Demystifying Betting Myths
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# 1×2 Football Betting – How to Compile a Winning Portfolio

This article moves away from betting on individual teams, and pushes strategic thinking further up the knowledge ladder.

The method described below explains how to use our HDA simulation tables for recognising profitable 1×2 betting strategies and building a portfolio from a selection of major European leagues.

Image: archideaphoto (Shutterstock)

Profitable betting on football is about compiling successful portfolios and understanding the underlying market economics.

The following analysis portrays just one successful scheme in detail – Have fun learning about market behaviour and deriving a betting system from it! 🙂

## Understanding the Betting Market

It is impossible to predict with total accuracy the outcome of one particular match; however, it is possible to identify and use historical distributions of data to judge the future in general.

If you do not know what the term ‘distribution’ means, check out this article for an introduction:
Goal Distribution Comparison – EPL, Bundesliga, Ligue 1, Eredivisie

However, understanding distributions, odds calculation and probabilities is only the first step.

The next step is to understand the market economics. Just in case you missed them here are two articles describing how the bookmaker market works:-

The main message of these two articles:

1. Bookmakers set odds based on a mixture of statistical probabilities and public opinion. Effectively, their odds match public opinion.
2. Bookmakers do not speculate (gamble). Their priority is balancing the books.

## Comprehending Market Economics to Elect a Strategy to Investigate Further

Remember your basic economics lessons in school or college which were about supply and demand.

Adapt this to the football betting market: In which situations will bookmakers reduce their prices (odds), and which prices will increase as a result? Which bets are traditionally the most popular?

The fact is the majority of punters prefer betting on favourites up to odds of 2.5. Just look at online odds comparison sites which show the percentage distribution of bets on a certain outcome. It is frequently above 60% on the favourite (independent from the offered odds), if not higher.

On the other hand, consumer demand for bets on the underdog is often much lower than the actual chance of it winning.

Bookmakers are aware of this market behaviour and try their best to predict trends, time the market, and choose the best outlets for their odds. Customer behaviour is well analysed and used to generate various marketing strategies aimed at balancing the books and boosting sales.

Therefore, for the bettor, it is safe to assume that many favourites will be under-priced to win, and draws and/or away wins will be over-priced to “make up and balance the book”.

For example, a traditionally strong team like Bayern Munich playing away will, of course, attract a good deal of punters betting on them to win rather than any weaker opponent playing at home. However, most punters are normally ignorant of the fact that even teams such as the mighty Bayern Munich win approximately just 50% of their away games.

In these game constellations bookmakers, simply by following market economics, have to reduce their prices for the (away) favourites massively and balance this by increasing the price of the less fancied home team.

## Investigating Distributions: Profit/Loss Inflection Points

From what has been explained in the previous chapter it should now be obvious that favourites are often under-priced to win, and draws and/or away are frequently over-priced. Therefore, it should be possible to find a workable strategy using this knowledge.

Now comes some maths… hang in there! 🙂

In the last five seasons, a total of 1,900 matches were played in the English Premier League (EPL), of which, 46.74% finished in a home win:

EPL: Full-time 1×2 distribution – Five seasons 2009-14

The home team was priced the favourite in 1,351 of these matches (home odds lower than the away odds), and a total of 763 games did indeed end in a home win, equating to 56.48%.

EPL: Favourite home wins – Five seasons 2009-14

The balance of 549 matches saw the home team priced as the underdog (home odds higher than the away odds). From these games, 125 finished in a home win for the underdog, equating to 22.77%.

EPL: Underdog home wins – Five seasons 2009-14

Now convert these favourite and underdog win percentages into odds:

Home wins (Favourite): 56.48% = 1.77 [European odds]
Home wins (Underdog): 22.77% = 4.40 [European odds]

The above two odds are “inflection points”, the points on a curve at which the curvature or concavity changes from plus to minus or, from minus to plus. Translated into layman’s language… the pivot points along the profit/loss curve where profits turn to losses or, where losses turn to profits.

However, these are purely the mathematical inflection points and do not take market forces into consideration.

Therefore, please do not start betting on every favourite at home priced below 1.77 in the EPL, or on every underdog playing at home priced above 4.40. (Although following this simple strategy would have produced quite a profit!).

Last Update: 5 December 2014

Categories:1x2 Betting Case Studies

### 33 Responses to “1×2 Football Betting – How to Compile a Winning Portfolio”

1. 17 November 2020 at 2:17 pm #

Dear Elena,

hope you’re doing well. I have the following somewhat interesting questions no one has asked before if I’m correct:

(1) The inflection Points of how many previous seasons in your opinion would be optimal to build your strategy on? You’ve mentioned previously that you think that 6 are too many.

(2) When the new season starts, do you discard the oldest season and include the Inflections of the last season?

Thank you for your valuable thoughts on that!

Florian

• 17 November 2020 at 3:16 pm #

Hi Florian,

as I already said, 6 seasons are probably too many. There are too many changes in the format of the leagues, different teams competing, or now, this virus affecting the 1×2 performance. There is always something going on. Five seasons for the Inflection Point graphs proved to be ideal and it certainly shows trends. However, if you calculate individual matches then you can always check your calculations by using the last 25 matches (that is 1.5 years). Anything less it’s too little and statistically speaking, too much noise.

To your (2) question: Yes, when the new season starts you drop the oldest season and replace it with the season that just finished.

By the way, currently, the Cluster Tables seem to perform much more reliable than the HDAFU tables. Playing without crowd hasn’t so much affected the total goal count but it somewhat seems that there are many more away teams currently winning than previously. Regarding odds and distribution, Rob is currently looking into that and writing on an article.

Good luck!
Soccerwidow