diff --git a/rowers/dataprep.py b/rowers/dataprep.py
index 9aa856ac..0d3303b0 100644
--- a/rowers/dataprep.py
+++ b/rowers/dataprep.py
@@ -1092,6 +1092,9 @@ def workout_goldmedalstandard(workout):
         return workout.goldmedalstandard,workout.goldmedalseconds
     if workout.workouttype in rowtypes:
         goldmedalstandard,goldmedalseconds = calculate_goldmedalstandard(workout.user,workout)
+        if workout.workouttype in otwtypes:
+            factor = 100./(100.-workout.user.otwslack)
+            goldmedalstandard = goldmedalstandard*factor
         workout.goldmedalstandard = goldmedalstandard
         workout.goldmedalseconds = goldmedalseconds
         workout.save()
diff --git a/rowers/interactiveplots.py b/rowers/interactiveplots.py
index dc004f32..fb7200f5 100644
--- a/rowers/interactiveplots.py
+++ b/rowers/interactiveplots.py
@@ -130,8 +130,6 @@ def build_goldmedalstandards(workouts,kfitness):
     for w in workouts:
         goldmedalstandard,goldmedalseconds = dataprep.workout_goldmedalstandard(w)
         ids.append(w.id)
-        if w.workouttype in mytypes.otwtypes:
-            goldmedalstandard = goldmedalstandard / (1.-w.user.otwslack/100.)
         if goldmedalseconds > 60:
             goldmedalstandards.append(goldmedalstandard)
             goldmedaldurations.append(goldmedalseconds)
@@ -1713,9 +1711,9 @@ def getfatigues(
     fatigue = 0
     fitness = 0
 
-    #impulses = []
-    #for f in fatigues:
-    #    impulses.append(0)
+    impulses = []
+    for f in fatigues:
+        impulses.append(0)
 
     lambda_a = 2/(kfatigue+1)
     lambda_c = 2/(kfitness+1)
@@ -1752,7 +1750,6 @@ def getfatigues(
 
         impulses.append(weight)
 
-
         fatigue = (1-lambda_a)*fatigue+weight*lambda_a
         fitness = (1-lambda_c)*fitness+weight*lambda_c
 
@@ -1762,6 +1759,7 @@ def getfatigues(
         testpower.append(np.nan)
         testduration.append(np.nan)
 
+
     return fatigues,fitnesses,dates,testpower,testduration,impulses
 
 def performance_chart(user,startdate=None,enddate=None,kfitness=42,kfatigue=7,
@@ -1771,6 +1769,9 @@ def performance_chart(user,startdate=None,enddate=None,kfitness=42,kfatigue=7,
     TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair'
     TOOLS2 = 'box_zoom,hover'
 
+    # to avoid data mess later on
+    startdate = arrow.get(startdate).datetime.replace(hour=0,minute=0,second=0,microsecond=0)
+
 
     modelchoice = 'coggan'
     p0 = 0
@@ -1782,6 +1783,7 @@ def performance_chart(user,startdate=None,enddate=None,kfitness=42,kfatigue=7,
     fatigues = []
     fitnesses = []
     testduration = []
+    impulses = []
 
     if showtests:
         workouts = Workout.objects.filter(user=user.rower,date__gte=startdate,
@@ -1809,6 +1811,7 @@ def performance_chart(user,startdate=None,enddate=None,kfitness=42,kfatigue=7,
         except IndexError:
             pass
 
+
         dates = [d for d in df['date']]
         testpower = df['testpower'].values.tolist()
         fatigues = df['fatigue'].values.tolist()
@@ -1836,6 +1839,7 @@ def performance_chart(user,startdate=None,enddate=None,kfitness=42,kfatigue=7,
         'impulse':impulses,
     })
 
+
     endfitness = fitnesses[-1]
     endfatigue = fatigues[-1]
     endform = endfitness-endfatigue
@@ -1853,6 +1857,9 @@ def performance_chart(user,startdate=None,enddate=None,kfitness=42,kfatigue=7,
     df = df.groupby(['date']).max()
     df['date'] = df.index.values
 
+    #for row in df.iterrows():
+    #    print(row)
+
     source = ColumnDataSource(
         data = dict(
             testpower = df['testpower'],
@@ -1929,7 +1936,10 @@ def performance_chart(user,startdate=None,enddate=None,kfitness=42,kfatigue=7,
 
     y2rangemin = df.loc[:,['form']].min().min()
     y2rangemax = df.loc[:,['form']].max().max()
-    if dofatigue:
+    if dofatigue and showtests:
+        y1rangemin = df.loc[:,['testpower','fitness','fatigue']].min().min()
+        y1rangemax = df.loc[:,['testpower','fitness','fatigue']].max().max()
+    elif dofatigue:
         y1rangemin = df.loc[:,['fitness','fatigue']].min().min()
         y1rangemax = df.loc[:,['fitness','fatigue']].max().max()
     else: