Jump Height Prediction in Volleyball

Project Overview:

• Using data from the teams of the Volleyball Nations League
• Performing a simple linear regression
• Creating a simple Webapp with Flask

Introduction:

In the following project, I gathered few data from professional Volleyballplayers. Based on their age, height and weight I build a simple regression model. The question I asked myself was: Can I predict the spike height and block height of a player based on this variables? But the maintask for me was to (finally!) deploy a model on a webapp. Therefore I used Flask and the resources listed below.

Usage

To use this model you need to download the data and the three .py files. Then you go to the Regression.py and enter the right sourcepath. After running the Regression.py you can go to your Anaconda Prompt. Type in:

1. cd "C:....yourpath..."
2. python webapp.py

After you run the app, you can copy the appearing adress to your browser. Now you can enter some values. Have fun!

Further Steps:

Adding more data would be benefitial for the accuracy of the prediction. Additionally one can think about finetuning the visual appearance of this simple Web-Application.

Resources:

• https://github.com/krishnaik06/Deployment-flask (Good tutorial and baseline for my code on how to build a webapp with Flask)