fix tränings länken och race day

server/public_training_profile.js

@@ -173,12 +173,23 @@ function buildPublicTrainingGoal(goal, currentLaps) {
 function buildPublicTrainingStats(laps) {
   const lapTimes = laps.map((lap) => lap.lapMs);
   const recent = lapTimes.slice(-30);
+  const previous = lapTimes.slice(Math.max(0, lapTimes.length - 60), Math.max(0, lapTimes.length - 30));
   const average = (values) => values.length ? Math.round(values.reduce((sum, value) => sum + value, 0) / values.length) : 0;
-  const sortedRecent = [...recent].sort((left, right) => left - right);
-  const percentile = (ratio) => sortedRecent.length
-    ? sortedRecent[Math.min(sortedRecent.length - 1, Math.max(0, Math.round((sortedRecent.length - 1) * ratio)))]
-    : 0;
+  const percentile = (values, ratio) => {
+    const sorted = [...values].sort((left, right) => left - right);
+    return sorted.length
+      ? sorted[Math.min(sorted.length - 1, Math.max(0, Math.round((sorted.length - 1) * ratio)))]
+      : 0;
+  };
+  const spread = (values) => {
+    const mean = average(values);
+    return mean ? ((percentile(values, 0.9) - percentile(values, 0.1)) / mean) * 100 : 0;
+  };
   const recentAverageMs = average(recent);
+  const previousRecentAverageMs = average(previous);
+  const consistencySpreadPct = spread(recent);
+  const previousConsistencySpreadPct = spread(previous);
+  const trendSampleReady = recent.length >= 10 && previous.length >= 10;
   const daily = new Map();
   laps.forEach((lap) => {
     const date = new Date(lap.timestamp);
@@ -211,21 +222,46 @@ function buildPublicTrainingStats(laps) {
   const bestThreeConsecutive = getPublicBestConsecutiveLaps(stints, 3);
   const bestFiveMinuteResult = getPublicBestDurationResult(stints, 5 * 60 * 1000);
 
-  return {
+  const stats = {
     totalLaps: laps.length,
     totalSessions: new Set(laps.map((lap) => lap.sessionId).filter(Boolean)).size,
     trainingDays: daily.size,
     bestLapMs,
     averageLapMs: average(lapTimes),
     recentAverageMs,
+    previousRecentAverageMs,
+    averageTrendMs: trendSampleReady ? previousRecentAverageMs - recentAverageMs : 0,
     recentLapCount: recent.length,
-    consistencySpreadPct: recentAverageMs ? ((percentile(0.9) - percentile(0.1)) / recentAverageMs) * 100 : 0,
+    consistencySpreadPct,
+    previousConsistencySpreadPct,
+    consistencyTrendPct: trendSampleReady ? previousConsistencySpreadPct - consistencySpreadPct : 0,
+    trendSampleReady,
     controlledLapStreak,
     dailySummaries,
     stintCount: stints.length,
     bestThreeConsecutive,
     bestFiveMinuteResult,
   };
+  return { ...stats, achievements: buildPublicTrainingAchievements(stats) };
+}
+
+function buildPublicTrainingAchievements(stats) {
+  const definitions = [
+    ["first_session", Number(stats.totalSessions || 0), 1],
+    ["laps_100", Number(stats.totalLaps || 0), 100],
+    ["laps_500", Number(stats.totalLaps || 0), 500],
+    ["laps_1000", Number(stats.totalLaps || 0), 1000],
+    ["laps_1500", Number(stats.totalLaps || 0), 1500],
+    ["days_3", Number(stats.trainingDays || 0), 3],
+    ["days_10", Number(stats.trainingDays || 0), 10],
+    ["controlled_5", Number(stats.controlledLapStreak || 0), 5],
+    ["five_minute", stats.bestFiveMinuteResult ? 1 : 0, 1],
+  ];
+  return definitions.map(([id, current, target]) => ({
+    id,
+    percent: Math.min(100, Math.max(0, (current / target) * 100)),
+    unlocked: current >= target,
+  }));
 }
 
 function splitPublicTrainingStints(laps, breakThresholdMs = 2 * 60 * 1000) {