The opening month of the 2020/21 Premier League season was one of the most entertaining in living memory.

Round two, spanning the 19th-21st of September, was particularly outstanding with 44 goals scored across ten fixtures – for the fans it could only be described as pure entertainment.

This tally broke the **existing record from February 2011** for the most goals scored in a single Premier League weekend under the 20-team format *(number of goals that weekend: 43)*.

With such a high quantity of matches making an impact on the ‘Over/Under’ sportsbook, there is inevitably a ripple-effect on other staples of Premier League wagering, such as HT/FT, handicap markets and BTTS (Both Teams to Score).

Feet Up, For the Big Match! *(photo courtesy of www.pxfuel.com)*

It almost seems that the absence of fans from Premier League games may lead to a shift in several key markets… Really?

*Here are a few thoughts. Feel free to share yours in the comment section.*

As can be seen from the wide **variety of live sportsbook betting markets** out there, there is now ample opportunity to explore a number of niche markets related purely to goal scoring.

Given the normal average of goals per week across previous seasons, it is widely accepted that using 2.5 goals as a division between ‘high’ and ‘low’ scoring encounters provides an optimal, and easy-to-negotiate meridian.

But perhaps further weekends of high scoring games with questionable defending from once-reliable teams may lead to Over/Under 3.5 goals becoming the new baseline in goal betting?

Naturally, the coming months will see player stamina impacted by European involvement for last season’s high-flyers and, for the newcomers, the continuing culture shock and adjustment needed to survive the rarified atmosphere of the Premier League.

With the glut of games ahead the use of the ‘2.5’ figure to make vital decisions in the total goals market may return to a balance.

What does seem certain is another boom in people backing both teams to score within Premier League multiples, accumulators and proposition bets. So too will there be a greater scrutiny upon teams that are often involved in such matches, such as Leeds United, who found themselves at both ends of two 4-3 scorelines, in consecutive games at the start of this campaign:

Again, this depends on continued shock results, such as Crystal Palace and Leicester winning by multiple-goal margins at Manchester clubs United and City respectively.

The absence of home-biased crowds, whether complete or partial shutouts, has undeniably played its part. When using last season as a source of information for future betting decisions, it has become common practice for many punters to split leagues into before and after the lockdown began.

Last season, there was little fluctuation in the Premier League, except for away underdogs drawing less often and winning or losing more without a hostile home crowd to face. The hosts’ lack of a ‘twelfth man’ (the crowd) seems to be a leveller, helping unfancied away teams achieve unlikely results at normally difficult venues.

A more attacking-style of play is now evident and it is becoming rarer to see away underdogs defending deep and attempting to play on the counter-attack. This sea change will undoubtedly be significant for the HT/FT and Goal Time markets, though **public opinion will continue to play its part**.

Backing goals earlier in live play can only become more of a phenomenon if underdogs continue to be adventurous from the start. And so too will backing late goals, as the effects of an energetic start are felt more amongst squads less accustomed to the rigors of Premier League action.

On early evidence, the unprecedented inflation of importance on the ‘Over 3.5’ threshold will certainly transfer to other major European leagues. For example, Bayern Munich’s opening two Bundesliga games illustrated this newfound sense of unpredictability in the Over/Under market. The two games produced a total of 13 goals – an 8-0 win and a **shock 4-1 defeat**.

Bayern Munich’s Allianz Arena *(photo courtesy of www.pxfuel.com)*

Both games paid out for anyone backing Over 5.5 goals, which represents the point at which the goal odds begin to surge upwards, regardless of how good the favourite is compared to the underdog.

The opening Saturday of Serie A also produced a number of high scores, with three of the four matches producing over 4.5 goals, and threatening the long-held stereotype that Italian football is focused more on defence.

Last season, the Bundesliga was also notable for seeing a decline in favourites losing away from home, with only 12.2% of teams losing to home underdogs between May and August.

Other leagues have seen a similar trend, albeit less drastically, and this certainly provides an opportunity for bettors. With or without fans, home advantage is usually observed as a factor for travelling favourites in many odds starting off longer than they otherwise would be. In turn, away favourites will perhaps become more of a staple than ever when it comes to placing the bets.

]]>**Will match results be more volatile? Can past statistics still be applied to predict the outcome of a forthcoming match? May leagues be abandoned mid-term? **

*Value and System Bettors… All having the bland main question in the back of their heads: *

What we know at the moment of writing is that the starts of the new league seasons in China, South Korea and Japan have been postponed. Many of Italy’s Serie A matches are currently being played in empty stadiums. Which leagues will follow suit?

The problem is that no-one truly knows in which direction things will develop. There is a great amount of uncertainty everywhere and the press is filled with reports about new outbreaks and rising numbers of infected people. It is no wonder that many of us feel a slight sense of panic creeping up.

But please remember, the Soccerwidow website is purely about numbers and we will, therefore, look at the statistics pragmatically (although always with a sympathetic nod to the growing situation).

As per 26th February 2020, some countries have started to mass test for the Covid-19 virus. At the time of writing, the UK had concluded 7,132 tests, 13 of which, were positive *(0.2% positivity rate)*. Italy had concluded 9,462 tests, 470 of which, were positive *(5.0% positivity rate)*. France has also been carrying out mass tests as well as Austria and the United States. No doubt more countries will follow.

The virus has the potential to reach pandemic levels and, therefore, every single country in this world is taking this threat very seriously and working very hard to reduce the risk faced by their populations in order to halt the spread of the virus.

Despite the apparent hysteria, as per the 26th of February…

- Worldwide, the number of newly recovered patients has been greater than the number of newly infected patients every day since February the 19th
*(for the past week)*. - The number of serious and critical cases, as well as of deaths attributed to the virus, is declining worldwide.

*[Source]*

- In China and other parts of the world, 82% of the infected people don’t show any or only very mild symptoms; the majority of them don’t even notice that they are infected by the virus. 10% come down with stronger symptoms, and only 8% of all the infected people show such severe symptoms that they have to be hospitalised.
The group of people with severe conditions are mainly elderly persons or people with pre-existing medical conditions.

- At the time of writing:

**China:**78,514 cases total >> 1.386 Billion population =affected by Coronavirus*0.0057%*of China’s population**South Korea:**1,595 cases total >> 51.47 Million population =affected by Coronavirus*0.0031%*of South Korea’s population**Italy:**470 cases total >> 60.48 Million population =affected by Coronavirus*0.0008%*of Italy’s populationTo put these numbers into perspective: In the UK 364 players won the National Lottery in 2019 and became millionaires – that’s a millionaire for practically every day of the year

*[Source]*>> 66.44 Million population =become National Lottery millionaires each year*0.0005%*of Great Britain’s population*(and this is only one of the many lotteries in that country)*.

