${renderGuidePanel("guide.dashboard_title", ["guide.dashboard_1", "guide.dashboard_2", "guide.dashboard_3", "guide.dashboard_4"], "", { t })}
- ${renderGuidePanel("guide.training_title", ["guide.training_1", "guide.training_2", "guide.training_3", "guide.training_4", "guide.training_5", "guide.training_6", "guide.training_7", "guide.training_8", "guide.training_9", "guide.training_10", "guide.training_11", "guide.training_12", "guide.training_13", "guide.training_14", "guide.training_15", "guide.training_16", "guide.training_17", "guide.training_18", "guide.training_19", "guide.training_20", "guide.training_21", "guide.training_22", "guide.training_23"], "", { t })}
+ ${renderGuidePanel("guide.training_title", ["guide.training_1", "guide.training_2", "guide.training_3", "guide.training_4", "guide.training_5", "guide.training_6", "guide.training_7", "guide.training_8", "guide.training_9", "guide.training_10", "guide.training_11", "guide.training_12", "guide.training_13", "guide.training_14", "guide.training_15", "guide.training_16", "guide.training_17", "guide.training_18", "guide.training_19", "guide.training_20", "guide.training_21", "guide.training_22", "guide.training_23", "guide.training_24", "guide.training_25"], "", { t })}
diff --git a/src/public_training.js b/src/public_training.js
index bd89af9..e22325f 100644
--- a/src/public_training.js
+++ b/src/public_training.js
@@ -64,6 +64,10 @@ const messages = {
fiveAverage: "Avg pace, bästa 5 min",
splitPassings: "Mellantidspasseringar",
bestSplit: "Bästa mellantid",
+ latestSectorGain: "Senaste sektorförbättring",
+ controlZone: "Kontrollzon",
+ outlierLaps: "Avvikande varv",
+ strongFinishes: "Starka avslutningar",
pitStops: "Depåstopp",
totalPit: "Total depåtid",
recentProgress: "Din senaste utveckling",
@@ -89,6 +93,8 @@ const messages = {
achievement_five_minute: "Fullföljd femminutersstint",
achievement_five_minutes_3: "3 fullföljda femminutersstintar",
achievement_consistency_5: "Jämnhet under 5 procent",
+ achievement_strong_finish: "Stark avslutning",
+ achievement_clean_five_minute: "Fem minuter utan avvikande varv",
achievement_pace_gain: "Förbättrat snittempo",
creditTitle: "Din träning räknas",
creditBody: "Varje genomfört varv bygger erfarenhet. Du jämförs med din egen utveckling, inte med andra förare.",
@@ -97,6 +103,9 @@ const messages = {
consistencyCredit: "{value} procentenheter jämnare körning",
controlledCredit: "{laps} kontrollerade varv i rad",
fiveMinuteCredit: "Du har fullföljt en femminutersstint",
+ sectorCredit: "Sektortiden förbättrad med {lap}",
+ strongFinishCredit: "Stark avslutning med bibehållet tempo",
+ cleanFiveCredit: "Fem minuter utan avvikande varv",
buildingCredit: "{laps} varv har redan byggt din erfarenhet",
readyCredit: "Första giltiga varvet startar din utvecklingsresa",
challenges: "Små utmaningar",
@@ -161,6 +170,10 @@ const messages = {
fiveAverage: "Average pace, best 5 min",
splitPassings: "Split passings",
bestSplit: "Best split",
+ latestSectorGain: "Latest sector improvement",
+ controlZone: "Control zone",
+ outlierLaps: "Outlier laps",
+ strongFinishes: "Strong finishes",
pitStops: "Pit stops",
totalPit: "Total pit time",
recentProgress: "Your recent development",
@@ -186,6 +199,8 @@ const messages = {
achievement_five_minute: "Completed five-minute stint",
achievement_five_minutes_3: "3 completed five-minute stints",
achievement_consistency_5: "Consistency below 5 percent",
+ achievement_strong_finish: "Strong finish",
+ achievement_clean_five_minute: "Five minutes without outlier laps",
achievement_pace_gain: "Improved average pace",
creditTitle: "Your practice counts",
