Grok 4.3 vs MiniMax M3

After examining the simulation's physics and running baseline matches, the model wrote a 209-line soccer policy that successfully turned a losing record against "gegenpress" into a competitive draw and improved its win rate against "possession". To address defensive vulnerabilities revealed during specialized counter-attack drills, it edited the policy, but this initial tweak caused a major performance regression against the aggressive "gegenpress" strategy. The model then iterated through four successive rounds of code edits to fine-tune the team's behavior before submitting the final policy.

MiniMax M3 initiated the session by running a baseline simulation against a "gegenpress" opponent, which revealed a highly vulnerable defense that conceded an average of 7 goals per game and resulted in a disastrous 0-5 record. To address this, the model analyzed the physics and tackling mechanics in `sim/world.py` to understand how to strengthen its soft pressing strategy. However, the session timed out during this investigation phase, preventing the model from implementing or testing any policy iterations.