BEST CORRECT SCORE FIXED MATCHES
BEST CORRECT SCORE FIXED MATCHES
DAILY FREE TIPS
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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Correct scores big odds
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.
Betting fixed matches
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.
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.