diff --git a/src/model.rs b/src/model.rs
index 4383481..f4dc6f8 100644
--- a/src/model.rs
+++ b/src/model.rs
@@ -326,8 +326,8 @@ fn derive_prices(
 
     let runners = weighted_probs.cols();
     let mut counts = Matrix::allocate(PODIUM, runners);
-    let all_selections = selection::top_n_matrix(PODIUM, runners);
-    engine.simulate_batch(all_selections.flatten(), counts.flatten_mut());
+    let top_n_selections = selection::top_n_matrix(PODIUM, runners);
+    engine.simulate_batch(top_n_selections.flatten(), counts.flatten_mut());
 
     let mut derived_probs = Matrix::allocate(PODIUM, runners);
     for runner in 0..runners {
diff --git a/src/model/fit.rs b/src/model/fit.rs
index e084d31..e452443 100644
--- a/src/model/fit.rs
+++ b/src/model/fit.rs
@@ -87,13 +87,13 @@ pub fn fit_all(options: &FitOptions, markets: &[Market]) -> Result<AllFitOutcome
         .with_podium_places(model::PODIUM)
         .into();
 
-    let all_selections = selection::top_n_matrix(model::PODIUM, num_runners);
+    let top_n_selections = selection::top_n_matrix(model::PODIUM, num_runners);
 
     let outcomes: Vec<_> = (1..model::PODIUM)
         .map(|rank| {
             let market = &markets[rank];
             let outcome = fit_individual(
-                &all_selections,
+                &top_n_selections,
                 &weighted_probs,
                 options.mc_trials,
                 options.individual_target_msre,
@@ -166,9 +166,9 @@ pub fn fit_place(
 ) -> Result<PlaceFitOutcome, anyhow::Error> {
     options.validate()?;
     let num_runners = place_market.probs.len();
-    let all_selections = selection::top_n_matrix(model::PODIUM, num_runners);
+    let top_n_selections = selection::top_n_matrix(model::PODIUM, num_runners);
     let outcome = fit_individual(
-        &all_selections,
+        &top_n_selections,
         weighted_probs,
         options.mc_trials,
         options.individual_target_msre,
@@ -217,7 +217,7 @@ pub struct IndividualFitOutcome {
 }
 
 fn fit_individual(
-    all_selections: &Matrix<Selections>,
+    top_n_selections: &Matrix<Selections>,
     weighted_probs: &Matrix<f64>,
     mc_trials: u64,
     target_msre: f64,
@@ -245,7 +245,7 @@ fn fit_individual(
             Rank::index(rank)
         );
         let mut counts = Matrix::allocate(podium_places, runners);
-        engine.simulate_batch(all_selections.flatten(), counts.flatten_mut());
+        engine.simulate_batch(top_n_selections.flatten(), counts.flatten_mut());
         let fitted_probs: Vec<_> = counts
             .row_slice(rank)
             .iter()
diff --git a/src/selection.rs b/src/selection.rs
index 6f50955..3865d31 100644
--- a/src/selection.rs
+++ b/src/selection.rs
@@ -214,13 +214,13 @@ impl<'a> FromStr for Selections<'a> {
 
 /// Builds a `podium_places` x `num_runners` matrix populated with top-_N_ selections.
 pub fn top_n_matrix(podium_places: usize, num_runners: usize) -> Matrix<Selections<'static>> {
-    let mut all_selections = Matrix::allocate(podium_places, num_runners);
+    let mut top_n_selections = Matrix::allocate(podium_places, num_runners);
     for runner in 0..num_runners {
         for rank in 0..podium_places {
-            all_selections[(rank, runner)] = vec![Runner::index(runner).top(Rank::index(rank))].into();
+            top_n_selections[(rank, runner)] = vec![Runner::index(runner).top(Rank::index(rank))].into();
         }
     }
-    all_selections
+    top_n_selections
 }
 
 pub fn validate_plausible_selections(selections: &[Selection]) -> Result<(), anyhow::Error> {