creditBody: "Every completed lap builds experience. You are compared with your own development, not other drivers.",
@@ -194,6 +209,9 @@ const messages = {
consistencyCredit: "{value} percentage points more consistent",
controlledCredit: "{laps} controlled laps in a row",
fiveMinuteCredit: "You completed a five-minute stint",
+ sectorCredit: "Sector time improved by {lap}",
+ strongFinishCredit: "Strong finish with pace maintained",
+ cleanFiveCredit: "Five minutes without outlier laps",
buildingCredit: "{laps} laps have already built your experience",
readyCredit: "Your first valid lap starts the development journey",
challenges: "Small challenges",
@@ -260,13 +278,13 @@ function getLocalDayKey(timestamp) {
return `${date.getFullYear()}-${String(date.getMonth() + 1).padStart(2, "0")}-${String(date.getDate()).padStart(2, "0")}`;
}
-function buildProfileMotivation(stats) {
+function buildProfileMotivation(stats, channelStats = {}) {
const todayKey = getLocalDayKey(Date.now());
const today = (Array.isArray(stats?.dailySummaries) ? stats.dailySummaries : []).find((day) => day.dateKey === todayKey);
const activeToday = Boolean(today);
const todayLaps = Number(today?.laps || 0);
- const controlled = activeToday ? Number(stats?.controlledLapStreak || 0) : 0;
- const completedFive = stats?.bestFiveMinuteResult ? 1 : 0;
+ const controlled = activeToday ? Number(stats?.todayControlledLapStreak || 0) : 0;
+ const completedFive = activeToday ? Number(stats?.todayCompletedFiveMinuteStints || 0) : 0;
const challenges = [
{ id: "Laps", current: todayLaps, target: 20 },
{ id: "Controlled", current: controlled, target: 5 },
@@ -282,6 +300,9 @@ function buildProfileMotivation(stats) {
if (stats?.trendSampleReady && Number(stats.consistencyTrendPct || 0) > 0.1) credits.push(t("consistencyCredit", { value: Number(stats.consistencyTrendPct).toFixed(1) }));
if (controlled >= 5) credits.push(t("controlledCredit", { laps: controlled }));
if (completedFive) credits.push(t("fiveMinuteCredit"));
+ if (Number(channelStats.latestSplitGainMs || 0) > 0) credits.push(t("sectorCredit", { lap: formatLap(channelStats.latestSplitGainMs) }));
+ if (Number(stats?.todayStrongFinishStints || 0) > 0) credits.push(t("strongFinishCredit"));
+ if (Number(stats?.todayCleanFiveMinuteStints || 0) > 0) credits.push(t("cleanFiveCredit"));
if (!credits.length && Number(stats?.totalLaps || 0) > 0) credits.push(t("buildingCredit", { laps: stats.totalLaps }));
if (!credits.length) credits.push(t("readyCredit"));
return { challenges, credits: credits.slice(0, 3) };
@@ -299,7 +320,7 @@ function renderProfile(data) {
const recommendation = activeClass?.recommendation || data.recommendation;
const goals = activeClass?.goals || data.goals || [];
const currentSession = activeClass?.currentSession || data.currentSession;
- const motivation = buildProfileMotivation(stats);
+ const motivation = buildProfileMotivation(stats, channelStats);
const recommendationText = recommendationCopy(recommendation);
const timerState = readTimerState();
const timerConfig = getTimerConfig(timerState);
@@ -462,11 +483,15 @@ function renderProfile(data) {
${escapeHtml(t("performance"))}
diff --git a/src/race_audio.js b/src/race_audio.js
index 23a0c96..7d2afad 100644
--- a/src/race_audio.js
+++ b/src/race_audio.js
@@ -13,6 +13,7 @@ export const RACE_AUDIO_EVENT_DEFINITIONS = Object.freeze([
event("personal_best", "race", "low", true, "effects/personal_best.wav", 1500),
event("fastest_lap", "race", "normal", true, "effects/fastest_lap_trophy.wav", 1500),
event("track_record", "race", "normal", true, "effects/track_record_fanfare.wav", 2000),
+ event("training_stable_pace", "training", "low", true, "", 120000),
event("new_leader", "race", "normal", true, "", 1000),