You can see from the numbers above that the risk of catching this virus is as low as it is to win the lottery and become a millionaire. It is a cold fact that there is a statistically lower chance of dying from Coronavirus than winning at least a million on the UK National Lottery.

The really serious problem with this highly infectious virus is the very high amount of people (82%) that are carriers of this potentially deadly infection but don’t notice it because they don’t have any symptoms. That’s a real big problem because if not controlled it will lead to a massive spread of the virus and collapse the medical systems in the countries affected.

Hence, the very strong control measures that are currently being observed all over the world. And strong control measures include high public awareness and, therefore, mass-media press coverage. That’s simple cause and effect, a phrase you may be familiar with.

However, please remember that high-level press coverage doesn’t mean that the real risk is higher than the actual statistical numbers show.

Therefore, in my opinion, as a scholar of numbers, there is absolutely no need for panic *(on a personal scale)*.

With all of the precautionary measures currently being put in place *(closing schools, closing towns and even regions, limiting travel, self-isolation, putting places into quarantine, etc.)*, it is very unlikely that the virus will spread in an uncontrolled manner.

I have been criticised for the title of this chapter but it is a cold fact that life will go on as usual, just with a few more precautions in place.

Look to The Facts We Know About the Coronavirus and, as per its date, just 0.0057% of China’s population is affected by Coronavirus, with the trend in decline. There is a sharp increase in cases outside of China and the two trends need to be analysed separately. For example, 0.0031% of South Korea’s population is affected by Coronavirus and, as harsh it may sound, these numbers will rise but are very unlikely to topple China’s figures.

Looking at all of this statistically, what can be probably said is that the maximum expectation is an infection of 0.01% of the population of any country and, the good news is that from these infected people, 82% will only suffer from very mild symptoms.

A maximum of 0.0018 % of a country’s population may come down with severe symptoms from this virus outbreak but probably far less.

0.0018% means that of 100,000 people there may be up to 2 cases. As stated previously, it is much more likely that you *(or your favourite football player)* will win a substantial amount on the UK National Lottery than suffer severe symptoms from Coronavirus.

Of course, all these quarantines and lock-downs do affect the economy and businesses but the psychological effects of the situation are probably worse.

However, please always keep in mind that professional football clubs are businesses and, like every other sound business, they will do everything possible to continue performing at the same high level as usual and not be affected by any virus outbreaks and panic.

In Italy, for example, many Serie A games have recently been played behind closed doors. However, there shouldn’t be any noticeable adverse effect on match results.

Do you remember the Japanese Tsunami in 2011 that caused a mighty number of 15,899 deaths? Although the league was halted after one round for seven weeks this pause had no effects on the statistical patterns of the J1 League during that season. And neither will Coronavirus; not in Japan or anywhere else.

Please be careful about making hasty judgements! At this stage, with comparatively low numbers of virus-related severe illnesses in each country, it is very unlikely that the virus will have any effect on the long-term outcome of a group of matches.

Currently, the newspapers are full every day with this topic *(public awareness has to be raised! Newspapers have to be sold!)* but please force yourself to think statistically and put everything into perspective.

Please bear in mind that seasons always have the habit of starting somewhat unpredictably, with or without Coronavirus. It always takes six to eight rounds to start rolling ‘statistically correctly’. Just have a look at our **League reports each season**.

People who calculate matches individually, using the Value Calculator or the Coursebook and its Cluster Tables, should find that any effects of Coronavirus *(if there are any)* will be taken into account when following the calculations as usual. The odds offered will always be a measure of the possible outcomes whatever the extraneous circumstances may be.

System betters, using the HDAFU Tables, also don’t need to worry. There shouldn’t be any impact on the distribution of the results, neither for the 1st or 2nd half of season systems.

As a suggestion, perhaps pick your Summer League systems this year in a normal way but only monitor them for a while without committing big money. It doesn’t do any harm to start betting with real money a little bit later.

**My general advice is:****The first 6-8 weeks of every season always tends to be a bumpy ride, with or without something like Coronavirus in the background. There is no shame in abstaining from betting during this period and using the time for paper testing.**

**How high should be a starting bank?
Is 5,000 units enough?**

Well, there is no standard answer to this question. It all depends on the individual strategy.

Image: Sergey Novikov (Shutterstock)

However, what is possible, is to calculate bank fluctuations *(i.e. winning and losing sequences)*.

With the help of knowing the best and worst case scenarios you can determine the ideal starting bank for any betting system of your choice.

At the end of the article you will find a few useful exercises to practise, with the solutions available as a free download to all of you who would like them.

It stands to reason that the smaller the probability of an event occurring *(i.e. higher odds)*, the longer the likely losing streak will be *(in between winning bets)*.

However, the big question is how often and for how long will the losing (and winning) streaks transpire?

It is possible to mathematically calculate many things with statistics, including streaks of luck and bad luck. However, it is important to note that no matter how accurate the results may appear, they are ‘models’ *(a formal representation of a theory)*.

In this article, we are talking about probabilities; what can we ‘predict’ about how things may develop in the future. Please bear in mind that any such hypothesis is always a “could happen” not a “will happen”.

Of course, the larger the sample size *(i.e. number of bets)*, the more likely the prediction is to be correct. But apart from the bookmakers themselves, who else has a betting portfolio comprising thousands of bets every weekend?

The longest expected losing streak *(or winning streak)* can be calculated using the following formula:

**n** = number of trials *(i.e. total number of bets)*

**ln** = natural logarithm^{1}

**P** = probability^{2}

**| .. |** = absolute value or ‘modulus’

^{1}*Suffice to say, explaining what natural logarithm is would be worthy of a series of articles. For the time being, use Excel to calculate this for you.*

^{2}*For winning streak calculations use the positive value (i.e. the probability of winning). For losing streak calculations use the negative probability value. For example, if the probability to win the bet is 33% then the probability that the bet loses (negative probability) is 67%.*

In practice, the formula is best applied to situations where you constantly bet repeatedly on the same probability, for example, on ‘red’ at the roulette wheel: its probability remains exactly the same with every new spin of the wheel.

For football betting the concept is much more difficult to apply as each bet is likely to have a different probability (e.g. one Over 2.5 Goals bet with a 55.3% chance, and the next with a 62.1% chance, etc.).

However, you can group bets in probability clusters – for example, bets with a 55%-60% expected hit rate, bets with a 60%-65% expected hit rate, and so on.

