In this post I am going to look at whether the favourite team tends to win more frequently when it comes to fixtures in mainstream football leagues. I will also be investigating some other closely related stats including how much more likely a strong favourite might be to win and how often underdog teams tend to win given their much higher pre-match odds.
I will be determining the favourite based upon odds data from Bet365 and the football results data I will be using for this post will be from the last 3 full seasons (2017/2018 to 2019/2020) of the following mainstream European leagues:
- English Premier League
- English Championship
- Spanish La Liga
- Spanish La Liga 2
- German Bundesliga
- German 2. Bundesliga
- French Ligue 1
- French Ligue 2
- Italian Serie A
- Italian Serie B
- Austrian Tipco Bundesliga
- Danish Superliga
- Netherlands Eredivisie
We have 13,772 games in this sample across the above leagues, 10,649 of them having available pre-match (1×2) odds from B365 (so please bear in mind that some of the older games in the smaller leagues don’t have odds data available and will be filtered out).
How Often Does the Favourite Team Win?
To start off I’m going answer the main question in this post, how often does the favourite team win when looking at the aforementioned European leagues. As usual, I will be delving into my own SQL Server football stats database and will be putting together some SQL (like below) to get to my answer!
Let’s start by defining a favourite, initially I will declare the favourite simply as the team with the lowest odds of the two according to Bet365 odds just before the beginning of the fixture (in the rare case the draw is priced as the “favourite” or both teams are priced the same I will exclude such games).
As can be seen in the workings out above, in the sample data specified for this set we see favourite teams winning some 50.7% of the time overall.
Now, this might initially seem like a low number but, as always, I like to take into account the variances we see between different leagues when calculating such figures. For a long time now I have written about the fact that different leagues can have very different characteristics when it comes to certain stats such as goals scored and when looking at favourite wins this is no exception! In the table below I am performing this same calculation but grouping the results per league so as to see leagues with the highest and lowest favourite win rates:
Now, with the new calculations above, we can see the number of wins per league, it starts to become immediately clear (as it often does when looking at football stats) that there is a big difference visible between certain leagues, a difference of 16.72% in this particular instance between those at the top and the bottom of the above table!
How Often Do Strong Favourites Win?
From the last section we learned that favourites overall win just over 50% of the time in mainstream football leagues. This 50% figure might, however, be a little misleading due to the massive difference in odds assigned to such teams pre-game (this range of values is between 1.02 and 2.8 in my particular sample).
Given that a team priced at odds of, say, 1.5 would be expected to win approximately two thirds of the time (and of course more if under 1.5), this wide range of odds might be skewing the result slightly in this case. As such, in this section I will be looking at favourites with odds of 1.5 and under (so, fairly strong favourites) to see how the win rates differ with these teams and how the results for the leagues themselves might vary as well.
As can be seen in the calculation above, at 73.61% the win rate for favourites at odds of 1.5 and under is significantly higher than that across all favourites which stood at 50.7%. Whilst this will be no surprise initially (as teams are usually priced at 1.5 and under for a good reason), the range of values across all sampled leagues might tell a different story:
In the table above it starts to become clear that (despite what might have been revealed in the earlier queries) we begin to see an even bigger range of values between the leagues when looking at such games. The Italian Serie B sees 80.64% of teams priced at 1.5 or under scoring a win whereas this drops sharply to just 54.16% when looking at the Spanish La Liga 2, a difference of 26.24% between these top and bottom values. Although at this point it is fair to point out that at 54.16% the La Liga 2 is something of an extreme value, the difference with this removed comes in at 16.82%, basically the same range we saw when looking at all favourites earlier on!
Before moving on (for me at least) this consistent ~16% range of values shows that between the top leagues for favourite wins and those at the bottom, we still see a relatively big difference in values thus further re-enforcing that, regardless of the parameters we set the leagues themselves do have characteristics when it comes to goal scoring!
How Often Do Underdogs Win?
One of the things that makes live sport so exciting to watch is that we can never be sure what will actually happen, in-turn, this means every now and then we see an underdog team go on to win! In this section of this post I want to look at how often this actually happens (as per my sample set of data) and see what differences we see at different odds levels (say, 5ish to 10ish and 10 or over).
