Competitive Fortnite Season Set to Reintroduce Siphon Mechanic

Monday, 9 September 2024, 08:50

Competitive Fortnite is set to welcome back the beloved Siphon mechanic for the 2025 season, exciting players and altering gameplay strategies. Following the conclusion of the FNCS 2024, where 'Pollo' and 'Peterbot' took the title, Epic Games announced significant changes. Key among these is the return of Siphon, rewarding players with health and shield upon eliminations, after extensive testing through Siphon Trials.
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Competitive Fortnite Season Set to Reintroduce Siphon Mechanic

Exciting Changes in Competitive Fortnite

Competitive Fortnite is poised for major gameplay updates in the upcoming 2025 season. Following the FNCS 2024 competition, where players showcased their skills for a $2,002,000 prize pool, Epic Games revealed excellent news regarding long-awaited features.

FNCS 2024 Recap

As we look back at this year’s FNCS season, Duos matches captivated audiences across multiple regions. Although the loot pool experienced shifts, the gameplay mechanics seemed reminiscent of the previous year.

  • Global Champs: 'Pollo' and 'Peterbot'
  • Prize Pool: $2,002,000
  • Switch from Duos to Trios for the next season

The Return of Siphon

Epic Games excited fans with the announcement of Siphon making a comeback. This mechanic, which provides health and shield when players score eliminations, will first appear in specialized tournaments dubbed Siphon Trials.

This strategic reintroduction aims to enhance the competitive landscape, but its inclusion in FNCS will depend on the results from these trials.

What is Siphon?

Siphon operates similarly to the Doombot Medallion, offering players rewards for successful eliminations, significantly influencing their gameplay approach.

Players are eager to see how this adjustment will impact the upcoming competitive scene!


This article was prepared using information from open sources in accordance with the principles of Ethical Policy. The editorial team is not responsible for absolute accuracy, as it relies on data from the sources referenced.


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