Longest Winning and Losing Streaks, depending on the number of bets (Examples for 50, 500 and 1,000 bets shown)

The tables above show the calculations of the expected maximum number of winning and losing streaks, depending on the expected hit rate *(probability of the bet to win)*.

To read the tables, let’s explain the 70% line *(odds in the region 1.4 and 1.45)*; in other words, bets with a 7 in 10 chance of winning.

The table on the left calculates the expectations of 50 tries *(50 bets in a row, one after the next)*. You can see that the player will experience at least one streak of three lost bets in a row somewhere in the sequence.

On the other hand, he can expect at least one series of 11 winning bets in a row during the same sequence of 50 bets.

In contrast look at the 30% line *(odds in the region of 3.2 to 3.4)*. In a series of 50 bets the bettor must expect at least one sequence of 11 consecutive losing bets, but will probably see only one set of three consecutive winning bets.

To develop a sense of probabilities and sequences, you can experiment with a dice. It has six faces; in other words, a probability of 16.67% (1 in 6 chance) of successfully landing on a chosen number.

Choose a number and count the number of throws until you succeed to roll it. Count also the number of consecutive successful rolls.

Choose two numbers that you do not want to roll (e.g. 5 and 6).

This means you have a 66.67% chance that one of the remaining four numbers is rolled.

In football betting terms, this equates to wagering on something like the full-time ‘Under 3.5 Goals’ market at odds of 1.50. (This experiment is just a little faster than waiting for 50 games to finish!)

Take a pen and paper and record 100 throws of the dice. If one of your four chosen numbers arrives mark a 1 on your paper; if the 5 or 6 are thrown, mark a 0. Count the number of winning and losing streaks you experience.

What is the maximum number of winning and losing streaks you experience in a sample size of 100 throws (bets)?

*Having learned how to calculate the expected length of winning and losing streaks, the next question to ask is: *

**How many bets is it likely to take before I encounter ‘X’ losses in a row?**

This formula is actually very simple:

= **1** divided by **P**, **to the power of** **a**

**P** = probability (expected hit rate or loss rate)

**a** = number of won or lost bets in a row

In the tables below you can see how many attempts (bets) it needs to experience a specific, expected length of luck or bad luck. Again, the assumption is that the bettor bets all the time on the same probability:

Expected time of occurrence of winning and losing streaks, depending on the hit rate

Looking firstly in the right-hand column at the Losing Sequences, if the expected hit rate is 45% *(what you should ‘expect’ at odds of around 2.2)*, then it is likely that you will experience a sequence of three losing bets in a row by the time your sixth bet is settled.

After 20 such bets it is likely that you will have seen a losing streak as long as five bets in a row.

Looking at the Winning Sequences column: you will win three times in a row at some stage during a series of 11 bets.

However, winning five in a row may only be seen once in every 54 bets.

As we mentioned before, in football betting it is extremely difficult, if not impossible, to find bets, all with the same probability of success.

However, you should at least try to understand the theory behind winning and losing streaks, as it will be **easier on your nerves** when you do encounter the inevitable run of bad fortune.

In particular, a thorough understanding of losing streaks is of enormous importance when setting both the size of your starting bank and stakes per bet.

**Example:**

A bettor prefers bets within the odds range of 2.0 to 2.5 with a hit rate between 40% and 50%. He plans to place 50 bets *(e.g. two bets per round on 25 rounds of matches)*.

After looking at the tables, he knows that the maximum losing sequence expected is likely to be as long as six to eight lost bets in a row. Therefore, he knows that there may be at least one sequence of three or four consecutive rounds *(weekends)* when all bets lose.

After every 5^{th} to 8^{th} bet, he is also aware that he is likely to experience a loss of three consecutive lost bets *(e.g. one weekend loses both bets, the following weekend only one loses)*.

He also knows that every 13 to 32 bets there will even be a streak of five losing bets in a row.

The bettor is fully aware that he has to take this into consideration and plan the starting bank accordingly to be able to ‘sit through’ these losing streaks.

Of course, he also knows that winning sequences will arrive too. In his case, with some ‘luck’, he may experience a winning sequence of five bets in a row after 32 bets. Every eight to 16 bets he will have a ‘lucky’ streak of three wins in a row.

This is certainly quite a fluctuation. When these ‘bad luck’ and ‘good luck’ streaks actually happen, nobody knows. However, what we do know is: They will happen!

A starting bank should be approximately five times the maximum expected losing streak. The reason for this is that a losing streak can happen right at the beginning, immediately followed by another bad run of luck. We are talking statistics here!

So if a bettor wants to stake 10 units per bet, the starting bank must be nine times (expected losing streak) the stake of 10 units multiplied by five = 450 units. Then he can risk 2.2% of his bank each time he bets (10 divided by 450). If losing, the stakes will remain constant at 2.2% and, if winning, raised gradually.

**Questions to ask before setting the starting bank:**

- What hit rate is expected
*(probability to win the bets)*? - How many bets are planned for the season?
- How long will the longest losing streak be?
- What is the desired stake per bet?

**Calculation of the starting bank:**

- A bettor pursues a strategy with a win probability of 60% per bet
*(e.g. Under 3.5 Goals)*. He places one bet after the other; in other words, he waits for the outcome of each bet before placing the next. In total he places 50 bets.What is the longest ‘losing streak’ (bad luck) that he can expect? How long is the longest ‘winning streak’ (luck) that can be expected?

- Same example as in (1): A strategy with a probability of 60% per bet; placing one bet after the other.
This time our punter is hoping for a ‘winning streak’ (luck) of 5 consecutive wins. How often does that happen?

- A gambler pursues a strategy with a probability of 20% per bet
*(e.g. ‘betting on the underdog’)*. Again, he places one bet after the other.With a total of 500 bets, how long is the longest ‘losing streak’ that he must expect? After how many bets can he expect the longest ‘winning streak’?

- Same example as in (3): Strategy with a probability of 20% per bet; placing one bet after another
The bettor was hoping for a ‘winning streak’ (good luck) of five consecutive wins. How often does that happen? After which bet number should he expect ‘bad luck’ of five consecutive losses?

- Following the above two strategies
*(one with a 60% chance to win, the other with 20%)*our bettor stakes 10 units per bet.How high should the starting bank be for the 60% strategy, and how much for the 20% strategy?

