diff --git a/rowers/views/userviews.py b/rowers/views/userviews.py
index a766b3f0..3ab68c22 100644
--- a/rowers/views/userviews.py
+++ b/rowers/views/userviews.py
@@ -566,6 +566,60 @@ def rower_prefs_view(request,userid=0,message=""):
             r.cprange = cprange
             r.save()
             messages.info(request,'Updated CP range value')
+            firstdate = datetime.date.today()-datetime.timedelta(days=cprange)
+            workouts = Workout.objects.filter(
+                date__gte=datetime.date.today()-datetime.timedelta(days=cprange),
+                workouttype__in=mytypes.otwtypes,
+                user = r,
+            )
+            dd,cpcp,avgpower,workoutnames = dataprep.fetchcp_new(r,workouts)
+            powerdf = pd.DataFrame({
+                'Delta':dd,
+                'CP':cpcp,
+            })
+
+
+            powerdf = powerdf[powerdf['CP']>0]
+            powerdf.dropna(axis=0,inplace=True)
+            powerdf.sort_values(['Delta','CP'],ascending=[1,0],inplace=True)
+            powerdf.drop_duplicates(subset='Delta',keep='first',inplace=True)
+
+            res2 = datautils.cpfit(powerdf)
+            if len(powerdf) != 0:
+                p1 = res2[0]
+                r.p0 = p1[0]
+                r.p1 = p1[1]
+                r.p2 = p1[2]
+                r.p3 = p1[3]
+                r.cpratio = res2[3]
+                r.save()
+
+            workouts = Workout.objects.filter(
+                date__gte=datetime.date.today()-datetime.timedelta(days=cprange),
+                workouttype__in=mytypes.otetypes,
+                user = r,
+            )
+            dd,cpcp,avgpower,workoutnames = dataprep.fetchcp_new(r,workouts)
+            powerdf = pd.DataFrame({
+                'Delta':dd,
+                'CP':cpcp,
+            })
+
+
+            powerdf = powerdf[powerdf['CP']>0]
+            powerdf.dropna(axis=0,inplace=True)
+            powerdf.sort_values(['Delta','CP'],ascending=[1,0],inplace=True)
+            powerdf.drop_duplicates(subset='Delta',keep='first',inplace=True)
+
+            res2 = datautils.cpfit(powerdf)
+            if len(powerdf) != 0:
+                p1 = res2[0]
+                r.ep0 = p1[0]
+                r.ep1 = p1[1]
+                r.ep2 = p1[2]
+                r.ep3 = p1[3]
+                r.ecpratio = res2[3]
+                r.save()
 
     return render(request, 'rower_preferences.html',
                   {