Inspiration
As an avid soccer fan, I always rooted for the top soccer teams of my childhood, particularly FC Barcelona and FC Manchester. With other friends I knew that wanted to predict the best team, I decided to undertake a program to predict a sport.
What it does
This program predicts the outcome of soccer games with past data. From past competitions to the most recent world cup victories, the program will be able to go through this data to output the predicted team.
How we built it
We decided to utilize the Python programming language. Libraries such as Matplotlib pandas sklearn and etc.
Challenges we ran into
Seemingly simple compilation errors led to complicated searching to remedy the problem. Some individual lines had issues due to improper formatting. In addition, training the dataset was time-consuming, due to the large amount of data passed in. This led to issues with fine-tuning the prediction.
Accomplishments that we're proud of
I was able to understand machine learning with the knowledge only a tangible project could lend. It was difficult, yet I was proud of how this project helped to strengthen my Python skills.
What we learned
I learned how to utilize pandas not only for data analysis, but to train data. I learned how to predict outcomes using other machine learning libraries, and the most efficient ways to do so.
What's next for Sports Analyzer
Eventually, I want to find more accurate sports data to improve predictions.
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