*Note: The initial bank should be approximately five times the maximum losing streak based on a total of 500 bets placed.*

*Just click on the button above and click on “Proceed to checkout” button in the new tab, then enter your name and e-mail address. Our automatic service will then deliver the file to you via e-mail, free of charge. The size of the PDF file is 320KB.*

The factor **5** used in this article to determine the betting bank is a risk variable for risk-averse bettors. It is also the factor advisable for strategies with a 45% to 55% win probability *(odds between 1.8 and 2.2)*.

Here is another article: **How to Calculate Losing Streaks & Optimal Bankroll** in which we provide a more detailed account of setting the ideal starting bank.

Risk management in sports betting is the foundation stone upon which all of your betting transactions should be built.

Risk management encompasses risk assessment, risk control and capital requirements, all of which cannot be addressed until you understand how winning and losing streaks are likely to impact upon your starting bank.

]]>Image: archideaphoto (Shutterstock)

‘1X2’ is an abbreviation of the three possible outcomes in a football match: home win (1); draw (X); away win (2).

This market is also known as ‘HDA’ (Home-Draw-Away), or sometimes simply ‘FT’ (Full-Time match result).

The act of 1X2 betting is referred to as “betting on the full-time result”, “match betting”, or can be termed a “three-way bet”.

Full-time is reached in a football match at the close of the second half of 45 minutes’ regulation time plus the time added-on by the officials for stoppages. When the added-time has elapsed, the referee’s whistle signals the end of the game.

All 1X2 (HDA) bets relating to the result of the match then begin to be settled by the bookmakers.

In a fixture requiring an outright winner, in the event of a draw or tied aggregate scoreline at the end of the regulation match time, two periods of **extra-time** may then be played to break a deadlock.

It is important to reiterate that full-time 1X2 bets are closed and settled on the result at the end of a regulation period of 90-minutes’ play (2x 45 minute halves, plus added time), and after this, new markets will then appear in most bookmaker platforms for extra periods of play (extra-time) or penalty shoot-outs.

It is possible to place a match-result bet either before the kick-off (ante-post bet), or whilst the game is in progress (in-play bet).

In the English Premier League (EPL) match shown below (screenshot courtesy of **Betdaq betting exchange**), we have elected to back the draw at odds of 3.5. (Decimal or ‘European’ odds).

In this case, the bet was requested by clicking on the yellow-highlighted square bearing the odds of 3.5 in the ‘Back All’ column.

*(Click on the image below to enlarge it in a new tab):*

Having clicked on the draw price, a bet slip opens up to the right of the screen, ready for insertion of our stake. Here, we have entered a figure of £10.

The profit due from our wager should the match indeed end in a draw is shown as £25.

In order to strike this bet, the next step would be to click the purple button ‘Place Bet(s)’.

Just as a side note… When we write articles showing mathematical calculations we always prefer to useEuropean odds, also known asdecimal odds.

It would go too far to explain in this article the whole concept of betting odds but here’s an article on that topic if you are interested in learning more:Understanding Betting Odds – Moneyline, Fractional Odds, Decimal Odds, Hong Kong Odds, IN Odds, MA Odds

In short, betting odds show how much you will be paid out if your bet wins.

However, odds can also be converted into their ‘implied’ probabilities and here’s the formula:

Betdaq’s prices for our example match (at the time of the screenshot grab) were:

Draw: 3.50 = 1/3.50 = 28.57%

Away win: 2.68 = 1/2.68 = 37.31%

Theoretically, because there are only three outcomes to a match (home, draw or away), the probability percentages of each should add up to 100%.

But, in reality, the percentages on any one match with any single bookmaker will always be above 100%; using our example odds, it’s 101.09% (35.21% + 28.57% + 37.31%).

Why should this be?

The percentage difference over and above the 100% base probability figure is known as the bookmaker ‘overround’, ‘margin’, or ‘vigorish’ (or ‘vig’). This represents the bookmaker’s expected profit.

In its simplest form, for every 101.09 units the bookmaker accepts as wagers on the odds of our example match, if the wagers remain stacked in the same proportions as the implied probability percentages, then the bookmaker will pay out only 100 units, thus ensuring a profit regardless of the match result.

However, our example here is a betting exchange. Like all other exchanges, it guarantees a profit from every match by charging commission on all winning bets. Here, Betdaq’s commission rate is 2%.

The overround calculations now become slightly different because the commission amount has to be factored in.

Draw (3.50): 1 / (3.50 – [(3.50-1)*0.02]) = 28.99%

Away win (2.68): 1 / (2.68 – [(2.68-1)*0.02]) = 37.79%

You can see that at the same odds, the implied probabilities now add up to 102.45%. Because of the commission element, exchanges tend to have a larger overround than bookmakers, even if it seems at first glance that exchanges have better prices. In fact, rewards are generally higher with a bookmaker.

Here’s the formula to convert odds in an exchange into their ‘real’ odds (after commission) in order to compare directly with bookmaker odds:

So, in our example match, the ‘corrected odds’ were as follows:

Draw (3.50): 3.50 – [(3.50-1)*0.02] =

Away win (2.68): 2.68 – [(2.68-1)*0.02] =

The important thing to remember is that converting odds into their implied probabilities is not an accurate indicator of the percentage chances of each outcome. Bookmakers adjust their odds (prices) due to demand, which leads to distorted ‘implied’ probabilities. These are normally very small and not easy to spot but enough for the bookmakers to stay in business and make consistent profits.

Implied probabilities reflect much more the public perception of the likely outcome (not the statistical likelihood), being a measure of the volume of money wagered on each outcome rather than its real chances of success.

And odds fluctuate throughout the ante-post and in-play markets according to the weight of money placed and other factors such as time elapsed in the match.

It is, therefore, not advisable to rely on the market odds (at any moment in time) as a totally accurate benchmark of the event probabilities.

In order to more accurately gauge ‘true’ probabilities, it is advisable to take a **purely mathematical approach** using historical results and statistics.

**The very nature of selecting two variables in what is effectively a combination bet or ‘double’ means that the odds are multiplied creating an opportunity for higher returns than backing each outcome individually.**

The attraction of higher odds and the perception that most games in modern football are free-flowing attacking affairs where both defences are likely to be breached have created a market for these types of combination bets.

You may also think that by ‘doubling’ the home or away result and BTTS, the wager is shrewder than simply picking the correct score of the match where the odds are higher but far disproportionate to the probability of a return?

Let’s take a look at these points in more detail.

Table 1: Winning & Losing – **FT Result + BTTS Double**

We have previously looked at **FT score distributions** using a sample of almost 11,000 matches from nine different leagues.

If you open the screenshot there you will find that clean-sheet victories (1-0; 2-0; 3-0; 4-0; 0-1; 0-2; 0-3; 0-4, etc.) by either the home or away team accounted for 38.22% of all results.

