add track-record reset; drop dead distance_penalty_factor knob

Track Record: new "Reset" action (POST /admin/track-record/reset) deletes all
trade setups so stats start fresh after material scoring/setup changes — live
setups regenerate on the next scan. Guarded by a confirm dialog.

Recommendation config: remove distance_penalty_factor, which was exposed in the
admin UI but consumed nowhere (the touch-probability model superseded it). A
knob that silently does nothing is worse than no knob. Remaining defaults are
left as-is — they're reasonable, and the honest way to tune them is backtesting
against accumulated outcomes, not invented "researched" numbers.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

app/routers/admin.py

@@ -274,6 +274,16 @@ async def cleanup_data(
     return APIEnvelope(status="success", data=counts)
 
 
+@router.post("/admin/track-record/reset", response_model=APIEnvelope)
+async def reset_track_record(
+    _admin: User = Depends(require_admin),
+    db: AsyncSession = Depends(get_db),
+):
+    """Wipe the track record: delete all trade setups so stats start fresh."""
+    counts = await admin_service.reset_trade_setups(db)
+    return APIEnvelope(status="success", data=counts)
+
+
 # ---------------------------------------------------------------------------
 # Job control
 # ---------------------------------------------------------------------------

app/schemas/admin.py

@@ -49,7 +49,6 @@ class RecommendationConfigUpdate(BaseModel):
     confidence_diff_threshold: float | None = Field(default=None, ge=0, le=100)
     signal_alignment_weight: float | None = Field(default=None, ge=0, le=1)
     sr_strength_weight: float | None = Field(default=None, ge=0, le=1)
-    distance_penalty_factor: float | None = Field(default=None, ge=0, le=1)
     momentum_technical_divergence_threshold: float | None = Field(default=None, ge=0, le=100)
     fundamental_technical_divergence_threshold: float | None = Field(default=None, ge=0, le=100)
 

app/services/admin_service.py

@@ -23,7 +23,6 @@ RECOMMENDATION_CONFIG_DEFAULTS: dict[str, float] = {
     "recommendation_confidence_diff_threshold": 20.0,
     "recommendation_signal_alignment_weight": 0.15,
     "recommendation_sr_strength_weight": 0.20,
-    "recommendation_distance_penalty_factor": 0.10,
     "recommendation_momentum_technical_divergence_threshold": 30.0,
     "recommendation_fundamental_technical_divergence_threshold": 40.0,
 }
@@ -236,7 +235,6 @@ async def get_recommendation_config(db: AsyncSession) -> dict[str, float]:
         "confidence_diff_threshold": config["recommendation_confidence_diff_threshold"],
         "signal_alignment_weight": config["recommendation_signal_alignment_weight"],
         "sr_strength_weight": config["recommendation_sr_strength_weight"],
-        "distance_penalty_factor": config["recommendation_distance_penalty_factor"],
         "momentum_technical_divergence_threshold": config["recommendation_momentum_technical_divergence_threshold"],
         "fundamental_technical_divergence_threshold": config["recommendation_fundamental_technical_divergence_threshold"],
     }
@@ -309,6 +307,19 @@ async def cleanup_data(db: AsyncSession, older_than_days: int) -> dict[str, int]
     return counts
 
 
+async def reset_trade_setups(db: AsyncSession) -> dict[str, int]:
+    """Delete all trade setups, wiping the track record for a fresh start.
+
+    Stats are derived from evaluated trade setups, so this resets the Track
+    Record to zero. Live setups regenerate on the next R:R scan. Used after
+    material changes to scoring / setup generation, when historical outcomes no
+    longer reflect current logic.
+    """
+    result = await db.execute(delete(TradeSetup))
+    await db.commit()
+    return {"trade_setups": result.rowcount}  # type: ignore[attr-defined]
+
+
 async def get_pipeline_readiness(db: AsyncSession) -> list[dict]:
     """Return per-ticker readiness snapshot for ingestion/scoring/scanner pipeline."""
     tickers_result = await db.execute(select(Ticker).order_by(Ticker.symbol.asc()))

app/services/recommendation_service.py

@@ -22,7 +22,6 @@ DEFAULT_RECOMMENDATION_CONFIG: dict[str, float] = {
     "recommendation_confidence_diff_threshold": 20.0,
     "recommendation_signal_alignment_weight": 0.15,
     "recommendation_sr_strength_weight": 0.20,
-    "recommendation_distance_penalty_factor": 0.10,
     "recommendation_momentum_technical_divergence_threshold": 30.0,
     "recommendation_fundamental_technical_divergence_threshold": 40.0,
 }

frontend/src/api/admin.ts

@@ -180,3 +180,10 @@ export function cleanupData(olderThanDays: number) {
     })
     .then((r) => r.data);
 }
+
+// Track record
+export function resetTrackRecord() {
+  return apiClient
+    .post<{ trade_setups: number }>('admin/track-record/reset')
+    .then((r) => r.data);
+}

frontend/src/components/admin/RecommendationSettings.tsx

@@ -9,7 +9,6 @@ const DEFAULTS: RecommendationConfig = {
   confidence_diff_threshold: 20,
   signal_alignment_weight: 0.15,
   sr_strength_weight: 0.2,
-  distance_penalty_factor: 0.1,
   momentum_technical_divergence_threshold: 30,
   fundamental_technical_divergence_threshold: 40,
 };
@@ -82,7 +81,6 @@ export function RecommendationSettings() {
 
