We have two handball players in our team so we decided to take on this challenge.

What it does

"Handball Prediction" is about easing the life of betting enthusiasts and scouting managers, within one of the Europe's fastest growing sports, by allowing them to make bigger profit with less effort. So the web app predicts the possible performance of the players in each season and the user can see the comparison between the actual and the computed scores.

How we built it

We parsed the actual scores from specialized sites and then we used machine learning to train the model based on different features of the players such as height, number of matches, number of goals etc. The front-end part of the project was build using HTML, CSS, Bootstrap Framework and JavaScript. Then we used Python and Django to integrate the predicted data into the web site. In order to to synchronize our work, we used GitLab environment, and later we switched to GitHub.

Challenges we ran into

Two things that represented an issue in our team were: parsing the data efficiently and fast from the website, and using git without having merge conflicts. Through teamwork and communication, we managed to overcome these problems.

Accomplishments that we're proud of

We are proud because we worked so efficiently as a team, succeeding to build a completely functional and useful web application in only 24 hours.

What we learned

StudentHack has been a great opportunity to learn new things: some of us started to use Visual Studio Code for the first time, we learned how to work with GitKraken and also how to deal with git merge conflicts. We understood how helpful can Beautiful Soup be when parsing data from the internet. Also, some of us improved their Machine Learning skills.

What's next for Handball Prediction

In the future, the next steps in our Handball Prediction project would be replacing the ".gif"s with handmade JavaScript animations and also adding a photo for each users.

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