event("position_gain", "race", "low", false, "effects/position_gain.wav", 750),
event("position_loss", "race", "low", false, "effects/position_loss.wav", 750),
diff --git a/src/training_logic.js b/src/training_logic.js
index 528cfb6..b9b6285 100644
--- a/src/training_logic.js
+++ b/src/training_logic.js
@@ -288,17 +288,47 @@ function getBestConsecutiveAverage(laps, count) {
return best;
}
+function getLongestControlledLapStreak(stints, controlTargetMs) {
+ let longest = 0;
+ (Array.isArray(stints) ? stints : []).forEach((stint) => {
+ let current = 0;
+ (Array.isArray(stint?.laps) ? stint.laps : []).forEach((lap) => {
+ if (lap.excludedFromPace || !controlTargetMs || Number(lap.lapMs || 0) > controlTargetMs) {
+ current = 0;
+ return;
+ }
+ current += 1;
+ longest = Math.max(longest, current);
+ });
+ });
+ return longest;
+}
+
+function getTrainingStintMetrics(stint) {
+ const laps = (Array.isArray(stint?.laps) ? stint.laps : []).filter((lap) => !lap.excludedFromPace);
+ const values = laps.map((lap) => Number(lap.lapMs || 0)).filter((lapMs) => lapMs > 500);
+ const medianMs = percentile(values, 0.5);
+ const outlierThresholdMs = medianMs ? medianMs * 1.15 : 0;
+ const outlierLaps = values.filter((lapMs) => outlierThresholdMs && lapMs > outlierThresholdMs).length;
+ const comparisonSize = values.length >= 6 ? Math.max(3, Math.floor(values.length / 3)) : 0;
+ const startPaceMs = comparisonSize ? trimmedAverage(values.slice(0, comparisonSize)) : 0;
+ const endPaceMs = comparisonSize ? trimmedAverage(values.slice(-comparisonSize)) : 0;
+ return {
+ laps,
+ values,
+ outlierLaps,
+ comparisonSize,
+ startPaceMs,
+ endPaceMs,
+ endChangeMs: startPaceMs && endPaceMs ? startPaceMs - endPaceMs : null,
+ strongFinish: Boolean(comparisonSize && endPaceMs <= startPaceMs * 1.01),
+ };
+}
+
export function buildTrainingStintAnalysis(state, driverId, classId = "") {
const stints = splitTrainingStints(getDriverTrainingLaps(state, driverId, classId));
const rows = stints.map((stint, index) => {
- const laps = stint.laps.filter((lap) => !lap.excludedFromPace);
- const values = laps.map((lap) => lap.lapMs);
- const medianMs = percentile(values, 0.5);
- const mistakeThresholdMs = medianMs ? medianMs * 1.15 : 0;
- const mistakes = values.filter((lapMs) => mistakeThresholdMs && lapMs > mistakeThresholdMs).length;
- const comparisonSize = values.length >= 6 ? Math.max(3, Math.floor(values.length / 3)) : 0;
- const startPaceMs = comparisonSize ? trimmedAverage(values.slice(0, comparisonSize)) : 0;
- const endPaceMs = comparisonSize ? trimmedAverage(values.slice(-comparisonSize)) : 0;
+ const { laps, values, outlierLaps, startPaceMs, endPaceMs, endChangeMs, strongFinish } = getTrainingStintMetrics(stint);
return {
id: `${stint.sessionId}:${stint.startedAt}:${index}`,
number: index + 1,
@@ -311,12 +341,13 @@ export function buildTrainingStintAnalysis(state, driverId, classId = "") {
paceMs: trimmedAverage(values),
racePace10Ms: values.length >= 10 ? getBestConsecutiveAverage(laps, 10) : 0,
fiveMinuteResult: getBestTrainingDurationResult([stint], 5 * 60 * 1000),
- mistakes,
- mistakePct: values.length ? (mistakes / values.length) * 100 : 0,
+ mistakes: outlierLaps,
+ mistakePct: values.length ? (outlierLaps / values.length) * 100 : 0,
consistencyPct: values.length >= 3 ? consistencySpread(values) : null,
startPaceMs,
endPaceMs,
- endChangeMs: startPaceMs && endPaceMs ? startPaceMs - endPaceMs : null,
+ endChangeMs,
+ strongFinish,
insufficient: values.length < 3,
};
});
@@ -344,6 +375,8 @@ export function buildTrainingAchievements(stats) {
["five_minute", source.bestFiveMinuteResult ? 1 : 0, 1],
