diff --git a/rowers/interactiveplots.py b/rowers/interactiveplots.py
index 1ed3e6ad..0c183790 100644
--- a/rowers/interactiveplots.py
+++ b/rowers/interactiveplots.py
@@ -25,7 +25,7 @@ import itertools
 from bokeh.plotting import figure, ColumnDataSource, Figure,curdoc
 from bokeh.models import CustomJS,Slider, TextInput,BoxAnnotation, Band
 
-from rowers.utils import myqueue
+from rowers.utils import myqueue, totaltime_sec_to_string
 import django_rq
 queue = django_rq.get_queue('default')
 queuelow = django_rq.get_queue('low')
@@ -105,9 +105,10 @@ from pandas.core.groupby.groupby import DataError
 def build_goldmedalstandards(workouts,kfitness):
     dates = []
     testpower = []
+    testduration = []
     fatigues = []
     fitnesses = []
-    
+
     data = []
     goldmedalstandards = []
     goldmedaldurations = []
@@ -118,26 +119,35 @@ def build_goldmedalstandards(workouts,kfitness):
         goldmedalstandards.append(goldmedalstandard)
         goldmedaldurations.append(goldmedalseconds)
 
-    df = pd.DataFrame({'workout':ids,'goldmedalstandard':goldmedalstandards})
+    df = pd.DataFrame({
+        'workout':ids,
+        'goldmedalstandard':goldmedalstandards,
+        'goldmedalduration':goldmedaldurations,
+        })
 
     for w in workouts:
         ids = [w.id for w in workouts.filter(date__gte=w.date-datetime.timedelta(days=kfitness),
                                              date__lte=w.date)]
 
         powerdf = df[df['workout'].isin(ids)]
+        indexmax = powerdf['goldmedalstandard'].idxmax()
         powertest = powerdf['goldmedalstandard'].max()
+        durationtest = powerdf.loc[indexmax,'goldmedalduration']
 
         dates.append(datetime.datetime.combine(w.date,datetime.datetime.min.time()))
         testpower.append(powertest)
+        testduration.append(durationtest)
+
         fatigues.append(np.nan)
         fitnesses.append(np.nan)
 
-    return dates, testpower, fatigues, fitnesses
+    return dates, testpower, testduration, fatigues, fitnesses
 
 
 def get_testpower(workouts,fitnesstestsecs,kfitness):
     dates = []
     testpower = []
+    testduration = []
     fatigues = []
     fitnesses = []
     data = []
@@ -195,6 +205,7 @@ def get_testpower(workouts,fitnesstestsecs,kfitness):
 
             dates.append(datetime.datetime.combine(w.date,datetime.datetime.min.time()))
             testpower.append(powertest)
+            testduration.append(fitnesstestsecs)
             fatigues.append(np.nan)
             fitnesses.append(np.nan)
 
@@ -1635,7 +1646,7 @@ def interactive_forcecurve(theworkouts,workstrokesonly=True,plottype='scatter'):
     return [script,div,js_resources,css_resources]
 
 def getfatigues(
-    fatigues,fitnesses,dates,testpower,
+    fatigues,fitnesses,dates,testpower,testduration,
     startdate,enddate,user,metricchoice,kfatigue,kfitness):
 
     fatigue = 0
@@ -1688,8 +1699,9 @@ def getfatigues(
         fitnesses.append(fitness)
         dates.append(datetime.datetime.combine(date,datetime.datetime.min.time()))
         testpower.append(np.nan)
+        testduration.append(np.nan)
 
-    return fatigues,fitnesses,dates,testpower,impulses
+    return fatigues,fitnesses,dates,testpower,testduration,impulses
 
 def performance_chart(user,startdate=None,enddate=None,kfitness=42,kfatigue=7,
                       metricchoice='trimp',doform=False,dofatigue=False):
@@ -1933,11 +1945,11 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
     df = pd.DataFrame()
 
     if not usegoldmedalstandard:
-        dates,testpower,fatigues,fitnesses = get_testpower(
+        dates,testpower,testduration, fatigues,fitnesses = get_testpower(
             workouts,fitnesstestsecs,kfitness
             )
     else:
-        dates,testpower,fatigues,fitnesses = build_goldmedalstandards(
+        dates,testpower, testduration,fatigues,fitnesses = build_goldmedalstandards(
             workouts,kfitness
         )
     # create CP data
@@ -1945,6 +1957,7 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
     df = pd.DataFrame({
         'date':dates,
         'testpower':testpower,
+        'testduration':testduration,
         'fatigue':fatigues,
         'fitness':fitnesses,
     })
@@ -1965,9 +1978,10 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
     testpower = df['testpower'].values.tolist()
     fatigues = df['fatigue'].values.tolist()
     fitnesses = df['fitness'].values.tolist()
+    testduration = df['testduration'].values.tolist()
 
-    fatigues,fitnesses,dates,testpower,impulses = getfatigues(
-        fatigues,fitnesses,dates,testpower,
+    fatigues,fitnesses,dates,testpower,testduration,impulses = getfatigues(
+        fatigues,fitnesses,dates,testpower,testduration,
         startdate,enddate,user,metricchoice,kfatigue,kfitness
     )
 
@@ -1975,6 +1989,7 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
     df = pd.DataFrame({
         'date':dates,
         'testpower':testpower,
+        'testduration':testduration,
         'fatigue':fatigues,
         'fitness':fitnesses,
     })
@@ -2000,6 +2015,7 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
     source = ColumnDataSource(
         data = dict(
             testpower = df['testpower'],
+            testduration = df['testduration'].apply(lambda x:totaltime_sec_to_string(x,shorten=True)),
             date = df['date'],
             fdate = df['date'].map(lambda x: x.strftime('%d-%m-%Y')),
             fitness = df['fitness'],
@@ -2109,7 +2125,8 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None,
     hover = plot.select(dict(type=HoverTool))
 
     hover.tooltips = OrderedDict([
-        (legend_label,'@testpower'),
+        (legend_label,'@testpower{int}'),
+        ('Test', '@testduration'),
         ('Date','@fdate'),
         (fitlabel,'@fitness'),
         (fatiguelabel,'@fatigue'),
diff --git a/rowers/utils.py b/rowers/utils.py
index 954a611a..c7573b69 100644
--- a/rowers/utils.py
+++ b/rowers/utils.py
@@ -377,6 +377,8 @@ def wavg(group, avg_name, weight_name):
         return d.mean()
 
 def totaltime_sec_to_string(totaltime,shorten=False):
+    if np.isnan(totaltime):
+        return ''
     hours = int(totaltime / 3600.)
     if hours > 23:
         message = 'Warning: The workout duration was longer than 23 hours. '