diff --git a/scheduler/propertyset.go b/scheduler/propertyset.go
index 85fe45d62..8ac9b48c6 100644
--- a/scheduler/propertyset.go
+++ b/scheduler/propertyset.go
@@ -234,9 +234,15 @@ func (p *propertySet) UsedCount(option *structs.Node, tg string) (string, string
 	if !ok {
 		return nValue, fmt.Sprintf("missing property %q", p.targetAttribute), 0
 	}
+	combinedUse := p.GetCombinedUseMap()
+	usedCount := combinedUse[nValue]
+	return nValue, "", usedCount
+}
 
-	// combine the counts of how many times the property has been used by
-	// existing and proposed allocations
+// GetCombinedUseMap counts how many times the property has been used by
+// existing and proposed allocations. It also takes into account any stopped
+// allocations
+func (p *propertySet) GetCombinedUseMap() map[string]uint64 {
 	combinedUse := make(map[string]uint64, helper.IntMax(len(p.existingValues), len(p.proposedValues)))
 	for _, usedValues := range []map[string]uint64{p.existingValues, p.proposedValues} {
 		for propertyValue, usedCount := range usedValues {
@@ -259,9 +265,7 @@ func (p *propertySet) UsedCount(option *structs.Node, tg string) (string, string
 			combinedUse[propertyValue] = 0
 		}
 	}
-
-	usedCount := combinedUse[nValue]
-	return nValue, "", usedCount
+	return combinedUse
 }
 
 // filterAllocs filters a set of allocations to just be those that are running
diff --git a/scheduler/spread.go b/scheduler/spread.go
index f9acede39..2035ccf59 100644
--- a/scheduler/spread.go
+++ b/scheduler/spread.go
@@ -8,6 +8,18 @@ const (
 	// ImplicitTarget is used to represent any remaining attribute values
 	// when target percentages don't add up to 100
 	ImplicitTarget = "*"
+
+	// evenSpreadBoost is a positive boost used when the job has
+	// even spread over an attribute. Any nodes whose attribute value is
+	// equal to the minimum count over all possible attributes gets boosted
+	evenSpreadBoost = 0.01
+
+	// evenSpreadPenality is a penalty used when the job has
+	// even spread over an attribute. Any nodes whose attribute value is
+	// greater than the minimum count over all possible attributes gets this penalty.
+	// This is to ensure that other nodes are preferred when one of the values
+	// has a larger number of allocations
+	evenSpreadPenalty = -0.5
 )
 
 // SpreadIterator is used to spread allocations across a specified attribute
@@ -119,25 +131,33 @@ func (iter *SpreadIterator) Next() *RankedNode {
 			}
 			spreadAttributeMap := iter.tgSpreadInfo[tgName]
 			spreadDetails := spreadAttributeMap[pset.targetAttribute]
-			// Get the desired count
-			desiredCount, ok := spreadDetails.desiredCounts[nValue]
-			if !ok {
-				// See if there is an implicit target
-				desiredCount, ok = spreadDetails.desiredCounts[ImplicitTarget]
-				if !ok {
-					// The desired count for this attribute is zero if it gets here
-					// don't boost the score
-					continue
-				}
-			}
-			if float64(usedCount) < desiredCount {
-				// Calculate the relative weight of this specific spread attribute
-				spreadWeight := float64(spreadDetails.weight) / float64(iter.sumSpreadWeights)
-				// Score Boost is proportional the difference between current and desired count
-				// It is multiplied with the spread weight to account for cases where the job has
-				// more than one spread attribute
-				scoreBoost := ((desiredCount - float64(usedCount)) / desiredCount) * spreadWeight
+
+			if len(spreadDetails.desiredCounts) == 0 {
+				// When desired counts map is empty the user didn't specify any targets
+				// Treat this as a special case
+				scoreBoost := evenSpreadScoreBoost(pset, option.Node)
 				totalSpreadScore += scoreBoost
+			} else {
+				// Get the desired count
+				desiredCount, ok := spreadDetails.desiredCounts[nValue]
+				if !ok {
+					// See if there is an implicit target
+					desiredCount, ok = spreadDetails.desiredCounts[ImplicitTarget]
+					if !ok {
+						// The desired count for this attribute is zero if it gets here
+						// don't boost the score
+						continue
+					}
+				}
+				if float64(usedCount) < desiredCount {
+					// Calculate the relative weight of this specific spread attribute
+					spreadWeight := float64(spreadDetails.weight) / float64(iter.sumSpreadWeights)
+					// Score Boost is proportional the difference between current and desired count
+					// It is multiplied with the spread weight to account for cases where the job has
+					// more than one spread attribute
+					scoreBoost := ((desiredCount - float64(usedCount)) / desiredCount) * spreadWeight
+					totalSpreadScore += scoreBoost
+				}
 			}
 		}
 