Draws (0-0 through to 4-4) made up a 25.33% quota of all results.

However, for the sake of this article, we are interested in home and away wins where both teams scored. When tallied, these accounted for precisely **33%** (19.76% + 13.24%) of all results:

10,723 Match Sample: Home or Away Wins where both teams scored

A sample size of 10,723 matches is a statistically significant amount and a fair benchmark to gauge other leagues by.

In comparison, of the 1,900 English Premier League (EPL) games that took place in the five seasons from 2012/13, there were 646 matches (34%) when betting on one of the teams to win and both teams to score could have returned a winning bet.

From these indications, there will be ‘around’ a third (33%) of matches in a season in any top-flight league where the combination of BTTS and a decisive match result occur.

But, of course, this assumes that the right teams were selected to win. Without taking account of any assumed preference for the favourite, the probability is as low as 16-17% (50-50) for a winning return across those games.

Typical odds in the market for the Win (home or away) + BTTS can be anything between 3.00 and 6.00 depending on the teams involved, but the average odds are around 4.00.

So, roughly speaking, there is a 1 in 6 chance (16% = 1 in 6.25; 17% = 1 in 5.88) of making a winning selection, which will, at average odds of 4.00, return winnings of three times your money.

But how does this compare with simply backing the correct score?

The EPL is considered **one of the most exciting leagues in the world**, but the most common result type, as it is in every league, is actually a (not very exciting) one-goal game (1-0 or 0-1).

One goal games accounted for 348 (18.32%) of the 1,900 EPL matches between the five seasons during 2013-18.

The second most common result is 2-1 either way. During the same five season period, the EPL recorded a 2-1 home win 142 times (7.47%), and a 1-2 away win 123 times (6.47%), equating to 13.94% of all results.

In comparison, adding the 2-1 and 1-2 occurrences in Table 2 above gives a total of 15.94%, but it is safe to say that, across the board, 1-0 and 2-1 score lines are generally the most common results.

Again, taking out any preference for favourites, and using the 50/50 measure to predict the right team winning the match 1-0 or 2-1, the probability of correctly predicting 1-0 either way are around 9% (half of 18.32% in our EPL example), and around 7% for predicting a 2-1 (half of 13.94%).

So, mathematically at least, there is a slightly lesser chance of winning with these bets. However, looking at the disparity in odds, the potential winnings in the Correct Score market are far, far greater.

Taking a typical weekend’s EFL Championship betting fixtures as an example, even allowing for favourites and serial 1-0 winners, the odds for correctly predicting a 1-0 win range from around 6.00 to 34.00, and average out at odds above 11.00.

So whilst there is statistically a 1 in 11 chance (9%) of making a winning 1-0 correct score selection, either way, the bet will on average return winnings of more than ten times your money, and potentially as high as thirty-three times the original stake.

**All things considered, betting on the correct score market provides a much larger reward than betting on the combination of match result and BTTS.**

In conjunction with the course and based on its teachings, Soccerwidow also publishes a set of dedicated **Over/Under Goals Cluster Tables** *(summer and winter leagues)*, which are a one-touch solution to identifying value within the over/under ‘X’ goals market for individual matches in a particular league.

A Cluster Table is an Excel spreadsheet containing an interactive data set, which displays goal distributions in a particular league during the five complete seasons immediately prior to the season currently in play.

Results are split into four equal-sized groups, or ‘clusters’, according to the historical home and away odds of each match within the five-season-data-set *(highest odds at close of ante post market)*, which act as a gauge of public opinion *(perceived strength of the teams)*, for the match under consideration.

Here are two cluster examples taken from a game in the English Premier League (EPL) during the 2017-18 season. The screenshots come directly from the EPL 2012-17 Cluster Table.

**Click on the images below to enlarge them in new tabs:**

As you can see, the four clusters representing 95 respective home and away games over five seasons are divided into almost equal sets *(3x 24 games; 1x 23 games)*, which determines the division of their **HO/AO** quotients *(Home Odds divided by Away Odds)*.

Two rows are highlighted: these are the corresponding rows for the match between these two teams on **10th March, 2018**.

The home odds of Manchester United were 3.30. Liverpool’s away odds were 2.61. The HO/AO quotient was therefore **1.26** *(3.30 divided by 2.61)*.

The HO/AO clusters for all teams are different from one another. But why?

Odds are determined according to a team’s historical (statistical) strength (success), or lack of it, and no two teams perform exactly the same, which will of course produce different quotient figures.

How then is it possible to compare two teams in this fashion?

The home odds and the away odds are set by the bookmakers according to historical distributions (statistical results) and therefore provide a constant benchmark to a team’s past performance (**looking backwards**).

By the time the ante post market closes, they also contain a deal of public perception in terms of demand for the bet in question (**looking forwards**).

**Therefore, the HO/AO clusters take the correlation between the ‘perceived’ strength of the teams involved (based on historical results) AND the market pressures (demand and supply) faced by the bookmakers when setting their odds.**

The HO/AO quotient is therefore an ideal method of comparing two teams by selecting from their historical results the nearest batch of equivalent games against teams of a similar perceived strength to the opponent under analysis.

If United are 3.30 to beat Liverpool and Liverpool are 2.61 to beat United, it makes sense to look at comparable results where both teams carried similar prices in their respective home and away games in the past (*i.e. the closest United home games to their price of 3.30 in this game, and the closest Liverpool away games to their price of 2.61)*.

Splitting five seasons’ worth of games into four clusters does not divide exactly. Each team plays 19 games at home and 19 away per season. This makes a total of 95 home and 95 away games for each team, hence why for United’s home games and Liverpool’s away games *(and any other team)* there are three clusters of 24 games grouped together, and one cluster of 23.

In our example, it is coincidental that the most relevant clusters for both teams to the calculated HO/AO quotient of 1.26 each contain 24 games over the last five seasons.

