Mexico is the winningest team in CONCACAF history

The modern history of the most popular sport on the planet spans more than 100 years of existence. It began in 1863, when "rugby football" (rugby) and "association football" (soccer) parted ways in England and the world's oldest association was founded: the Football Association, the sport's first governing body. 

Years later, Brazil's dominance in soccer has been overwhelming. Figures such as Gilmar, Roberto Carlos, Cafú, Sócrates, Zico, Ronaldo, Romario, Ronaldinho, Bebeto, and of course the greatest, Pelé, have tipped the scales not only in the history of World Cups but also in ordinary matches. 

This is shown in this visualization chart where you can see the number of matches and matches won per selection sorted by victories. 

The graph shows Brazil's overwhelming dominance with 625 matches won out of 981 played, which would give it a "Winner Conversion" (percentage of matches won over matches played) of 63.71%. 

Surprisingly, the Mexican national soccer team ranks seventh in this privileged FIFA historical ranking, a breeze of fresh air for Mexican supporters, and fuels hopes for the USMNT match with Martino at the helm. 

Friendlies and World Cup as a statistical universe

Friendlies and Qualifiers occupy more than 50% of the sample analyzed, followed by UEFA, African Cup, and FIFA.

El Tri's most painful friendly match in history

One of the most painful friendly matches in history for El Tri was the one played in London against England, losing by 8 goals. A resounding 8-0 defeat that left the Mexican national team depressed.

Mexico surpasses Uruguay in the history

By occupying a privileged place, Mexico surpasses Italy, France, Spain, Netherlands, and mighty Uruguay as the team with the most matches won in history, a milestone and a trophy for the Tri that should be cherished for the rest of its life. 

What system is applied to predict this data?

In El Futbolero Mexico, we decided to apply our own measurement system based on historical data of both teams, helped by "The Professor'', knowing statistical patterns and Poisson distributions applicable through Python programming.

Thanks to this we can predict the number of goals that each team can score based on historical results.