diff --git a/src/factor_graph.rs b/src/factor_graph.rs
new file mode 100644
index 0000000..e6f6ce7
--- /dev/null
+++ b/src/factor_graph.rs
@@ -0,0 +1,54 @@
+use std::cmp;
+
+use gaussian::Gaussian;
+
+pub struct Variable {
+    gaussian: Gaussian,
+}
+
+impl Variable {
+    pub fn new() -> Variable {
+        Variable {
+            gaussian: Gaussian::new(0.0, 0.0),
+        }
+    }
+
+    fn delta(&self, other: &Variable) -> f32 {
+        let pi_delta = self.gaussian.pi - other.gaussian.pi;
+
+        if pi_delta.is_infinite() {
+            0.0
+        } else {
+            let tau_delta = (self.gaussian.tau - other.gaussian.tau).abs();
+
+            if pi_delta > tau_delta {
+               pi_delta
+            } else {
+                tau_delta
+            }
+        }
+    }
+}
+
+pub trait Factor {
+    fn down(&self) -> f32 {
+        0.0
+    }
+}
+
+pub struct PriorFactor {
+    variable: Variable,
+    dynamic: f32
+}
+
+impl PriorFactor {
+    pub fn new(variable: Variable, dynamic: f32) -> PriorFactor {
+        PriorFactor { variable, dynamic }
+    }
+}
+
+impl Factor for PriorFactor {
+    fn down(&self) -> f32 {
+        0.0
+    }
+}
diff --git a/src/gaussian.rs b/src/gaussian.rs
new file mode 100644
index 0000000..702b677
--- /dev/null
+++ b/src/gaussian.rs
@@ -0,0 +1,10 @@
+pub struct Gaussian {
+    pub pi: f32,
+    pub tau: f32,
+}
+
+impl Gaussian {
+    pub fn new(pi: f32, tau: f32) -> Gaussian {
+        Gaussian { pi, tau }
+    }
+}
diff --git a/src/lib.rs b/src/lib.rs
index e771301..812f6c6 100644
--- a/src/lib.rs
+++ b/src/lib.rs
@@ -1,6 +1,9 @@
 mod matrix;
+mod factor_graph;
+mod gaussian;
 
 use matrix::Matrix;
+use factor_graph::*;
 
 /// Default initial mean of ratings.
 const MU: f32 = 25.0;
@@ -35,6 +38,38 @@ impl Default for Rating {
     }
 }
 
+
+fn _team_sizes(rating_groups: &[&[Rating]]) -> Vec<usize> {
+    let mut team_sizes = Vec::new();
+
+    for group in rating_groups {
+        let last = team_sizes.last().map(|v| *v).unwrap_or(0);
+
+        team_sizes.push(group.len() + last);
+    }
+
+    team_sizes
+}
+
+fn factor_graph_builders(rating_groups: &[&[Rating]]) {
+    let flatten_ratings = rating_groups
+        .iter()
+        .flat_map(|group| group.iter())
+        .collect::<Vec<_>>();
+
+    let flatten_weights = vec![1.0; flatten_ratings.len()].into_boxed_slice();
+
+    let size = flatten_ratings.len();
+    let group_size = rating_groups.len();
+
+    let rating_vars = (0..size).map(|_| Variable::new()).collect::<Vec<_>>();
+    let perf_vars = (0..size).map(|_| Variable::new()).collect::<Vec<_>>();
+    let team_perf_vars = (0..group_size).map(|_| Variable::new()).collect::<Vec<_>>();
+    let team_diff_vars = (0..group_size - 1).map(|_| Variable::new()).collect::<Vec<_>>();
+
+    let team_sizes = _team_sizes(rating_groups);
+}
+
 fn rate(rating_groups: &[&[Rating]]) {
     let ranks = (0..rating_groups.len()).collect::<Vec<_>>();
     let weights = vec![1.0; rating_groups.len()];