diff --git a/TRAINING.md b/TRAINING.md
index bef34855..27df2098 100644
--- a/TRAINING.md
+++ b/TRAINING.md
@@ -201,11 +201,26 @@ direct 100-episode head-to-head between the two finished 36-39 with 25 draws —
 a dead heat, so the wider indirect margin does not reflect a real strength
 difference. Attempt 3 was taken on the tiebreakers: it is the later checkpoint
 (it resumed from attempt 2) and edges every telemetry metric. That head-to-head
-also measured a 17% physical side imbalance (physical teams 0-1 = 29-46, with
-`retry1` going 15-25 as team 0 but 21-14 as team 1) — inside the 20% bar used
-elsewhere, but large enough to be worth understanding rather than assuming it
-is noise, since it affects both models equally and may point at an asymmetry in
-the arena or in `ship_observations.gd`'s team-1 mirroring.
+also measured a 17% physical side imbalance (physical teams 0-1 = 29-46), which
+looked worth investigating as a possible asymmetry in the arena or in
+`ship_observations.gd`'s team-1 mirroring. **It is not — it is seed variance.**
+A follow-up ran `hard.json` against *itself* (self-play, so any split is purely
+positional and cannot be a strength difference) over 10 independent seeds at 30
+episodes each: pooled 113-125 across 300 episodes, a 4.0% imbalance, sign test
+p = 0.48, with team 1 ahead in only 3 of the 10 seeds. Per-seed imbalance
+ranged from 0.0% to 43.3%, so swings far larger than the original observation
+occur by chance at these episode counts.
+
+The trap worth remembering: `evaluate.py --seed` defaults to 1, so every
+evaluation in this file that did not pass `--seed` shares one paired
+starting-state sequence, and seed 1 happens to favour team 1 (7-19 in the
+self-play run above, 29-46 in the 100-episode head-to-head — same direction
+because it is the same seed, not because it replicates). Two such runs are one
+observation sampled twice, not independent confirmation. Vary the seed before
+concluding anything from a side split. This also means the
+`physical_side_imbalance_ceiling` gate in `generation5.py` is a single-seed
+measurement and should be read as a coarse catastrophe check, not evidence
+about side balance either way.
 
 Every tier runs at full trained cadence (`reaction_ticks=8`, `action_noise=0`)
 — the game does not manufacture difficulty gaps by handicapping a model. When