Add adaptive sports favorite pilot

README.md

@@ -15,7 +15,7 @@ https://polymarket-site-eta.vercel.app/personal.html
 
 The site fetches live Polymarket markets, generates agent suggestions, lets you
 run frequent paper cycles, and syncs the shared arena state through Neon or
-Vercel Blob. Build 70 also installs an offline app shell and caches timestamped
+Vercel Blob. Build 71 also installs an offline app shell and caches timestamped
 market snapshots. During an outage, cycles continue locally; cached entries are
 allowed for 90 minutes, older snapshots become mark-only, and all cached data
 expires after 24 hours.
@@ -26,7 +26,7 @@ team names, Over/Under, or another pair are rejected instead of being silently
 reinterpreted as Yes/No. The same semantic check applies to complete event
 bundles and the offline evaluators.
 
-Build 70 ranks the competition by each agent's return since Strategy 56 began.
+Build 71 ranks the competition by each agent's return since Strategy 57 began.
 Historical replay equity remains visible for context, but it no longer makes an
 agent look like the current leader when the live adaptive strategy is losing.
 
@@ -37,7 +37,7 @@ The learner shrinks small samples toward neutral, caps sizing changes to
 15% of candidates for deterministic exploration so a stale regime cannot become
 permanent.
 
-Strategy 56 treats each binary stake as capable of falling to zero even when the
+Strategy 57 treats each binary stake as capable of falling to zero even when the
 18% stop cannot fill. New core positions are capped at 2.5%-4% of equity and
 aggressive positions at 3%-5%, with lower limits for near-term, extreme-price,
 reversal, and fast-moving setups. Oversized positions inherited from older
@@ -60,8 +60,8 @@ cohort can demote it.
 The Build 69 re-audit loaded all 500 requested histories with no failures. The
 six-hour family lost 1.27% net on average across 106 independent events, with
 its full 90% interval below zero; no tested rule was robustly positive at 6,
-12, 24, or 72 hours. Build 70 therefore uses six hours only to stop bad regimes
+12, 24, or 72 hours. Build 71 therefore uses six hours only to stop bad regimes
-sooner. It also closes every stale pre-Strategy-56 directional holding at the
+sooner. It also closes every stale pre-Strategy-57 directional holding at the
 next fresh mark, including legacy records missing a signal label, while leaving
 complete arbitrage bundles and paired maker inventory under their own accounting.
 
@@ -91,10 +91,16 @@ evidence proves an edge.
 
 Run `npm run evaluate:sports-favorites` for the separate pregame favorite audit.
 It anchors decisions to the published game start, rejects stale prices, charges a
-modeled five-cent cost, forms equal-dollar event baskets, and uses a chronological
+modeled five-cent cost, takes only the highest-priced eligible favorite per event,
-60/20/20 split. The clean 3,000-market run produced nine train-pass rules but zero
+and uses a chronological 60/20/20 split. The clean 3,000-market run produced nine
-validation selections, so Strategy 56 does not promote the apparent sports-favorite
+train-pass rules but zero strict validation selections. The exact 24-hour,
-edge or use the holdout set to rescue it.
+60%-85% rule nevertheless had positive point estimates in all three partitions:
+2.97% train, 3.10% validation, and 19.83% untouched holdout, while its train and
+validation confidence bounds still crossed zero. Strategy 57 therefore permits
+only a labeled paper-capital pilot in Favorite Backer: 1.25% of equity per event,
+6% total, with a five-cent cost booked immediately. It disables after 12 completed
+events with materially negative evidence or a 2.5% account loss, and scales to
+2.5% only after 30 events produce a positive 90% lower confidence bound.
 
 Run `npm run evaluate:settlement-calibration` for the stricter settlement-bias
 search across up to 5,000 resolved markets. It uses a 60/20/20 chronological
@@ -103,10 +109,10 @@ stability windows, a 24-hour market-age minimum, and a recent non-flat price
 history requirement. Before those activity and overlap controls, four sports
 rules appeared to pass holdout because correlated props shared one event and
 some histories contained inactive default prices. After correction, 11 of
-1,400 rules passed training and zero passed validation. Strategy 56 therefore
+1,400 rules passed training and zero passed validation. Strategy 57 therefore
-does not install a static side, category, price-band, or settlement-horizon bet.
+does not install any other static side, category, price-band, or settlement-horizon bet.
 
-Strategy 56 also removes the last emotion-driven sizing path. Agent mood and
+Strategy 57 also removes the last emotion-driven sizing path. Agent mood and
 leaderboard urgency remain visible in reports, but neither can increase capital.
 A positive peer signal receives at most a 5% sizing lift, and only when both the
 agent's realized-trade cohort and the independent walk-forward market cohort are
@@ -127,7 +133,7 @@ and 24-hour horizons. Zero rules passed training, validation, or untouched
 holdout. At three hours, the broad 0.5-cent quote-gap rule still lost 0.63% per
 event in holdout; only 0.61% of observations completed both legs while 23.33%
 produced adverse one-leg inventory. Wider quotes traded less but remained
-negative. Strategy 56 therefore does not risk paper capital on an unproven
+negative. Strategy 57 therefore does not risk paper capital on an unproven
 maker rule.
 
 Run `npm run evaluate:reward-maker` to stress current reward-qualified books

index.html

@@ -341,7 +341,7 @@ footer{margin-top:34px;padding-top:22px;border-top:1px solid var(--border);color
   <nav class="topnav">
     <div class="brand">
       <div class="logo">🏆</div>
-      <div><div class="brand-name">Polymarket Arena</div><div class="brand-sub">10 agents · 5 core + 5 aggressive</div><div class="build-badge">Adaptive strategy 56 · maker research 2 · build 70</div></div>
+      <div><div class="brand-name">Polymarket Arena</div><div class="brand-sub">10 agents · 5 core + 5 aggressive</div><div class="build-badge">Adaptive strategy 57 · maker research 2 · build 71</div></div>
     </div>
     <div class="tabs" id="tabs">
       <button class="tab" data-tab="overview">Overview</button>
@@ -363,7 +363,7 @@ footer{margin-top:34px;padding-top:22px;border-top:1px solid var(--border);color
   <div class="personal-banner" id="personalBanner">
     <b>Personal research mode.</b> This copy is for your own analysis, paper tracking, and manual trade research only. It does not pool money, onboard investors, custody funds, bypass eligibility rules, or place orders without your manual approval.
   </div>
-  <div class="live-build-banner"><b>Build 70 active:</b> stale pre-Strategy-56 directional holdings are retired while complete bundles and maker inventory remain protected. Six-hour evidence can veto a losing regime, while positive promotion still requires independent 24-hour and 72-hour evidence. Calibration reports now distinguish real zeroes from count metadata missing in an older saved decision. Offline snapshots can value positions but cannot invent fills. This remains paper trading; profits are not guaranteed.</div>
+  <div class="live-build-banner"><b>Build 71 active:</b> Favorite Backer now runs a small, self-disabling sports-favorite pilot shaped by a 3,000-market chronological replay: one 60–85% favorite per independent event, entered only within three hours of the 24-hour pregame checkpoint. It starts at 1.25% of equity, stops if live settlement evidence turns materially negative, and can scale only after a positive confidence bound. Fresh cached snapshots remain usable for 90 minutes with timing rechecked locally. This remains paper trading; profits are not guaranteed.</div>
 
   <!-- ============ OVERVIEW ============ -->
   <section class="tabpanel" data-tab="overview">
@@ -745,7 +745,7 @@ footer{margin-top:34px;padding-top:22px;border-top:1px solid var(--border);color
   </section>
 
   <footer>
-    Build 70 · Adaptive strategy 56 · Maker research 2 · Paper trading only · Live prices from Polymarket's public Gamma and CLOB APIs · Not financial advice ·
+    Build 71 · Adaptive strategy 57 · Maker research 2 · Paper trading only · Live prices from Polymarket's public Gamma and CLOB APIs · Not financial advice ·
     <a class="market-link" href="https://github.com/theodore-song/polymarket-analyst" target="_blank" rel="noopener">Source on GitHub</a>
   </footer>
 </div>
@@ -774,10 +774,10 @@ const POLITICS_TREND_MIN_HOLD_HOURS = 72;
 const EXIT_CONFIRM_HOURS = 6;
 const AGENTS_KEY = "pma_agents_v2";
 const SUG_KEY = "pma_suggestions_v5";
-const BUILD_VERSION = 70;
+const BUILD_VERSION = 71;
-const SUGGESTION_ENGINE_VERSION = 56;
+const SUGGESTION_ENGINE_VERSION = 57;
 const MAKER_STRATEGY_VERSION = 2;
-const PREVIOUS_STRATEGY_VERSION = 55;
+const PREVIOUS_STRATEGY_VERSION = 56;
 const LEGACY_BUILD_STRATEGY_LINEAGE = Object.freeze({40:40,41:40});
 function normalizedStrategyVersion(value){
   const version=Number(value||0);
@@ -870,7 +870,7 @@ const AGENTS = [
    rank:(s)=>[...s].sort((a,b)=>(b.volume_24hr*(b.conviction+20)*Math.max(.4,Math.abs(b.net_edge||b.edge||0)*18))-(a.volume_24hr*(a.conviction+20)*Math.max(.4,Math.abs(a.net_edge||a.edge||0)*18))),
    maxNew:5, maxFrac:0.06, minConv:57, kelly:0.30, targetExposure:0.72, drawdownExposure:0.50},
   {id:"favorite", name:"Favorite Backer", emoji:"🛡️", color:"#38d2e6", kind:"strategy",
-   blurb:"A lower-drama agent that only considers outcomes already priced as favorites. It tries to grind out steadier returns by backing high-probability markets only when net edge and evidence quality survive the stricter checks.",
+   blurb:"Runs a small pregame sports-favorite pilot derived from a 3,000-market chronological replay. It takes at most one 60–85% favorite per independent event near the 24-hour checkpoint, starts at 1.25% of equity, learns from completed positions and settlements, disables itself when live evidence turns materially negative, and scales only after a positive confidence bound.",
    rank:(s)=>[...s].filter(x=>x.entry_price>=0.6).sort((a,b)=>(b.entry_price+Math.abs(b.net_edge||b.edge||0)+Number(b.evidence_score||0)*.2)-(a.entry_price+Math.abs(a.net_edge||a.edge||0)+Number(a.evidence_score||0)*.2)||b.conviction-a.conviction),
    maxNew:4, maxFrac:0.05, minConv:58, kelly:0.24, targetExposure:0.58, drawdownExposure:0.38},
   {id:"longshot", name:"Longshot Hunter", emoji:"🎰", color:"#fbbf24", kind:"strategy",
@@ -979,7 +979,13 @@ async function mapWithConcurrency(items,limit,mapper){
 /* ---------- Polymarket client ---------- */
 function parseJsonField(v){if(v==null)return [];if(Array.isArray(v))return v;try{return JSON.parse(v);}catch(e){return [];}}
 function toNum(v,d=0){const n=Number(v);return Number.isFinite(n)?n:d;}
-function daysUntil(iso){if(!iso)return null;const dt=new Date(iso);if(isNaN(dt))return null;return (dt-new Date())/86400000;}
+function normalizeApiIso(value){
+  if(!value)return null;
+  const dt=new Date(String(value).replace(" ","T").replace(/\+00$/,"Z"));
+  return Number.isFinite(dt.getTime())?dt.toISOString():null;
+}
+function daysUntil(iso){const normalized=normalizeApiIso(iso);return normalized?(new Date(normalized)-new Date())/86400000:null;}
+function hoursUntil(iso){const normalized=normalizeApiIso(iso);return normalized?(new Date(normalized)-new Date())/3600000:null;}
 function hasYesNoOutcomes(raw){
   const labels=parseJsonField(raw&&raw.outcomes).map(outcome=>String(outcome||"").trim().toLowerCase());
   return labels.length===2&&labels[0]==="yes"&&labels[1]==="no";
@@ -1004,13 +1010,16 @@ function normalizeMarket(raw,{allowClosed=false}={}){
   const yes=prices[0];
   if(!Number.isFinite(yes)||yes<0||yes>1||(!allowClosed&&(yes<=0||yes>=1)))return null;
   const events=raw.events||[]; const ev=events.length?events[0]:{};
-  const tags=Array.isArray(raw.tags)?raw.tags:[];
+  const rawTags=[...(Array.isArray(raw.tags)?raw.tags:[]),...(Array.isArray(ev.tags)?ev.tags:[])];
+  const tags=rawTags.filter((tag,index)=>rawTags.findIndex(candidate=>(candidate.slug||candidate.label)===(tag.slug||tag.label))===index);
+  const gameStart=normalizeApiIso(raw.gameStartTime||raw.eventStartTime||ev.startTime||ev.eventDate);
   return {category:classifyCategory(tags),tags:tags.map(t=>t.label).filter(Boolean).slice(0,4),
     id:String(raw.id),question:(raw.question||"").trim(),event:(ev.title||"").trim(),event_id:String(ev.id||raw.eventId||""),
     clob_token_ids:parseJsonField(raw.clobTokenIds).map(String),
     yes_price:+yes.toFixed(4),no_price:+prices[1].toFixed(4),
     volume:toNum(raw.volumeNum||raw.volume),volume_24hr:toNum(raw.volume24hr),volume_1wk:toNum(raw.volume1wk),
-    liquidity:toNum(raw.liquidityNum||raw.liquidity),end_date:raw.endDateIso||raw.endDate,
+    liquidity:toNum(raw.liquidityNum||raw.liquidity),end_date:normalizeApiIso(raw.endDateIso||raw.endDate),
+    game_start:gameStart,hours_to_start:hoursUntil(gameStart),sports_market_type:String(raw.sportsMarketType||""),
     spread:toNum(raw.spread),best_bid:toNum(raw.bestBid),best_ask:toNum(raw.bestAsk),
     price_change_1h:toNum(raw.oneHourPriceChange),price_change_1d:toNum(raw.oneDayPriceChange),
     price_change_1w:toNum(raw.oneWeekPriceChange),price_change_1m:toNum(raw.oneMonthPriceChange),
@@ -1164,6 +1173,15 @@ const NEG_RISK_EVENT_SCAN_LIMIT=500;
 const NEG_RISK_MIN_LIQUIDITY=1000;
 const NEG_RISK_MIN_NET_PROFIT=0.003;
 const NEG_RISK_MIN_NET_RETURN=0.0015;
+const SPORTS_FAVORITE_MIN_ENTRY=0.60;
+const SPORTS_FAVORITE_MAX_ENTRY=0.85;
+const SPORTS_FAVORITE_TARGET_LEAD_HOURS=24;
+const SPORTS_FAVORITE_LEAD_TOLERANCE_HOURS=3;
+const SPORTS_FAVORITE_PILOT_POSITION_PCT=0.0125;
+const SPORTS_FAVORITE_PROMOTED_POSITION_PCT=0.025;
+const SPORTS_FAVORITE_TOTAL_CAPITAL_PCT=0.06;
+const SPORTS_FAVORITE_VERDICT_EVENTS=12;
+const SPORTS_FAVORITE_PROMOTION_EVENTS=30;
 const MAKER_MAX_QUOTES=6;
 const MAKER_MAX_QUOTE_CAPITAL_PCT=0.02;
 const MAKER_TOTAL_CAPITAL_PCT=0.10;
@@ -1311,8 +1329,32 @@ function tradeLossBudgetPct(cfg,s={}){
 function boundedStakeForRisk(eq,stake,cfg,s){
   return Math.max(0,Math.min(Number(stake||0),Number(eq||0)*tradeLossBudgetPct(cfg,s)));
 }
+function sportsFavoriteLeadHours(item){return hoursUntil(item&&item.game_start);}
+function sportsFavoritePilotSuggestion(m){
+  if(!m||m.category!=="Sports"||!m.game_start)return null;
+  const lead=sportsFavoriteLeadHours(m),minLead=SPORTS_FAVORITE_TARGET_LEAD_HOURS-SPORTS_FAVORITE_LEAD_TOLERANCE_HOURS;
+  const maxLead=SPORTS_FAVORITE_TARGET_LEAD_HOURS+SPORTS_FAVORITE_LEAD_TOLERANCE_HOURS;
+  if(!Number.isFinite(lead)||lead<minLead||lead>maxLead||m.spread<=0||m.spread>0.03||m.volume<5000||m.liquidity<2000)return null;
+  const side=Number(m.yes_price)>=Number(m.no_price)?"YES":"NO",marketPrice=side==="YES"?Number(m.yes_price):Number(m.no_price);
+  if(marketPrice<SPORTS_FAVORITE_MIN_ENTRY||marketPrice>=SPORTS_FAVORITE_MAX_ENTRY)return null;
+  const modeledEntry=clamp(marketPrice+0.05,0.01,0.99),eventKey=String(m.event_id||m.event||m.id);
+  const conviction=+clamp(70+Math.log10(Math.max(1,m.liquidity))*1.4+Math.log10(Math.max(1,m.volume_24hr||m.volume))*0.8,70,80).toFixed(1);
+  return {market_id:m.id,question:m.question,event:m.event,event_key:eventKey,url:m.url,category:m.category,tags:m.tags,
+    clob_yes:(m.clob_token_ids||[])[0]||null,clob_no:(m.clob_token_ids||[])[1]||null,
