I built a KBO probability and evaluation website — looking for feedback on how it presents predictions
I've been building CIKADA, a website that lets readers explore KBO game predictions and compare them with recorded outcomes.
The site includes:
- Matchup-level win probabilities for both teams.
- Game schedules, starting pitcher information, and bullpen information.
- An archive of prediction records and results.
- Historical evaluation information, including hit rate and Brier score.
- A fan discussion area alongside the analytical content.
The purpose is to let readers inspect more than a predicted winner. They can see the probability assigned to a matchup, explore the game information, and review how past predictions performed.
The site presents its 2025 out-of-sample evaluation separately from current predictions. Retrospective reference records also need to be distinguished from predictions recorded before a game; those aren't interchangeable evidence of model performance.
I spent about eight months on this alongside my day job. AI helped with implementation, while much of my own time went into checking game identities, matching results, and resolving inconsistent records.
Disclosure: this is my own project.
https://www.cikadabaseball.com
I'd welcome feedback on the probability displays and archive. Can you find enough information to assess a prediction, and what additional calibration or baseline comparisons would you want to see?