diff --git a/x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/aggs/heuristic/PValueScore.java b/x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/aggs/heuristic/PValueScore.java
index 0149d7feec9d1..f365e4758cc94 100644
--- a/x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/aggs/heuristic/PValueScore.java
+++ b/x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/aggs/heuristic/PValueScore.java
@@ -113,6 +113,15 @@ public double getScore(long subsetFreq, long subsetSize, long supersetFreq, long
             return 0.0;
         }
 
+        // casting to `long` to round down to nearest whole number
+        double epsAllDocsInClass = (long)eps(allDocsInClass);
+        double epsAllDocsNotInClass = (long)eps(allDocsNotInClass);
+
+        docsContainTermInClass += epsAllDocsInClass;
+        docsContainTermNotInClass += epsAllDocsNotInClass;
+        allDocsInClass += epsAllDocsInClass;
+        allDocsNotInClass += epsAllDocsNotInClass;
+
         // Adjust counts to ignore ratio changes which are less than 5%
         // casting to `long` to round down to nearest whole number
         docsContainTermNotInClass = (long)(Math.min(
@@ -120,41 +129,34 @@ public double getScore(long subsetFreq, long subsetSize, long supersetFreq, long
             docsContainTermInClass / allDocsInClass * allDocsNotInClass
         ) + 0.5);
 
-        // casting to `long` to round down to nearest whole number
-        double epsAllDocsInClass = (long)eps(allDocsInClass);
-        double epsAllDocsNotInClass = (long)eps(allDocsNotInClass);
-
-        if ((allDocsInClass + epsAllDocsInClass) > Long.MAX_VALUE
-            || (docsContainTermInClass + epsAllDocsInClass) > Long.MAX_VALUE
-            || (allDocsNotInClass + epsAllDocsNotInClass) > Long.MAX_VALUE
-            || (docsContainTermNotInClass + epsAllDocsNotInClass) > Long.MAX_VALUE) {
+        if (allDocsInClass > Long.MAX_VALUE
+            || docsContainTermInClass > Long.MAX_VALUE
+            || allDocsNotInClass > Long.MAX_VALUE
+            || docsContainTermNotInClass > Long.MAX_VALUE) {
             throw new AggregationExecutionException(
                 "too many documents in background and foreground sets, further restrict sets for execution"
             );
         }
 
         double v1 = new LongBinomialDistribution(
-            (long)(allDocsInClass + epsAllDocsInClass),
-            (docsContainTermInClass + epsAllDocsInClass)/(allDocsInClass + epsAllDocsInClass)
-        ).logProbability((long)(docsContainTermInClass + epsAllDocsInClass));
+            (long)allDocsInClass, docsContainTermInClass / allDocsInClass
+        ).logProbability((long)docsContainTermInClass);
 
         double v2 = new LongBinomialDistribution(
-            (long)(allDocsNotInClass + epsAllDocsNotInClass),
-            (docsContainTermNotInClass + epsAllDocsNotInClass)/(allDocsNotInClass + epsAllDocsNotInClass)
-        ).logProbability((long)(docsContainTermNotInClass + epsAllDocsNotInClass));
+            (long)allDocsNotInClass, docsContainTermNotInClass / allDocsNotInClass
+        ).logProbability((long)docsContainTermNotInClass);
 
-        double p2 = (docsContainTermInClass + docsContainTermNotInClass + epsAllDocsNotInClass + epsAllDocsInClass)
-            / (allDocsInClass + allDocsNotInClass + epsAllDocsNotInClass + epsAllDocsInClass);
+        double p2 = (docsContainTermInClass + docsContainTermNotInClass) / (allDocsInClass + allDocsNotInClass);
 
-        double v3 = new LongBinomialDistribution((long)(allDocsInClass + epsAllDocsInClass), p2)
-            .logProbability((long)(docsContainTermInClass + epsAllDocsInClass));
+        double v3 = new LongBinomialDistribution((long)allDocsInClass, p2)
+            .logProbability((long)docsContainTermInClass);
 