@@ -149,6 +169,48 @@ func (iter *SpreadIterator) Next() *RankedNode {
 	}
 }
 
+// evenSpreadScoreBoost is a scoring helper that calculates the score
+// for the option when even spread is desired (all attribute values get equal preference)
+func evenSpreadScoreBoost(pset *propertySet, option *structs.Node) float64 {
+	combinedUseMap := pset.GetCombinedUseMap()
+	if len(combinedUseMap) == 0 {
+		// Nothing placed yet, so return 0 as the score
+		return 0.0
+	}
+	// Get the nodes property value
+	nValue, ok := getProperty(option, pset.targetAttribute)
+	currentAttributeCount := uint64(0)
+	if ok {
+		currentAttributeCount = combinedUseMap[nValue]
+	}
+	minCount := uint64(0)
+	maxCount := uint64(0)
+	for _, value := range combinedUseMap {
+		if minCount == 0 || value < minCount {
+			minCount = value
+		}
+		if maxCount == 0 || value > maxCount {
+			maxCount = value
+		}
+	}
+	if currentAttributeCount < minCount {
+		// Small positive boost for attributes with min count
+		return evenSpreadBoost
+	} else if currentAttributeCount > minCount {
+		// Negative boost if attribute count is greater than minimum
+		// This is so that other nodes will get a preference over this one
+		return evenSpreadPenalty
+	} else {
+		// When min and max are same the current distribution is even
+		// so we penalize
+		if minCount == maxCount {
+			return evenSpreadPenalty
+		} else {
+			return evenSpreadBoost
+		}
+	}
+}
+
 // computeSpreadInfo computes and stores percentages and total values
 // from all spreads that apply to a specific task group
 func (iter *SpreadIterator) computeSpreadInfo(tg *structs.TaskGroup) {
@@ -167,7 +229,8 @@ func (iter *SpreadIterator) computeSpreadInfo(tg *structs.TaskGroup) {
 			si.desiredCounts[st.Value] = desiredCount
 			sumDesiredCounts += desiredCount
 		}
-		if sumDesiredCounts < float64(totalCount) {
+		// Account for remaining count only if there is any spread targets
+		if sumDesiredCounts > 0 && sumDesiredCounts < float64(totalCount) {
 			remainingCount := float64(totalCount) - sumDesiredCounts
 			si.desiredCounts[ImplicitTarget] = remainingCount
 		}
diff --git a/scheduler/spread_test.go b/scheduler/spread_test.go
index e546a2e6d..e6457d56e 100644
--- a/scheduler/spread_test.go
+++ b/scheduler/spread_test.go
@@ -245,3 +245,189 @@ func TestSpreadIterator_MultipleAttributes(t *testing.T) {
 	}
 
