diff --git a/candidate-selection/src/num.rs b/candidate-selection/src/num.rs
index 2c5481c..4acbf38 100644
--- a/candidate-selection/src/num.rs
+++ b/candidate-selection/src/num.rs
@@ -16,6 +16,10 @@ impl Normalized {
         Some(Self(value))
     }
 
+    pub fn clamp(value: f64, min: f64, max: f64) -> Option<Self> {
+        Self::new(value.clamp(min, max))
+    }
+
     pub fn as_inner(&self) -> NotNan<f64> {
         self.0
     }
diff --git a/indexer-selection/src/lib.rs b/indexer-selection/src/lib.rs
index d91d4b9..da53d3f 100644
--- a/indexer-selection/src/lib.rs
+++ b/indexer-selection/src/lib.rs
@@ -157,11 +157,11 @@ fn score_zero_allocation(zero_allocation: bool) -> Normalized {
 /// https://www.desmos.com/calculator/v2vrfktlpl
 pub fn score_latency(latency_ms: u16) -> Normalized {
     let s = |x: u16| 1.0 + E.powf(((x as f64) - 400.0) / 300.0);
-    Normalized::new(s(0) / s(latency_ms)).unwrap()
+    // Since high latency becomes bad success rate via timeouts, latency scores should have a floor.
+    Normalized::clamp(s(0) / s(latency_ms), 0.001, 1.0).unwrap()
 }
 
 /// https://www.desmos.com/calculator/df2keku3ad
 fn score_success_rate(success_rate: Normalized) -> Normalized {
-    let min_score = 1e-8;
-    Normalized::new(success_rate.as_f64().powi(7).max(min_score)).unwrap()
+    Normalized::clamp(success_rate.as_f64().powi(7), 1e-8, 1.0).unwrap()
 }
diff --git a/indexer-selection/src/test.rs b/indexer-selection/src/test.rs
index 41a1dfa..9693d99 100644
--- a/indexer-selection/src/test.rs
+++ b/indexer-selection/src/test.rs
@@ -162,6 +162,62 @@ fn sensitivity_seconds_behind() {
     );
 }
 
+#[test]
+fn sensitivity_seconds_behind_vs_latency() {
+    let candidates = [
+        Candidate {
+            indexer: hex!("0000000000000000000000000000000000000000").into(),
+            deployment: hex!("0000000000000000000000000000000000000000000000000000000000000000")
+                .into(),
+            url: "https://example.com".parse().unwrap(),
+            perf: ExpectedPerformance {
+                success_rate: Normalized::new(0.99).unwrap(),
+                latency_ms: 0,
+            },
+            fee: Normalized::ZERO,
+            seconds_behind: 35_000_000,
+            slashable_grt: 1_600_000,
+            versions_behind: 0,
+            zero_allocation: false,
+        },
+        Candidate {
+            indexer: hex!("0000000000000000000000000000000000000001").into(),
+            deployment: hex!("0000000000000000000000000000000000000000000000000000000000000000")
+                .into(),
+            url: "https://example.com".parse().unwrap(),
+            perf: ExpectedPerformance {
+                success_rate: Normalized::new(0.99).unwrap(),
+                latency_ms: 10_000,
+            },
+            fee: Normalized::ZERO,
+            seconds_behind: 120,
+            slashable_grt: 100_000,
+            versions_behind: 0,
+            zero_allocation: true,
+        },
+    ];
+
+    println!(
+        "score {} {:?}",
+        candidates[0].indexer,
+        candidates[0].score(),
+    );
+    println!(
+        "score {} {:?}",
+        candidates[1].indexer,
+        candidates[1].score(),
+    );
+    assert!(candidates[0].score() <= candidates[1].score());
+
+    let selections: ArrayVec<&Candidate, 3> = crate::select(&candidates);
+    assert_eq!(1, selections.len(), "select exatly one candidate");
+    assert_eq!(
+        Some(candidates[1].indexer),
+        selections.first().map(|s| s.indexer),
+        "select candidate closer to chain head",
+    );
+}
+
 #[test]
 fn multi_selection_preference() {
     let candidates = [