Tag: BEST CORRECT SCORE FIXED MATCHES

BEST CORRECT SCORE FIXED MATCHES

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BEST CORRECT SCORE FIXED MATCHES

BEST CORRECT SCORE FIXED MATCHES

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Date: 09.10.2022     Day: Sunday

League: FRANCE Ligue 1
Match: Rennes  vs  Nantes
Tip: HOME WIN
Odds: 1.55      Fulltime 3:0

 

Date: 09.10.2022     Day: Sunday

League: KAZAKHSTAN Premier League
Match: FC Astana  vs  Ordabasy
Tip: HOME WIN
Odds: 1.45     Fulltime 6:0

 

Date: 09.10.2022     Day: Sunday

League: ITALY Serie A
Match: AS Roma  vs  Lecce
Tip: HOME WIN
Odds: 1.40     Fulltime 2:1

 

Date: 09.10.2022     Day: Sunday

League: NETHERLANDS Eredivisie
Match: Utrecht  vs  AZ Alkmaar
Tip: OVER 2.5 goals
Odds: 1.70     Fulltime 1:2

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With BEST CORRECT SCORE FIXED MATCHES As a bettor are you aware that you can use standard deviation to predict sure betting outcomes ? Find out what the standard deviation is, how to calculate it and apply it to your betting correct scores.

In BEST CORRECT SCORE FIXED MATCHES, we explained why professional bettors should not solely rely on the average, given its tendency to be influenced by outliers, and its inability to show the dispersion within a set of numbers.

A quantity expressing by how much the value of a group differ from the mean value for the group. Different metrics are either used directly or are input parameters for a function or distribution of BEST CORRECT SCORE FIXED MATCHES.

Poisson vs. Normal Distribution

For example, vip bettors are known to use a Poisson distribution model to predict the number of goals score per team in a sure soccer game. However, this distribution has just one input parameter – the average – and is a discrete distribution – produces outputs as whole numbers.

Predicting goals spread in the Premier League

As a test case let’s look at game goal difference in soccer. The goal difference per match seems to be normally distribute. The goal difference is the number of goals score by the home team minus the goals score by the away team, with a zero resulting in a draw.

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Lets look at the data from the 2013/14 Premier League season:

  • Man City recorded the biggest home win – 7-0 against Norwich
  • Liverpool’s 5-0 win at Tottenham was the biggest away victory
  • The average goal difference was 0.3789 (median & mode = 0)
  • The standard deviation was 1.9188.

BEST CORRECT SCORE FIXED MATCHES

A number of conclusions can be take from the data. Primarily the most popular goal difference is a draw, and the distribution is close to symmetric, with a favour towards home wins. However, our focus for the article is the standard deviation.

Calculating BEST CORRECT SCORE FIXED MATCHES

The normal distribution uses the two parameters (average and standard deviation) to create a standardised curve. In this, around 68% of the distribution lies within one standard deviation away from the mean, and 95% lies within 2 standard deviations.

In this case we expect 68% of games to end up between -1.5399 and 2.2977 goals (i.e. 0.3789 + 1.9188). The continuous nature of the curve does have its limitations: -1.5399 goal difference is not possible.

Rigged soccer games

In order to estimate a home win by a goal difference of 1. 1 can be move from a discrete (whole) value of 1, to represent the continuous range between 0.5 and 1.5. For each value we can then calculate its difference from the mean in terms of standard deviations.

BEST CORRECT SCORE FIXED MATCHES

The great thing about this is that we can now remodel the normal distribution as shown. In this case we’d need to find the area of the region shaded in orange.

The area shade in blue, showing the probability of less than 1 goal (or its continuous equivalent being less than 0.5 goals) can be find to be 52.15%.

While it is not the aim to delve deep into the BEST CORRECT SCORE FIXED MATCHES of this. It can be find using most spreadsheet software (in MS Excel: =NORM.DIST(0.5,0.3789, 1.9188,1). Similarly the probability of under 1.5 goals is 72.05%. Therefore we expect 19.53% between these two values.