["five_minutes_3", Number(source.completedFiveMinuteStints || 0), 3],
["consistency_5", source.recentLapCount >= 30 && source.consistencySpreadPct <= 5 ? 1 : 0, 1],
+ ["strong_finish", Number(source.strongFinishStints || 0), 1],
+ ["clean_five_minute", Number(source.cleanFiveMinuteStints || 0), 1],
["pace_gain", source.trendSampleReady && source.averageTrendMs > 0 ? 1 : 0, 1],
];
return definitions.map(([id, current, target]) => ({
@@ -380,7 +413,7 @@ function buildDailySummaries(laps) {
.sort((left, right) => right.latestTimestamp - left.latestTimestamp);
}
-function getControlledLapStreak(lapTimes, controlTargetMs) {
+export function getControlledLapStreak(lapTimes, controlTargetMs) {
let streak = 0;
for (let index = lapTimes.length - 1; index >= 0; index -= 1) {
if (!controlTargetMs || lapTimes[index] > controlTargetMs) break;
@@ -530,16 +563,22 @@ export function buildDriverTrainingStats(state, driverId, classId = "") {
const previousBestMs = earlierLapTimes.length ? Math.min(...earlierLapTimes) : 0;
const recentBestMs = recentLapTimes.length ? Math.min(...recentLapTimes) : 0;
const personalBestGainMs = previousBestMs && recentBestMs ? Math.max(0, previousBestMs - recentBestMs) : 0;
+ const controlZoneMinMs = bestLapMs;
const controlTargetMs = bestLapMs ? Math.round(bestLapMs * 1.08) : 0;
- const controlledLapStreak = getControlledLapStreak(lapTimes, controlTargetMs);
const dailySummaries = buildDailySummaries(paceLaps);
const stints = splitTrainingStints(laps);
+ const stintMetrics = stints.map((stint) => ({ stint, ...getTrainingStintMetrics(stint) }));
+ const controlledLapStreak = getLongestControlledLapStreak(stints, controlTargetMs);
const completedFiveMinuteStints = stints.filter((stint) => getBestTrainingDurationResult([stint], 5 * 60 * 1000)).length;
+ const cleanFiveMinuteStints = stintMetrics.filter(({ stint, outlierLaps }) => !outlierLaps && getBestTrainingDurationResult([stint], 5 * 60 * 1000)).length;
+ const strongFinishStints = stintMetrics.filter((metrics) => metrics.strongFinish).length;
+ const outlierLaps = stintMetrics.reduce((sum, metrics) => sum + metrics.outlierLaps, 0);
const bestThreeConsecutive = getBestConsecutiveTrainingLaps(stints, 3);
const bestFiveMinuteResult = getBestTrainingDurationResult(stints, 5 * 60 * 1000);
const todayKey = getLocalDayKey(Date.now());
const todayLaps = laps.filter((lap) => getLocalDayKey(lap.timestamp) === todayKey);
const todayStints = splitTrainingStints(todayLaps);
+ const todayStintMetrics = todayStints.map((stint) => ({ stint, ...getTrainingStintMetrics(stint) }));
const todayLapTimes = todayLaps.filter((lap) => !lap.excludedFromPace).map((lap) => lap.lapMs);
const stats = {
@@ -554,12 +593,20 @@ export function buildDriverTrainingStats(state, driverId, classId = "") {
recentBestMs,
previousBestMs,
personalBestGainMs,
+ controlZoneMinMs,
+ controlZoneMaxMs: controlTargetMs,
controlledLapStreak,
+ outlierLaps,
+ strongFinishStints,
+ cleanFiveMinuteStints,
todayLaps: todayLaps.length,
todayBestLapMs: todayLapTimes.length ? Math.min(...todayLapTimes) : 0,
todayAverageLapMs: average(todayLapTimes),
- todayControlledLapStreak: getControlledLapStreak(todayLapTimes, controlTargetMs),
+ todayControlledLapStreak: getLongestControlledLapStreak(todayStints, controlTargetMs),
+ todayOutlierLaps: todayStintMetrics.reduce((sum, metrics) => sum + metrics.outlierLaps, 0),
+ todayStrongFinishStints: todayStintMetrics.filter((metrics) => metrics.strongFinish).length,
todayCompletedFiveMinuteStints: todayStints.filter((stint) => getBestTrainingDurationResult([stint], 5 * 60 * 1000)).length,
+ todayCleanFiveMinuteStints: todayStintMetrics.filter(({ stint, outlierLaps: count }) => !count && getBestTrainingDurationResult([stint], 5 * 60 * 1000)).length,