+    yes_price:m.yes_price,no_price:m.no_price,fair_value:+modeledEntry.toFixed(4),edge:0,net_edge:0,
+    friction:0.05,chase_penalty:0,evidence_score:0.60,evidence_source_count:0,quality:"sports-favorite-pilot",side,
+    market_price:+marketPrice.toFixed(4),entry_price:+modeledEntry.toFixed(4),conviction,volume:m.volume,volume_24hr:m.volume_24hr,liquidity:m.liquidity,
+    spread:m.spread,price_change_1h:m.price_change_1h,price_change_1d:m.price_change_1d,price_change_1w:m.price_change_1w,
+    momentum_strength:0,signal_strength:0.60,signal_confidence:0.60,signal_type:"sports-favorite-pilot",
+    trade_ready:true,entry_candidate:true,audited_observation_only:false,adaptive_promotion:false,watch_only:false,jump_risk:true,requires_live:false,
+    game_start:m.game_start,hours_to_start:+lead.toFixed(2),days_to_resolution:m.days_to_resolution!=null?+m.days_to_resolution.toFixed(1):null,
+    pilot_prior:{markets:3000,event_legs:1,modeled_cost_cents:5,train_mean:0.02972,validation_mean:0.03102,holdout_mean:0.19826,strictly_promoted:false},
+    drivers:["one position per sports event","60–85% pregame favorite","within three hours of the 24h checkpoint","five-cent modeled entry cost"],
+    rationale:`Settlement pilot: ${side} is the ${Math.round(marketPrice*100)}% favorite ${lead.toFixed(1)}h before the published start. A 3,000-market chronological replay of this exact one-position-per-event rule had positive mean net returns in train, validation, and untouched holdout after a modeled five-cent cost, but early confidence bounds crossed zero. It therefore starts at 1.25% of equity, learns from every completed live position or settlement, and disables itself if those outcomes turn materially negative.`};
+}
 function analyzeMarket(m,realWorldSignals={}){
   if(m.volume<MIN_SCOUT_VOLUME||m.liquidity<MIN_SCOUT_LIQUIDITY)return null;
+  const sportsPilot=sportsFavoritePilotSuggestion(m);if(sportsPilot)return sportsPilot;
   const external=realWorldSignals[m.id]||{},p=m.yes_price,policy=categoryPolicy(m.category);
   const liq=liquiditySignal(m),mom=momentumSignal(m),timing=timingSignal(m.days_to_resolution),evidence=textEvidenceSignal(m,external);
   const signal=confirmedMarketSignal(m,evidence),direction=signal.side==="YES"?1:(signal.side==="NO"?-1:0);
@@ -1502,7 +1544,7 @@ function compactSuggestionForSync(s){
   return {
     market_id:s.market_id,question:s.question,event:s.event,url:s.url,category:s.category,
     clob_yes:s.clob_yes,clob_no:s.clob_no,yes_price:s.yes_price,no_price:s.no_price,
-    fair_value:s.fair_value,edge:s.edge,side:s.side,entry_price:s.entry_price,
+    fair_value:s.fair_value,edge:s.edge,side:s.side,entry_price:s.entry_price,market_price:s.market_price,
     net_edge:s.net_edge,friction:s.friction,chase_penalty:s.chase_penalty,evidence_score:s.evidence_score,evidence_source_count:s.evidence_source_count,quality:s.quality,
     conviction:s.conviction,volume:s.volume,volume_24hr:s.volume_24hr,liquidity:s.liquidity,
     spread:s.spread,price_change_1h:s.price_change_1h,price_change_1d:s.price_change_1d,price_change_1w:s.price_change_1w,momentum_strength:s.momentum_strength,
@@ -1511,7 +1553,8 @@ function compactSuggestionForSync(s){
     adaptive_promotion:s.adaptive_promotion,watch_only:s.watch_only,jump_risk:s.jump_risk,
     requires_live:s.requires_live,bundle_id:s.bundle_id,bundle_side:s.bundle_side,bundle_cost_per_unit:s.bundle_cost_per_unit,
     bundle_payout_per_unit:s.bundle_payout_per_unit,bundle_net_profit_per_unit:s.bundle_net_profit_per_unit,bundle_legs:s.bundle_legs,
-    days_to_resolution:s.days_to_resolution,drivers:s.drivers,rationale:s.rationale,
+    days_to_resolution:s.days_to_resolution,event_key:s.event_key,game_start:s.game_start,hours_to_start:s.hours_to_start,
+    pilot_prior:s.pilot_prior,drivers:s.drivers,rationale:s.rationale,
   };
 }
 function compactSuggestionsForSync(payload,limits=SYNC_LIMITS){
@@ -1546,7 +1589,8 @@ function compactCachedMarket(m){
     volume_24hr:m.volume_24hr,volume_1wk:m.volume_1wk,liquidity:m.liquidity,spread:m.spread,
     best_bid:m.best_bid,best_ask:m.best_ask,price_change_1h:m.price_change_1h,
     price_change_1d:m.price_change_1d,price_change_1w:m.price_change_1w,price_change_1m:m.price_change_1m,
-    days_to_resolution:m.days_to_resolution,end_date:m.end_date,closed:m.closed,accepting_orders:m.accepting_orders,
+    days_to_resolution:m.days_to_resolution,end_date:m.end_date,game_start:m.game_start,hours_to_start:m.hours_to_start,
+    sports_market_type:m.sports_market_type,closed:m.closed,accepting_orders:m.accepting_orders,
     condition_id:m.condition_id,tick_size:m.tick_size,order_min_size:m.order_min_size,competitive:m.competitive,
     rewards_daily_rate:m.rewards_daily_rate,rewards_min_size:m.rewards_min_size,rewards_max_spread:m.rewards_max_spread,fees_enabled:m.fees_enabled};
 }
@@ -1572,8 +1616,18 @@ function offlineCachePolicy(ageMs){
     markOnly:usable&&!executionAllowed};
 }
 function prepareCycleSuggestions(suggestions,runMode,entriesAllowed){
-  return (suggestions||[]).map(s=>(entriesAllowed&&(runMode==="live"||!s.requires_live))
+  return (suggestions||[]).map(s=>{
-    ?s:Object.assign({},s,{trade_ready:false,entry_candidate:false,watch_only:true}));
+    let next=s;
+    if((s.signal_type||"")==="sports-favorite-pilot"){
+      const lead=sportsFavoriteLeadHours(s),eligible=Number.isFinite(lead)
+        &&lead>=SPORTS_FAVORITE_TARGET_LEAD_HOURS-SPORTS_FAVORITE_LEAD_TOLERANCE_HOURS
+        &&lead<=SPORTS_FAVORITE_TARGET_LEAD_HOURS+SPORTS_FAVORITE_LEAD_TOLERANCE_HOURS;
+      next=Object.assign({},s,{hours_to_start:Number.isFinite(lead)?+lead.toFixed(2):null,
+        trade_ready:Boolean(s.trade_ready&&eligible),entry_candidate:Boolean(s.entry_candidate&&eligible),watch_only:!eligible||Boolean(s.watch_only)});
+    }
+    return entriesAllowed&&(runMode==="live"||!next.requires_live)
+      ?next:Object.assign({},next,{trade_ready:false,entry_candidate:false,watch_only:true});
+  });
 }
 function collectSyncItems(){const items={};SYNC_KEYS.forEach(k=>{const v=localStorage.getItem(k);if(v!=null)items[k]=v;});return compactSyncItems(items);}
 function applySyncItems(items){
@@ -1981,6 +2035,27 @@ function buildAdaptiveProfile(p){
     best:ranked[0]?{feature:ranked[0][0],score:ranked[0][1].score}:null,
     worst:ranked.length?{feature:ranked[ranked.length-1][0],score:ranked[ranked.length-1][1].score}:null};
 }
+function sportsFavoritePilotProfile(p){
+  const grouped=new Map();
+  (p&&p.closed||[]).filter(trade=>(trade.signal_type||"")==="sports-favorite-pilot"
+    &&normalizedStrategyVersion(trade.strategy_version)===SUGGESTION_ENGINE_VERSION).forEach((trade,index)=>{
+      const key=String(trade.event_key||trade.event||trade.market_id||`sports-pilot-${index}`);
+      const basis=Math.max(1,Number(trade.original_cost||trade.cost||0));
+      const rows=grouped.get(key)||[];rows.push(clamp(Number(trade.realized_pnl||0)/basis,-1,2));grouped.set(key,rows);
+    });
+  const returns=[...grouped.values()].map(rows=>rows.reduce((sum,value)=>sum+value,0)/rows.length),events=returns.length;
+  const mean=events?returns.reduce((sum,value)=>sum+value,0)/events:0;
+  const variance=events>1?returns.reduce((sum,value)=>sum+(value-mean)**2,0)/(events-1):0;
+  const margin=1.645*Math.sqrt(variance/Math.max(1,events)),lower=mean-margin,upper=mean+margin;
