Miyeon and Soyeon Bring Sass, Honesty, and Laughs to “Running Man”

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Fans of (G)I-DLE, get ready—Miyeon and Soyeon are bringing their bold personalities and honest charm to the next episode of Running Man!

Set to air on May 25 at 6:10 p.m. KST, this episode is shaping up to be a must-watch for both Neverlands and variety show lovers alike.

A Game of Wits and Brutal Honesty

In the preview clip released on May 18, the Running Man cast and guests are suddenly thrown into a mystery game full of clever twists and hidden agendas.

It’s every person for themselves as they try to figure out the rules and outsmart each other.

Soyeon and Miyeon immediately shine with their quick wit and hilariously candid commentary. When asked by Ji Suk Jin whether his pants are stylish, Soyeon doesn’t hold back:

“They’re not pretty, but they’re hip.”

Her no-nonsense attitude keeps the room laughing—and on edge.

Meanwhile, Miyeon isn’t shy about flaunting her visuals, and the dynamic duo doesn’t hesitate to tease and roast others during a rowdy bus ride.

Miyeon’s Dance Surprise

Although Soyeon cheekily reveals that “Miyeon doesn’t really like dancing,” the episode takes a turn when Miyeon unexpectedly delivers a passionate dance performance, even pulling fellow cast member Ji Ye Eun into the spotlight.

The moment not only surprises fans but also shows Miyeon’s playful and competitive side.

Why You Should Watch?

This episode promises a blend of chaos, comedy, and unexpected bonding as Miyeon and Soyeon dive headfirst into the unpredictable world of Running Man.

Whether it’s savage one-liners, team challenges, or surprising dance moves, there’s plenty to look forward to.

Written by Emma Brooks Kpop Streaming Strategist Analytics, Kpop, Streaming, Metrics, Trends, Fandom, Charts Emma Brooks has 3+ years of experience in music data analysis and holds a degree in Digital Media with training in statistical modeling and platform analytics.

Emma Brooks focuses on evaluating K-pop performance through structured data interpretation and platform signals. She examines how releases perform across streaming services and short form platforms, identifying patterns tied to timing and audience response. She produces analysis that prioritizes measurable outcomes over assumptions.

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