BetSense: Dual Insights for Fans & Bookies

From fans tracking bets to bookmakers managing risk, this project tells one story through two perspectives: excitement for fans and clarity for operators.

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Project Story: BetSense

Inspiration

As sports fans ourselves, we’ve often looked at betting platforms and wondered:

  • Where are most people putting their money?
  • Which outcomes actually pay out more often?
  • How can I make a smarter choice before placing a bet?

At the same time, we realized bookies need the exact opposite perspective; they worry about payouts, profitability, and exposure.

That’s when the idea clicked: why not build a dual-view dashboard that serves both sides of the story?

BetSense was born to empower fans like us with insights to bet smarter, while also giving bookies a clear view of their risk and revenue.

What We Learned

  • Betting data can look messy, but with the right semantic model, it becomes a powerful story.
  • Even with the same dataset, fans and bookies ask very different questions: designing for both taught us a lot about user-centered thinking.
  • KPIs like Net Profit, Exposure, Stake Distribution, and Payout Ratio are not just numbers, they represent confidence and decision-making power for the people using them.

How We Built It

  1. Semantic Model: Defined core entities. Events, Bets, Outcomes, and Transactions — to capture how bets flow from fans to payouts.
  2. Fan View Dashboard:
    • KPIs: Total Stake, Number of Bets, Avg Stake, Total Payouts
    • Charts: Top Events by Stake, Stake Distribution by Outcome, Historical Payouts, Bet Volume by Time
    • Goal: Help a fan see trends and decide which event and outcome might be worth betting on.
  3. Admin (Bookie) View Dashboard:
    • KPIs: Net Profit, Payout Ratio, Avg Profit per Bet, Highest Exposure
    • Charts: Stake Over Time, Bets by Weekday, Bet Size Distribution, Exposure by Outcome
    • Goal: Help bookies understand where they make money, where they risk losses, and how betting behavior changes over time.

Challenges

  • Making odds human-friendly: Decoding line values (like -110, +108) and spreads (like -3.5) was harder than expected, but critical for telling the betting story.
  • Too many ideas, too little space: We had to cut down to the most impactful KPIs and charts that could fit cleanly into one dashboard each.
  • Design balance: We constantly had to ask ourselves, Does this insight help a fan? Or is it only useful for a bookie? That balance was tricky but rewarding.

Headline

BetSense: Smarter Insights for Fans, Sharper Decisions for Bookies

Future Work

  • Add real-time odds updates so fans see the freshest data.
  • Use predictive models to forecast likely outcomes and payouts.
  • Personalize dashboards: fans could see recommendations based on their betting style, while bookies could flag risky outcomes faster.

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