From 457ea41e94cfd6a088fce815e829d5b63f9b1742 Mon Sep 17 00:00:00 2001
From: maeries <8ij4neqiu@mozmail.com>
Date: Sun, 23 Mar 2025 21:28:12 +0100
Subject: [PATCH] added k factor validation and set k accordingly
---
main.py | 26 +++++++++++++++++++++++++-
1 file changed, 25 insertions(+), 1 deletion(-)
diff --git a/main.py b/main.py
index 4fa5a3a..988983b 100644
--- a/main.py
+++ b/main.py
@@ -16,7 +16,7 @@ from tools import *
from world_ranking_list import get_world_ranking_html
# Constants for Elo calculation
-K_FACTOR = 10
+K_FACTOR = 15
INITIAL_ELO = 1500 # Starting Elo for all teams
@@ -467,6 +467,30 @@ class EloSystem:
dpi=100)
plt.close()
+ def optimize_k(self):
+ self.load_and_process_csv_files()
+ error_history = []
+ for comp in self.competition_history:
+ if self.get_competition_name(comp) in ("DE", "EA", "AT", "NL", "AA", "ES", "UK", "IT", "CZ", "CH"):
+ if 2020 > self.get_competition_date(comp).year > 2016:
+ results = self.competition_history[comp]['results']
+ error = 0
+ for result in results:
+ error = error + abs(result[3] / K_FACTOR)
+ error = error / len(results)
+ error_history.append(error)
+ pass
+ # calculate RMSE of the list of error
+ squared_errors = [error ** 2 for error in error_history]
+ mean_squared_error = sum(squared_errors) / len(squared_errors)
+ rmse = math.sqrt(mean_squared_error)
+
+ print(f"K of {K_FACTOR} results in a prediction RMSE of {rmse}")
+
+
+def run_optimize_k():
+ elo_system = EloSystem('csv_files', 'public/elo_website_combustion', "combustion")
+ elo_system.optimize_k()
def main():
"""Main function to run the Elo ranking system"""
--
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