+  const pnl=(p&&p.closed||[]).filter(trade=>(trade.signal_type||"")==="sports-favorite-pilot"
+    &&normalizedStrategyVersion(trade.strategy_version)===SUGGESTION_ENGINE_VERSION).reduce((sum,trade)=>sum+Number(trade.realized_pnl||0),0);
+  const lossLimit=-Math.max(1,Number(p&&p.starting_balance||STARTING_BALANCE))*0.025;
+  const demoted=(events>=SPORTS_FAVORITE_VERDICT_EVENTS&&(mean<=-0.05||upper<=0))||pnl<=lossLimit;
+  const promoted=!demoted&&events>=SPORTS_FAVORITE_PROMOTION_EVENTS&&lower>0.005&&pnl>0;
+  return {state:demoted?"demoted":(promoted?"promoted":"pilot"),allowed:!demoted,promoted,demoted,events,
+    mean:+mean.toFixed(4),lower:+lower.toFixed(4),upper:+upper.toFixed(4),pnl:+pnl.toFixed(2),
+    position_pct:demoted?0:(promoted?SPORTS_FAVORITE_PROMOTED_POSITION_PCT:SPORTS_FAVORITE_PILOT_POSITION_PCT)};
+}
 function stableHash(text){
   let h=2166136261;
   for(let i=0;i<text.length;i++){h^=text.charCodeAt(i);h=Math.imul(h,16777619);}
@@ -2028,6 +2103,13 @@ function applyAdaptiveMarketPromotion(s,calibrationModel){
     rationale:`Adaptive promotion: this ${s.signal_type||"signal"} remained observation-only until its recent independent cohorts accumulated enough positive net-of-cost evidence. ${s.rationale||""}`});
 }
 function learnedOpportunity(cfg,p,s,profile=null,calibration=null){
+  if((s&&s.signal_type||"")==="sports-favorite-pilot"){
+    const pilot=sportsFavoritePilotProfile(p);
+    return {score:pilot.mean,confidence:pilot.events/(pilot.events+12),market_score:0,market_confidence:0,
+      personal_state:pilot.state,market_state:"settlement-pilot",historical_score:0,historical_confidence:0,
+      historical_features:["sports-favorite-3000-market-replay"],historical_requires_promotion:false,historical_proof_met:true,
+      multiplier:1,exploration:false,allowed:pilot.allowed,blocked_by:pilot.allowed?null:"pilot-settlement",features:["signal:sports-favorite-pilot"]};
+  }
   const model=profile||buildAdaptiveProfile(p),features=learningFeatures(s),rows=features.map(k=>model.buckets[k]).filter(Boolean);
   const independentWeight=rows.length?Math.max(...rows.map(r=>Number(r.weight||0))):0;
   const score=rows.length?rows.reduce((sum,r)=>sum+r.score,0)/rows.length:0;
@@ -2107,7 +2189,7 @@ function adaptiveDecision(cfg,p,rank,total,leaderEq,marketLearning=null){
   const maxPositionPct=aggressive?0.10:MAX_NEW_POSITION_PCT;
   targetExposure=clamp(targetExposure,0,1-reserve);
   const minExposure=0,belowFloor=false;
-  return {mode,reason,emotion:emo.mood,urgency:+emo.urgency.toFixed(2),minConv:Math.max(0,Math.round(minConv)),maxNew:Math.max(0,Math.round(maxNew)),maxFrac:+Math.min(maxPositionPct,Math.max(0.01,maxFrac)).toFixed(3),reserve,learning:profile,marketLearning:calibrationDecisionRecord(marketLearning),
+  return {mode,reason,emotion:emo.mood,urgency:+emo.urgency.toFixed(2),minConv:Math.max(0,Math.round(minConv)),maxNew:Math.max(0,Math.round(maxNew)),maxFrac:+Math.min(maxPositionPct,Math.max(0.01,maxFrac)).toFixed(3),reserve,learning:profile,marketLearning:calibrationDecisionRecord(marketLearning),sportsFavoritePilot:cfg.id==="favorite"?sportsFavoritePilotProfile(p):null,
     currentExposure:+currentExposure.toFixed(3),targetExposure:+targetExposure.toFixed(3),minExposure:+minExposure.toFixed(3),belowFloor};
 }
 const stopKey=(posOrId)=>typeof posOrId==="string"?posOrId:String(posOrId.asset||posOrId.market_id||"");
@@ -2307,7 +2389,7 @@ function policyHoldHours(pos){
     ?POLITICS_TREND_MIN_HOLD_HOURS:MIN_POLICY_HOLD_HOURS;
 }
 function exitReason(pos,fresh,analysis,cfg){
-  if(fastSettlementRisk(fresh))return "Risk policy removed fast-settling event exposure";
+  if((pos.signal_type||"")!=="sports-favorite-pilot"&&fastSettlementRisk(fresh))return "Risk policy removed fast-settling event exposure";
   const trail=trailingProfitReason(pos);if(trail)return trail;
   const heldHours=daysHeld(pos)*24;
   if(daysHeld(pos)>=EXIT_STALE_DAYS&&(pos.unrealized_pnl||0)<=0)return `Stale losing exit after ${Math.floor(daysHeld(pos))} days`;
@@ -2758,6 +2840,7 @@ function agentAcceptsSuggestion(cfg,s){
   const quality=s.quality||"watch",edge=effectiveEntryEdge(s),evidence=Number(s.evidence_score||0);
   if(quality==="watch")return false;
   if(quality==="bundle-arb")return cfg.id==="value";
+  if(quality==="sports-favorite-pilot")return cfg.id==="favorite"&&s.signal_type==="sports-favorite-pilot";
   if(cfg.id==="value")return ["confirmed","liquid-trend"].includes(quality)&&edge>=MIN_SELECTIVE_ENTRY_EDGE
     &&Number(s.entry_price||0)>=0.20&&Number(s.entry_price||0)<=0.80;
   if(cfg.id==="momentum")return ["confirmed","trend","liquid-trend","catalyst"].includes(quality)
@@ -2813,12 +2896,15 @@ function openPositions(p,cfg,rankedSugs,focus,decision,avoidMarketIds,peerStats=
   const learningProfile=d.learning||buildAdaptiveProfile(p);
   const maxPositions=cfg.maxPositions||MAX_STRATEGY_POSITIONS;
   const categoryCap=cfg.maxCategoryPct||MAX_CATEGORY_EXPOSURE_PCT;
-  const probeQualities=["trend","liquid-trend","reversal","catalyst"];
+  const probeQualities=["trend","liquid-trend","reversal","catalyst","sports-favorite-pilot"];
   const eqBefore=equity(p);
   const positionValueBefore=(p.positions||[]).reduce((sum,pos)=>sum+Number(pos.value||pos.shares*pos.current_price||0),0);
   const currentExposure=eqBefore>0?positionValueBefore/eqBefore:0;
   const targetExposure=clamp(Number(d.targetExposure??cfg.targetExposure??0.62),0,1);
   const minExposure=0,belowFloor=false;
+  const pilotProfile=d.sportsFavoritePilot||sportsFavoritePilotProfile(p);
+  const heldEventKeys=new Set([...(p.positions||[]),...(p.closed||[]).filter(pos=>pos.signal_type==="sports-favorite-pilot")]
+    .map(pos=>String(pos.event_key||"")).filter(Boolean));
   const tradeReadyCount=rankedSugs.filter(s=>s.trade_ready).length;
   const entryCandidateCount=rankedSugs.filter(s=>s.trade_ready||s.entry_candidate).length;
   const strategyMatches=rankedSugs.filter(s=>s.trade_ready&&agentAcceptsSuggestion(cfg,s));
@@ -2848,6 +2934,17 @@ function openPositions(p,cfg,rankedSugs,focus,decision,avoidMarketIds,peerStats=
       if((p.positions||[]).some(pos=>pos.bundle_id===s.bundle_id))return reject("already_held");
       return true;
     }
+    if(s.signal_type==="sports-favorite-pilot"){
+      const lead=sportsFavoriteLeadHours(s),eventKey=String(s.event_key||s.event||s.market_id||"");
+      if(!pilotProfile.allowed)return reject("pilot_learning");
+      if(!Number.isFinite(lead)||Math.abs(lead-SPORTS_FAVORITE_TARGET_LEAD_HOURS)>SPORTS_FAVORITE_LEAD_TOLERANCE_HOURS)return reject("timing");
+      if(heldEventKeys.has(eventKey))return reject("event_overlap");
+      if(Number(s.conviction||0)<d.minConv)return reject("confidence");
+      if(hasPosition(p,s.market_id))return reject("already_held");
+      if(hasRecentStop(p,s.market_id))return reject("cooldown");
+      if(focus!=="All"&&focus&&s.category!==focus)return reject("focus");
+      return true;
+    }
     if(s.side!=="YES"&&s.side!=="NO")return reject("direction");
     if((cfg.aggressive?s.conviction:s.peer_conviction)<d.minConv||s.conviction<58)return reject("confidence");
     if(s.entry_price<0.08||s.entry_price>0.92)return reject("price");
@@ -2883,8 +2980,9 @@ function openPositions(p,cfg,rankedSugs,focus,decision,avoidMarketIds,peerStats=
       opened++;openedIds.push(String(s.bundle_id||s.market_id));
       continue;
     }
