I Simulated 1,810,053 Battles to Find the Strongest Pokémon

Astroid Videos
11 May 202422:13

Summary

TLDRThe video script details a simulation program that ranks Pokémon based on their strength in battles. It humorously discusses the underperformance of certain Pokémon like Cosmog and the surprising strength of others, like Melmetal. The script also touches on the impact of abilities, items, and type advantages, concluding with the revelation of the 'strongest' Pokémon, which is humorously left for viewers to discover.

Takeaways

  • 🧩 The video discusses a simulation program that determines the strongest Pokémon through millions of trainer battles.
  • 🐉 Mega Rayquaza is considered a strong contender in the simulation, with its ability to hold an item during Mega Evolution and powerful moves.
  • 🔥 The simulation excludes Dynamax and Z-moves to focus on traditional battling mechanics, but includes Mega Evolutions for their appeal.
  • 🥇 Cosmog and Cosmoem are at the bottom of the ranking due to their limited move sets and lack of offensive capabilities.
  • 🐟 Magikarp surprisingly won 92 out of 3000 battles, leveraging its move Bounce against Bug types.
  • 📉 The performance of Pokémon like Spectre is hindered by the AI's suboptimal strategy, such as overusing Curse.
  • 🌿 The video ranks starter Pokémon, with Gen 8 starters performing the best on average and Gen 6 starters underperforming.
  • 🔨 The Handyman razor by Manscaped is promoted as a compact and precise shaving tool, offering a significant battery life.
  • 🏆 The top Pokémon are often special attackers, suggesting a trend in the metagame favoring special over physical moves.
  • 🔮 The video speculates on the best and worst Pokémon of each type, with Dragon types generally being strong and Bug types being weaker.
  • 🥈 The strongest Pokémon in the simulation is revealed to be Mew, known for being powerful and difficult to obtain in the games.
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Related Tags
Pokémon BattlesSimulationGamingStrategyCompetitive PlayMega EvolutionLegendary PokémonType AdvantageRanking SystemAI AnalysisFan Engagement