Chivas, central to Mexico’s historic role in the 2026 World Cup | OneFootball

La Selección Mexicana continues to put together a memorable campaign at the 2026 FIFA World Cup, and on that road to the Round of 16 after a 2-0 win over Ecuador, the presence of Guadalajara players has been decisive.

The red-and-white influence has been constant since before the start of the tournament. In fact, Mexico has now gone five straight matches, including its final warm-up game before the World Cup, in which a Chivas player has been directly involved in a Tricolor goal.

The streak began against Serbia, when Brian Gutiérrez chipped in with an assist. Then, in the World Cup, Roberto Alvarado provided an assist in the opening match; later, Luis Romo scored the winning goal against South Korea. Against Czechia, Romo and Alvarado were on the scoresheet again with one assist each, and against Ecuador, “Piojo” showed up once more with a precise pass that paved the way for the win that secured Mexico’s place in the next round.

However, the red-and-white contribution is not limited to the attack. The two Mexico National Team players with the most minutes played in the World Cup are Raúl Rangel (347’) and Roberto Alvarado (337’), both of whom have started and seen action in all four matches for the national team.

Individually, Alvarado has established himself as Mexico’s top assist provider in the tournament with three assists, while “Tala” Rangel boasts a flawless record between the posts, keeping a clean sheet in all four World Cup matches.

For his part, Luis Romo has also made an outstanding contribution with one goal and one assist, reaffirming, along with the rest of the red-and-white contingent, the major role Guadalajara plays in the Tricolor’s project.

With decisive performances, consistent prominence, and a presence in the biggest moments, Chivas players have been key to Mexico’s run to the Round of 16 and to keeping the World Cup dream alive with an unmistakable red-and-white stamp.

This article was translated into English by Artificial Intelligence. You can read the original version in 🇪🇸 here.