**When it comes to football trading strategies I prefer to look for non-obvious winning opportunities. Although betting markets are generally assumed to be efficient, the markets still tend to leave space for profitable in-game trades. One of the interesting trading opportunities arises in football matches where one team is the clear underdog. Although we know that the underdog has a small chance of winning the match, their chance of scoring the first goal is actually a lot bigger. This might seem counter intuitive at first, but in this betting guide we will see why this holds and how we can exploit this surprising phenomenon.**

**Note – This series includes a handy Excel spreadsheet (download link on the bottom of this page). By using this Excel spreadsheet you can immediately use this guide to improve your football trading strategies.*

## ► Practical example – Brighton versus Man City

Do you remember the match Brighton – Manchester City on the 12th of May in 2019? *The Citizens* needed a win to retain their Premier League title that day, but Brighton was not going to surrender without a fight. They even took a ‘surprising’ lead after 27 minutes. Despite this one goal advantage the match resulted in a 1-4 victory for City, which ensured their league title. We see this happen all too often. The underdog takes a one (or two) goal advantage, but the favourite is still able to turn things around and win the match.

Based on the above scenario I have asked myself the following two questions:

- Is this underdog scoring first scenario coincidence, or can this be explained?
- How much money can we make by trading the underdog?

## ► How (un)likely is a Brighton win?

For answering the above questions we should first look for the 1X2 match odds (home, draw, away) of this specific match. The website OddsPortal is a great source for retrieving historical match odds for many bookmakers and betting markets. They offer an overview of the odds offered by many different bookmakers, for many different betting markets (including the Correct Score, Over/Under and Match Odds markets). On this webpage from OddsPortal we can find the 1X2 match odds for Brighton – Man City on the 12th of May in 2019. As you can see, the odds for many different bookmakers and betting markets are included. Since Pinnacle is one of my favorite bookmakers, we will use the Pinnacle match odds for this guide.

Next, we copy-and-paste the 1X2 match odds to our Excel spreadsheet. This enables us to calculate the true winning probabilities for both teams, based on the Pinnacle match odds.

As you can see from the above image the odds of Brighton winning the match are equal to 13.15. In Step 2 we have calculated the corresponding probabilities. We can do this by applying the following formula: 1/*ODDS*. For example, the bookmaker probability for a Brighton win equals 1/13.15=7.6%.

However, we are not there yet! If we add up all bookmaker probabilities (7.6% + 13.8% + 82% = 103.4%), we can see that their sum exceeds 100%. This difference of 3.4% is called the bookmaker margin.

In order to derive the ‘true’ probabilities we divide all the bookmaker probabilities by their sum (103.4%). For example, the ‘true’ probability of Brighton winning the match is exactly 7.6% / 103.4% = **7.4%**. Since betting markets are assumed to be efficient we can expect that this probability is a correct reflection of the actual winning probability for Brighton. This leaves little space for betting opportunities. However, in this scenario we are not interested in the winning probability of Brighton. Our main goal is to calculate the likelihood of Brighton scoring first.

## ► What is the chance of Brighton scoring first?

Now the next steps are very important. By assuming that the 7.4% winning probability of Brighton is a correct reflection of the truth, we indirectly assume that there is little to no space for placing value bets on a Brighton win. Therefore it is better to look for less obvious football trading opportunities, like backing the underdog to score first.

The main question of this guide can be formulated as follows: knowing that Brighton has a 7.4% chance of winning the match, what is the chance that they will score the first goal of the match?

*P[Brighton scoring first] = ?*

### ► Let’s calculate the chance of Brighton scoring first

The first step is to calculate the number of goals that both teams are expected to score in this match. For this we can use the Excel spreadsheet again. We only have to fill in the match odds, and the Excel spreadsheet will do all the maths for you. Great, isn’t it?

We have already calculated the 1X2 match probabilities. Based on these probabilities, the Excel spreadsheet returns the corresponding expected number of goals that both team are most likely to score in this match. The Excel function used for this is **VLOOKUP**. Based on the probabilities that we have calculated, this Lookup function basically searches through an external Lookup table and returns the corresponding expected goals for both teams. If you want to know more about how I have applied the VLOOKUP function, I advise you to download the Excel spreadsheet on the bottom of this guide.

From the above image we can see that the corresponding expected goals rates for Brighton and Man City are 0.71 and 2.70 goals respectively. Since we can assume that the betting markets (and thus the match odds) are efficient, it can be assumed that the expected goals predictions are accurate as well. This holds because we have derived the expected goals directly from the match odds market.

Knowing the expected goals from both teams we can easily calculate the probability that the underdog will score first. Now **IF** a goal is scored, we know that there is a 20.8% chance that Brighton scored the goal. How do we know this? Easy! We only have apply the below formula.

### ► Important – Take goalless (0-0) draws into account

However, we are not there yet! We should also take into account the probability that the match will end goalless. For this match the probability of a nil-nil draw (P[0-0]) is equal to 3.3%. If you want to know how to calculate this, check my previous guide on extracting correct score odds from the expected number of goals in a match.

Now the last step is to multiply the above probability of 20.8% with the probability of the match **not** ending in 0-0. Below you can see the corresponding formula.

##### P[Brighton scoring first]

As you can see the chance of Brighton scoring first is 20.1%. Isn’t that fascinating? Although Brighton only has a 7.4% chance of winning the match, their chance of scoring the first goal is almost three times (!) bigger. You can imagine that these kinds of matches contain trading value.

##### Why does the above hold? » Apply the theory of the Poisson distribution

Why can we use the above formulas to calculate the probability that Brighton scores first? For calculating this probability we assume that goals scored in football matches can be modeled by the Poisson distribution. The Poisson distribution is often used for predicting goals in football. If you want to dive deeper into the Poisson distribution and its formulas, check this excellent guide. This guide covers everything you need to know about the Poisson distribution.

Since we assume that expected goal rates follow the Poisson distribution, we can apply the following well-known Poisson rule. Let’s take two Poisson processes *P1* and *P2*. The probability that a certain process *P1* occurs before *P2* is equal to *P1*/(*P1*+*P2*).

Do you recognize that this is exactly what we have done in order to calculate the above 20.1% chance for Brighton?

## ► Football trading strategy – Back the underdog

**Note – This example trading scenario is only applicable to betting exchanges like Betfair and Betdaq, since it requires the possibility for placing both back and lay bets.*

In this guide we have seen that the likelihood of Brighton winning the match is only 7.4%, but their chance of scoring first (20.1%) is a lot bigger. This difference is interesting, as it leaves space for trading opportunities. For example: let’s assume that have backed Brighton to win before the match, and wanted to hedge our profits after the Brighton goal. What profits can we expect?

As you can see, we could have made a nice £275 profit by backing Brighton at odds of 13.15 with a stake of £100. The actual profit will differ per game, but on average you can expect something like this. Now it’s obvious that you still need to pick the right matches, but you can see that this counter-intuitive trading strategy can be very profitable. Especially if you take into account the risk/reward ratio of this strategy.

## ► Concluding – Trading the underdog in football?

In this guide we have seen that the underdog scores more often than we would expect. If you apply the theory of this guide to the right football matches, you have a good chance of finding yourself a profitable football trading strategy.

Another takeaway from this guide is to always look for non-obvious trading opportunities. Simply backing the favorite (i.e. Man City) is probably not going to make you any money on the long term. Analyze your markets, think outside the box! If you ask me, this is one of the most important aspects of succesful betting/trading.

##### Download Excel spreadsheet

## ► Final words

Hopefully you have enjoyed this betting guide. As always: if you have any questions you can either reply below, or send me an e-mail: info@georgebets.com. Feedback is always welcome!

this is really interesting stuff.

I suppose the only problem is applying this to a weekend of football as it would be very time consuming

Hi Stuart,

Thanks for your reply!

It entirely depends on your strategy. Some strategies require thorough manual research, with a lower number of matches and a relatively high ROI. Other strategies require less human interference (for example trading bots) and are more scalable.

Betting on 10-15 matches per weekend is possible with this spreadsheet format, but if you want to place like 30+ bets a weekend it would probably require programming skills to do this.