diff --git a/src/Charts/CPPlot.cpp b/src/Charts/CPPlot.cpp
index 1e7ec1e5d..6877f4bd7 100644
--- a/src/Charts/CPPlot.cpp
+++ b/src/Charts/CPPlot.cpp
@@ -25,6 +25,7 @@
 #include "CPPlot.h"
 #include "PowerProfile.h"
 #include "RideCache.h"
+#include "Banister.h"
 
 #include <QDebug>
 #include <qwt_series_data.h>
@@ -1384,7 +1385,7 @@ CPPlot::plotBests(RideItem *rideItem)
                     // away from a linear regression
 
                     // the best we found is stored in here
-                    struct { int i; double p, t, d; } keep;
+                    struct { int i; double p, t, d, pix; } keep;
 
                     for(int i=0; i<t.count(); i++) {
 
@@ -1399,6 +1400,7 @@ CPPlot::plotBests(RideItem *rideItem)
                             keep.i=i;
                             keep.p=p[i];
                             keep.t=t[i];
+                            keep.pix=powerIndex(keep.p, keep.t);
 
                             // but clear since we iterate beyond
                             if (i>0) { // always keep pmax point
@@ -1413,8 +1415,10 @@ CPPlot::plotBests(RideItem *rideItem)
 
                                     // if its beloe the line multiply distance by -1
                                     double d = (p[x] * t[x] * 60.0f) - ((slope * t[x] * 60.00f) + intercept);
+                                    double pix = powerIndex(p[x],t[x]);
 
-                                    if (keep.d < d) {
+                                    // use the regression for shorter durations and 3p for longer
+                                    if ((keep.t < 120 && keep.d < d) || (keep.t >= 120 && keep.pix < pix)) {
                                         keep.d = d;
                                         keep.i = x;
                                         keep.p = p[x];
diff --git a/src/Metrics/Banister.cpp b/src/Metrics/Banister.cpp
index 0ad4712d6..a116b36ea 100644
--- a/src/Metrics/Banister.cpp
+++ b/src/Metrics/Banister.cpp
@@ -48,6 +48,23 @@ const double typical_CP = 261,
 // and also useful to normalise TTEs for use in the Banister model as a
 // performance measurement.
 //
+
+double powerIndex(double averagepower, double duration)
+{
+    // so now lets work out what the 3p model says the
+    // typical athlete would do for the same duration
+    //
+    // P(t) = W' / (t - (W'/(CP-Pmax))) + CP
+    double typicalpower = (typical_WPrime / (duration - (typical_WPrime/(typical_CP-typical_Pmax)))) + typical_CP;
+
+    // make sure we got a sensible value
+    if (typicalpower < 0 || typicalpower > 2500)  return 0;
+
+    // we could convert to linear work time model before
+    // indexing, but they cancel out so no value in doing so
+    return(100.0 * averagepower/typicalpower);
+}
+
 class PowerIndex : public RideMetric {
     Q_DECLARE_TR_FUNCTIONS(PowerIndex)
     public:
@@ -100,24 +117,13 @@ class PowerIndex : public RideMetric {
             return;
         }
 
-        // so now lets work out what the 3p model says the
-        // typical athlete would do for the same duration
-        //
-        // P(t) = W' / (t - (W'/(CP-Pmax))) + CP
-        //
-        double typicalpower = (typical_WPrime / (duration - (typical_WPrime/(typical_CP-typical_Pmax)))) + typical_CP;
-
-        // make sure we got a sensible value
-        if (typicalpower < 0 || typicalpower > 2500) {
-            setValue(RideFile::NIL);
-            setCount(0);
-            return;
-        }
+        // calculate power index, 0=out of bounds
+        double pix = powerIndex(averagepower, duration);
 
         // we could convert to linear work time model before
         // indexing, but they cancel out so no value in doing so
-        setValue(100.0 * averagepower/typicalpower);
-        setCount(1);
+        setValue(pix);
+        setCount(pix > 0 ? 1 : 0);
     }
 
     MetricClass classification() const { return Undefined; }
diff --git a/src/Metrics/Banister.h b/src/Metrics/Banister.h
index 8f434b04b..efb298b7c 100644
--- a/src/Metrics/Banister.h
+++ b/src/Metrics/Banister.h
@@ -23,4 +23,7 @@
 // using floats because they are typically used in calculations
 // that require float precision (the actual values are integers)
 extern const double typical_CP, typical_WPrime, typical_Pmax;
+
+// calculate power index, used to model in cp plot too
+extern double powerIndex(double averagepower, double duration);
 #endif