting, food for thought if nothing else and please feel free to leave me any comments below!

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