To start off, lets look at games which have been won by a team starting off at odds of 10 or over:
As can be seen above, out of the 10,656 games I have with odds available, we see teams with odds of 10 or higher winning just 0.44% of the time (as to be expected, very little wins here overall). Next, let’s bring this down a little and look at winning teams with odds between 5 and 9.99 to see the difference this will make:
Now, having re-run the query for winning teams with odds between 5 and 9.99 we see this win rate jump up to 3.82% of all games, still small in percentage terms but bear in mind this is across all games and that many games will have more evenly matched teams than we are looking at here. As such, I will run both of these queries again to see how often we see underdogs win, as a percentage, only in games with an underdog present as opposed to across all games (again, many games have more evenly matched teams which can skew the figures here a little).
First, looking at the games with teams at odds of 10 or over we see 721 games available and 6.51% of those teams going on to win (a much more reliable statistic maybe, given how few of these games we see (721 in my sample data)). Next, I will re-run the query for any games with teams between 5 and 9.99 and calculate the percentage of wins seen:
Whilst looking at games with odds between 5 and 9.99 (above) we see 3069 games included and the underdog team going on to win in 408 of these games for a percentage win rate of 13.29% (a much more significant number).
In both cases when looking at underdog teams, whilst underdog wins are fairly low frequency on the whole, when looking only at games including an underdog team we start to see the win frequency is actually much high than might originally be thought of for teams with such high odds.
Just as a quick side note, following on from the above, I have noticed over the years that bookies (generally speaking) tend to offer very mean prices on such underdog teams. This is especially so given that most bookies aren’t too bad when it comes to offering odds on a strong favourite, but when it comes to an outsider this can change drastically and a team that might be, say 9/1 at a bookies could be double this price on the exchanges!
With over 10,649 games (with odds available) sampled across the aforementioned mainstream European leagues, we can finally conclude how likely a favourite team is to win (in general, just over 50% of the time across all leagues). As per the sections above, what makes these stats interesting is how this value changes when talking about strong favourites and then at the opposite end of the scale with underdog teams at very high odds.
I made reference to this above but often, despite having a relatively high win rate (at above 6% of all games with an underdog team present) when looking at the odds on offer, some of the underdog teams could actually provide very good value over the long term (not so much at the bookies but when looking at out of favour outsiders at the exchanges, sometimes with very inflated prices!).
And finally, I think the league characteristics themselves are something to take note of. As was mentioned earlier on in this post I have covered lots of different stats here on Bet on James and I always like to point out these differences in characteristics we see between the different leagues when it comes to scoring stats. If you are looking for an angle to further improve your football trading or value betting systems then profiling leagues (as opposed to just the teams themselves) could potentially be of great value! But I will leave it at that for today 🙂
I hope you have found this article interesting, I like to piece together such data and break away from the hum-drum (and quite frankly boring) football stats you littered across the web. Digging deeper into stats such as those mentioned above can also help in understanding teams and leagues much better in terms of their performance, in turn this knowledge can then used to help develop successful football trading strategies (such as those discussed in my football trading strategies article).
If you are interested in building up you own, professional standard, football stats database and in-turn learning the skills needed to query it and develop such stats for yourself, please check out my detailed eBook course: Supercharge Your Football Betting Stats!
Furthermore, if you are looking for detailed football data (including in-game events data for goals etc.) then be sure to take a look at my Pro-Data football data service. With Pro-Data you can gain access to highly detailed football data and stats which is updated every day for a simple, one-off annual fee. Pro-Data also comes with a 14 day risk-free money back guarantee meaning it is definitely worth a look if you are interested in pursuing more advanced football stats for yourself!
All of the above data is contained within my own (private) football stats database, a database in which I make every reasonable effort possible to ensure is correct and accurate. This database is built with and regularly updated form a reliable 3rd party data source with my own verification checks along the way to help ensure maximum accuracy.
Having said this, please use this data for entertainment purposes only, do not use or re-produce in a commercial context and use fully at you own risk!