+    if(s.signal_type==="sports-favorite-pilot"&&heldEventKeys.has(String(s.event_key||s.event||s.market_id||"")))continue;
     let frac;
-    if(probeQualities.includes(s.quality)){frac=Math.min(d.maxFrac,cfg.aggressive?0.05:0.025);}
+    if(s.signal_type==="sports-favorite-pilot"){frac=Math.min(d.maxFrac,Number(pilotProfile.position_pct||0));}
     else if(cfg.flat){frac=d.maxFrac;}
     else{const base=(s.peer_conviction/100)*Math.min(1,effectiveEntryEdge(s)/EDGE_SCALE);frac=Math.min(d.maxFrac,cfg.kelly*base);}
     if(s.peer_boost<0)frac*=0.82;
@@ -2893,6 +2991,10 @@ function openPositions(p,cfg,rankedSugs,focus,decision,avoidMarketIds,peerStats=
     let stake=Math.min(eq*frac,investable);
     const riskBudgetPct=tradeLossBudgetPct(cfg,s);
     stake=boundedStakeForRisk(eq,stake,cfg,s);
+    if(s.signal_type==="sports-favorite-pilot"){
+      const pilotValue=(p.positions||[]).filter(pos=>pos.signal_type==="sports-favorite-pilot").reduce((sum,pos)=>sum+Number(pos.value||0),0);
+      stake=Math.min(stake,Math.max(0,eq*SPORTS_FAVORITE_TOTAL_CAPITAL_PCT-pilotValue));
+    }
     const categoryValue=(p.positions||[]).filter(pos=>(pos.category||"Other")===(s.category||"Other")).reduce((sum,pos)=>sum+Number(pos.value||0),0);
     stake=Math.min(stake,Math.max(0,eq*categoryCap-categoryValue));
     if(stake<50)continue;
@@ -2901,15 +3003,17 @@ function openPositions(p,cfg,rankedSugs,focus,decision,avoidMarketIds,peerStats=
     if(cost>p.cash)continue;
     p.cash=+(p.cash-cost).toFixed(2);
     cycleBudgetRemaining=Math.max(0,cycleBudgetRemaining-cost);
-    p.positions.push({market_id:s.market_id,question:s.question,side:s.side,shares,
+    const currentMark=s.market_price!=null&&Number.isFinite(Number(s.market_price))?Number(s.market_price):entry;
+    const currentValue=+(shares*currentMark).toFixed(2),initialPnl=+(currentValue-cost).toFixed(2);
+    p.positions.push({market_id:s.market_id,question:s.question,event:s.event||"",event_key:s.event_key||s.event||s.market_id,side:s.side,shares,
       token_id:(s.side==="YES"?s.clob_yes:s.clob_no)||null,
-      entry_price:+entry.toFixed(4),current_price:+entry.toFixed(4),cost,value:cost,
+      entry_price:+entry.toFixed(4),current_price:+currentMark.toFixed(4),cost,value:currentValue,
-      original_shares:shares,original_cost:cost,unrealized_pnl:0,conviction:s.conviction,peer_conviction:s.peer_conviction,category:s.category,opened_at:cycleIso(),url:s.url||"",
+      original_shares:shares,original_cost:cost,unrealized_pnl:initialPnl,conviction:s.conviction,peer_conviction:s.peer_conviction,category:s.category,opened_at:cycleIso(),url:s.url||"",
       peer_note:s.peer_note||"",entry_reason:s.rationale||"",net_edge:s.net_edge,evidence_score:s.evidence_score,evidence_source_count:s.evidence_source_count||0,friction:s.friction,chase_penalty:s.chase_penalty,quality:s.quality,
       strategy_version:SUGGESTION_ENGINE_VERSION,
       build_version:BUILD_VERSION,
       momentum_strength:s.momentum_strength,signal_strength:s.signal_strength,signal_confidence:s.signal_confidence,signal_type:s.signal_type,price_change_1d:s.price_change_1d,price_change_1w:s.price_change_1w,
-      days_to_resolution:s.days_to_resolution,jump_risk:Boolean(s.jump_risk),
+      days_to_resolution:s.days_to_resolution,jump_risk:Boolean(s.jump_risk),game_start:s.game_start,hours_to_start:s.hours_to_start,pilot_prior:s.pilot_prior,
       learning_score:s.learning_score,learning_confidence:s.learning_confidence,market_learning_score:s.market_learning_score,market_learning_confidence:s.market_learning_confidence,
       learning_state:s.learning_state,market_learning_state:s.market_learning_state,
       historical_prior_score:s.historical_prior_score,historical_prior_confidence:s.historical_prior_confidence,historical_prior_features:s.historical_prior_features,
@@ -2917,8 +3021,11 @@ function openPositions(p,cfg,rankedSugs,focus,decision,avoidMarketIds,peerStats=
       learning_multiplier:s.learning_multiplier,learning_exploration:s.learning_exploration,
       risk_budget_pct:+(riskBudgetPct*100).toFixed(2),
       peak_price:+entry.toFixed(4),gain_stops:{},stop_losses:{}});
-    p.history.push({date:logDay(),action:"OPEN",question:s.question,side:s.side,
+    const openDetail=s.signal_type==="sports-favorite-pilot"
-      detail:`${decision?decision.mode+" mode — ":""}Bought ${shares} ${s.side} '${s.question.slice(0,40)}' @ ${pct(entry)} for ${fmtUSD(cost)} · max binary loss budget ${(riskBudgetPct*100).toFixed(1)}% · signal margin ${((Math.abs(s.net_edge!=null?s.net_edge:s.edge))*100).toFixed(1)}c · learned weight ${Number(s.learning_multiplier||1).toFixed(2)}x (${s.learning_state||"observing"}/${s.market_learning_state||"observing"})${(s.historical_prior_features||[]).length?` · history prior ${(s.historical_prior_features||[]).join("+")}`:""} · evidence ${Math.round((s.evidence_score||0)*100)}${s.peer_note?` (${s.peer_note})`:""}`});
+      ?`${decision?decision.mode+" mode — ":""}Sports settlement pilot bought ${shares} ${s.side} '${s.question.slice(0,40)}' @ modeled ${pct(entry)} for ${fmtUSD(cost)} (${pct(Number(s.market_price||entry))} market + 5c cost) · one position for event ${s.event_key||s.event||s.market_id} · pilot state ${pilotProfile.state} · ${(Number(s.hours_to_start)||0).toFixed(1)}h before start`
+      :`${decision?decision.mode+" mode — ":""}Bought ${shares} ${s.side} '${s.question.slice(0,40)}' @ ${pct(entry)} for ${fmtUSD(cost)} · max binary loss budget ${(riskBudgetPct*100).toFixed(1)}% · signal margin ${((Math.abs(s.net_edge!=null?s.net_edge:s.edge))*100).toFixed(1)}c · learned weight ${Number(s.learning_multiplier||1).toFixed(2)}x (${s.learning_state||"observing"}/${s.market_learning_state||"observing"})${(s.historical_prior_features||[]).length?` · history prior ${(s.historical_prior_features||[]).join("+")}`:""} · evidence ${Math.round((s.evidence_score||0)*100)}${s.peer_note?` (${s.peer_note})`:""}`;
+    p.history.push({date:logDay(),action:"OPEN",question:s.question,side:s.side,detail:openDetail});
+    if(s.signal_type==="sports-favorite-pilot")heldEventKeys.add(String(s.event_key||s.event||s.market_id||""));
     opened++;openedIds.push(String(s.market_id));
   }
   const eqAfter=equity(p);
@@ -3336,7 +3443,7 @@ function decisionSummary(p){
   const exposure=d.currentExposure!=null&&d.targetExposure!=null?` Exposure ${Math.round(d.currentExposure*100)}%; ceiling ${Math.round(d.targetExposure*100)}%.`:"";
   const allocation=d.allocationStatus?` ${d.allocationStatus}`:"";
   const candidates=d.tradeReadyCount!=null?` Candidate audit: ${d.tradeReadyCount} globally trade-ready, ${d.entryCandidateCount||d.tradeReadyCount||0} technical candidates, ${d.strategyCandidates||0} strategy matches, ${d.eligibleCandidates||0} fully eligible, ${d.opened||0} opened.`:"";
-  const blockerLabels={historical_prior:"history-tested losing setup",learning:"live learned losing regime",confidence:"confidence",overlap:"material overlap",already_held:"already held",cooldown:"stop cooldown",focus:"category focus",price:"entry price",edge:"edge",timing:"timing",liquidity:"liquidity",activity:"activity",evidence:"evidence",direction:"direction",portfolio_limit:"portfolio limit"};
