diff --git a/triangle_analysis.m b/triangle_analysis.m
index bd511cfb41181de695a6b1595dcffe0321d14386..a2e2319b7f4f9b7f696ce84f1212bd4a7d75ec35 100644
--- a/triangle_analysis.m
+++ b/triangle_analysis.m
@@ -226,6 +226,7 @@ TableForm[Transpose[histograms],TableHeadings->{nlabels,taulabels}]
 
  (* Stats for a single run at every (n,tau) *)
 timeWindow=Round[Length[gdata[[1,1,1,2]]]/10];
+skipPts=Max[1,Round[timeWindow/100]];
 getSingleStats[runs_]:=Module[{run,avg,stddev},
     run=runs[[1]]; (* Select some run *)
     avg=N[Mean[run[[2,-timeWindow;;-1]]]];
@@ -234,7 +235,8 @@ getSingleStats[runs_]:=Module[{run,avg,stddev},
     stddev/avg,
     (run[[2,1]])/avg, (* EG starting point *)
     Map[N[#/avg]&,run[[4]]],  (* GCM1 counts *)
-    Map[N[#/avg]&,run[[5]]] (* GCM2 counts *)
+    Map[N[#/avg]&,run[[5]]],  (* GCM2 counts *)
+    (run[[2,-timeWindow;;-1;;skipPts]])/avg  (* counts in uniform distribution *)
     }
 ]
 singleStats=Map[getSingleStats,gdata,{2}];
@@ -242,7 +244,8 @@ singleStats=Map[getSingleStats,gdata,{2}];
 
 (* Yellow: GCM1 (take new highest everytime *)
 (* Blue: GCM2 (finish highest first, more similar to EG) *)
-histogramsSingle=Map[Histogram[{#[[4]],#[[5]]},PlotRange->{{0,5},Automatic},ImageSize->300,PlotLabel->"ErdosGallai="<>ToString[NumberForm[#[[3]],3]]<>"\[Cross]average. stddev="<>ToString[NumberForm[#[[2]],3]]<>"\[Cross]average"]&,singleStats,{2}];
+(* Green: Actual uniform distribution *)
+histogramsSingle=Map[Histogram[{#[[4]],#[[5]],#[[6]]},PlotRange->{{0,3},Automatic},ImageSize->300,PlotLabel->"ErdosGallai="<>ToString[NumberForm[#[[3]],3]]<>"\[Cross]average"]&,singleStats,{2}];
 
 
 TableForm[histogramsSingle,TableHeadings->{taulabels,nlabels}]
@@ -250,12 +253,13 @@ TableForm[histogramsSingle,TableHeadings->{taulabels,nlabels}]
 
  (* Consider all runs *)
 timeWindow=Round[Length[gdata[[1,1,1,2]]]/10];
+skipPts=Max[1,Round[timeWindow/100]];
 getAverage[run_]:=Module[{avg,stddev},
     avg=N[Mean[run[[2,-timeWindow;;-1]]]];
     {
     Mean[run[[4]]]/avg,(* GCM1 counts *)
     Mean[run[[5]]]/avg, (* GCM2 counts *)
-    (run[[2,1]])/avg (* EG starting point *)
+    (run[[2,1]])/avg, (* EG starting point *)
     }
 ]
 getTotalStats[runs_]:=Transpose[Map[getAverage,runs]];
@@ -263,15 +267,13 @@ totalStats=Map[getTotalStats,gdata,{2}];
 
 
 (* Yellow: GCM1 (take new highest everytime *)
-(* Blue: GCM2 (finish\[AliasDelimiter] highest first, more similar to EG) *)
+(* Blue: GCM2 (finish highest first, more similar to EG) *)
 histogramsTotal=Map[Histogram[#,{0.1},PlotRange->{{0,5},Automatic},ImageSize->300]&,totalStats,{2}];
 
 
 TableForm[histogramsTotal,TableHeadings->{taulabels,nlabels}]
 
 
-
-
 (* ::Subsection:: *)
 (*GCM1 vs GCM2 success rates*)