Sports Sphere

Inspiration

People who move to a new city, switch colleges, travel temporarily, or simply want to expand their friend circle struggle to find others to play sports with. Existing options (general social networks, meetup pages, local groups) are noisy, slow, and unspecific — it’s hard to find someone: who plays the same sport at the same skill level, at the same time window and nearby location, and who wants the same type of session (casual pickup, competitive scrimmage, coached session, or Esports squad). Consequences: missed opportunities, less social connection, underused local facilities, and fragmented casual sports communities.

What it does

Our app is a sports-based social platform that helps people quickly find others to play with—whether it’s outdoor sports (football, cricket, badminton, basketball, etc.) or Esports (Valorant, BGMI, FIFA, etc.). It solves the problem of “I want to play, but I have no one to play with.”

How we built it

We built it using Base 44.

Challenges we ran into

Users expect nearby matches, but exact GPS feels creepy. Workaround: Stored only approximate locations (neighborhood + distance buckets) and showed distance ranges Showing live session updates and presence (who’s online / joined) caused high update churn. Matching by sport, role, skill level, time overlap and distance quickly becomes combinatorial. Workaround: Built a simple weighted scoring function (distance + skill delta + availability overlap) and deterministic filters for MVP.

Accomplishments that we're proud of

We designed, developed, and deployed a complete end-to-end app that lets users sign up, discover players, create/join sports sessions, and chat — all within the hackathon timeframe. Successfully built a matching flow that connects people based on sport, skill level, availability, and location. Users can find relevant partners or teams instantly.

What we learned

We learned that focusing on the main value (matching players + joining sessions) early helps us move fast, avoid distractions, and deliver something that actually works. Handling live location updates, chat, and session changes taught us about debouncing, optimizing queries, and reducing unnecessary reads/writes to keep the app smooth.

What's next for SquadSync

We plan to improve our matchmaking by analyzing: play frequency, preferred times, skill patterns, past successful matches This will help us recommend the best teammates automatically.

Built With

• 44
• base