SportsConnect

Inspiration

Athletes are often disconnected from the public and seen as a statistic or a number rather than being treated like a normal human being. We felt like this was a theme that has been going on for too long, and change needed to come. Athletes have quite high depression rates, and their mental health isn’t the best. We wanted to also connect fans that felt disconnected from athletes and felt like they were on an entire other level. We wanted to create a web app that connects users and athletes and shows empathy towards athletes, as well as improving the users experience.

What it does

SportsConnect asks you a few general questions and then based on the inputs you provided gives you the most relatable athlete to you from a dataset created by KindoAI. Then, the traits you share with that athlete are listed, and a summary is provided about the athlete using KindoAI. The summary is for the user to get to know more about the athlete, and not just statistics, but also about their life. Then, the next page is when the user can see the database of athletes and see which one they are relatable to by simply picking the athlete. We believe that this simple feature is effective, and engages the user.

How we built it

We built it by first visualizing our model which we did by using the Kindo AI agent to create a workflow for the inspiration for our desired goal. We built the web user interface by utilizing javascript, html, and css along with the help of Kindo whose API we utilized to get customized summary for each athlete.

Challenges we ran into

We had a difficult time learning how to utilize APIs for Kindo, and how to incorporate these to our project. Since all of us have little to no experience in web development or utilizing javascript, html or css, we struggled a lot trying to learn how to make a web application, but we gradually learned with the help of Kindo and its AI models, such as GPT-4o and WhiteRabbitNeo. This project took us way longer than it should have, but it was extremely rewarding and gave ideas for our future projects and things to consider.

Accomplishments that we're proud of

We are proud of successfully finishing the project with satisfiable outcome, especially since it's our first time at a hackathon and first time working together. The first two-thirds of the hackathon was a big struggle for us, being new to almost everything we are using for our project, but we are really proud that we managed to get pass that and agreed on the fact that we learned so many lessons from this hackathon.

What we learned

The first few hours were exhausting, the following few hours were confusing, but they were are really rewarding. We learned to integrate KindoAI and successfully use the API, which will make our future projects much more effective utilizing APIs. We also learned how to manage CSS using LLM, and I believe that was one of the most successful things we learned. Our coding abilities also grew, quite exponentially. We also learned how to use KindoAI to its capabilities, as we were basically using it for everything, including the codes, and designing the web pages.

What's next for SportsConnect

The project on a bigger scale is what is the biggest demand so far, and this will be possible with more time spent on creating a larger dataset and improving the css, javascript, and the html files. This comes with time to improve and learn like this hackathon, and I believe SportsConnect can be the next “big” trend for youth to connect to athletes. Many people use applications like “Wordle” or “Akinator,” and SportsConnect is similar to these web apps as it is a quick, engaging activity for users to interact and spend time with.