Excel-Driven NRL Stats Analytics
Budget / SalaryA$30–250
TypeFreelance project
LocationRemote
Posted2 hours ago
I have several seasons of NRL historical game data stored in multiple spreadsheets and an early-stage predictive model that I built in Excel. I now need that raw information turned into a reliable, well-structured dataset, then pushed further through rigorous statistical analysis and sports-performance modelling—all inside Excel.
Here’s what I want to achieve:
• A fully cleaned and consistently formatted workbook where every match, team and player field lines up perfectly for formulas, PivotTables or Power Query refreshes.
• Advanced statistical exploration of the cleansed data (regressions, significance testing, variance analysis, etc.) to surface the variables that truly drive match outcomes.
• Integration and refinement of my existing predictive model so it is easier to maintain, delivers clear probability outputs for upcoming fixtures and can be stress-tested against past seasons.
• A short write-up or on-sheet notes that explain the methodology, any key formulas/VBA you introduce and how to refresh the model with new rounds of data.
Success for me means: the workbook updates with one click, the model’s accuracy is demonstrably improved over my current version, and I can trace each metric back to the original cleaned data without manual intervention.
If deep Excel expertise and sports analytics—specifically NRL—are in your wheelhouse, I’d love to see how you can sharpen this project.
Here’s what I want to achieve:
• A fully cleaned and consistently formatted workbook where every match, team and player field lines up perfectly for formulas, PivotTables or Power Query refreshes.
• Advanced statistical exploration of the cleansed data (regressions, significance testing, variance analysis, etc.) to surface the variables that truly drive match outcomes.
• Integration and refinement of my existing predictive model so it is easier to maintain, delivers clear probability outputs for upcoming fixtures and can be stress-tested against past seasons.
• A short write-up or on-sheet notes that explain the methodology, any key formulas/VBA you introduce and how to refresh the model with new rounds of data.
Success for me means: the workbook updates with one click, the model’s accuracy is demonstrably improved over my current version, and I can trace each metric back to the original cleaned data without manual intervention.
If deep Excel expertise and sports analytics—specifically NRL—are in your wheelhouse, I’d love to see how you can sharpen this project.
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