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Thai Esports Athlete Expelled From SEA Games for Cheating During Arena of Valor Match
Naphat Warasin used unauthorized software during the first game of a women’s Arena of Valor match, leading to her expulsion and a lifetime ban from the game publisher.
- On Monday , Naphat Warasin, a Thai esports athlete, was expelled from the ongoing 33rd Southeast Asian Games in Thailand after organisers concluded she cheated and imposed a final Personal Penalty of Expulsion from the esports competition.
- On Monday , Naphat Warasin, known as "Tokyogurl," used "unauthorised third-party software or hardware modification" during Game 1 of the Thailand–Vietnam match.
- After the expulsion, the player deleted her TikTok and Facebook accounts, and game publisher Garena imposed a lifetime Games ban while her talent agency terminated her contract; she drew flak for a vulgar hand sign during the broadcast livestream.
- The Thailand Esports Federation said it accepted the organisers' ruling, announced the Thai women's Arena of Valor team withdrawal, pledged an internal investigation, and TESF president Santi Lothong apologised.
- The SEA Games, which opened last week and run until December 20, features esports since 2019 and faces regional tensions after Thailand–Cambodia clashes this month.
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11 Articles
11 Articles
SEA Games shame: Thai eSports player caught cheating, disqualified
The fallout has been severe for Thailand eSports player Warasin “Tokyogurl” Naraphat who has been disqualified from the Thailand SEA Games after being caught using unauthorised software to cheat during an Arena of Valor match against Vietnam.
·Malaysia
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Bangkok PostReposted by 
GMA Filipino News
GMA Filipino NewsThai esports player expelled from SEA Games for cheating
A female Thai contestant has been expelled from the Southeast Asian Games in Bangkok for using unauthorised third-party software during the AoV (Arena of Valor) esports event.
·Bangkok, Thailand
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Coverage Details
Total News Sources11
Leaning Left2Leaning Right3Center2Last UpdatedBias Distribution43% Right
Bias Distribution
- 43% of the sources lean Right
43% Right
L 29%
C 28%
R 43%
Factuality
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