consistencySpreadPct,
previousConsistencySpreadPct,
consistencyTrendPct: trendSampleReady ? previousConsistencySpreadPct - consistencySpreadPct : 0,
@@ -611,12 +658,24 @@ export function buildDriverTimingChannelStats(state, driverId, classId = "") {
pitStops.sort((left, right) => Number(left.enteredAt || 0) - Number(right.enteredAt || 0));
const splitTimes = splits.map((split) => split.splitMs);
const pitTimes = pitStops.map((stop) => stop.pitStopMs);
+ let runningBestSplitMs = 0;
+ let latestSplitGainMs = 0;
+ let latestSplitGainAt = 0;
+ splits.forEach((split) => {
+ if (runningBestSplitMs && split.splitMs < runningBestSplitMs) {
+ latestSplitGainMs = runningBestSplitMs - split.splitMs;
+ latestSplitGainAt = Number(split.timestamp || 0);
+ }
+ if (!runningBestSplitMs || split.splitMs < runningBestSplitMs) runningBestSplitMs = split.splitMs;
+ });
return {
splitCount: splits.length,
splitSessions: new Set(splits.map((split) => split.sessionId)).size,
bestSplitMs: splitTimes.length ? Math.min(...splitTimes) : 0,
averageSplitMs: splitTimes.length ? Math.round(splitTimes.reduce((sum, value) => sum + value, 0) / splitTimes.length) : 0,
lastSplitMs: splitTimes.at(-1) || 0,
+ latestSplitGainMs,
+ latestSplitGainAt,
pitStopCount: pitStops.length,
pitSessions: new Set(pitStops.map((stop) => stop.sessionId)).size,
totalPitMs: pitTimes.reduce((sum, value) => sum + value, 0),
@@ -644,12 +703,18 @@ export function buildDriverActivePracticeStats(state, driverId, nowTs = Date.now
&& (!startedAt || Number(passing?.timestamp || 0) >= startedAt)
))
.map((passing) => ({
+ sessionId: String(session.id || ""),
+ sourceId: String(passing.competitorKey || passing.carId || passing.transponder || passing.driverId || "default"),
timestamp: Math.max(0, Number(passing.timestamp || 0) || 0),
lapMs: Math.round(Number(passing.lapMs || 0) || 0),
excludedFromPace: Boolean(passing.excludedFromPace || passing.validationWarning === "above_max_stint"),
+ stintBoundary: Boolean(passing.stintBoundary || passing.validationWarning === "above_max_stint"),
}))
.sort((left, right) => left.timestamp - right.timestamp);
const paceLapTimes = laps.filter((lap) => !lap.excludedFromPace).map((lap) => lap.lapMs);
+ const bestLapMs = paceLapTimes.length ? Math.min(...paceLapTimes) : 0;
+ const controlZoneMaxMs = bestLapMs ? Math.round(bestLapMs * 1.08) : 0;
+ const activeStints = splitTrainingStints(laps);
return {
sessionId: String(session.id || ""),
@@ -657,9 +722,12 @@ export function buildDriverActivePracticeStats(state, driverId, nowTs = Date.now
startedAt,
elapsedMs: startedAt ? Math.max(0, Number(nowTs || 0) - startedAt) : 0,
laps: laps.length,
- bestLapMs: paceLapTimes.length ? Math.min(...paceLapTimes) : 0,
+ bestLapMs,
averageLapMs: average(paceLapTimes),
lastLapMs: laps.at(-1)?.lapMs || 0,
+ controlZoneMinMs: bestLapMs,
+ controlZoneMaxMs,
+ controlledLapStreak: getLongestControlledLapStreak(activeStints, controlZoneMaxMs),
};
}
@@ -730,6 +798,9 @@ export function buildTrainingHighlights(stats) {
const highlights = [];
if (source.todayLaps > 0) highlights.push({ id: "today_laps", value: Number(source.todayLaps) });
if (source.personalBestGainMs > 0) highlights.push({ id: "personal_best", value: Number(source.personalBestGainMs) });
+ if (source.latestSplitGainMs > 0) highlights.push({ id: "sector_gain", value: Number(source.latestSplitGainMs) });
+ if (source.todayStrongFinishStints > 0) highlights.push({ id: "strong_finish", value: Number(source.todayStrongFinishStints) });
+ if (source.todayCleanFiveMinuteStints > 0) highlights.push({ id: "clean_five_minute", value: Number(source.todayCleanFiveMinuteStints) });
