# The gun selector is currently NEGATIVE value

**Measured. The best single gun beats the full rack, and not by a little.**

| arm | runs | shots | hits | real % | dmg/run | per-run range | exact two-sided p vs `full` |
|---|---:|---:|---:|---:|---:|---|---:|
| `full` (shipped rack) | 7 | 3898 | 270 | **6.93** | 159 | 2.54–10.37 | — |
| **`onlyPattern`** | 7 | 4582 | 494 | **10.78** | **287** | 9.14–11.85 | **0.0012** |
| `onlyKNN` | 7 | 4033 | 207 | 5.13 | 119 | 4.15–6.47 | 0.1340 |
| `onlyLinear` | 7 | 3215 | 105 | 3.27 | 65 | 1.85–4.69 | 0.0082 |
| `onlyGF` | 7 | 3193 | 72 | 2.25 | 45 | 1.52–3.47 | 0.0012 |

**Firing `Pattern` alone: +3.85 pp pooled hit rate, +80% damage per run, p = 0.0012.**
It also fires MORE shots (4582 vs 3898), so it dominates on rate *and* volume.

This is **not** "any single gun wins" — `full` beats `onlyLinear`, `onlyGF` and `onlyKNN`.
It is specifically **"Pattern alone beats the rack"**.

## Method

One frozen binary built from clean `HEAD` via `git archive` (other agents had `common_libs/guns/*`
dirty), sha256 `f02481d8…`. Arms selected with the rack knobs only (`TR_RACK_<GUN>=off`), no source
edits. 5 arms × 7 runs × 7 rounds, 8 concurrent bridge battles, real DrussGT, judged ONLY on
server-side real hit rate from the events sidecar. Exact two-sided permutation test on per-run rates
(C(14,7)=3432 splits). Each arm's liveness verified from the selected-gun mix.

Harness preserved at `tools/ab/which_gun_*.sh` and `tools/ab/which_gun_analyze.py`.

## Why: the virtual fitness signal mis-ranks guns vs real outcomes

From the `full` arm's own selection mix and per-gun real rates:

- **`HeadOn` is massively over-selected** — **31.4% of ticks**, the most real shots (1070), but only
  **4.5% real**. It alone drags the rack down.
- **`Pattern`** has the best *virtual* rank and near-best *real* rate (11.9%, real rank 2), yet is
  selected only **22.6%** of the time.
- **`Linear`'s apparent strength was SELECTION BIAS.** Conditional on being selected it looked like
  15.2% (n=33); its *unconditional* rate (`onlyLinear`) is **3.27%**. Every earlier per-gun "real
  rate" in this repo is conditional on selection and is therefore confounded — this experiment is
  the clean measurement.

## What this does NOT yet settle

- **One adversary.** Everything here is vs DrussGT. `Pattern` should be re-checked against other
  bots before it becomes the default on the strength of this alone. (Supporting evidence: an offline
  audit found `Pattern` is the only gun competitive in *every* distance/speed bucket.)
- **Whether a SMALL good rack beats `Pattern` alone.** The selector is negative value on the current
  bloated rack; that does not prove it is negative value on a rack of only good guns. That is the
  next experiment, and it decides whether the selection apparatus gets fixed or disabled.
- **The user's directive was to KEEP the virtual-fitness selection mechanism.** This measurement
  conflicts with that directive, so the next step is to test the selector on a small, good rack
  rather than to assume either answer.

## Prior context: three failed selection-side attempts

| attempt | result |
|---|---|
| hysteresis (commit to incumbent) | 7.02% → 5.10%, p=0.002 |
| commitment (remove the random draw) | 7.17% → 4.44%, p=0.0012 |
| arrival-accuracy tie-break (rank by path, narrow by point) | 7.08%, p=0.88 — null |

So the per-tick random draw is load-bearing on three independent measurements, and no attempt to
"smarten" the tied band has helped. This experiment shows the problem is one level up: **which guns
are in the rack, and the fact that the virtual signal ranks them wrongly.**