train_test_split random_state not working; produces different output everytime

So, I've been using KNN on a set of data, with a random_state = 4 during the train_test_split phase. Despite of using the random state, the output of accuracy, classification report, prediction, etc, are different each time. Was wondering why was that?

Here's the head of the data: (predicting the position based on all_time_runs and order)

order position  all_time_runs
0     10   NO BAT           1304
1      2  CAN BAT           7396
2      3   NO BAT           6938
3      6  CAN BAT           4903
4      6  CAN BAT           3761

And here's the code for the classification and prediction:

#splitting data into features and target

X = posdf.drop('position',axis=1)
y = posdf['position']   


knn = KNeighborsClassifier(n_neighbors = 5)

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.3, random_state = 42)

#fitting the KNN model
knn.fit(X_train, y_train)

#predicting with the model
prediction = knn.predict(X_test)

#knn score
score = knn.score(X_test, y_test)