When are Most Goals Scored in a Football Match?

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    In this post I am going to look at which parts of football games usually yield the most goals, this is with the aim of helping to profile fixtures across several different leagues and determine when goals might be more likely to happen. I will also be addressing other factors including home team advantage and higher vs lower leagues of teams amongst a few other things.

    The data I am using for this post is from the last 5 full seasons (2015/2016 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

    When are Most Goals Scored (Across all Leagues)

    Firstly lets have a look across all of the aforementioned European leagues and the past 5 seasons to see a general picture of where goals are most likely to come from. Note that I am looking at all goals here (not just the first) and multiple goals in any given game will count towards all relevant 10 minute brackets seen below.

    most goals scored - all leagues sample graph

    A can be seen on the chart above, when looking at the full sample of goal data it is clear that goals are seen more towards the end of a game than the beginning. This trend is particularly true when looking at the time brackets in the first half of games versus those which occur in the second which are noticeably all higher.

    The very last time bracket within full time (81mins to 90mins) contains the most goals in total (7296) with the last 3 full-time brackets all comfortably outpacing the first three by over 1000 goals in each case (an increase of at least 22.6% in the worse case scenario of the second bracket (11min to 20min) versus the 81 min to 90 min bracket).

    when are most goals scored - percentage increase to 81 to 90 mins

    As can be seen in the table above, all time brackets below the 81min to 90min bracket need to be increased by up to 46% in order to match the number of goals scored in the last full-time (81min to 90min) bracket.

    As a football trader for many years now I can confidently say this matches up with my experience and, on a side note, also backs up how the late goals trading strategy can be a great place to develop your football trading strategies (have a look at my football trading strategies article for more info on this).

    The very last bracket shown above (91mins to 110 mins) is about half the size of the preceding few bars on the chart, but bear in mind many games will go into approx 4 or 5 minutes of injury time meaning that this will always be approx half the size of what it might have been had the injury time always lasted a full 10 minutes. Perhaps not the most scientific explanation but hopefully you can see where I am coming from here, it is artificially lower than the rate of goals scored in such a bracket might otherwise be.

    Another interesting thing to point out is goals scored above the 100 minute mark (the 101_110 bracket), even with 61,317 goals used to compile this data we see only 8 scored in this bracket, clearly not the place to wait for goals!

    When are the Most First Goals Scored (Across all Leagues)

    Next let’s have a look at something (potentially) a little more interesting, that is when the first goal of the game is scored! For this section of the article I will be using the same group of leagues and seasons as before and only counting the first goal of the game using the same time bracket structure as before.

    first goal timings chart

    As can be seen above, we see a very different picture this time around, the majority of first goals tend to be scored towards the beginning of games and this number decreases dramatically as the game progresses. It also needs to be pointed out that this set of data will (naturally) exclude any 0-0 games which, of course wont have any first goal timings.

    first goal timing percentage table

    The table above show this data set with a percentage worked out for each goal bracket versus the total number of goals for this sample (21,302). If we look up to the 41min to 50min bracket it is clear that after this point the number drops off very quickly, it is also very clear that, based on these brackets, we are much more likely to see a first goal in the first half of a game than in the second!

    To try and add some more context to this result I have run this set again but this time only included games with a single goal scored in the entire game (so, the first goal in single goal games).

    single goal games - first goal timings

    As can be seen above, when looking at such single goal games we start to see a very different angle to this problem. Whilst multi-goal games tend to have early initial goals, those with only a single goal tend to have that goal much later on in the game (although the distribution is a lot more equal this time around).

    single goal games - first goal percentages

    The above table is, again, the single goal games with the percentages worked out for the number of goals per time bracket. I personally feel this is a very interesting contrast and when combined with the ability to predict a slow moving game could make for a very interesting late goals trading strategy (i.e. 0-0 / draw will be a very low price to lay in such games towards the end).

    When are the Most Home Goals vs Away Goals Scored

    Something else which is interesting in the context of when most goals are scored is that of home team goals vs away team goals. It is fairly well established that home teams have a slight statistical advantage and as such score more goals on average per home game, but how does this fare with the timing of these goals?

    home vs away goal timings chart

    As can be seen in the chart above, we can see that home teams consistently score more games than away teams in every time bracket of the game, not really a surprise as we know the home team advantage does exist when we start looking at large numbers of professional games.

    What is particularly interesting in this example is that this home advantage very clearly starts to disappear (or is at least is significantly reduced) when games go into injury time, let’s look at the percentages of home vs away goals per bracket to see this more clearly.

    home vs away goal timings - percentage differences

    In the above table we can see for both home and away teams what percentage of total goals are delivered in each time bracket (for the total number of goals across all games). This is expressed as a percentage of the total for each home and away time bracket respectively.

    Here we can see that thanks to the final column showing the different in percentages between home and away team brackets a very interesting phenomenon. Whilst home teams have a small advantage the whole way through a game, this advantage is significantly lower at the very end of the game (in injury time) and also in the first 10 minutes of the game (where the percentage difference between home and away teams is at its lowest excluding injury time).

    So the data above tells us that the small home advantage tends to appear more in the middle and end parts of a game and statistically that home teams are at their weakest at the very beginning and the very end of games in injury time.

    First Leagues vs Second Leagues Goal Timings

    Finally I wants to address how higher leagues might fare versus lower leagues, for example, the English Premier League versus the English Championship and the Bundesliga vs the 2 Bundesliga. I will be grouping all of the above leagues which have a second league in to higher and lower groups and comparing these two groups directly as I have with the other metrics above.

    It would be logical to assume, over the long term at least, that teams in higher leagues should score more goals and in-turn this would mean we see goals sooner in any given series of games. Let’s have a look at the data and see what we find.

    NB – Just for clarity, these two groups I am using comprise of the following leagues:

    Higher group: English Premier League, Spanish La Liga, German Bundesliga, French Ligue 1, Italian Serie A

    Lower group: English Championship, Spanish La Liga 2, German 2. Bundesliga, French Ligue 2, Italian Serie B

    As can be seen below, in almost every time bracket (except 21min to 30 min) the group of lower leagues scored consistently more goals than the group of higher leagues.

    higher vs lower leagues goal timings chart

    Interestingly, we still see the same distribution as before i.e. most games being higher scoring in the later parts of the game as opposed to the beginning. This phenomenon is seemingly present across all leagues including just higher leagues and just lower leagues, very interesting!

    Also interesting is that collectively lower leagues (consistently) tend to deliver more goals more frequently than those in the higher leagues, the obvious answer here has to be that higher league teams tend to concede less than lower league teams when statistically assessing many hundreds of games!


    The basic answer to the question is that most goals tend to be scored in the later stages of professional football games. It is also interesting to note that, statistically speaking, home team advantage is at its lowest at the very beginning and very end of games, and this is a consistent trend across the many thousands of goals surveyed.

    Also interesting is, regardless of what sub-sets of data we look at, we see these same patterns across many subsets of this data including home teams, away teams, lower leagues and higher leagues etc. With over 61 thousand goals making up this data set it is safe to conclude all teams, regardless of league or home / away status tend to follow this same pattern of tending to score later on in the game!

    And Finally…

    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 see littered across the web. Digging deeper into stats such as those 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!

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