if (source.trendSampleReady && source.averageTrendMs > 0) highlights.push({ id: "pace_gain", value: Number(source.averageTrendMs) });
if (source.trendSampleReady && source.consistencyTrendPct > 0.1) highlights.push({ id: "consistency_gain", value: Number(source.consistencyTrendPct) });
if (source.todayControlledLapStreak >= 5) highlights.push({ id: "controlled_streak", value: Number(source.todayControlledLapStreak) });
diff --git a/src/training_views.js b/src/training_views.js
index 146b38d..ab62bc3 100644
--- a/src/training_views.js
+++ b/src/training_views.js
@@ -1,13 +1,16 @@
import { getDriverProfileGroups, getDriverProfileReferences } from "./driver_profile_logic.js";
function renderStintRow(row, { t, escapeHtml, formatLap, formatRaceClock }) {
- const endChange = row.endChangeMs == null
+ const paceRetention = row.endChangeMs == null
? "-"
: row.endChangeMs > 0
? t("training.stint_faster", { lap: formatLap(row.endChangeMs) })
: row.endChangeMs < 0
? t("training.stint_slower", { lap: formatLap(Math.abs(row.endChangeMs)) })
: t("training.stint_same");
+ const endChange = row.strongFinish
+ ? `${paceRetention} · ${t("training.strong_finish")}`
+ : paceRetention;
return `
| ${row.number} |
@@ -101,7 +104,7 @@ export function renderTrainingView(deps) {
const recommendation = buildTrainingRecommendation(stats);
const nextMilestone = getNextTrainingMilestone(stats);
const missions = buildTrainingMissions(stats);
- const highlights = buildTrainingHighlights(stats);
+ const highlights = buildTrainingHighlights({ ...stats, latestSplitGainMs: channelStats.latestSplitGainMs });
const paceBuckets = buildTrainingPaceBuckets(state, selectedProfileId, selectedClassId, 30).slice(-24);
const weekdayStats = buildTrainingWeekdayStats(state, selectedProfileId, selectedClassId);
const stintAnalysis = buildTrainingStintAnalysis(state, selectedProfileId, selectedClassId);
@@ -326,6 +329,8 @@ export function renderTrainingView(deps) {
${trainingInsight(t("training.best_lap"), formatLap(activePractice.bestLapMs))}
${trainingInsight(t("training.average_lap"), formatLap(activePractice.averageLapMs))}
${trainingInsight(t("training.latest_lap"), formatLap(activePractice.lastLapMs))}
+ ${trainingInsight(t("training.control_zone"), activePractice.controlZoneMaxMs ? `${formatLap(activePractice.controlZoneMinMs)} - ${formatLap(activePractice.controlZoneMaxMs)}` : "-")}
+ ${trainingInsight(t("training.controlled_streak"), t("training.lap_count", { laps: activePractice.controlledLapStreak }))}
${escapeHtml(t("training.live_practice_hint"))}
@@ -510,7 +515,10 @@ export function renderTrainingView(deps) {
${trainingInsight(t("training.average_lap"), formatLap(stats.averageLapMs))}
${trainingInsight(t("training.recent_average"), formatLap(stats.recentAverageMs))}
+ ${trainingInsight(t("training.control_zone"), stats.controlZoneMaxMs ? `${formatLap(stats.controlZoneMinMs)} - ${formatLap(stats.controlZoneMaxMs)}` : "-")}
${trainingInsight(t("training.controlled_streak"), t("training.lap_count", { laps: stats.controlledLapStreak }))}
+ ${trainingInsight(t("training.outlier_laps"), String(stats.outlierLaps))}
+ ${trainingInsight(t("training.strong_finishes"), String(stats.strongFinishStints))}
${trainingInsight(t("training.last_activity"), lastActivity)}
${trainingInsight(t("training.stints"), String(stats.stintCount))}
${trainingInsight(t("training.best_three"), stats.bestThreeConsecutive ? `3/${formatRaceClock(stats.bestThreeConsecutive.totalMs)}` : "-")}
@@ -518,6 +526,7 @@ export function renderTrainingView(deps) {
${trainingInsight(t("training.five_avg_pace"), stats.bestFiveMinuteResult ? formatLap(stats.bestFiveMinuteResult.averageLapMs) : "-")}
