Recorded teams // BatoForge observations

Recorded teams.
Observed results.

BatoForge observations show complete teams and their recorded battle results. Choose a mode, region and Run Day to see the most common squads — and how their battles on that exact day went.

This window covers 2026-10-29 08:50 UTC – 2026-10-29 09:00 UTC, recorded teams: 37,599.

Contains this Batomon

Casual · Pantra // Day 1

Most-seen teams.

100 teams observed on this day. Squads recorded only once are not listed; these rows cover 12% of them, ranked by how often they show up.

Most-seen teams, pick rate and per-battle win rate on day 1 in the Casual · Pantra group
Rank	Team	Pick rate	Win rate	Sample
1	PebblerVenopuff	2.0%	100.0%95% lower bound 34.2%	2
2	JoltailVelocect	2.0%	100.0%95% lower bound 34.2%	2
3	BumbleboltJoltail	2.0%	0.0%95% lower bound 0.0%	2
4	MagmiteScorchimp	2.0%	0.0%95% lower bound 0.0%	2
5	StingardeVenopuff	2.0%	50.0%95% lower bound 9.5%	2
6	StingardeVelocect	2.0%	0.0%95% lower bound 0.0%	2

Battle results: win rate is the share of these teams' battles won on Day 1. Only runs still in progress reach this day, so teams eliminated earlier are missing from its results. Each Run / Day team counts once within this completed window.Compare the sample sizes and team setups when using these results to plan a build. Species-level statistics →

Reading the numbers

What one row means.

See how teams and battles are counted, and what the results leave out.

The unit

A recorded team

One row groups complete squads with the same species composition in this group on this Run Day. Each Run / Day team counts once within the completed window; another Run Day is a separate team-day observation.

The rates

Battle by battle

Win rate uses these squads' battles on this Run Day. The 95% confidence lower bound shows uncertainty from the battle sample; it is not a guaranteed future win rate. Teams eliminated earlier are absent, so later-day results favor surviving runs.

The privacy

Counts only

This page shows anonymous aggregate counts without player identities.

Species-level statistics →Prefer to plan a team by hand? →How to read these statistics →