add stat

server/public_training_profile.js

@@ -147,6 +147,9 @@ function buildPublicTrainingStats(laps) {
     if (!controlTargetMs || lapTimes[index] > controlTargetMs) break;
     controlledLapStreak += 1;
   }
+  const stints = splitPublicTrainingStints(laps);
+  const bestThreeConsecutive = getPublicBestConsecutiveLaps(stints, 3);
+  const bestFiveMinuteResult = getPublicBestDurationResult(stints, 5 * 60 * 1000);
 
   return {
     totalLaps: laps.length,
@@ -159,9 +162,80 @@ function buildPublicTrainingStats(laps) {
     consistencySpreadPct: recentAverageMs ? ((percentile(0.9) - percentile(0.1)) / recentAverageMs) * 100 : 0,
     controlledLapStreak,
     dailySummaries,
+    stintCount: stints.length,
+    bestThreeConsecutive,
+    bestFiveMinuteResult,
   };
 }
 
+function splitPublicTrainingStints(laps, breakThresholdMs = 2 * 60 * 1000) {
+  const stints = [];
+  (Array.isArray(laps) ? laps : []).forEach((lap) => {
+    const previousStint = stints.at(-1);
+    const previousLap = previousStint?.laps.at(-1);
+    const lapStartedAt = Math.max(0, Number(lap.timestamp || 0) - Number(lap.lapMs || 0));
+    const breakMs = previousLap ? Math.max(0, Number(lap.timestamp || 0) - Number(previousLap.timestamp || 0)) : 0;
+    const startsNewStint = !previousStint
+      || String(previousLap.sessionId || "") !== String(lap.sessionId || "")
+      || breakMs > breakThresholdMs;
+    const normalizedLap = {
+      ...lap,
+      excludedFromPace: Boolean(previousLap && breakMs > breakThresholdMs && Number(lap.lapMs || 0) > breakThresholdMs),
+    };
+    if (startsNewStint) {
+      stints.push({ sessionId: String(lap.sessionId || ""), laps: [normalizedLap] });
+    } else {
+      previousStint.laps.push(normalizedLap);
+    }
+  });
+  return stints;
+}
+
+function getPublicBestConsecutiveLaps(stints, lapCount) {
+  let best = null;
+  (Array.isArray(stints) ? stints : []).forEach((stint) => {
+    const paceLaps = stint.laps.filter((lap) => !lap.excludedFromPace);
+    for (let index = 0; index <= paceLaps.length - lapCount; index += 1) {
+      const laps = paceLaps.slice(index, index + lapCount);
+      const totalMs = laps.reduce((sum, lap) => sum + Number(lap.lapMs || 0), 0);
+      const candidate = { lapCount, totalMs, averageLapMs: Math.round(totalMs / lapCount) };
+      if (!best || candidate.totalMs < best.totalMs) best = candidate;
+    }
+  });
+  return best;
+}
+
+function getPublicBestDurationResult(stints, targetMs) {
+  let best = null;
+  (Array.isArray(stints) ? stints : []).forEach((stint) => {
+    const paceLaps = stint.laps.filter((lap) => !lap.excludedFromPace);
+    for (let startIndex = 0; startIndex < paceLaps.length; startIndex += 1) {
+      const firstLap = paceLaps[startIndex];
+      const startedAt = Math.max(0, Number(firstLap.timestamp || 0) - Number(firstLap.lapMs || 0));
+      const cutoffAt = startedAt + targetMs;
+      const counted = [];
+      for (let index = startIndex; index < paceLaps.length; index += 1) {
+        const lap = paceLaps[index];
+        const lapStartedAt = Math.max(0, Number(lap.timestamp || 0) - Number(lap.lapMs || 0));
+        if (lapStartedAt >= cutoffAt) break;
+        counted.push(lap);
+      }
+      const lastLap = counted.at(-1);
+      if (!lastLap || Number(lastLap.timestamp || 0) < cutoffAt) continue;
+      const totalMs = Number(lastLap.timestamp || 0) - startedAt;
+      const lapCount = counted.length;
+      const candidate = {
+        targetMs,
+        lapCount,
+        totalMs,
+        averageLapMs: Math.round(counted.reduce((sum, lap) => sum + Number(lap.lapMs || 0), 0) / lapCount),
+      };
+      if (!best || candidate.lapCount > best.lapCount || (candidate.lapCount === best.lapCount && candidate.totalMs < best.totalMs)) best = candidate;
+    }
+  });
+  return best;
+}
+
 function normalizePublicLogoDataUrl(value) {
   const logo = String(value || "").trim();
   return logo.length <= 2_000_000 && /^data:image\/(?:png|jpeg|webp);base64,/i.test(logo) ? logo : "";
@@ -192,4 +266,7 @@ module.exports = {
   hasPublicTrainingShare,
   normalizePublicTrainingSince,
   normalizePublicTrainingWindow,
+  splitPublicTrainingStints,
+  getPublicBestConsecutiveLaps,
+  getPublicBestDurationResult,
 };