## (4) How to Calculate Value?

Value is the “mathematical advantage” (expected return/ ROI) of a bet in relation to the investment.

**Market odds vs. True odds**

*Value computation (ROI and relative deviation)*

The investment is the risk (loss) which is hazarded when buying a bet.

Value is calculated from the price of a bet (market betting odds) computed in relation to the ‘true’ betting odds (calculated based on the actual expected probability of occurrence).

**Example of an over 1.5 goals bet:**

Betting odds in the market: 1.27 **(78.7%)**

True betting odds (own computation): 1.23 (81.3%)

**(market odds minus 1) divided by (true odds minus 1) minus 1**

(1.27 -1) / (1.23 -1) -1 = 17.4%

The above result (17.4%) is **Value I** (= expected ROI), in this example, from a back bet on over 1.5 goals.

If one gambles 100 times an amount of 10 units on the above odds (1.27), one expects that 81.3% *(own calculated probability)* of the placed bets will win. The formula is:-

**100**[bets]

**x 10**[units]

**x**

Net Return[European market odds minus 1]

Net Return

**x Expected Hit Rate**[own computed probability]

100 × 10 × 0.27 × 81.3% = 219.51 units

It is expected that the remaining 18.7% (100% minus 81.3%) of the bets will lose:

Thus, the

**expected profit**from this repeat transaction is

**32.72 units**(219.51 minus 186.99).

The **overall risk** [investment] of the bet is **186.99 units** *(the total of losing bets)*.

As 81.3% of the bets will win, 81.3% of the stakes will be returned *( not lost)*. These bets do not count as ‘investment’.

Dividing the expected profit (32.72 units) by the investment (186.99 units) equals **17.4%**. This is the **‘value’** of this particular bet in the example (= ROI, or expected cash flow from the investment).

Both of the above calculation methods lead to the same result: 17.4% -> **Value I**: mathematical advantage (expected ROI).

The above example is taken from myOver / Under ‘X’ Goals coursewhere I explain in detail betting odds calculation using the example of the over/under market as well as value computations and their interpretation.

The course includes many sample calculations, an introduction to cluster grouping, a multitude of formulas (for backing as well as laying), examples aplenty, and exercises at the end of each section for you to perform in order to hone your skills. (Answers are provided at the end of the course).

Knowledge of betting odds calculation and value computation is a MUST for people who seriously want to make money with sports betting.

Hello, have you ever thought about taking in consideration recent Games and their Results of both Teams against common opponents? You can find this information on sites like fussball.wettpoint.com . For example

Team Avellino won 30 % of the Games against common opponents (with 30 % Draws)

and the Team Frosinone won up to today 45 % of these Games (45 % Draw). Adding this stats to the final real odds.

In this particular game the “real odds” according to the spreadsheet are 37.5% 27.1% 35.4% but we can use also the stats from above and make an average of real odds.

So now the real odds should look like this 33.8% 36% and 30.2% for the draw. I hope you understand me my english is not my first language.

Hi Manu,

if you want to take into consideration recent games then you can only use games against equally strong opponents

(find the stats for the last 6 games by.HO/AO quotient)Next, calculate the observed distributions for the 5 previous seasons; without any games of the current season

(again, for the HO/AO quotient of the match analysed)That is the ‘expectation’ (expectancy value) for the current season.Last, take into consideration the phenomenon:

Regression toward the Mean. This statistical phenomenon means that if a variable is extreme on its first measurement, it will tend to be closer to the average on its second measurement—and if it is extreme on its second measurement, it will tend to have been closer to the average on its first.Very simplified example:(= expected distribution): 45% home wins – 40% draws – 15% away wins(to get closer to the expectancy values): 40% home wins – 50% draws – 10% away winsPlease keep in mind that 1×2 calculations are unfortunately not as straightforward as the above example (e.g. you also have to take goal differences into consideration) but something along these lines.

Hope that helps you to think in the right direction.

Best wishes,

Soccerwidow

I have to disagree with you when you say that ‘Betting odds can be converted into implied probabilities but these have little to do with the actual expected distribution of results’. Depending on the market you choose, betting odds are a much better indicator of an event outcome than any other method out there. Given that the chosen bookmaker has enough transctions on a single event, the prediction extracted from odds probabilities are most accurate. The ‘wisdom of the crowd’ is not just a theory it’s a fact and many studies have oroven that.

Hi Max, if bookmakers would always price their odds ‘true’ then they couldn’t stay in business and grow. They have to underprice the most likely outcomes and ensure that the mathematical advantage is always on their side. They utilise the ‘wisdom of the crowd’ to their advantage.

Here are a few articles which explain this enigma a little bit more in detail:

How Bookmakers’ Odds Match Public Opinion

5 Simple Steps to Win Over and Under Betting

Finding Betting Odds Inflection Points – Bet and Win

Hi Soccerwidow

I get what you are saying, but what do you think about articles like this?

According to the efficient market hypothesis, the closing odds provide the most efficient or most accurate representation of the probabilities of actual results, since they reflect the most amount of information expressed in the form of wagers by the betting public.

[…..]

