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Win Rate & Forecast Accuracy Tracker

Every forecast call category — Commit, Best Case, Pipeline — is a prediction. This tool checks those predictions against what actually happened: win rate by stage and forecast category, how close actual closed value landed versus what was called Commit, how often close dates slipped, and whether the pattern points to overcommitting (calling deals too early) or sandbagging (under-calling deals that then win). Paste your deal list below — nothing leaves your browser.

Your numbers

Format per line: Stage, Forecast Category, Outcome, Forecast Close Date, Actual Close Date, Value — one deal per row, fields comma-separated. Outcome must be Won, Lost, or Open (leave Actual Close Date blank for Open deals). Dates as YYYY-MM-DD or DD/MM/YYYY. Value in £ is optional but needed for the forecast £ accuracy figure. Replace the sample rows above with your own pipeline export.
How many days either side of the forecast close date still counts as "on time".
What a healthy "Commit" call should convert at in your business. Used to flag overcommitting.

Method & assumptions

  • Win rate = Won ÷ (Won + Lost) among closed deals only; Open deals are excluded from win-rate and date-accuracy maths but still count toward committed £ pipeline.
  • Forecast £ accuracy compares total value of every deal ever called "Commit" against total value actually Won, using 1 − |variance| ÷ forecast — the standard forecast-accuracy formula sales leaders use for commit vs. actual bookings.
  • The bias verdict combines four independent signals — Commit win rate vs. your benchmark, average close-date slip, share of wins that came from outside Commit ("surprise wins"), and £ variance — the majority direction decides Overcommitting vs. Sandbagging vs. Balanced.
  • Accepts dates as YYYY-MM-DD or DD/MM/YYYY. A row needs at least Stage, Forecast Category, Outcome and a Forecast Close Date to be counted; malformed rows are skipped and flagged rather than breaking the calculation.

How to use it

Export or copy your deal list from the CRM (stage, forecast category, Won/Lost/Open, forecast close date, actual close date, and deal value if you have it) and paste one deal per line into the box, replacing the sample rows. Adjust the on-time window and Commit benchmark to match how your team actually operates, then read the KPIs, stage/category breakdowns, and the bias verdict at the bottom. Re-run monthly against the latest closed deals to catch overcommitting or sandbagging drift early.

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