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Fixes #776 MMA Fight Prediction #777

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Nov 5, 2024
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Fixes #776 MMA Fight Prediction #777

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Fixes #776
Varunshiyam Nov 5, 2024
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Create Readme.md
Varunshiyam Nov 5, 2024
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45 changes: 45 additions & 0 deletions Prediction Models/MMA_Fight_prediction/Readme.md
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# MMA Fight Prediction Model

This repository contains a machine learning model designed to predict the outcome of MMA fights. Using historical data and various fighter statistics, the model aims to determine the probability of each fighter winning a given matchup.

## Table of Contents
- [Introduction](#introduction)
- [Problem Statement](#problem-statement)
- [Model Overview](#model-overview)
- [Data](#data)
- [Installation](#installation)
- [Usage](#usage)
- [Results](#results)
- [Contributing](#contributing)
- [License](#license)

## Introduction

Predicting the outcome of MMA fights is challenging due to the high variability of the sport. Factors such as a fighter's style, reach, weight, previous fight record, and current form all influence the fight outcome. This project explores using machine learning techniques to analyze fight data and predict the probability of each fighter winning a matchup.

## Problem Statement

MMA fight outcomes are influenced by numerous factors, many of which are dynamic and hard to quantify. This project aims to address:
- **Outcome Variability**: Accurately predicting outcomes amid unpredictable events and variations.
- **Data Limitations**: Working with potentially sparse or incomplete historical data.
- **Feature Engineering**: Identifying significant features to improve prediction accuracy.
- **Generalization**: Ensuring the model works well across various fighters and events.

## Model Overview

The model uses historical fight data and fighter statistics to predict fight outcomes. It leverages a mix of machine learning techniques, such as:
- Logistic Regression
- Decision Trees
- Ensemble Methods

Key features include fighter-specific data like win-loss records, average fight time, strike accuracy, and takedown success rate. By training on historical fight outcomes, the model aims to generalize to future fight predictions.

## Data

The model is built using historical MMA data, which includes:
- Fighter statistics: strikes, takedowns, reach, weight, etc.
- Fight records: win/loss record, recent performance, and historical matchup outcomes.
- Event details: location, fight date, and weight class.

**Note**: Data files should be placed in the `data/` directory in CSV format. Example data files are provided in the repository.

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