Football is one of the most widely developed, most influential, most charming sports with the largest number of fans in the world today, especially European football. In addition to the five major leagues (Premier League, La Liga, Bundesliga, Ligue 1, and Serie A), the annual competition is In addition, there will also be the Champions League (European Champions League), which has attracted many fans with its superb skills and perfect tactics. According to statistics, professional football first appeared in England in 1885. It has been 134 years since then. A large amount of event data has been accumulated (scores, odds, handicap, goals, corner kicks). With the advancement of science and technology, it is difficult to imagine that , football will be linked to big data. The past few years have been a boom for big data. With the birth of Internet+, Internet big data has been applied to various industries, and the use of big data technology to analyze and predict football and basketball events is no exception. Many friends who watch and buy football have a question: How to read the football handicap? How to analyze football odds? Only in this way can we correctly analyze and predict the outcome of the game. In the era of big data, there are actually rules to follow in football odds and handicaps. Today, the author will share a game prediction method with an accuracy of over 90%, which is obtained by using football odds and big data analysis. It's very simple. Using football odds handicap data as the basis for analysis, under the big data aggregation model, the results of many high-probability handicap odds are clear at a glance. Through the massive football handicap odds data in the past ten years, the author has independently developed hundreds of models and calculated dozens of high-probability handicap odds results. Those who are interested can take a look.
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Note: This method must meet the following conditions to be established.
1. The English Premier League (must be the Premier League) Australian Food gives the initial handicap as the main handicap handicap (0.0). 2. Bwin’s European initial win loss is lower than William Hill’s European initial win loss. 3. Bwin’s European odds, initial flat and negative losses, are higher than William Hill’s European odds, initial flat and negative losses. For Premier League games that meet the above three points, combined with big data analysis, we can boldly predict that in such games, the home team will be undefeated, that is, the home team will make a sure profit in a draw in the Asian handicap.
Is it such a god? The author counted the Premier League football matches in the 18-19 season. There were 12 games with odds and handicap that met the above three conditions. The final results were the same as those analyzed by big data. The home teams all remained undefeated. Among them, the home team remained undefeated. There were 7 wins and 5 draws. Haha, the analysis of football handicap combined with big data technology is really accurate. Below we will take the following games as analysis cases to gradually analyze
Example 1
Round 30 of the 18-19 English Premier League Burnley VS Southampton Match Time: 2019-02-02 20:00
Figure 1
Figure 1 shows the Asian handicap data of this football match. It can be clearly seen that the initial handicap issued by the Macau company is 0.0, which is a tie handicap, which meets the first condition above.
Figure II
Figure 2 shows the European odds data for this football match in mysql. You can clearly see that the European odds given by Bwin are lower than the initial odds given by William Hill. The initial flat compensation and negative compensation provided by Bwin are both higher than the initial flat compensation and negative compensation provided by William Hill. Meet the second and third conditions above.
As we said above, this type of football match can be boldly predicted through big data aggregation modeling and analysis, and the home team will be undefeated. Whether it is accurate or not, let's take a look at the result of the game. In the end, Burnley 1:1 Southampton, the prediction is accurate and successful.
Example 2
Round 36 of the 2018-19 English Premier League Leicester City VS Arsenal Game Time: 2019-04-29 19:00
Figure 1
Figure 1 shows the Asian handicap data of this football match. It can be clearly seen that the initial handicap issued by the Macau company is 0.0, which is a tie handicap, which meets the first condition above.
Figure II
Figure 2 shows the European odds data for this football match in mysql. You can clearly see that the European odds given by Bwin are lower than the initial odds given by William Hill. The initial flat compensation and negative compensation provided by Bwin are both higher than the initial flat compensation and negative compensation provided by William Hill. Meet the second and third conditions above.
The result was still as predicted by our big data analysis, successfully avoiding an upset, and in the end Leicester City beat Arsenal 3:0. It can be seen that various companies in football games give football handicap, and football odds are the entry point for our analysis and prediction. There will be many such games later, so I will not give examples one by one here. Anyone who is interested can verify it. , all predictions are accurate, big data will not panic.