Estimator Inputs
Example Data Table
These samples show how changing inputs shifts estimated outcomes.
| Scenario | Skill | Interview | Network | Competition | Referrals | Estimated Win |
|---|---|---|---|---|---|---|
| Offer: Mid role | 82% | 78% | 62% | 6/10 | 1 | ~52% |
| Promotion: Senior | 75% | 70% | 58% | 7/10 | 2 | ~38% |
| Scholarship: Entry | 88% | 82% | 45% | 8/10 | 0 | ~29% |
Formula Used
This estimator combines a baseline success rate with weighted signals, then converts the score into a probability.
How to Use This Calculator
- Select your target type and seniority to set a baseline.
- Enter scores for skill match, portfolio, interviews, networking, and fit.
- Set competition intensity and preparation time realistically.
- Choose a weight preset, or enable custom weights for fine control.
- Press Estimate Win Probability to view results above the form.
- Download CSV for sharing or save a PDF for your notes.
Decision Contexts and Baselines
A win estimate starts with a baseline that matches your situation. For a cold application, try 3–8%. With an intro or referral, use 10–25%. Internal promotion cycles can begin around 15–40% when you already meet the bar. Scholarship and fellowship rounds may start near 5–15% before interviews. If you track outcomes, replace these defaults with your historical win rate.
Signal Inputs That Move Odds
The estimator scores key signals on a 0–100 scale: skill match, portfolio strength, interview readiness, networking strength, and role fit. Use anchors to stay consistent: 50 means “meets requirements,” 70 means “clearly above,” and 90 means “top tier.” With default weights, a 10‑point lift in interview readiness can add roughly 2–6 probability points when the baseline is near 20%. Custom weights help you reflect context, such as portfolio-heavy roles or leadership promotions.
Competition and Pipeline Pressure
Competition intensity (1–10) represents how crowded the funnel is. In this calculator, moving from 4 to 8 can reduce estimated odds by about one‑third, even if other inputs stay fixed. Consider the ratio of qualified candidates to open slots: 10:1 feels like 6/10, while 30:1 can feel like 9/10. Preparation time helps counter pressure; adding 10 focused hours often offsets 1–2 competition points in the score.
Calibration and Confidence Bands
Calibration controls how strongly inputs swing results. Higher calibration is useful for structured funnels with clear rubrics; lower calibration suits noisy outcomes, such as early-stage networking or unposted roles. Confidence sets a practical band around the estimate: low confidence widens the range, while high confidence narrows it. Use a wider band when signals are self-reported or the decision-makers are unknown. Treat the band as planning space, not a guarantee.
Action Planning From Results
Use the breakdown to pick the highest‑impact levers and set weekly targets. If interviews are weak, schedule mock rounds, record answers, and track pass rates. If networking is low, aim for five targeted conversations per week and one referral request. If portfolio strength is low, ship one measurable project in 14 days. Re‑run scenarios after each upgrade and log inputs alongside outcomes. The goal is momentum: small, measurable improvements that compound over time.
FAQs
What does the win probability represent?
It is an estimated chance of success for your selected target, based on your inputs and the chosen baseline. Use it to compare scenarios and decide where improvement will matter most.
How should I score skill match and role fit?
Score against the written requirements. Use 50 for “meets,” 70 for “strong match,” and 90 for “exceptional.” Keep the same anchors each time so repeated runs stay comparable.
How do I choose competition intensity?
Think in ratios. If you expect about 10 qualified candidates per slot, use 6/10. If it feels closer to 30 per slot, use 9/10. Adjust as you learn more about the pipeline.
When should I enable custom weights?
Enable custom weights when one factor clearly dominates, such as portfolio strength for creative roles or interview readiness for structured panels. Keep total weights balanced; extreme weights can overreact to small score changes.
Why is there a probability range?
The band reflects uncertainty. Low confidence widens the range when information is limited or subjective. High confidence narrows it when you have clear evidence, repeatable performance signals, and stable decision criteria.
Does a higher estimate guarantee an outcome?
No. Real decisions include timing, budgets, and other candidates. Use the estimate as a planning tool: improve the highest‑impact inputs, run “before vs after” scenarios, and track actual outcomes over time.