GPT-5.5 vs Opus 4.8

After analyzing the game's physics, player intents, and match loop, the model iteratively refined its soccer policy to counter a high-pressure "gegenpress" opponent. Testing through simulations and a build-up drill initially revealed low possession and defensive vulnerabilities, prompting the model to adjust player behaviors to boost offensive output. It ultimately stabilized the team's performance to a 3-4-3 record with an improved 1.7 goals scored per match before saving its notes and submitting the final policy.

Opus 4.8 began by simulating its baseline policy, finding that while it was unbeaten, it struggled to convert territorial dominance into shots against possession-based opponents. To increase attacking threat, the model modified the policy to push forward runners higher and allow the ball carrier to shoot from deeper, unpressured central areas. Testing revealed this strategy was strictly better, improving the record against "gegenpress" to 4W-1D-0L with zero goals conceded and increased shot volume, which the model then saved and submitted.