Social Network Analysis of Sports Community
Social network analysis about any sports in a particular event can help a lot in predicting to which country/team people are supporting the most. This project comprises of a web application that contains all type of predictions about a particular event of a sport, the predictions are shown graphical
2025-06-28 16:36:00 - Adil Khan
Social Network Analysis of Sports Community
Project Area of Specialization Internet of ThingsProject SummarySocial network analysis about any sports in a particular event can help a lot in predicting to which country/team people are supporting the most. This project comprises of a web application that contains all type of predictions about a particular event of a sport, the predictions are shown graphically. Social network prediction is based on likeliness of people in social media platform like twitter, so for this we will scrape the data. In addition to these two more types of predictions will be shown i.e., before event prediction which is based on previous team/country stats (each player total score, strike rate, bowling economy, batting average and bowling average) and during event prediction which is based on team’s previous performance and during event team performance. This project aims to provide full sport analysis where the visitor can also vote for his/her favorite team/country. During event points table of all teams/countries will be shown followed by the predictions. This project will help people by providing a single platform where they can examine their team performance, future predictions and can vote for their team. Representing the most favorite teams among people will help sports analyst in predicting which team can win the event.
Project ObjectivesThis application will provide full sports analysis, along with social network prediction there is another prediction graph which will show before event prediction. It is based on past performance of in squad players and overall team performance. The performance stats are crawled from different official sports sites. An efficient algorithm is designed that provides a performance number for each player and team which are further manipulated to provide an overall performance number of each team on behalf of which prediction meter shows prediction.
There is a third and final prediction graph in this application that will show during event prediction. It is based on current performance of team and players in the event, their previous performance stats at that venue in the upcoming match and they’re before event performance stats.
At the bottom of the prediction meters there is a performance table of all the teams participating in the event. It will show number of matches played by a team, number of matches won and loss by a team and total number of points in the event against team name.
After performance table there will be an option of polling. The user can vote for his/her favorite team which will affect social network prediction accordingly. For this there will be a signup option, user has to create an account providing his/her basic personal information
Project Implementation Method- Python
- PHP
- Bootstrap
- HTML 5
- CSS 3
- JavaScript
- Microsoft Word, Power point
- Face pager
This project aims to provide full sports analysis where the visitors can vote for their favorite team. We will predict winning and losing teams depending upon various factors. We will provide a platform where people can examine different statistics regarding teams, go through to the chances of their team to win or lose, their previous performances in specific country or playing venue etc.
Technical Details of Final DeliverableThe functional requirements of the purpose system are listed as follow:
Admin:
- Login
- Signup
- View Users
- Remove Users
- Add Events
- Remove Events
- Create poll
- Poll Analysis
- Update admin information
- Change Password
User:
- Login
- Signup
- Receive Notification
- View Live Events
- View Prediction Graph
- Cast vote
- View Final Results of Prediction
- View Score Board
- Update Information
- Forgot Password
- View Team/Player Performance
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 70000 | |||
| High End Laptop | Equipment | 1 | 70000 | 70000 |