What does BTTS mean in soccer betting

BTTS in soccer betting is short for “Both Teams To Score”. It’s a betting market where the punter tries to predict if both teams will have scored by the end of the match. In other words, if none of the teams will keep a clean sheet at the end of the match.

Simple cases

The simplest BTTS bet just focuses on predicting if both teams will score by the end of the match. You can bet on it to happen (BBTS Yes) or you can bet against it to happen, which is the same as betting on at least one of the teams to keep a clean sheet (BTTS no).

Many times you will see BTTS bets mentioning only one team, together with their next fixture. In the table below, for simplicity, we have both teams (Manchester City and Arsenal). You will always see the odds of both outcomes (BTTS Yes and No) in the table.

Let’s say the match ends in a 1-1 draw. In this case, betting $100 on the outcome of both Arsenal and Manchester City to score will win you $61, because both teams have scored by the end of the match.

Let’s suppose instead that the match ends in a 1-0 win by Manchester City. In this case betting on BTTS No will win you the bet, and you will take home $120.

Match result and BTTS

A little more complex case happens when the BTTS bet is combined with the match outcome. In this case, the punter can bet on both teams to score and one of the teams to win the match. Many times you will see BTTS+win bets mentioning only one of the teams in the match (the one you will bet for or against).

For example, in the table below you only have Manchester City mentioned. You can bet on Manchester City winning the match and conceding at least one goal (BTTS + Win Yes) or on Manchester City scoring and conceding at least one goal, but losing or drawing the match (BTTS + Win No).

Let’s say the punter bets $100 on BTTS + Win Yes. In case the match ends up with both Manchester City and its rivals scoring, with Manchester City winning, the punter wins $161. If either one of the team does not score or Manchester City doesn’t win, the punter loses the bet.

Let’s say instead, the punter bets $100 on BTTS + Win No. In case the match ends up with both Manchester City and its rivals scoring, with Manchester City drawing or losing, the punter wins $220. If either one of the team does not score or Manchester City wins, the punter loses the bet.

Soccer Betting on BTTS

BTTS is an interesting market because it doesn’t need you to predict the outcome of the match, but only if both teams will score by the end of the match. For this reason, it’s not necessary to compare the teams strength and identify which one will score more than the other. It is however necessary to evaluate the strength of the teams attack and defense. This will definitely correlate with the probability of teams to score or concede a goal.

If we want to build a model for BTTS, the first step is to get all the information as possible about the offensive and defensive strength of a team, in other words some metrics and statistics about the team performance. Some information that is easy to find and valuable to build a model is the following:

• total shots
• total shots on target
• total shots conceded
• total shots on target conceded
• total goals made
• total goals conceded

The idea is to predict the goals that both teams will score and concede in the next match. There are many approaches to this. One possible approach is to analyze the teams current season statistics and try to evaluate what is the probability of each of the teams scoring at least one goal, extrapolating it from the historical data.

Collect the data about the historical performance of teams in current season.

This involves looking at the previous matches of current season. You can easily find those online. Football-data is a good resource to download data from all the most important Soccer Leagues in Europe and the World.
As you can imagine, this can be a tedious work, but it can be automated using some simple programming.

Calculate the probability of scoring and conceding a goal

Once we have the data, we can look at how many times a team has scored or conceded at least one goal in the previous matches. This can be already an estimate of the probability of the team scoring/conceding in the next match. Let’s say for example, data looks like this for Manchester City and Arsenal at some point in the 2023/24 season.

From those data we can for example calculate the percentage of matches where each team has scored/conceded at least one goal.

In a simple model, those can already be our estimated probabilities for the team to score and concede a goal. One of the ways to estimate the probability is to calculate the combined probability that one team, let’s say Arsenal, will both score and concede at least a goal. Assuming that those are not correlated (they probably are) we have

p(BTTS) = p(score)*p(concede) =
70.6 * 52.9 = 37.3%

So the probability of Both Teams To Score p(BTTS) is the product of the probability of Arsenal to score p(score) times the probability of Arsenal to concede p(concede).

An alternative way to calculate p(BTTS) can be to take into account both teams offensive strength. So, in this case we calculate the probability that both Arsenal and Manchester City will score (regardless of the teams defense). In this case we have

p(BTTS) = p(Arsenal score)*p(Man City score) =
70.6 * 69.7 = 49.2%

Train a model to predict the probability of a team to score or concede a goal

The above approach is correct but relies on several assumptions, that can affect the reliability of our predictions. In order to correctly estimate the probability of a BTTS outcome, it is better to rely on more advanced techniques that take into account not only the goals scored by a team in the season, but also the strength of the opponent defense the recent form and other factors. This usually involves building a model, collecting feature data from past seasons and setting the correct target prediction metric (in this case, it will be the number of matches where both teams scored).

If you are interested in learning more about how to build a Soccer Betting Model, check out my books where I go into the details of how to get the data, visualize and train a model, complete with code examples.

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