-        double v4 = new LongBinomialDistribution((long)(allDocsNotInClass + epsAllDocsNotInClass), p2)
-            .logProbability((long)(docsContainTermNotInClass + epsAllDocsNotInClass));
+        double v4 = new LongBinomialDistribution((long)allDocsNotInClass, p2)
+            .logProbability((long)docsContainTermNotInClass);
 
         double logLikelihoodRatio = v1 + v2 - v3 - v4;
         double pValue = CHI_SQUARED_DISTRIBUTION.survivalFunction(2.0 * logLikelihoodRatio);
-        return -FastMath.log(FastMath.max(pValue, Double.MIN_NORMAL));
+        return FastMath.max(-FastMath.log(FastMath.max(pValue, Double.MIN_NORMAL)), 0.0);
     }
 
     private double eps(double value) {
diff --git a/x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/aggs/heuristic/PValueScoreTests.java b/x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/aggs/heuristic/PValueScoreTests.java
index 24119d31c080a..42346627b17d5 100644
--- a/x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/aggs/heuristic/PValueScoreTests.java
+++ b/x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/aggs/heuristic/PValueScoreTests.java
@@ -22,7 +22,6 @@
 import static org.hamcrest.Matchers.allOf;
 import static org.hamcrest.Matchers.closeTo;
 import static org.hamcrest.Matchers.equalTo;
-import static org.hamcrest.Matchers.greaterThan;
 import static org.hamcrest.Matchers.greaterThanOrEqualTo;
 import static org.hamcrest.Matchers.lessThanOrEqualTo;
 
@@ -110,7 +109,7 @@ public void testPValueScore() {
         );
         assertThat(
             FastMath.exp(-new PValueScore(false).getScore(10, 100, 10, 1000)),
-            closeTo(0.002988594884934073, eps)
+            closeTo(0.003972388976814195, eps)
         );
         assertThat(
             FastMath.exp(-new PValueScore(false).getScore(10, 100, 200, 1000)),
@@ -118,23 +117,23 @@ public void testPValueScore() {
         );
         assertThat(
             FastMath.exp(-new PValueScore(false).getScore(20, 10000, 5, 10000)),
-            closeTo(0.6309430298306147, eps)
+            closeTo(1.0, eps)
         );
     }
 
     public void testSmallChanges() {
         assertThat(
             FastMath.exp(-new PValueScore(false).getScore(1, 4205, 0, 821496)),
-            closeTo(0.9572480202044421, eps)
+            closeTo(0.9999037287868853, eps)
         );
         // Same(ish) ratios
         assertThat(
             FastMath.exp(-new PValueScore(false).getScore(10, 4205, 195, 82149)),
-            closeTo(0.9893886454928338, eps)
+            closeTo(0.9995943820612134, eps)
         );
         assertThat(
             FastMath.exp(-new PValueScore(false).getScore(10, 4205, 1950, 821496)),
-            closeTo(0.9867689169546193, eps)
+            closeTo(0.9999942565428899, eps)
         );
 
         // 4% vs 0%
@@ -145,12 +144,12 @@ public void testSmallChanges() {
         // 4% vs 2%
         assertThat(
             FastMath.exp(-new PValueScore(false).getScore(168, 4205, 16429, 821496)),
-            closeTo(4.78464746423625e-06, eps)
+            closeTo(8.542608559219833e-5, eps)
         );
         // 4% vs 3.5%
         assertThat(
             FastMath.exp(-new PValueScore(false).getScore(168, 4205, 28752, 821496)),
-            closeTo(0.4728938449949742, eps)
+            closeTo(0.8833950526957098, eps)
         );
     }
 
@@ -186,7 +185,7 @@ public void testIncreasedSubsetIncreasedScore() {
         for (int j = 1; j < 11; j++) {
             double nextScore = getScore.apply(j*10L);
             assertThat(nextScore, greaterThanOrEqualTo(0.0));
-            assertThat(nextScore, greaterThan(priorScore));
+            assertThat(nextScore, greaterThanOrEqualTo(priorScore));
             priorScore = nextScore;
         }
     }