When looking at the tables in the EPL for any team, the following categories become apparent when dividing games into ‘perceived strength’:

- HO/AO:
**up to 0.2248**

The home team is the clear favourite with a very good chance of winning*(the weight of money makes the home team the overwhelming favourite)* - HO/AO:
**0.2249 to 0.4902**

The home team is definitely stronger than the away team, but there is also a good chance of a draw in the game*(fluctuating opinion between home or draw)* - HO/AO:
**0.4903 to 0.7730**

It is not really clear in which direction the game will develop*(no overwhelming favourite)* - HO/AO:
**0.7731 to 1.6922**

The chance of a draw is quite high as both teams are perceived to be of equal strength*(no overwhelming favourite)* - HO/AO:
**over 1.6923**

The home team is weaker than the away team; it could be an away win*(the perceived favourite is the away team)*

After the setting and publishing of opening odds for sale, the price of a bet is then influenced by:

- The popularity for that bet amongst punters
*(***demand**) - A balancing act of monies received between the outcomes carried out by the bookmaker via price fluctuations to create its margin/profit
*(***supply**)

The price fluctuations *(changes in the odds)* from the opening of the market right up until the end of the event are therefore driven by both demand *(punters)* and supply *(bookmakers)*, and contrary to popular belief, not dictated solely by the bookmaker.

If the zero odds of an event are known it is possible to identify temporary or lasting pricing ‘errors’, large and small, caused by these fluctuations in demand and supply. These errors can then be used to ensure that every bet placed contains ‘value’, the essential element in making long-term profits from gambling.

As a reminder:

- Prices offered
**above**zero odds represent value back bet opportunities - Prices offered
**below**zero odds represent value lay bet opportunities

Zero odds are those at which, if every bet were placed at this price, the overall outcome of any number of bets would be a ‘zero’ sum game.

Finding ‘value’ is therefore about determining the implied *(actual estimated)* probability of an event *(based on historical results)*, and obtaining odds representing a lower probability (i.e. higher odds) if backing, or a higher probability *(lower odds)* if laying.

Of course, the higher the odds obtained above zero odds are, the more profitable your long-term back bet portfolio should be and the lower the odds obtained below zero odds are, the more profitable your long-term lay bet portfolio should be.

The HO/AO quotient was

1.26, suggesting that public perception of the event was that thedrawwas probably the most likely outcome.In the images above, the Over 2.5 Goals bet type is highlighted.

HO/AO

1.26sits in thefourth clusterof United’s cluster table, and the percentage chance of Over 2.5 Goals for their home games within this cluster was37.60%HO/AO

1.26sits in thethird clusterof Liverpool’s cluster table, and the percentage chance of Over 2.5 Goals for their away games within this cluster was62.40%Calculate the average of these percentages: 37.60% + 62.40% = 100.00% / 2 =

50.00%Calculate the zero odds: 1 / 50.00% =

2.00

It just so happens that the highest Over 2.5 Goals odds on offer for this event were also 2.00, providing no value in backing or laying.

The result was 2-1 to United, meaning that public perception of the event most likely being a draw was proved to be wrong. Public perception of likely outcomes and the eventual reality are very difficult to reconcile, which is why odds movements should never be relied upon as a guide to potential outcomes.

You should also note that the most popular games to bet on are usually those most intensely analysed *(United vs. Liverpool is just about the most high-profile club game in the world)*. Because of this, the highest pre-match odds available for many of the different bet types are usually very accurate compared to the statistical likelihoods. In this case, we calculated 2.00 as the zero odds and indeed, 2.00 was the highest pre-match price available.

Once again, we reiterate just how accurate the Cluster Tables are in calculating probabilities.

The Cluster Tables are an extremely powerful tool for checking market odds against ‘true’ odds in order to select bets containing ‘value’ for long-term profit.

The tables can also be utilised for predicting odds movements before kick-off and much, much more, but we will write about these benefits in other articles.

A **German reader** once commented that he couldn’t believe we were selling the Cluster Tables because to him, “*these five season tables are something like a ‘money printing machine’!*“.

If you wish to play around with the table used in our example above, you can purchase the EPL Cluster Table for the 2017-18 season here for just £2:

This table comes with the added bonus of a **£5 discount voucher** applicable to the **Fundamentals of Sports Betting Course – Over/Under Goals**.

You can use this table for **backtesting the 2017-18 EPL season**. Randomly select any weekend and carry out the calculations as demonstrated in this article. Try experimenting a little and perhaps compile different portfolios such as:

- Choosing only Under 3.5 Goal bets
- Choosing bets which have at least a 60% probability to win
- Choosing bets with a strong home favourite only
- … and so on! Use your wits and imagination to find a system that actually works for you!

Once you understand how the Cluster Tables work and have found a system to focus on, picking bets for a weekend becomes truly very easy!

Please note that after the 2017-18 EPL season finishes this sample table will expire and should not be relied upon for betting purposes after that. Sorry, you will have to buy the 2018-19 replacement table. However, the 2017-18 version will certainly give you a good idea of the table’s full functionality.

If you have any further questions on how to use the cluster tables, please use the comments section below.

Thanks for reading and good luck with your value betting!

]]>You can bet on Over/Under 2.5, or Over/Under 2,25 or Over/Under 2. But what are Over 2.5 bets, or even 2.25? There are no half goals! Or quarter goals! It doesn’t seem to make sense. Does it?

We will explain what the different Goal Lines signify and after you’ve finished the article you will never be confused again!

One of the most common bet types is **Over/ Under .5 goals**.

Obviously, there is no way for half a goal to be scored in a game. The expression .5 is just an aid to ensure that it is clear on what you are betting.

For example, if you place a bet on Over/Under 2.5 goals, then the .5 is the ‘turning point’. You win if there are at least 3 goals scored, and you lose if the match ends with less than 2 goals scored.

Here’s an example…

If you still have difficulties understanding the concept, here’s another article on the .5 bet: **A Brief Introduction to Over Under Goals Betting**.

Bets on whole numbers are often called **Goal Lines** or **Asian Goal Lines**. Although, technically, this isn’t correct as all bets described here are ‘goal lines’, but we will be using the term as it’s widely used by punters and bookmakers.

They are somewhat similar to Asian Handicap betting on the 1×2 result. As the name suggests, the possibility of a refund exists if a certain result comes in, in this case the ‘Goal Line’.

Similar to the AH, if the match finishes in a draw result (= ‘goal line’), it’s a “push”. The punter gets their money back. Otherwise, if there are less goals scored than the goal line, the stake is lost, and if more goals are scored, it is a win.

In the above example, if you were to bet on Over 2 Goals then you get your stake back (push) if the final score is exactly 2 goals (e.g. 2-0, 1-1, 0-2).

All the other Goal Lines naturally follow the same pattern.

If the **.5 bets** are **combined with Asian Goal Line bets**, then you get **.75 or .25 Goals bets**. Half of your stake is placed on the .5 bet whilst the other half is placed on the Asian Goal Line bet.

These bets are often shown as either Over 2.25 – or – Over 2, 2.5.

For example, if you place a bet of £20 on Over 2, 2.5 it means that you are placing a split bet. £10 on the 2 Goals Asian Goal Line, and £10 on Over 2.5 Goals.

