diff --git a/data_preparation/IndividualMetrics.R b/data_preparation/IndividualMetrics.R
new file mode 100644
index 0000000..cfa8f78
--- /dev/null
+++ b/data_preparation/IndividualMetrics.R
@@ -0,0 +1,152 @@
+source("readData.R")
+
+library(tidyverse)
+
+
+RPEData <-readNArpeData()
+wellnessData <- readWellnessData()
+normalizedWellnessData <- readNormalizedMetrics()
+RPEData
+
+
+playerIDS <- playerIds <-unique(RPEData$PlayerID)
+
+
+numDays <- max(RPEData$TimeSinceAugFirst)
+
+
+dayList <- 0:numDays
+
+
+dayCol <- c()
+playerid <- c()
+
+dailyLoadCol <- c()
+acuteChronicRatioCol <- c()
+trainDuration <- c()
+
+sleepHoursCol <- c()
+fatigueRawCol <- c()
+sleepQualityCol <- c()
+sorenessCol <- c()
+
+normFatCol <-c()
+normSoreCol <- c()
+normSleepHours <- c()
+normSleepQuality <- c()
+
+notatAllCol <- c()
+absCol <-c()
+somewhatCol <- c()
+unknownCol <- c()
+
+
+
+
+
+for(day in dayList)
+{
+  for(id in playerIDS)
+  {
+    cat("Player:", id, "Day:", day, "\n", sep=" ")
+    
+    
+    trainDay <- subset(RPEData, TimeSinceAugFirst == day & PlayerID == id)
+    #workLoad <- c(workLoad, sum(daylyActivities$SessionLoad, na.rm = T))
+
+    wellnessDay <- subset(wellnessData, TimeSinceAugFirst == day & PlayerID == id)
+
+    
+    normalizedDay <- subset(normalizedWellnessData, TimeSinceAugFirst == day & playerID == id)
+    #if(length(normalizedDay$playerID) > 0)
+    #{
+    #  print("good")
+    #}
+    
+    dayCol <- c(dayCol, day)
+    playerid <- c(playerid, id)
+    
+    
+    if(length(wellnessDay$SleepHours) > 0)
+    {
+      fatigueRawCol <- c(fatigueRawCol, mean(wellnessDay$Fatigue, na.rm =T))
+      sleepQualityCol <- c(sleepQualityCol, mean(wellnessDay$SleepQuality, na.rm = T))
+      sleepHoursCol <- c(sleepHoursCol, sum(wellnessDay$SleepHours, na.rm = T))
+      sorenessCol <- c(sorenessCol, mean(wellnessDay$Soreness, na.rm = T))
+    }
+    else
+    {
+      sleepQualityCol <- c(sleepQualityCol, median(wellnessData$SleepQuality, na.rm = T))
+      sleepHoursCol <- c(sleepHoursCol, median(wellnessData$SleepHours))
+      fatigueRawCol <- c(fatigueRawCol, median(wellnessData$Fatigue))
+      sorenessCol <- c(sorenessCol, median(wellnessData$Soreness))
+    }
+
+    
+    if(length(normalizedDay$normSoreness) > 0)
+    {
+      normFatCol <- c(normFatCol, mean(normalizedDay$normFatigue, na.rm=T))
+      normSoreCol <- c(normSoreCol, mean(normalizedDay$normSoreness, na.rm = T))
+      normSleepHours <- c(normSleepHours, mean(normalizedDay$normSleepHours, na.rm =T))
+      normSleepQuality <- c(normSleepQuality, mean(normalizedDay$normSleepQuality, na.rm=T))
+    }
+    else
+    {
+      normFatCol <- c(normFatCol, mean(normalizedWellnessData$normFatigue, na.rm=T))
+      normSoreCol <- c(normSoreCol, mean(normalizedWellnessData$normSoreness, na.rm = T))
+      normSleepHours <- c(normSleepHours, mean(normalizedWellnessData$normSleepHours, na.rm =T))
+      normSleepQuality <- c(normSleepQuality, mean(normalizedWellnessData$normSleepQuality, na.rm=T))
+    }
+    
+    if(length(trainDay$SessionLoad) > 0)
+    {
+      dailyLoadCol <- c(dailyLoadCol, mean(trainDay$DailyLoad,na.rm = T))
+      acuteChronicRatioCol <- c(acuteChronicRatioCol, mean(trainDay$AcuteChronicRatio, na.rm =T))
+      trainDuration <- c(trainDuration, sum(trainDay$Duration, na.rm = T))
+      
+      notatAllCol <- c(notatAllCol, max(trainDay$BestOutOfMyselfNotAtAll))
+      absCol <- c(absCol, max(trainDay$BestOutOfMyselfAbsolutely))
+      somewhatCol <- c(somewhatCol, max(trainDay$BestOutOfMyselfSomewhat))
+      unknownCol <- c(unknownCol, max(trainDay$BestOutOfMyselfUnknown))
+    }
+    else
+    {
+      dailyLoadCol <- c(dailyLoadCol, 0)
+      acuteChronicRatioCol <- c(acuteChronicRatioCol, 0)
+      trainDuration <- c(trainDuration, 0)
+      
+      
+      notatAllCol <- c(notatAllCol, 0)
+      absCol <- c(absCol, 0)
+      somewhatCol <- c(somewhatCol, 0)
+      unknownCol <- c(unknownCol, 1)
+    }
+  }
+  
+}
+
+
+dailyLoadCol[is.na(dailyLoadCol)] <- 0
+acuteChronicRatioCol[is.na(acuteChronicRatioCol)] <- 0
+
+
+
+massiveTibble <- tibble(day = dayCol,
+                        playerID = playerid,
+                        DailyLoad = dailyLoadCol,
+                        acuteChronicRatio = acuteChronicRatioCol,
+                        trainDuration = trainDuration,
+                        sleepHours = sleepHoursCol,
+                        fatigue = fatigueRawCol,
+                        sleepQuality = sleepQualityCol,
+                        soreness = sorenessCol,
+                        fatigueNorm = normFatCol,
+                        sorenessNorm = normSoreCol,
+                        sleepHoursNorm = normSleepHours,
+                        sleepQualityNorm = normSleepQuality,
+                        BestOutOfMyselfNotAtAll = notatAllCol,
+                        BestOutOfMyselfAbsolutely = absCol,
+                        BestOutOfMyselfSomewhat = somewhatCol,
+                        BestOutOfMyselfUnknown = unknownCol)
+
+write.csv(massiveTibble, "cleaned/personal.csv")
diff --git a/data_preparation/exponentialSmoothing.R b/data_preparation/exponentialSmoothing.R
new file mode 100644
index 0000000..b4ad16b
--- /dev/null
+++ b/data_preparation/exponentialSmoothing.R
@@ -0,0 +1,28 @@
+fatigueFunction <- function(workLoad, index)
+{
+  if(index == 1)
+  {
+    return(workLoad[1])
+  }
+  else
+  {
+    return(workLoad[index] + 0.7*fatigueFunction(workLoad, index -1))
+  }
+}
+
+
+smoothVector <- function(dataV)
+{
+  dataNew <- c()
+  
+  for(i in 1:length(dataV))
+  {
+    dataNew <- c(dataNew, fatigueFunction(dataV, i))
+  }
+  dataNew
+}
+
+
+smoothVector(c(1,2,3,4))
+
+plot(1:100, smoothVector(1:100))
\ No newline at end of file
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