From 1c32f0304f75f40cb737ac3e608803dba673b189 Mon Sep 17 00:00:00 2001
From: Haoran Hua <haohu678@student.liu.se>
Date: Thu, 17 Apr 2025 23:15:20 +0000
Subject: [PATCH] Update file README.md

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-# Predicting Ice Hockey Goals Using Random Forest and XGBoost
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 ## Intro
 Our project aims to predict goal outcomes in ice hockey by leveraging over 500,000 event-level entries from the Linhac24-25 dataset. Treating it as a binary classification task, the research focuses on identifying key factors—such as puck position, game state, and player context—that influence the likelihood of scoring. The motivation lies in improving tactical insights, player evaluation, and fan engagement by understanding which in-game situations most frequently lead to goals.
 
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GitLab