If the match finishes…

- with 3 or more goals, then you will receive the winnings of both bets
- with exactly 2 goals, half of the stake will be returned as it was a push (2 Goals Asian Goal Line), and you will lose the other half (Over 2.5 bet)
- with less than 2 goals… your entire stake is lost

The same applies to the .75 bets, as shown below:

In this example you place a £20 bet on the Over 2.5, 3 goal line. Again, you would be placing a split bet. £10 on the 3 Goals Asian Goal Line and £10 on Over 2.5 Goals.

If this match finishes…

- with 4 or more goals, you will receive the winnings of both bets
- with exactly 3 goals, half of the stake will be returned as it was a push (3 Goals Asian Goal Line), but you will win the other half (Over 2.5 bet)
- with 2 or less goals… your entire stake is lost

To be honest, I would recommend keeping your hands away from these bets, although it may sound tempting to get half of the stake back. Although these are referred to as being a single bet they are actually two completely different bets rolled into one!

If you do not really understand odds calculation and probabilities, then it is definitely a bet which bookmakers love! They can adjust the pricing as they like, without the average punter fully understanding the maths behind it, ensuring that the mathematical advantage lies with the bookmaker.

Anyway, the silver lining is that it is quite unlikely to be exposed to the temptation as these bets are rarely offered by European bookmakers.

Here is another diagram to demonstrating split bets:

At the end of the day the goal of each punter should be betting for profit. Am I right?

Bookmakers make a living from betting by using maths. They analyse and calculate the chances of an outcome and then price their bets. Of course, they make sure that the mathematical advantage is on their side, just like anyone operating a game of chance (e.g. Casinos).

The punter who relies only on gut feeling does not have a chance against the bookmakers.

However, with Over/Under Goal bets the punter at least has a chance to start understanding the statistics behind the bet. It isn’t too difficult to calculate the probabilities of the various results and number of goals in a game and to then find value bets.

If you are interested in starting to bet for profit, then you should seriously consider buying our **Fundamentals of Sports Betting** course. For the first volume, we have chosen to write about the Over/Under goal market as this is the easiest betting market to teach the fundamentals of statistics and maths on, without the need to dive deeper into more advanced formulas and concepts. Give it a try!

There are all kinds of explanations on the Internet about various odds types, and the majority of them distinguish between fractional, decimal, and moneyline odds.

Image: paffy (Shutterstock)

Unfortunately, this is misleading and mathematically speaking, incorrect. There are only two types of odds, which are unrelated to their displays as fractions, decimals or, as in America, whole numbers.

Just remember those long ago school days (for some of us!)… A fraction, such as 6/5, converts into a decimal 1.2, or vice versa. Both numbers are the same, only written using different formats.

Here are the **two main types of odds**, including their formulas…

Fractional and Hong Kong odds are actually exchangeable. The only difference is that the UK odds are presented as a fractional notation (e.g. 6/5) whilst the Hong Kong odds are decimal (e.g. 1.2). Both exhibit the **net return**.

The European odds also represent the potential winnings (net returns), but in addition they factor in the stake (e.g. 6/5 or 1.2 plus 1 = 2.2).

Odds commonly referred to as ‘moneyline’ are mainly US bookmakers odds and also known as American odds. Moneyline means the money wagered either to win 100 units (e.g. -400), or money which will be won from a 100 units wager (e.g. +120).

However, both Indonesian and Malaysian odds, although **displayed as decimals** are, strictly speaking, ‘moneyline’ odds but their basis is 1 unit and not 100. Whilst the Indonesian odds closely resemble the American moneyline odds, Malaysian odds are a kind of “inverted” Indonesian style, combined with Hong Kong odds.

Although this may all sound pretty confusing, and the odds certainly look very different at first glance *(see table below)*, just have a closer look at the above formulas – all odds are calculated using their net returns *(formula for net return: 1/probability – 1)* and change their formula at 50% probability

BETTING ODDS CONVERSION TABLE

Fractional odds are favoured by bookmakers in the United Kingdom and Ireland.

Fractional odds quote the net return that will be paid out to the bettor, should he win, relative to his stake. Odds of 6/5 (“six-to-five”) imply that the bettor will cash £120 from a £100 stake. Should the punter win, he always receives his original stake back, plus the winnings.

So, if the odds are 6/5 and the stake is £100, then the total return is £220 (£120 winnings plus the original £100 stake).

Odds of 1/1 are known as ‘evens’ or ‘even money’. Not all fractional odds traditionally show the lowest common denominator. Perhaps most unusually, odds of 10/3 are read as “one-hundred-to-thirty”.

Image: Scott Maxwell (Shutterstock)

Hong Kong Odds are mainly used by people living in Hong Kong. Until 1997, Hong Kong was under British rule and therefore it should not be a surprise that HK odds closely resemble traditional British odds. The only difference is that HK odds are written in a decimal notation whilst the UK odds use fractions.

Hong Kong odds, as well as their UK counterparts, both quote the net return that will be paid out to the bettor should he win, relative to his stake. Odds of 1.2 in Hong Kong are the same as 6/5 (“six-to-five”) in the UK and both imply that the bettor will earn a net profit of £120 from a £100 stake. Should the punter win, he always receives his original stake back, plus the profit.

It follows that if the HK odds are 1.2 and the stake is £100 then the total return is £220 (£120 winnings plus the original £100 stake).

Decimal odds are standard on betting exchanges and they are favoured in continental Europe, Australia, and Canada.

Decimal odds are equivalent to the decimal value of the fractional odds, plus one. Because decimal odds are simply 1 divided by probability (= 1/probability) they are easier to use in calculations and we therefore favour them for our articles and explanations.

Thus, ‘even odds’ 1/1 are quoted in decimal notation as 2.0; the 6/5 fractional odds (1.2 HK odds) discussed above are quoted as 2.2. Decimal odds quote the net return paid out to the bettor PLUS the original stake.

So if the odds are 2.2 and the stake is €100 then the total return is €220 (€120 winnings including the original €100 stake).

Highlighting the Amount of Money Risked, or the Amount of Money Won

Change of Formula at 50% Probability

Odds commonly referred to as ‘moneyline’ are the odds which are mainly used by US bookmakers. These odds mean the money wagered either to win 100 units, or the money which will be won from a 100 unit wager.

Please note that both Indonesian and Malaysian odds are also ‘moneyline’ odds although often wrongly referred to just as ‘decimal odds’, probably due to their decimal notation, whilst US moneyline odds are shown in whole numbers.

