Sports Betting Model Backtester

I have a collection of Excel spreadsheets with historical bet data and I need a Windows-based desktop app, complete with a straightforward GUI, that can back-test the profitability of my sports-betting models. The core task is to ingest those spreadsheets, let me apply custom filters, and instantly return key performance metrics such as yield, ROI, and max drawdown.

The app must handle football, basketball, tennis and other sports data. While testing a strategy I need to be able to narrow results by league, team, specific odds ranges, as well as more nuanced factors like dropping odds or average odds movements across multiple bookmakers. Whenever I adjust a filter, the results and charts should refresh on the fly so I can see the impact immediately.

A clean layout with import-file browsing, filter panels, and an output area for tables and charts is essential. Under the hood I am flexible on the tech stack—whether you prefer C#/WPF, Python with PyQt or Tkinter, or another Windows-friendly framework—so long as the final executable runs smoothly on current Windows versions without extra setup.

Deliverables
• Compiled Windows executable and full source code
• GUI that imports .xlsx/.csv files, applies the filters above, and outputs yield, ROI, max drawdown (plus total profit, hit rate, stake turnover if easily added)
• Real-time filtering with responsive tables and optional basic charts
• Short user guide covering installation, file import, and feature use

Acceptance Criteria
The app must read at least 100 k rows in under 10 seconds on a mid-range PC, produce accurate metrics matching a provided sample calculation, and preserve every filter option listed.

If you have previous experience with data-driven sports analytics apps or betting back-testers, let me know—looking forward to seeing what you can build.