 }
+
+func TestSpreadIterator_EvenSpread(t *testing.T) {
+	state, ctx := testContext(t)
+	dcs := []string{"dc1", "dc2", "dc1", "dc2", "dc1", "dc2", "dc2", "dc1", "dc1", "dc1"}
+	var nodes []*RankedNode
+
+	// Add these nodes to the state store
+	for i, dc := range dcs {
+		node := mock.Node()
+		node.Datacenter = dc
+		if err := state.UpsertNode(uint64(100+i), node); err != nil {
+			t.Fatalf("failed to upsert node: %v", err)
+		}
+		nodes = append(nodes, &RankedNode{Node: node})
+	}
+
+	static := NewStaticRankIterator(ctx, nodes)
+	job := mock.Job()
+	tg := job.TaskGroups[0]
+	job.TaskGroups[0].Count = 10
+
+	// Configure even spread across node.datacenter
+	spread := &structs.Spread{
+		Weight:    100,
+		Attribute: "${node.datacenter}",
+	}
+	tg.Spreads = []*structs.Spread{spread}
+	spreadIter := NewSpreadIterator(ctx, static)
+	spreadIter.SetJob(job)
+	spreadIter.SetTaskGroup(tg)
+
+	scoreNorm := NewScoreNormalizationIterator(ctx, spreadIter)
+
+	out := collectRanked(scoreNorm)
+
+	// Nothing placed so both dc nodes get 0 as the score
+	expectedScores := map[string]float64{
+		"dc1": 0,
+		"dc2": 0,
+	}
+	for _, rn := range out {
+		require.Equal(t, expectedScores[rn.Node.Datacenter], rn.FinalScore)
+	}
+
+	// Update the plan to add allocs to nodes in dc1
+	// After this step dc2 nodes should get boosted
+	ctx.plan.NodeAllocation[nodes[0].Node.ID] = []*structs.Allocation{
+		{
+			Namespace: structs.DefaultNamespace,
+			TaskGroup: tg.Name,
+			JobID:     job.ID,
+			Job:       job,
+			ID:        uuid.Generate(),
+			NodeID:    nodes[0].Node.ID,
+		},
+	}
+	ctx.plan.NodeAllocation[nodes[2].Node.ID] = []*structs.Allocation{
+		{
+			Namespace: structs.DefaultNamespace,
+			TaskGroup: tg.Name,
+			JobID:     job.ID,
+			Job:       job,
+			ID:        uuid.Generate(),
+			NodeID:    nodes[2].Node.ID,
+		},
+	}
+
+	// Reset the scores
+	for _, node := range nodes {
+		node.Scores = nil
+		node.FinalScore = 0
+	}
+	static = NewStaticRankIterator(ctx, nodes)
+	spreadIter = NewSpreadIterator(ctx, static)
+	spreadIter.SetJob(job)
+	spreadIter.SetTaskGroup(tg)
+	scoreNorm = NewScoreNormalizationIterator(ctx, spreadIter)
+	out = collectRanked(scoreNorm)
+
+	// Expect nodes in dc2 with existing allocs to get a boost
+	// dc1 nodes are penalized because they have allocs
+	expectedScores = map[string]float64{
+		"dc1": -0.5,
+		"dc2": 0.01,
+	}
+	for _, rn := range out {
+		require.Equal(t, expectedScores[rn.Node.Datacenter], rn.FinalScore)
+	}
+
+	// Update the plan to add more allocs to nodes in dc2
+	// After this step dc1 nodes should get boosted
+	ctx.plan.NodeAllocation[nodes[1].Node.ID] = []*structs.Allocation{
+		{
+			Namespace: structs.DefaultNamespace,
+			TaskGroup: tg.Name,
+			JobID:     job.ID,
+			Job:       job,
+			ID:        uuid.Generate(),
+			NodeID:    nodes[1].Node.ID,
+		},
+		{
+			Namespace: structs.DefaultNamespace,
+			TaskGroup: tg.Name,
+			JobID:     job.ID,
+			Job:       job,
+			ID:        uuid.Generate(),
+			NodeID:    nodes[1].Node.ID,
+		},
+	}
+	ctx.plan.NodeAllocation[nodes[3].Node.ID] = []*structs.Allocation{
+		{
+			Namespace: structs.DefaultNamespace,
+			TaskGroup: tg.Name,
+			JobID:     job.ID,
+			Job:       job,
+			ID:        uuid.Generate(),
+			NodeID:    nodes[3].Node.ID,
+		},
+	}
+
+	// Reset the scores
+	for _, node := range nodes {
+		node.Scores = nil
+		node.FinalScore = 0
+	}
+	static = NewStaticRankIterator(ctx, nodes)
+	spreadIter = NewSpreadIterator(ctx, static)
+	spreadIter.SetJob(job)
+	spreadIter.SetTaskGroup(tg)
+	scoreNorm = NewScoreNormalizationIterator(ctx, spreadIter)
+	out = collectRanked(scoreNorm)
+
+	// Expect nodes in dc2 to be penalized because there are 3 allocs there now
+	// dc1 nodes are boosted because that has 2 allocs
+	expectedScores = map[string]float64{
+		"dc1": 0.01,
+		"dc2": -0.5,
+	}
+	for _, rn := range out {
+		require.Equal(t, expectedScores[rn.Node.Datacenter], rn.FinalScore)
+	}
+
+	// Add another node in dc3
+	node := mock.Node()
+	node.Datacenter = "dc3"
+	if err := state.UpsertNode(uint64(1111), node); err != nil {
+		t.Fatalf("failed to upsert node: %v", err)
+	}
+	nodes = append(nodes, &RankedNode{Node: node})
+
+	// Add another alloc to dc1, now its count matches dc2
+	ctx.plan.NodeAllocation[nodes[4].Node.ID] = []*structs.Allocation{
+		{
+			Namespace: structs.DefaultNamespace,
+			TaskGroup: tg.Name,
+			JobID:     job.ID,
+			Job:       job,
+			ID:        uuid.Generate(),
+			NodeID:    nodes[4].Node.ID,
+		},
+	}
+
+	// Reset scores
+	for _, node := range nodes {
+		node.Scores = nil
+		node.FinalScore = 0
+	}
+	static = NewStaticRankIterator(ctx, nodes)
+	spreadIter = NewSpreadIterator(ctx, static)
+	spreadIter.SetJob(job)
+	spreadIter.SetTaskGroup(tg)
+	scoreNorm = NewScoreNormalizationIterator(ctx, spreadIter)
+	out = collectRanked(scoreNorm)
+
+	// Expect dc1 and dc2 to be penalized because they have 3 allocs
+	// dc3 should get a boost because it has 0 allocs
+	expectedScores = map[string]float64{
+		"dc1": -0.5,
+		"dc2": -0.5,
+		"dc3": 0.01,
+	}
+	for _, rn := range out {
+		require.Equal(t, expectedScores[rn.Node.Datacenter], rn.FinalScore)
+	}
+
+}