Serve an honest grade: the letter was carrying 1/6 the information of the

number beside it

PHASE 0 corrects the order's premise. A grade letter has been served all
along -- engine1.gradeProp builds it from an additive factor index,
computed INDEPENDENTLY of p_win. gradeBands is orphaned for a different
reason than assumed: it defines what a letter MEANS from realized
outcomes, and every band collapses to base-rate at current resolution.

The measurement that changed this order, on 3,417 settled props:

  grade  n      realized  mean p_win
  A         8    0.500      0.647     <- the TOP grade did WORST
  B       985    0.640      0.700
  C     1,695    0.602      0.676
  D       303    0.558      0.604
  F       426    0.535      0.588

  letter resolution 0.00116 (0.48% of variance)
  p_win  resolution 0.00715 (2.98%)
  -> the letter carried 0.16x the information of the number beside it

Concretely, from the hand-verify: Christian Encarnacion's 0.95 over
graded C and his 0.05 under ALSO graded C -- same hitter, opposite
forecasts, same letter. The gap was never that grades don't ship; it is
that the weaker of two available signals shipped as the headline.

PHASE 1 — model/servedGrade.js derives the letter from p_win with bands
anchored on MEASURED realized rates (B+ 0.663 / B 0.646 / C+ 0.615 /
C 0.589 / C- 0.548 / D 0.512 / F 0.447, base 0.6005).

NO MANUFACTURED A, structurally: A+/A/A- are UNISSUABLE, not rare. The
realized rate plateaus at 0.65-0.68 above p_win 0.70, so no band has
earned a top letter; a test sweeps every p_win 0..1 and asserts none
produces one. Even 0.99 tops out at B+ with its realized 0.663 attached.
Raising that ceiling later is a deliberate, visible act.

Bands that cannot separate SAY so -- C+/C/C- carry
separates_from_base_rate false and copy naming it, which is the honest
description of a forecast explaining 3% of variance. Every grade states
its basis (forecast_only vs forecast_plus_matchup_factors, naming which
factors fired) and calibrated:false. engine1.grade is preserved as
engine_grade so nothing downstream breaks.

PHASE 2 — refusals render real states: insufficient_data -> "not enough
history to call this one"; juiced_no_edge -> "the book has priced the vig
past any edge on this side". 1,870 refused snapshots carry exactly those
two reasons and both now surface.

PHASE 3 — hand-verified on 12 real served props. Freeman/Rice/Encarnacion
0.95 overs now B+ (was B, C, B); the 0.05 unders now F (was C). Refused
doubles render NO READ with their reason. never-blank PASS,
no-manufactured-A PASS.

Serving change; nine frozen model modules unchanged including engine1;
p_win never mutated; no calibrated number leaks (deployed set empty); no
Bonferroni slot.

STILL TRUE: the forecast explains ~3% of outcome variance. This order did
not make the model better. It made the letter stop overstating it.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01W1sivYNqY2TS5ftykmHBU9

src/services/intelligence/analyzeViaEngine1.js

@@ -574,6 +574,27 @@ async function analyzeViaEngine1(rawProp = {}) {
       ? (Number.isFinite(pOver) ? 1 - pOver : null)
       : (Number.isFinite(pOver) ? pOver : null);
     if (pWin != null) legacy.p_win = Math.round(pWin * 1000) / 1000;
+    // ── THE SERVED GRADE ────────────────────────────────────────────────
+    // Derived from the forecast, not from engine1's additive factor index.
+    // Measured on 3,417 settled props, that index carried 0.16x the information
+    // of the p_win printed beside it, and its A grade hit 0.500 while its F hit
+    // 0.535 -- the top letter did worse than the bottom. Concretely: the same
+    // hitter's 0.95 over and 0.05 under both graded C.
+    //
+    // engine1.grade is PRESERVED on the payload as `engine_grade` so nothing
+    // downstream breaks and the two remain comparable, but `served_grade` is
+    // what a user should see.
+    try {
+      const sg = require('../model/servedGrade');
+      legacy.engine_grade = legacy.grade;
+      legacy.served_grade = sg.gradeFor({
+        p_win: legacy.p_win,
+        refused: legacy.refused || legacy.insufficient_data,
+        refusal_reason: legacy.refusal_reason,
+        factor_adjustment: factorTrace,
+      });
+    } catch { /* the grade surface must never break the read */ }
+
     if (factorTrace) {
       legacy.factor_adjustment = factorTrace;
       legacy.p_win_prefactor = Math.round((dir === 'under' ? 1 - factorTrace.p_before : factorTrace.p_before) * 1000) / 1000;