However, both Indonesian as well as Malaysian odds have the same underlying formulas as the US moneyline odds, only that their basis is 1 unit and not 100.

]]>Image: Gts (Shutterstock)

Over/Under is a great way for people new to betting to get their feet wet…

With **over/under betting**, the first thing to understand is that you are **betting in relation to the number of goals scored in the game**. It doesn’t matter which team scores the goals or even who wins.

You just take the number of goals scored by each of the teams and add them together to get the total goals scored during the game.

The simplicity of this bet is what makes it such a common wager.

When you place an over/under bet, you have to choose two things:

**What**“goal line” you want to bet, and**Whether**you bet that the total goals scored in the game will end**over**that goal line.*or*under

It doesn’t matter how close the result is to the goal line either, the bet pays the same whether the end result is close to the bet’s goal line or far away.

**Over/Under bets that end in “.5” have only two outcomes.**

You either win the bet and get paid an amount equal to your stake multiplied by the betting odds or you lose the bet and your stake.

Because you can’t score half a goal, every bet is either a win or a loss.

Let’s take the most popular goal line in football: **2.5**.

If you think the total goals in the game will be three or more, you would want to bet “Over 2.5”. If you think the total goals in the game will be two or less, you would choose to bet “Under 2.5”.

Over/Under bets without the “.5” or with different fractions *(such as 2.25)* may return part or all of your stake to you even if you don’t win.

For example, with a Total Goals bet, if you bet “Over 2” and exactly 2 goals are scored, you will not win the wager but you will get your stake refunded.

The graphic below shows which bet (over or under) will win given a certain score in the game for various goal lines.

When you are betting in football, the only goals that count towards over/under bets are the ones scored during the regulation 90 minutes of each match.

If the game ends tied after 90 minutes any goals scored in extra-time or a penalty shoot-out do not count towards the over/under goals tally.

The result of the match itself does not matter; drawn matches with scorelines like 0-0, 1-1, 2-2, etc., also contribute to over-under bet results.

We are using 2.5 as an example here because although there are many possible over/under bets, 2.5 happens to be the most popular goal line for football bets.

It turns out that when you look at a long history of football games, **even across different leagues**, the average number of total goals scored per game is very close to 2.5.

As a result, you often have a similar number of punters backing each side of the 2.5 goal line where the odds are similar no matter which choice of over or under is made.

Bookmakers set the odds of over and under for each available goal line using statistical information on the teams who are playing each other as well as football games in general.

Demand on each side of the bet can change the bookmaker odds and knowing what the statistics say can help you determine whether a particular bet is a good or bad one to take.

**The best bet is not always the bet that is closest to the actual score you expect.**

In fact, it is often the bets further away from expectations that offer the greatest difference between the betting odds offered in the markets and the true statistical predictions.

Some punters are surprised at how important the underlying mathematics are, but long-term success at over/under betting is much more science than art!

Continue to follow our blog to learn more, or check out our book: **Fundamentals of Sports Betting**.

Even the term **‘Stake’**, at least so long as it is money related, is easily understandable.

Whatever level your stake is, there are only two options: you either lose the bet and your stake, or you win the bet, retrieving your stake and adding to it your winnings.

However, the term **‘Odds’** is far more difficult for most bettors, especially as odds are connected to market prices, fluctuations, probabilities, expectations, etc.

**Hand on heart, can YOU reliably define the terms “bet”, “odds”, and “stake”?**

** Definition of ‘Bet’:** Technically speaking, a ‘bet’ is an agreement between two parties that the one who makes an incorrect prediction about an uncertain outcome will forfeit something stipulated to the other – a wager.

Betting is all about risking something, usually a sum of money, against the money of someone else based on the outcome of a future event, such as the result of a race or other competitive event.

The term, ‘odds’, is somewhat ambiguous.

Here are two definitions from well-known dictionaries:

** Macmillan Dictionary**: The chances that are used for calculating how much money you will get if the person or thing you bet on wins a race or competition.

** Oxford Dictionary**: The ratio between the amounts staked by the parties to a bet, based on the expected probability either way.

**The problem** with the above definitions *(and many other definitions found in dictionaries)* is that odds are not necessarily connected to the real chances of something happening, not even to ‘expected’ probabilities.

Just think of **British odds, European odds, and US Moneyline odds**.

British odds show the net return of a bet, European odds display the net return of a bet plus the original stake, and US Moneyline odds exhibit the money wagered either to win 100 units, or the money which will be won from a 100 unit stake.

Another deviant example is that **bookmakers adjust their odds to public opinion** in order to **balance their books**.

Therefore, it is simply * incorrect to say* that ‘odds’ display the chances of something happening. Odds are not even necessarily based on expected probabilities.

Betting Odds are the Prices for a Bet

* Learning Point:* There is

** Definition of ‘Stake’:** Money or property risked on the result of a horse race, card game, match outcome, etc.

Stake (or ‘wager’ in America), is straightforward terminology.

You bet with your friend on a game of pool, and stake £5 each. Whoever wins the game gets £5 from the other party, and whoever loses is £5 poorer.

In betting, the stake (or ‘wager’) usually means money, which is countable.

The concept of stake becomes much more complicated if property is wagered, such as houses, cars, or in some countries even wives! If you gamble property then you not only have to calculate the true probabilities of a bet to compute the odds, but also convert the staked property into a monetary value.

In these cases bets are very often lopsided and unfair, with a huge advantage to the person who is better in maths than the other. *(Read an example: Arsenal fan staked his house on a bet with a Manchester United fan, who offered his wife and Toyota car in return )*

The only honest advice I can give – **Do not bet if you do not understand odds!**

Unless money is no object, few people will go shopping and load their basket with goods without checking and comparing the prices of different brands. Most of us need to ensure we have enough money available to pay for the purchases, and some of us like to ensure we are getting the best value for the money we pay.

** Understanding Odds is CRITICAL!** If you constantly go shopping without paying attention to the prices

Always remember: Odds are the price for a bet, they very rarely stand for the real probabilities, or chances.

Of course, odds available in the market can be converted into their ‘implied’ probabilities, which can then be compared to your own calculations of the ‘real’ expected probabilities, and vice versa.

If you want to become a winner you MUST understand odds and be able to compare and distinguish between the implied probabilities suggested by the odds offered in the market and the real (or true) probabilities suggested by historical statistics. There is no alternative – a lucky gambler is never lucky all the time.

*If you wish to learn odds calculation, please check out:*

Fundamentals of Sports Betting Course: Betting on Over / Under ‘X’ Goals