diff --git a/src/model/binary.rs b/src/model/binary.rs
index 97f0041..b090af8 100644
--- a/src/model/binary.rs
+++ b/src/model/binary.rs
@@ -142,7 +142,9 @@ impl BinaryModel {
         elems.extend(self.process_items(team_2, -1.0));
 
         let prob = match self.win_obs {
-            BinaryModelObservation::Probit => probit_win_observation(&elems, t, 0.0, &self.storage),
+            BinaryModelObservation::Probit => {
+                ProbitWinObservation::probability(&self.storage, &elems, t, 0.0)
+            }
             BinaryModelObservation::Logit => todo!(),
         };
 
diff --git a/src/model/ternary.rs b/src/model/ternary.rs
index 729f616..ba577e7 100644
--- a/src/model/ternary.rs
+++ b/src/model/ternary.rs
@@ -169,14 +169,14 @@ impl TernaryModel {
 
         let prob_1 = match self.obs {
             TernaryModelObservation::Probit => {
-                probit_win_observation(&elems, t, margin, &self.storage)
+                ProbitWinObservation::probability(&self.storage, &elems, t, margin)
             }
             TernaryModelObservation::Logit => unimplemented!(),
         };
 
         let prob_2 = match self.obs {
             TernaryModelObservation::Probit => {
-                probit_tie_observation(&elems, t, margin, &self.storage)
+                ProbitTieObservation::probability(&self.storage, &elems, t, margin)
             }
             TernaryModelObservation::Logit => unimplemented!(),
         };
diff --git a/src/observation/ordinal.rs b/src/observation/ordinal.rs
index 370829d..473ea22 100644
--- a/src/observation/ordinal.rs
+++ b/src/observation/ordinal.rs
@@ -3,18 +3,6 @@ use crate::utils::logphi;
 
 use super::{f_params, Core, Observation};
 
-pub fn probit_win_observation(
-    elems: &[(usize, f64)],
-    t: f64,
-    margin: f64,
-    storage: &Storage,
-) -> f64 {
-    let (m, v) = f_params(&elems, t, &storage);
-    let (logpart, _, _) = mm_probit_win(m - margin, v);
-
-    logpart.exp()
-}
-
 fn mm_probit_win(mean_cav: f64, cov_cav: f64) -> (f64, f64, f64) {
     // Adapted from the GPML function `likErf.m`.
     let z = mean_cav / (1.0 + cov_cav).sqrt();
@@ -37,6 +25,13 @@ impl ProbitWinObservation {
             margin,
         }
     }
+
+    pub fn probability(storage: &Storage, elems: &[(usize, f64)], t: f64, margin: f64) -> f64 {
+        let (m, v) = f_params(&elems, t, &storage);
+        let (logpart, _, _) = mm_probit_win(m - margin, v);
+
+        logpart.exp()
+    }
 }
 
 impl Observation for ProbitWinObservation {
@@ -81,15 +76,6 @@ impl Observation for LogitWinObservation {
     }
 }
 
-pub fn probit_tie_observation(
-    _elems: &[(usize, f64)],
-    _t: f64,
-    _margin: f64,
-    _storage: &Storage,
-) -> f64 {
-    unimplemented!();
-}
-
 pub struct ProbitTieObservation {
     //
 }
@@ -98,6 +84,10 @@ impl ProbitTieObservation {
     pub fn new(_storage: &mut Storage, _elems: &[(usize, f64)], _t: f64, _margin: f64) -> Self {
         todo!();
     }
+
+    pub fn probability(storage: &Storage, elems: &[(usize, f64)], t: f64, margin: f64) -> f64 {
+        todo!();
+    }
 }
 
 impl Observation for ProbitTieObservation {