diff --git a/rowers/fitness.py b/rowers/fitness.py
new file mode 100644
index 00000000..bcced876
--- /dev/null
+++ b/rowers/fitness.py
@@ -0,0 +1,112 @@
+import polars as pl
+import datetime
+import arrow
+import numpy as np
+
+from rowers.dataprep import rscore_approx
+
+from rowers.models import Rower, Workout
+
+def weightfromrecord(row,metricchoice):
+    vv = row[metricchoice][0]
+    if vv > 0:
+        return vv
+    if metricchoice == 'rscore': # pragma: no cover
+        return rscore_approx(row)
+
+    return 0 # pragma: no cover
+
+
+def getfatigues(df, fatigues, fitnesses, dates, impulses, startdate, kfatigue, kfitness):
+    fatigue = 0
+    fitness = 0
+    impulses = []
+
+    for f in fatigues:
+        impulses.append(0)
+
+    lambda_a = 2/(kfatigue+1)
+    lambda_c = 2/(kfitness+1)
+
+    enddate = datetime.date.today()
+    nrdays = (enddate - startdate).days
+
+    for i in range(nrdays+1):
+        date = startdate + datetime.timedelta(days=i)
+        datekey = date.strftime('%Y-%m-%d')
+        weight = 0
+
+        try:
+            df2 = df.filter(pl.col('date') == date)
+            if type(df2) == pl.Series:
+                weight += weightfromrecord(df2, 'rscore')
+            else:
+                for row in df2.iter_slices(n_rows=1):
+                    weight += weightfromrecord(row, 'rscore')
+        except KeyError:
+            pass
+
+        impulses.append(weight)
+
+        fatigue = (1 - lambda_a) * fatigue + lambda_a * weight
+        fitness = (1 - lambda_c) * fitness + lambda_c * weight
+
+        fatigues.append(fatigue)
+        fitnesses.append(fitness)
+        dates.append(arrow.get(date).datetime)
+
+    return fatigues, fitnesses, dates, impulses
+
+def calculate_fitness(rower):
+    workouts = Workout.objects.filter(user=rower, date__gte=datetime.date.today() - datetime.timedelta(days=90),
+                                      duplicate=False).order_by('date')
+
+    kfitness = rower.kfit
+    kfatigue = rower.kfatigue
+    
+
+    records = []
+
+    for w in workouts:
+        dd = {
+            'date': w.date,
+            'trimp': w.trimp,
+            'rscore': w.rscore,
+            'hrtss':w.hrtss,
+            'duration': w.duration,
+            'id': w.id,
+            'rpe': w.rpe,
+        }
+        records.append(dd)
+
+    df = pl.from_records(records)
+    if df.is_empty():
+        return 0, 0
+
+    dates = [arrow.get(w.date).datetime for w in workouts]
+    impulses = [np.nan for w in workouts]
+    fitnesses = [np.nan for w in workouts]
+    fatigues = [np.nan for w in workouts]
+
+    fatigues, fitnesses, dates, impulses = getfatigues(
+        df,
+        fatigues,
+        fitnesses,
+        dates,
+        impulses,
+        datetime.date.today()-datetime.timedelta(days=90),
+        kfatigue, kfitness
+    )
+
+    df = pl.DataFrame({
+        'date': dates,
+        'fatigue': fatigues,
+        'fitness': fitnesses,
+        'impulse': impulses,
+    })
+
+    endfitness = fitnesses[-2]
+    endfatigue = fatigues[-2]
+
+    return endfitness, endfatigue
+