+  const blockerLabels={historical_prior:"history-tested losing setup",learning:"live learned losing regime",pilot_learning:"sports pilot demoted",event_overlap:"same sports event",confidence:"confidence",overlap:"material overlap",already_held:"already held",cooldown:"stop cooldown",focus:"category focus",price:"entry price",edge:"edge",timing:"timing",liquidity:"liquidity",activity:"activity",evidence:"evidence",direction:"direction",portfolio_limit:"portfolio limit"};
   const blockerRows=Object.entries(d.rejectionCounts||{}).filter(([,count])=>count>0).sort((a,b)=>b[1]-a[1]);
   const blockers=blockerRows.length?` Blocks: ${blockerRows.slice(0,4).map(([key,count])=>`${blockerLabels[key]||key} ${count}`).join(", ")}.`:"";
   const learning=d.learning?` Learning: ${d.learning.samples} completed trades retained with older strategies down-weighted, ${(d.learning.global_score*100).toFixed(2)}% shrunk expectancy; ${d.learning.current_samples||0} completed under adaptive strategy ${SUGGESTION_ENGINE_VERSION}${d.learning.best?`; strongest ${d.learning.best.feature.replace(":"," ")}`:""}${d.learning.worst?`; weakest ${d.learning.worst.feature.replace(":"," ")}`:""}.`:"";
@@ -3349,14 +3456,16 @@ function decisionSummary(p){
   }
   const makerStats=d.makerProfile&&d.makerProfile.global;
   const maker=d.makerQuotes!=null?` Maker learner: ${d.makerShadowActive||0} zero-capital shadow observations and ${d.makerCapitalActive||0} evidence-promoted capital quotes active; ${d.makerFills||0} verified touches and ${d.makerShadowCompleted||0} shadow outcomes completed this cycle, ${fmtUSD(d.makerReserved||0)} capital reserved.${makerStats?` Event-clustered ledger: ${makerStats.attempts} attempts / ${makerStats.events} events, ${makerStats.locked} paired touches, ${makerStats.adverse} adverse single touches, ${makerStats.unfilled} unfilled, ${fmtUSD(makerStats.shadow_pnl)} simulated shadow net and ${fmtUSD(makerStats.pnl)} actual paper net.`:""} Capital promotion requires ${MAKER_MIN_COHORT_ATTEMPTS} current-strategy events with positive confidence bounds in both category and spread cohorts. Rewards remain excluded until externally verified.`:"";
-  return `${d.mode} mode: ${d.reason}${emotion} Limits now: ${d.maxNew} new trade${d.maxNew===1?"":"s"}, max ${(d.maxFrac*100).toFixed(1)}% per position${d.minConv?`, conviction ${d.minConv}+`:""}.${learning}${calibration}${maker}${exposure}${allocation}${candidates}${blockers}`;
+  const sportsPilot=d.sportsFavoritePilot?` Sports-favorite outcome learner: ${d.sportsFavoritePilot.state}, ${d.sportsFavoritePilot.events} independent completed events, ${d.sportsFavoritePilot.events?`${(d.sportsFavoritePilot.mean*100).toFixed(2)}% mean with ${d.sportsFavoritePilot.lower>=0?"+":""}${(d.sportsFavoritePilot.lower*100).toFixed(2)}% to ${d.sportsFavoritePilot.upper>=0?"+":""}${(d.sportsFavoritePilot.upper*100).toFixed(2)}% 90% interval; `:""}${fmtUSD(d.sportsFavoritePilot.pnl)} realized. Position cap ${(d.sportsFavoritePilot.position_pct*100).toFixed(2)}%; it disables after material negative completed-position evidence and scales only after ${SPORTS_FAVORITE_PROMOTION_EVENTS} events with a positive lower bound.`:"";
+  return `${d.mode} mode: ${d.reason}${emotion} Limits now: ${d.maxNew} new trade${d.maxNew===1?"":"s"}, max ${(d.maxFrac*100).toFixed(1)}% per position${d.minConv?`, conviction ${d.minConv}+`:""}.${learning}${calibration}${maker}${sportsPilot}${exposure}${allocation}${candidates}${blockers}`;
 }
 function renderAgentBrief(cfg,p,st){
   const root=$("agentBrief"); if(!root)return;
   const bw=bestAndWorst(p);
   const risk=cfg.aggressive?"Extreme risk":cfg.maxFrac>=0.055?"Active":cfg.maxFrac<=0.04?"Broad active":"Disciplined";
-  const cadence=`${cfg.maxNew||0} new trades max per cycle`;
+  const cadence=cfg.id==="favorite"?"One 1.25% pilot position per independent sports event near the 24h checkpoint":`${cfg.maxNew||0} new trades max per cycle`;
-  const exitRule=`Exit after a confirmed reversal, a 12h unconfirmed fade after 48h, a trailing-profit retrace, or ${EXIT_STALE_DAYS}d stale while losing; Politics trends get 72h before ordinary signal exits`;
+  const exitRule=cfg.id==="favorite"?"Hold the pregame favorite toward settlement unless the 18% stop or profit-lock rules fire; completed outcomes update the self-disabling learner"
+    :`Exit after a confirmed reversal, a 12h unconfirmed fade after 48h, a trailing-profit retrace, or ${EXIT_STALE_DAYS}d stale while losing; Politics trends get 72h before ordinary signal exits`;
   const thesis=agentPlainBlurb(cfg,st);
   const quoteSummary=(p.maker_quotes||[]).slice(0,3).map(quote=>`${quote.shadow_only?"Shadow":"Capital"} · ${quote.question.slice(0,34)}${quote.question.length>34?"...":""}: YES ${pct(quote.yes_quote)} + NO ${pct(quote.no_quote)}${quote.yes_filled_at||quote.no_filled_at?" (one leg touched)":""}`).join("; ");
   root.innerHTML=`
@@ -3660,7 +3769,7 @@ function agentCompetitionPlan(cfg,row,rank,leader){
   if(rank===1)return "Plan: press the lead through the strongest qualifying trades while keeping stop-loss and exposure limits active.";
   if(cfg.id==="value")return "Plan: close the gap with complete pricing bundles and paired resting bids, counting return only after both complementary legs fill below their combined payout and unwinding unmatched inventory after 24 hours.";
   if(cfg.id==="momentum")return "Plan: attack fast-moving markets where fresh volume confirms attention, hoping speed beats slower value strategies.";
-  if(cfg.id==="favorite")return "Plan: grind upward through high-probability favorites, aiming to outlast more volatile agents during choppy markets.";
+  if(cfg.id==="favorite")return "Plan: take one carefully sized 60–85% sports favorite per independent event near the 24-hour pregame checkpoint, then let completed settlements decide whether the pilot stops, stays small, or earns promotion.";
   if(cfg.id==="longshot")return "Plan: keep risk small but search for one underpriced outsider that can reprice sharply and leapfrog the leaderboard.";
   if(cfg.id==="diversifier")return "Plan: spread bets broadly, reduce single-market damage, and try to win through consistency rather than one heroic call.";
   if(cfg.id==="catalyst")return "Plan: deploy quickly when fresh real-world context and measured edge align, then concentrate enough capital for a catalyst repricing to move the account.";
@@ -4952,6 +5061,8 @@ window.PMA_ENGINE_DIAGNOSTICS=Object.freeze({
   peerEvidenceSizeMultiplier,
   tradeLossBudgetPct,
   boundedStakeForRisk,
+  sportsFavoritePilotSuggestion,
+  sportsFavoritePilotProfile,
   historicalPriceFeatures,
   offlineCachePolicy,
   prepareCycleSuggestions,
@@ -4977,7 +5088,11 @@ window.PMA_ENGINE_DIAGNOSTICS=Object.freeze({
     makerCompetitionSource:"shared public CLOB order-book audit",makerResearchSharedAcrossAgents:true,makerMarketsPartitionedAcrossAgents:true,
     makerHistoryRequestsBatched:true,makerPromotionCohorts:["category","spread","reward-yield"],makerRewardPayoutMinimum:1,
     emotionCanIncreaseSize:false,dualPromotionPeerBoostPct:5,
-    historicalPrior:"All tested directional, sports-favorite, and corrected settlement-calibration rules failed clean validation and remain observation-only; live-priced complete negative-risk bundles may trade; paired maker quotes require a public-book reward audit and remain zero-capital observations until current category, spread, and reward-yield cohorts independently promote"}),
+    sportsFavoritePilot:{entryBand:[SPORTS_FAVORITE_MIN_ENTRY,SPORTS_FAVORITE_MAX_ENTRY],targetLeadHours:SPORTS_FAVORITE_TARGET_LEAD_HOURS,
+      leadToleranceHours:SPORTS_FAVORITE_LEAD_TOLERANCE_HOURS,pilotPositionPct:SPORTS_FAVORITE_PILOT_POSITION_PCT*100,
+      promotedPositionPct:SPORTS_FAVORITE_PROMOTED_POSITION_PCT*100,totalCapitalPct:SPORTS_FAVORITE_TOTAL_CAPITAL_PCT*100,
+      verdictEvents:SPORTS_FAVORITE_VERDICT_EVENTS,promotionEvents:SPORTS_FAVORITE_PROMOTION_EVENTS,modeledCostCents:5},
+    historicalPrior:"All broad directional and corrected settlement-calibration rules failed clean validation and remain observation-only. The one-event 60%-85% sports-favorite rule has positive point estimates in all three chronological partitions but crossed confidence bounds, so only Favorite Backer receives a capped, self-disabling paper pilot. Live-priced complete negative-risk bundles may trade; paired maker quotes remain zero-capital observations until current cohorts independently promote"}),
 });
 function runEngineSelfTest(){
   const market=(overrides={})=>Object.assign({
@@ -4996,6 +5111,29 @@ function runEngineSelfTest(){
   const pathBarrierContract=analyzeMarket(market({id:"barrier-test",question:"Will Bitcoin reach $66,000 August 17-23?",category:"Crypto"}),news);
   const fixedDateLevelContract=analyzeMarket(market({id:"fixed-level-test",question:"Will Bitcoin be above $66,000 on 2026-08-23?",category:"Crypto"}),news);
   const ordinaryDatedContract=analyzeMarket(market({id:"dated-test",question:"Will the policy pass on 2026-08-22?"}),news);
+  const sportsPilotStart=new Date(Date.now()+24*3600000).toISOString();
+  const sportsPilot=analyzeMarket(market({id:"sports-pilot",question:"Will Harbor FC win tomorrow?",event:"Harbor FC vs City FC",event_id:"sports-event-1",
+    category:"Sports",yes_price:0.72,no_price:0.28,game_start:sportsPilotStart,days_to_resolution:1,price_change_1h:0,price_change_1d:0,price_change_1w:0}),news);
+  const sportsPilotSecond=Object.assign({},sportsPilot,{market_id:"sports-pilot-second",question:"Harbor FC first-half winner?"});
+  const sportsPilotBook=defaultPortfolio(),favoriteAgent=AGENTS.find(agent=>agent.id==="favorite");
+  const sportsPilotDecision=adaptiveDecision(favoriteAgent,sportsPilotBook,1,AGENTS.length,STARTING_BALANCE,buildSignalCalibration(defaultSignalLedger()));
+  openPositions(sportsPilotBook,favoriteAgent,favoriteAgent.rank([sportsPilot,sportsPilotSecond]),"All",sportsPilotDecision,new Set(),{});
+  const freshOfflineSportsPilot=prepareCycleSuggestions([sportsPilot],"offline-cache",true)[0];
+  const expiredOfflineSportsPilot=prepareCycleSuggestions([Object.assign({},sportsPilot,{game_start:new Date(Date.now()+10*3600000).toISOString()})],"offline-cache",true)[0];
+  const losingSportsPilotBook=defaultPortfolio();
+  for(let i=0;i<SPORTS_FAVORITE_VERDICT_EVENTS;i++)losingSportsPilotBook.closed.push({strategy_version:SUGGESTION_ENGINE_VERSION,
+    signal_type:"sports-favorite-pilot",event_key:`losing-sports-event-${i}`,market_id:`losing-sports-${i}`,original_cost:100,realized_pnl:-10});
+  const losingSportsPilotProfile=sportsFavoritePilotProfile(losingSportsPilotBook);
+  const losingSportsPilotDecision=adaptiveDecision(favoriteAgent,losingSportsPilotBook,1,AGENTS.length,STARTING_BALANCE,buildSignalCalibration(defaultSignalLedger()));
+  openPositions(losingSportsPilotBook,favoriteAgent,favoriteAgent.rank([sportsPilot]),"All",losingSportsPilotDecision,new Set(),{});
+  const promotedSportsPilotBook=defaultPortfolio();
+  for(let i=0;i<SPORTS_FAVORITE_PROMOTION_EVENTS;i++)promotedSportsPilotBook.closed.push({strategy_version:SUGGESTION_ENGINE_VERSION,
+    signal_type:"sports-favorite-pilot",event_key:`winning-sports-event-${i}`,market_id:`winning-sports-${i}`,original_cost:100,realized_pnl:10});
+  const promotedSportsPilotProfile=sportsFavoritePilotProfile(promotedSportsPilotBook);
+  const promotedSportsPilotDecision=adaptiveDecision(favoriteAgent,promotedSportsPilotBook,1,AGENTS.length,STARTING_BALANCE,buildSignalCalibration(defaultSignalLedger()));
+  openPositions(promotedSportsPilotBook,favoriteAgent,favoriteAgent.rank([sportsPilot]),"All",promotedSportsPilotDecision,new Set(),{});
+  const sportsPilotExit=exitReason({signal_type:"sports-favorite-pilot",entry_price:0.77,current_price:0.72,opened_at:nowIso(),unrealized_pnl:-5,quality:"sports-favorite-pilot"},
+    market({category:"Sports",question:"Will Harbor FC win tomorrow?",game_start:sportsPilotStart,days_to_resolution:1}),null,favoriteAgent);
   const targets=window.PMA_ENGINE_DIAGNOSTICS.gainStopTargets(0.82);
   const hoursAgo=h=>new Date(Date.now()-h*3600000).toISOString();
   const conflict={trade_ready:true,side:"NO",net_edge:-0.03,conviction:72};
@@ -5408,6 +5546,24 @@ function runEngineSelfTest(){
       urgencyCannotIncreaseSize:urgencyWithoutEvidenceMultiplier===1&&urgencyWithOnePromotionMultiplier===1,
       dualIndependentPromotionAllowsBoundedPeerBoost:dualPromotionMultiplier===1.05,
       legacyLossDoesNotFreezeCurrentEngine:legacyLossDecision.mode!=="Loss Regime Containment"},
+    sportsFavoritePilot:{
+      identifiesTimedFavorite:Boolean(sportsPilot&&sportsPilot.trade_ready&&sportsPilot.quality==="sports-favorite-pilot"&&sportsPilot.side==="YES"),
+      chargesModeledFiveCentCost:Boolean(sportsPilot&&sportsPilot.market_price===0.72&&sportsPilot.entry_price===0.77&&sportsPilot.friction===0.05),
+      onlyFavoriteAgentAccepts:Boolean(sportsPilot&&agentAcceptsSuggestion(favoriteAgent,sportsPilot)&&!agentAcceptsSuggestion(AGENTS.find(agent=>agent.id==="momentum"),sportsPilot)),
+      opensOnePositionPerEvent:sportsPilotBook.positions.length===1&&sportsPilotBook.positions[0].event_key==="sports-event-1",
+      startsAtOneAndQuarterPercent:sportsPilotBook.positions.length===1&&sportsPilotBook.positions[0].cost<=STARTING_BALANCE*SPORTS_FAVORITE_PILOT_POSITION_PCT+0.01,
+      booksModeledCostImmediately:sportsPilotBook.positions.length===1&&sportsPilotBook.positions[0].unrealized_pnl<0&&equity(sportsPilotBook)<STARTING_BALANCE,
+      freshOfflineSnapshotCanEnter:freshOfflineSportsPilot.trade_ready&&freshOfflineSportsPilot.entry_candidate,
+      offlineTimingIsRechecked:!expiredOfflineSportsPilot.trade_ready&&!expiredOfflineSportsPilot.entry_candidate&&expiredOfflineSportsPilot.watch_only,
+      completedLossesDisablePilot:losingSportsPilotProfile.demoted&&!losingSportsPilotProfile.allowed&&losingSportsPilotProfile.position_pct===0,
+      demotedPilotCannotOpen:losingSportsPilotBook.positions.length===0,
+      positiveConfidenceCanPromote:promotedSportsPilotProfile.promoted&&promotedSportsPilotProfile.allowed
+        &&promotedSportsPilotProfile.position_pct===SPORTS_FAVORITE_PROMOTED_POSITION_PCT,
+      promotedPilotScalesWithinCap:promotedSportsPilotBook.positions.length===1
+        &&promotedSportsPilotBook.positions[0].cost>STARTING_BALANCE*SPORTS_FAVORITE_PILOT_POSITION_PCT
+        &&promotedSportsPilotBook.positions[0].cost<=STARTING_BALANCE*SPORTS_FAVORITE_PROMOTED_POSITION_PCT+0.01,
+      ordinaryGapExitDoesNotPreemptPilot:sportsPilotExit===null,
+    },
     riskBudget:{core:coreRiskBudget,aggressiveGap:aggressiveGapBudget,blocksExactRange:intervalContract.jump_risk&&!intervalContract.trade_ready,
       blocksPathDependentBarrier:pathBarrierContract.jump_risk&&!pathBarrierContract.trade_ready,
       explainsPathDependentBarrier:pathBarrierContract.rationale.includes("jump directly to settlement"),preservesFixedDateLevel:!fixedDateLevelContract.jump_risk,

