redback-fit-sports-performance

This repository contains information related to sports performance analysis project.

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Redback Operations - Sports Performance Analysis

Overview

Welcome to the Sports Performance Analysis project by Redback Operations! Our platform is designed to provide insightful analysis in football, cricket, and cycling.

Features

Football Analysis:

1. EPL Data Analysis:

   • Explore EPL data to gain insights into team and player performance.
   • Visualize team standings, goal differentials, and scoring patterns.

2. Cleaned EPL Results Data:

   • Utilize cleaned EPL results data for accurate trend analysis.
   • Showcase historical match outcomes and key performance indicators.

Cricket Analysis:

1. 2023 World Cup Data:

   • Analyze player and team statistics from the 2023 Cricket World Cup.
   • Identify standout performances and key trends during the tournament.

2. IPL Data Analysis:

   • Explore IPL data for valuable insights into player and team dynamics.
   • Visualize team strategies, player contributions, and match outcomes.

3. Predictive Analysis of Player Performance:

   • Develop models to forecast player performances based on historical data.
   • Evaluate model accuracy and provide recommendations for player selection.

4. Toss Decision Analysis on T20 2022 World Cup:

   • Investigate the impact of toss decisions on match outcomes.
   • Provide statistical evidence on the correlation between toss decisions and winning teams.

5. Historical Data of T20 World Cup Venues (2022):

   • Explore historical data of venues where the T20 World Cup 2022 matches occurred.
   • Provide insights into pitch conditions, team performances, and winning trends at each venue.

Cycling Analysis:

1. Data Exploration Programs:

   • Develop Python code for exploring cycling performance datasets.
   • Create basic predictive models to assess data reliability.

2. Strava Export Programs:

   • Implement programs to extract data from Strava using the Strava API and web scraping.
   • Compare different methods for data extraction and evaluate their reliability.

3. Cyclist Data (2023 T2 Redback Operations Project):

   • Analyze cyclist data from the 2023 T2 Redback Operations project.
   • Address issues in the dataset, such as invalid data in duration fields.

4. Strava Data Dump and Cleaning:

   • Explain the process of downloading a Strava data dump and cleaning the data.
   • Highlight challenges faced and solutions implemented during the data cleaning process.

5. Data Format:

   • Store cycling data in .csv and .xlsx formats for convenient analysis.

6. Documentation:

   • Include links to detailed documentation describing cycling data and its issues.
   • Refer users to resources on downloading Strava files and bulk export options.