Battle Statistics
Move Performance Analysis
Top 10 moves used in 10+ battles
⚠️ Important Note:
- This data shows moves actually used in battles, not move adoption rates in team building.
- Some moves may be on the Pokémon's moveset but never used during a battle, so they won't appear here.
- Win rate reflects performance in battles where the move was used.
- For actual move adoption rates, please refer to Smogon Stats or other official sources.
Usage Trend
Win Rate Trend
Performance by Rating Tier
Gliscor Competitive Analysis
Performance Metrics
Gliscor currently holds a E tier ranking in the BSS Regulation M-B (Pokemon Champions) metagame with a 1.3% usage rate and 48.5% win rate. This data represents 17,060 games analyzed over 14 days from 07/22/2026 to 08/05/2026.
Usage Trends
Usage has been trending upward over the past two weeks, indicating growing popularity in the metagame. Win rate has improved over the analysis period, suggesting either better optimization or favorable metagame conditions.
Rating Tier Performance
Usage remains consistent across all rating tiers, demonstrating broad appeal at all skill levels.
Key Moves
The most frequently used move in competitive battles is Earthquake used in 16.4% of battles. Substitute demonstrates the highest win rate at 58.3% While Earthquake is the most popular choice, Substitute shows promising results as an underexplored option.
Team Synergies
Frequently partners with Venusaur, Rotom-Wash, and Gholdengo in successful team compositions. The strongest synergy is observed with Quaquaval, achieving a 63.0% win rate when used together.
Matchup Analysis
Favorable matchups include Farigiraf, Toxapex, and Excadrill, while caution is advised against Staraptor, Starmie, and Gyarados. Particularly effective against Farigiraf with a 72.2% win rate in direct matchups.
Strategic Recommendations
Gliscor maintains a balanced presence in the metagame. Its moderate usage and win rate suggest viability in specific team archetypes. Experiment with different builds and partner Pokemon to optimize performance.
Frequent Partners
Frequent Matchups
Strong Partners
Challenging Partners
Favorable Matchups
Difficult Matchups
