ScopeCalc - Monte Carlo Calculator
Paste your team's cycle times and get probabilistic delivery forecasts in seconds.
Enter how long your last completed items took (separate by commas or new lines).
How many items are in your upcoming project or sprint?
Results will appear here after running the simulation.
Why Monte Carlo + cycle times beat traditional estimates
A quick primer on the mathematical approach to forecasting that's replacing story point guesswork.
What is cycle time?
Cycle time measures how long work actually takes from start to finish. Unlike story points, cycle times are objective—they're based on real historical data from your team's completed work.
Monte Carlo simulation
Running thousands of simulations using your historical cycle times calculates the probability of completing projects within different timeframes—so you share confidence intervals instead of false precision.
Better than estimates
Instead of guessing story points and hoping for the best, you get probabilistic forecasts based on your team's actual performance. No more “two weeks” that becomes six.
📊 We'll be publishing research and deep-dive articles on probabilistic forecasting soon. This is just the beginning.
Help us build this feature
🎯 You're helping shape ScopeCone's roadmap! This calculator demonstrates Monte Carlo forecasting we're considering building. Love it? Tell us how you'd want to use it.
What we're considering
Automatic cycle time tracking from Jira, GitHub, or Linear—no manual data entry required.
Your input needed
How would your team use Monte Carlo forecasting? Sprint planning? Stakeholder reports? Help us prioritize.
Be a research partner
Join our research program and help design this feature from the ground up. Early access included.
2-minute survey • Help us build what you need • Early access included