We are a team of foosball enthusiasts hoping to introduce our love of the game to everyone! Foosball is the perfect sport - it combines the pure adrenaline and competitiveness created by (non-American) football with the convenience and dexterity needed in an indoor sport. Among a group of friends, there is always much debate about who is objectively the best foosball player. With Foosrank, you can finally settle this for once and for all (while watching riveting replays of your best shots)!

What it does

Foosrank is an ELO-based foosball automation & analysis system. It keeps track of your previous games, records and calculates your relative rating, and provides instant video replays of points.

As a player, you get features including: Statistics about your previous games ELO graph over time Live stream (with a red box tracking the ball) as point is being played out Instant replays when goals are scored Automatic point tracking using sensors of photoresistors and LEDs

How we built it

We built it from a previous project that 2 of us created, Foosrank (this was done with permission from the HackMIT organizers). Foosrank was an webapp that just offered players ELO calculation rankings and none of the other features we mentioned above, but our work on FoosTrack during this hackathon takes it to the next level.

We used the following technologies / hardware to make FoosTrack: Arduino LEDs and photoresistors Raspberry Pi v1 + camera with Python Google Firebase Nose.js with HTML, CSS, Javascript

Challenges we ran into

The wiki on the Raspberry Pi was extremely slow, so installing packages took many tries, and we had to find workarounds in order to ensure that we could still image process in real time.

Accomplishments that we're proud of

We’re proud that we were able to create an image processing algorithm to accurately track the ball. In addition, as we have little previous experience in hardware, we feel accomplished that we were able to successfully create a stand for the camera above the foosball table, solder components togehrer, and use the sensors in the arduino and the raspberry pi to realize our final goal.

What we learned

We learned a lot about how to use Raspberry Pis and cameras. We also experimented a lot with different heuristics to track the ball in the video.

What's next for Foosrank

In the future, we hope to continue adding features to Foosrank with the goal of making the user experience as intuitive and convenient as possible. This includes implementing facial recognition in lieu of google / typing authentication, building a studier stand for long-term durability, keeping track of statistics on goal shots from specific foosball figures on the foosball table, and refining our image processing algorithm.

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