Consequently out of 380 matches, we would have estimated 74.22 games ending with the home team winning with just one goal difference. In reality there were 75 games, so this was very close.

BEST CORRECT SCORE FIXED MATCHES

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BEST CORRECT SCORE FIXED MATCHES

BEST CORRECT SCORE FIXED MATCHES

Date: 26.08.2022     Day: Friday

League: GERMANY3. Liga
Match: Hallescher  vs  Meppen
Tip: Over 2.5 goals
Odds: 1.75    Result: 1:1

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How to Analyze odds using Expected Value

This article will help you understand why getting our PAID fixed matches will help you in beating all odds. Betting Resources already has many articles covering Expected Value or EV, so let’s just summarize BEST CORRECT SCORE FIXED MATCHES  briefly with an equation:

Expected Value = (Bookmaker’s odds / True odds) – 1

If the true odds are 2.00 and the bookmaker’s odds are 2.10, this means the EV is 0.05, or 5%. If the true odds are 4.00 and the bookmaker’s odds are 3.50, the BEST CORRECT SCORE FIXED MATCHES is -0.125, or -12.5%. Serious bettors are only interest if the expect value is greater than 0%, or when the bookmaker offers odds that are longer than the true odds.

Of course, knowing what the true odds are is another matter altogether. Sports betting is not like dice or roulette and the markets are complex systems, for which there are no simple algorithms that will tell you what the true outcome probabilities are. We have to estimate them via data modeling and perhaps a bit of intuition as well. The better your model, the closer your estimate BEST CORRECT SCORE FIXED MATCHES will be to the true probabilities.

fixedmatches.cc model is a combination of their own data analysis and the market information they acquire about their customers’ models, meaning it’s one of the best at estimating true probabilities. Of course, it won’t always be right, but on average it’s surprisingly good. For example, about 50% of their prices of 2.00 (after you’ve removed their margin) win and 25% of their prices of 4.00 win.

Profitable soccer matches

Individually, it’s impossible to know which odds were closer to the true odds and which were not so close, but on average, the errors are broadly cancelled out.

How to apply Expected Value to soccer matches

As the closing odds before a soccer match starts contain more information about the match than the odds when fixedmatches.cc first published them, on average the closing odds are closer to the true odds than the initial ones.

We might propose that the amount by which the odds move provides a measure of how much Expected Value there was available in the initial odds. This is not to argue that the closing odds are always correct, nor that the initial odds are always incorrect.

BEST CORRECT SCORE FIXED MATCHES

Instead, this means that the ratio of the two can be used as a proxy measure of Expected Value, given that we can’t know what the true odds are. This can be formulated as follows:

Expected Value = (First odds / Last odds) – 1

Naturally, sometimes both the BEST CORRECT SCORE FIXED MATCHES and the closing odds will be shorter than the true odds.

With this assumption in mind, how much Expected Value exists in soccer betting markets ? For a sample of 158,092 soccer matches and 474,276 home-draw-away betting odds, I divided fixedmatches.cc ’s initial odds by their closing odds, having removed their margin from the closing odds, and subtracted one.

So, how many odds had Expected Value greater than 0%? The figure was 29.7%. That’s actually quite a surprise, as it means nearly a third of fixedmatches.cc bet’s initial odds actually hold some Expected Value.

Best correct scores soccer games

How meaningful is BEST CORRECT SCORE FIXED MATCHES?

We might expect there to be more occurrences of low Expect Value (e.g. 2%) than high Expected Value (e.g. 20%). But how much more ? I ranked the size of the expected value for each bet in ascending order, then calculated a cumulative percentage.. For example, 29.7% of odds held EV greater than 0%, but this falls to 21.7% for EV greater than 2%. This is how such a trend appears on a graph:

Evidently, there is a lot of expect value to be find in the soccer match betting market. However, don’t expect a lot of big gifts.

Of course, the much bigger problem for bettors is knowing the expected value is there in the first place. Using this proxy measure, you won’t know that it was there until fixedmatches.cc. I have published their closing odds and by then, the initial odds have gone.