${trainingInsight(t("training.split_passings"), String(channelStats.splitCount))}
${trainingInsight(t("training.best_split"), channelStats.splitCount ? formatLap(channelStats.bestSplitMs) : "-")}
+ ${trainingInsight(t("training.latest_sector_gain"), channelStats.latestSplitGainMs ? formatLap(channelStats.latestSplitGainMs) : "-")}
${trainingInsight(t("training.average_split"), channelStats.splitCount ? formatLap(channelStats.averageSplitMs) : "-")}
${trainingInsight(t("training.pit_stops"), String(channelStats.pitStopCount))}
${trainingInsight(t("training.total_pit_time"), channelStats.pitStopCount ? formatRaceClock(channelStats.totalPitMs) : "-")}
@@ -907,6 +916,9 @@ function trainingInsight(label, value) {
function formatTrainingHighlight(highlight, { t, formatLap }) {
if (highlight.id === "personal_best") return t("training.highlight_personal_best", { lap: formatLap(highlight.value) });
+ if (highlight.id === "sector_gain") return t("training.highlight_sector_gain", { lap: formatLap(highlight.value) });
+ if (highlight.id === "strong_finish") return t("training.highlight_strong_finish", { count: highlight.value });
+ if (highlight.id === "clean_five_minute") return t("training.highlight_clean_five_minute", { count: highlight.value });
if (highlight.id === "pace_gain") return t("training.highlight_pace_gain", { lap: formatLap(highlight.value) });
if (highlight.id === "consistency_gain") return t("training.highlight_consistency_gain", { value: Number(highlight.value).toFixed(1) });
if (highlight.id === "controlled_streak") return t("training.highlight_controlled_streak", { laps: highlight.value });
diff --git a/tests/decoder_runtime.test.js b/tests/decoder_runtime.test.js
index 33e12e5..ab7a262 100644
--- a/tests/decoder_runtime.test.js
+++ b/tests/decoder_runtime.test.js
@@ -60,6 +60,18 @@ function createHarness(options = {}) {
return { state, session, passing, overlayEvents, audioEvents, getSaveCount: () => saveCount };
}
+test("five controlled practice laps trigger one stable-pace voice cue", () => {
+ const harness = createHarness({ sessionType: "open_practice" });
+ for (let lap = 1; lap <= 5; lap += 1) harness.passing(1_000 + lap * 20_000, "main");
+ assert.equal(harness.audioEvents.filter((event) => event === "training_stable_pace").length, 1);
+});
+
+test("stable-pace training cue is never emitted during a race", () => {
+ const harness = createHarness({ sessionType: "team_race" });
+ for (let lap = 1; lap <= 5; lap += 1) harness.passing(1_000 + lap * 20_000, "main");
+ assert.equal(harness.audioEvents.includes("training_stable_pace"), false);
+});
+
test("split decoder records intermediate time without changing main lap state", () => {
const harness = createHarness();
assert.equal(harness.passing(17_000, "main"), true);
diff --git a/tests/public_training_profile.test.js b/tests/public_training_profile.test.js
index 6543d09..1318cae 100644
--- a/tests/public_training_profile.test.js
+++ b/tests/public_training_profile.test.js
@@ -105,6 +105,7 @@ test("public profile contains only the selected driver's sanitized aggregates",
splitCount: 2,
bestSplitMs: 7000,
averageSplitMs: 7100,
+ latestSplitGainMs: 200,
pitStopCount: 1,
totalPitMs: 12500,
bestPitStopMs: 12500,
diff --git a/tests/race_audio.test.js b/tests/race_audio.test.js
index 1dc17ef..96840e7 100644
--- a/tests/race_audio.test.js
+++ b/tests/race_audio.test.js
@@ -88,7 +88,7 @@ test("event catalog covers every supported race-audio event", () => {
const keys = new Set(RACE_AUDIO_EVENT_DEFINITIONS.map((item) => item.key));
[
"grid_open", "grid_closed", "race_1_minute", "race_30_seconds", "race_10_seconds", "drivers_ready", "start_sequence", "start_tone", "false_start", "restart_race",