         <NumberInput label="Signal Alignment Weight" value={form.signal_alignment_weight} min={0} max={1} step={0.01} onChange={(v) => setField('signal_alignment_weight', v)} />
         <NumberInput label="S/R Strength Weight" value={form.sr_strength_weight} min={0} max={1} step={0.01} onChange={(v) => setField('sr_strength_weight', v)} />
-        <NumberInput label="Distance Penalty Factor" value={form.distance_penalty_factor} min={0} max={1} step={0.01} onChange={(v) => setField('distance_penalty_factor', v)} />
 
         <NumberInput label="Momentum-Technical Divergence Threshold" value={form.momentum_technical_divergence_threshold} min={0} max={100} onChange={(v) => setField('momentum_technical_divergence_threshold', v)} />
         <NumberInput label="Fundamental-Technical Divergence Threshold" value={form.fundamental_technical_divergence_threshold} min={0} max={100} onChange={(v) => setField('fundamental_technical_divergence_threshold', v)} />

frontend/src/components/signals/TrackRecordPanel.tsx

@@ -3,7 +3,7 @@ import { useMutation, useQueryClient } from '@tanstack/react-query';
 import { useActivation } from '../../hooks/useActivation';
 import { activationSummary } from '../../lib/qualification';
 import { usePerformance } from '../../hooks/usePerformance';
-import { triggerJob } from '../../api/admin';
+import { triggerJob, resetTrackRecord } from '../../api/admin';
 import { Button } from '../ui/Button';
 import { Callout } from '../ui/Callout';
 import { Disclosure } from '../ui/Disclosure';
@@ -112,6 +112,29 @@ export function TrackRecordPanel() {
     },
   });
 
+  const resetMutation = useMutation({
+    mutationFn: () => resetTrackRecord(),
+    onSuccess: (data) => {
+      toast.addToast('success', `Track record reset — ${data.trade_setups} setups cleared. Run the scanner to rebuild.`);
+      queryClient.invalidateQueries({ queryKey: ['performance'] });
+      queryClient.invalidateQueries({ queryKey: ['trades'] });
+    },
+    onError: () => {
+      toast.addToast('error', 'Failed to reset track record');
+    },
+  });
+
+  const onReset = () => {
+    if (
+      window.confirm(
+        'Reset the track record? This permanently deletes ALL trade setups and their outcomes. ' +
+          'Live setups will regenerate on the next R:R scan. This cannot be undone.',
+      )
+    ) {
+      resetMutation.mutate();
+    }
+  };
+
   return (
     <div className="space-y-6">
       <div className="glass-sm flex flex-wrap items-center justify-between gap-3 px-4 py-3">
@@ -145,9 +168,14 @@ export function TrackRecordPanel() {
             evaluator runs nightly after OHLCV collection.
           </p>
         </Disclosure>
-        <Button onClick={() => evaluateMutation.mutate()} loading={evaluateMutation.isPending} className="shrink-0">
-          {evaluateMutation.isPending ? 'Evaluating…' : 'Evaluate Now'}
-        </Button>
+        <div className="flex shrink-0 items-center gap-2">
+          <Button onClick={() => evaluateMutation.mutate()} loading={evaluateMutation.isPending}>
+            {evaluateMutation.isPending ? 'Evaluating…' : 'Evaluate Now'}
+          </Button>
+          <Button variant="danger" onClick={onReset} loading={resetMutation.isPending}>
+            {resetMutation.isPending ? 'Resetting…' : 'Reset'}
+          </Button>
+        </div>
       </div>
 
       {isLoading && (

frontend/src/lib/types.ts

@@ -307,7 +307,6 @@ export interface RecommendationConfig {
   confidence_diff_threshold: number;
   signal_alignment_weight: number;
   sr_strength_weight: number;
-  distance_penalty_factor: number;
   momentum_technical_divergence_threshold: number;
   fundamental_technical_divergence_threshold: number;
 }

tests/property/test_recommendation_properties.py

@@ -37,7 +37,6 @@ def test_property_strength_monotonic_probability(strength_low, strength_high):
     config = {
         "recommendation_signal_alignment_weight": 0.15,
         "recommendation_sr_strength_weight": 0.20,
-        "recommendation_distance_penalty_factor": 0.10,
     }
     scores = {"technical": 65.0, "momentum": 65.0}
 
@@ -74,7 +73,6 @@ def test_property_distance_probability_relationship(near_distance, far_distance)
     config = {
         "recommendation_signal_alignment_weight": 0.15,
         "recommendation_sr_strength_weight": 0.20,
-        "recommendation_distance_penalty_factor": 0.10,
     }
     scores = {"technical": 65.0, "momentum": 65.0}