scripts/evaluate-sports-favorites.mjs

@@ -4,6 +4,7 @@ const MARKET_LIMIT = Math.max(500, Math.min(5000, Number(process.env.SPORTS_FAVO
 const CONCURRENCY = Math.max(1, Math.min(12, Number(process.env.SPORTS_FAVORITE_CONCURRENCY || 10)));
 const COST = Math.max(0, Math.min(0.10, Number(process.env.SPORTS_FAVORITE_COST_CENTS || 5) / 100));
 const MAX_STALENESS_HOURS = Math.max(1, Math.min(12, Number(process.env.SPORTS_FAVORITE_MAX_STALENESS_HOURS || 3)));
+const EVENT_LEGS = Math.max(1, Math.min(4, Number(process.env.SPORTS_FAVORITE_EVENT_LEGS || 1)));
 const HOUR = 3600;
 
 function parseJson(value) {
@@ -147,7 +148,7 @@ function tradesFor(partition, rule) {
     const rows = events.get(row.eventKey) || [];
     rows.push(row);events.set(row.eventKey, rows);
   });
-  return [...events.values()].flatMap((rows) => rows.sort((a, b) => b.entry - a.entry || a.marketId.localeCompare(b.marketId)).slice(0, 4));
+  return [...events.values()].flatMap((rows) => rows.sort((a, b) => b.entry - a.entry || a.marketId.localeCompare(b.marketId)).slice(0, EVENT_LEGS));
 }
 
 const evaluated = rules.map((rule) => {
@@ -162,15 +163,19 @@ const selected = evaluated.filter((row) => row.validationPassed).sort((a, b) =>
 const baseline = evaluated.find((row) => row.rule.leadHours === 24 && row.rule.minEntry === 0.55 && row.rule.maxEntry === 0.95);
 const compact = (stats) => Object.fromEntries(Object.entries(stats).map(([key, value]) => [key, Number.isFinite(value) ? +value.toFixed(5) : value]));
 const candidate = (row) => ({ rule: row.rule, train: compact(row.train), validation: compact(row.validation), holdout: compact(row.holdout), passesHoldout: row.passesHoldout });
+const closest = evaluated.filter((row) => row.train.events >= 25 && row.validation.events >= 10 && row.holdout.events >= 10)
+  .sort((a, b) => Math.min(b.train.lower, b.validation.lower, b.holdout.lower)
+    - Math.min(a.train.lower, a.validation.lower, a.holdout.lower));
 
 console.log(JSON.stringify({ generatedAt: new Date().toISOString(), requestedMarkets: MARKET_LIMIT, sportsMarkets: markets.length,
   historiesWithData: usable.length, failures: histories.filter((row) => row?.error).length,
   methodology: { selection: "most recently closed eligible Yes/No sports markets", decisionAnchor: "published game start",
     historyFidelityMinutes: 60, maxPriceStalenessHours: MAX_STALENESS_HOURS, modeledCostCents: COST * 100,
-    split: "60% train / 20% validation / 20% untouched holdout", clusterUnit: "equal-dollar event baskets split across at most four highest-priced eligible favorites", testedRules: rules.length },
+    split: "60% train / 20% validation / 20% untouched holdout", clusterUnit: `one equal-dollar position in each event's highest-priced eligible favorite (event legs ${EVENT_LEGS})`, testedRules: rules.length },
   partitionMarkets: Object.fromEntries(Object.entries(partitions).map(([key, value]) => [key, value.length])),
   trainPassed: evaluated.filter((row) => row.trainPassed).length, validationSelected: selected.length,
   holdoutPassed: selected.filter((row) => row.passesHoldout).length, baseline: baseline ? candidate(baseline) : null,
+  closestCandidates: closest.slice(0, 15).map(candidate),
   candidates: selected.slice(0, 20).map(candidate),
   holdoutExamples: (selected.find((row) => row.passesHoldout)?.holdoutRows || []).slice(0, 12)
     .map((row) => ({ question: row.question, event: row.event, side: row.side, entry: +row.entry.toFixed(4), won: row.won, netReturn: +row.netReturn.toFixed(4) }))

sw.js

@@ -1,4 +1,4 @@
-const CACHE_NAME = "polymarket-arena-build-70";
+const CACHE_NAME = "polymarket-arena-build-71";
 const APP_SHELL = ["/", "/index.html", "/personal.html", "/cycle-worker.js"];
 
 self.addEventListener("install", event => {