diff --git a/README.md b/README.md
index e74fb69..e5a0f39 100644
--- a/README.md
+++ b/README.md
@@ -24,7 +24,7 @@ Training of AI bots is the work in progress.
 
 - game rules and game state are implemented in the _store/_ folder.
 - the command-line application is implemented in _client_cli/_; it allows you to play against a bot, or to have two bots play against each other
-- the bots algorithms and the training of their models are implemented in the _bot/_ and _spiel_bot_ folders.
+- the bots algorithms and the training of their models are implemented in the _bot/_ folder
 
 ### _store_ package
 
diff --git a/bot/Cargo.toml b/bot/Cargo.toml
index d24adcc..de957df 100644
--- a/bot/Cargo.toml
+++ b/bot/Cargo.toml
@@ -13,7 +13,7 @@ path = "src/burnrl/main.rs"
 pretty_assertions = "1.4.0"
 serde = { version = "1.0", features = ["derive"] }
 serde_json = "1.0"
-trictrac-store = { path = "../store", features = ["python"] }
+trictrac-store = { path = "../store" }
 rand = "0.9"
 env_logger = "0.10"
 burn = { version = "0.20", features = ["ndarray", "autodiff"] }
diff --git a/client_cli/Cargo.toml b/client_cli/Cargo.toml
index d85dd8b..52318cb 100644
--- a/client_cli/Cargo.toml
+++ b/client_cli/Cargo.toml
@@ -13,7 +13,7 @@ bincode = "1.3.3"
 pico-args = "0.5.0"
 pretty_assertions = "1.4.0"
 renet = "0.0.13"
-trictrac-store = { path = "../store", features = ["python"] }
+trictrac-store = { path = "../store" }
 trictrac-bot   = { path = "../bot" }
 spiel_bot      = { path = "../spiel_bot" }
 itertools = "0.13.0"
diff --git a/spiel_bot/Cargo.toml b/spiel_bot/Cargo.toml
index 1458d66..b541adc 100644
--- a/spiel_bot/Cargo.toml
+++ b/spiel_bot/Cargo.toml
@@ -4,7 +4,7 @@ version = "0.1.0"
 edition = "2021"
 
 [dependencies]
-trictrac-store = { path = "../store", features = ["python"] }
+trictrac-store = { path = "../store" }
 trictrac-bot   = { path = "../bot" }
 anyhow         = "1"
 rand           = "0.9"
diff --git a/spiel_bot/src/mcts/search.rs b/spiel_bot/src/mcts/search.rs
index 4d36acc..1d9750d 100644
--- a/spiel_bot/src/mcts/search.rs
+++ b/spiel_bot/src/mcts/search.rs
@@ -156,13 +156,7 @@ pub(super) fn simulate<E: GameEnv>(
         let returns = env
             .returns(&next_state)
             .expect("terminal node must have returns");
-        let v = returns[player_idx];
-        // Update child stats so PUCT and mcts_policy count terminal visits.
-        // Store from player_idx's perspective so child.q() is directly usable
-        // by the parent's PUCT selection (high = good for the selecting player).
-        child.n += 1;
-        child.w += v;
-        v
+        returns[player_idx]
     } else {
         let child_player = next_cp.index().unwrap();
         let v = if crossed_chance {
@@ -172,13 +166,12 @@ pub(super) fn simulate<E: GameEnv>(
             // previously cached children would be for a different outcome.
             let obs = env.observation(&next_state, child_player);
             let (_, value) = evaluator.evaluate(&obs);
-            // Store from player_idx's (parent's) perspective so PUCT works correctly.
-            // `value` is from child_player's POV; negate when child is the opponent
-            // so that child.q() = expected return for the player CHOOSING this child.
-            // Without the negation, root would maximise the opponent's Q-value and
-            // systematically pick the worst action.
+            // Record the visit so that PUCT and mcts_policy use real counts.
+            // Without this, child.n stays 0 for every simulation in games where
+            // every player action is immediately followed by a chance node (e.g.
+            // Trictrac), causing mcts_policy to always return a uniform policy.
             child.n += 1;
-            child.w += if child_player == player_idx { value } else { -value };
+            child.w += value;
             value
         } else if child.expanded {
             simulate(child, next_state, env, evaluator, config, rng, child_player)
diff --git a/store/Cargo.toml b/store/Cargo.toml
index fbb4f6d..935a2a0 100644
--- a/store/Cargo.toml
+++ b/store/Cargo.toml
@@ -12,10 +12,6 @@ name = "trictrac_store"
 # "staticlib" → used by the C++ OpenSpiel game (cxxengine)
 crate-type = ["cdylib", "rlib", "staticlib"]
 
-[features]
-# Enable Python bindings (required for maturin / AI training). Not available on wasm32.
-python = ["pyo3"]
-
 [dependencies]
 anyhow = "1.0"
 base64 = "0.21.7"
@@ -24,7 +20,7 @@ cxx = "1.0"
 log = "0.4.20"
 merge = "0.1.0"
 # generate python lib (with maturin) to be used in AI training
-pyo3 = { version = "0.23", features = ["extension-module", "abi3-py38"], optional = true }
+pyo3 = { version = "0.23", features = ["extension-module", "abi3-py38"] }
 rand = "0.9"
 serde = { version = "1.0", features = ["derive"] }
 transpose = "0.2.2"
diff --git a/store/src/lib.rs b/store/src/lib.rs
index 25d2dcb..4fc8dff 100644
--- a/store/src/lib.rs
+++ b/store/src/lib.rs
@@ -20,7 +20,6 @@ pub use dice::{Dice, DiceRoller};
 pub mod training_common;
 
 // python interface "trictrac_engine" (for AI training..)
-#[cfg(feature = "python")]
 mod pyengine;
 
 // C++ interface via cxx.rs (for OpenSpiel C++ integration)
diff --git a/store/src/player.rs b/store/src/player.rs
index cca02b5..1e48593 100644
--- a/store/src/player.rs
+++ b/store/src/player.rs
@@ -1,4 +1,3 @@
-#[cfg(feature = "python")]
 use pyo3::prelude::*;
 use serde::{Deserialize, Serialize};
 use std::fmt;
@@ -6,7 +5,7 @@ use std::fmt;
 // This just makes it easier to dissern between a player id and any ol' u64
 pub type PlayerId = u64;
 
-#[cfg_attr(feature = "python", pyclass(eq, eq_int))]
+#[pyclass(eq, eq_int)]
 #[derive(Copy, Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
 pub enum Color {
     White,