- "transponder_pass", "lap_completed", "personal_best", "fastest_lap", "track_record", "new_leader", "position_gain", "position_loss", "final_lap", "one_minute_remaining", "thirty_seconds_remaining", "ten_seconds_remaining", "time_expired", "race_finished",
+ "transponder_pass", "lap_completed", "personal_best", "fastest_lap", "track_record", "training_stable_pace", "new_leader", "position_gain", "position_loss", "final_lap", "one_minute_remaining", "thirty_seconds_remaining", "ten_seconds_remaining", "time_expired", "race_finished",
"track_call", "track_clear", "yellow_flag", "red_flag", "race_paused", "race_resumed", "marshal_warning", "marshal_required", "penalty", "stop_and_go", "drive_through", "disqualified",
"pit_lane_open", "pit_lane_closed", "entering_pits", "leaving_pits", "pit_speed_warning",
"qualifying_start", "qualifying_remaining", "qualifying_finished", "provisional_pole", "pole_position",
diff --git a/tests/training_logic.test.js b/tests/training_logic.test.js
index d9e7d4c..b936fe3 100644
--- a/tests/training_logic.test.js
+++ b/tests/training_logic.test.js
@@ -134,7 +134,8 @@ test("driver statistics remain isolated and aggregate days and sessions", () =>
assert.equal(stats.trainingDays, 2);
assert.equal(stats.bestLapMs, 16500);
assert.equal(stats.averageLapMs, 17167);
- assert.equal(stats.controlledLapStreak, 2);
+ // A flow streak never carries over into another session or stint.
+ assert.equal(stats.controlledLapStreak, 1);
assert.equal(stats.dailySummaries[0].laps, 1);
assert.equal(stats.dailySummaries[1].laps, 2);
});
@@ -193,6 +194,7 @@ test("split and pit statistics aggregate by personal profile and selected class"
assert.equal(stats.splitCount, 2);
assert.equal(stats.bestSplitMs, 7900);
assert.equal(stats.averageSplitMs, 8000);
+ assert.equal(stats.latestSplitGainMs, 200);
assert.equal(stats.pitStopCount, 2);
assert.equal(stats.totalPitMs, 22000);
assert.equal(stats.bestPitStopMs, 9500);
@@ -292,6 +294,9 @@ test("active practice stats include only the selected driver's current valid lap
bestLapMs: 16_000,
averageLapMs: 16_500,
lastLapMs: 17_000,
+ controlZoneMinMs: 16_000,
+ controlZoneMaxMs: 17_280,
+ controlledLapStreak: 2,
});
});
@@ -391,6 +396,31 @@ test("a stint shorter than the target duration has no five-minute result", () =>
assert.equal(getBestTrainingDurationResult(stints, 300_000), null);
});
+test("training progress recognizes a clean five-minute stint and strong finish", () => {
+ const ledger = Array.from({ length: 16 }, (_, index) => ({
+ driverId: "driver_1",
+ sourceId: "transponder_1",
+ sessionId: "practice_1",
+ timestamp: (index + 1) * 20_000,
+ lapMs: 20_000,
+ }));
+ const state = { training: { ledger } };
+ const stats = buildDriverTrainingStats(state, "driver_1");
+ const analysis = buildTrainingStintAnalysis(state, "driver_1");
+
+ assert.equal(stats.controlZoneMinMs, 20_000);
+ assert.equal(stats.controlZoneMaxMs, 21_600);
+ assert.equal(stats.controlledLapStreak, 16);
+ assert.equal(stats.outlierLaps, 0);
+ assert.equal(stats.strongFinishStints, 1);
+ assert.equal(stats.cleanFiveMinuteStints, 1);
+ assert.equal(stats.achievements.find((item) => item.id === "strong_finish").unlocked, true);
+ assert.equal(stats.achievements.find((item) => item.id === "clean_five_minute").unlocked, true);
+ assert.equal(analysis.rows[0].strongFinish, true);
+ assert.equal(analysis.rows[0].fiveMinuteResult.lapCount, 15);
+ assert.equal(analysis.rows[0].fiveMinuteResult.totalMs, 300_000);
+});
+
test("recommendations select baseline, consistency, and progression", () => {
assert.equal(buildTrainingRecommendation({ totalLaps: 9 }).level, "baseline");
assert.deepEqual(