Given the strength of the correlation and its almost perfect 1:1 relationship between expected and observed yields (Football-data.co.uk)

or this one

Through looking at the correlation between the expected probability of a game’s outcome and the actual outcome it is possible to determine how accurate a bookmaker’s odds are. From a sample size of 397,935 football games offered by Pinnacle Sports, a sharp bookmaker, there existed a high correlation (r-squared = 0.997) between the closing lines and the observed probabilities. In other words, Pinnacle’s odds accurately predicted the real world outcome 99.7% of the time. Meaning that that their odds are very efficient. (blog.tradematesports.com)

The football-data.co.uk article is about the accurancy of the expected Yield, not about the accuracy of odds…

For example, if he bet a team at a price of 2.50 which subsequently closed at 2.00, his expected value would be 2.50/2.00 or 25%. This expected value would thus be equivalent to his expected yield over a larger sample of wagers.The other article from blog.tradematesports.com is a very long article, and what I can see on the first glance it’s mainly targeted at traders… It’s mainly about that

trades close to kick-off reduces the likelihood that the edge will change dramatically.I agree with the statement that

The closing line in high liquidity markets reflects the true odds, because it incorporates all of the information that exists in the market, but there is also the statementLower liquidity markets are much more volatile and thus riskier than high liquidity markets..As already said, this article is targeting traders and these people are mainly interested into high liquidity markets, but Soccerwidow is targeting punters and value bettors, and therefore I stick to my statement that

Bookmakers’ Odds Match Public Opinionif they can make use of the ‘wisdom of the crowd’, or in other words, of the ‘gut feelings’ of the bettors.And isn’t than more effective to use the closing line from high liquidity markets against the small bookmakers who are not able to update their odds in real time. In my opinion this is where we can find real value odds. At least it worked for me for many years. I find it useless to chase all sorts of fantasy stats when you have such a good indicator of a game outcome. At least this is my opinion.

Hi,

In your spreadsheet for U 3,5 goals you have a Value 1 = 25,3%, how did you calculate this?

I tried with your method from page 3: (0,52 / 0,42) – 1 = 23,8%

Thanks.

Hi Pettersen,

the odds (1.42) shown in the spreadsheet originate from 70.67% converted into odds = 1.415028, and then rounded to 1.42 to be shown in the spreadsheet.

The calculation is based on the 1.415028. Please try again, and you will see that it results in 25.3%.

Remember as a general rule always to calculate with percentages, and not with odds.

Dear soccerwidow

The above shows how a back bet value edge is counted.

I can’t seems to understand the way you count a lay bet value

Do you mind showing me how?

Hi TechChuan,

to calculate the ‘value’ for a lay bet you have simply to reverse the calculations.

Just repeat the calculations as shown on page #3, and reverse the odds. Assume that the implied probability was 81.3% (market odds 1.23), and the true odds 78.7% (1.27).

thank you very much. Ill look more into it.

Where can I find total goal odds calculation in your web? Ive been looking into every article of yours but I can’t find any info regarding total goal calculation

You will actually only find one article regarding total goal distribution on the website:

Goal Distribution Comparison – EPL, Bundesliga, Ligue 1, EredivisieThe problem is that writing articles like this not only takes a few days of writing time, but also requires hundreds of working hours of research and calculations.

I’m sorry, but it is impossible to provide substantial work for free. Therefore, for those interested into goal calculation there is a

(paid)course available:Football Betting Odds Calculation Course – How to Calculate Odds – Over / Under ‘X’ GoalsDear soccer widow

May I ask which parameter do you weight more before deciding to bet, value or hit rate?

Your site has the most complete knowledge of value bets and probability that i can find.

I have spent many days reading through all your articles. Still a lot to learn from you all.

Thank you so much for your great effort.

TeckChuan

I’m risk avers, so for me, the hit rate is more important.

We have a nice saying in German:

Kleinvieh macht auch MistThe literal translation is:

Flock makes also muck.The meaning is that even small amounts add up to big piles. It’s about steadiness.I think the English proverb equivalent is:

Many a little makes a mickle.Dear soccerwidow

How about the hit rate of a lay bet ?

Say Wales has a true odd of 8.33 to win, market odds is 6.2

So lay bet value is 34% and hit rate of Wales not winning is 88%?

Thanks a lot

Correct!

The lay bet value is 34.35%, and the expected hit rate of Wales not winning 88%.

By the way, the value here calculated is the expected Yield if bets like this are carried out over and over again.

TC1 – Thanks for the praise (blush!). Sadly we have no plans at present to re-start a value betting tipping service. Firstly, it was very time-consuming and secondly, very difficult to maintain an ethical approach against a backdrop of clients who praised when things went well, and those who criticised when things didn’t work out for them in the short-run.

Value betting is a long-term strategy but no matter how many times we point this out to people, they still get tense and agitated when the inevitable losing streaks occur. We don’t wish to martyr ourselves again, so producing picks is not on the agenda at this time.

Sorry to disappoint and thanks for all your past and valued contributions to Soccerwidow.

will you be resuming your tips ( value bets ) like you produced for Betfair , always found them very good

just, Thank You!

I do need to read again.. and probably again and again and again, but this is the first thing ever that makes even a starter amount of sense (I am a bookie offer taker) but never believed all offers were “long term” value

Hi Soccerwidow! Thank for your site. How find value in correct score market? Can we apply this article to correct score market? Thanks

Hi Soccerwidow,

thanks a lot for your articles.

I think I found a small error in the alternative calculation method on page 3.

It says: 100 × 10 × 0.23 × 81.3% = 219.51 units

Correct would be 0.27 instead of 0.23. The result stays the same.

Daniel

Hi Daniel,

Many thanks for taking the trouble to point out the typing error, which has now been corrected.

Your support is greatly appreciated,

Soccerwidow 🙂