Track Analytics Engine · Model 09
High frequency ≠ a recommendation to enter blindly.
The Track Analytics Engine scores the 5 major tracks on 8 dimensions + Monte Carlo sampling (N=15,000), outputting top-pick frequency, ranking robustness, and counter-scenarios. We want you to see clearly why you 'want' to enter this track before you decide whether to.
5 Tracks · 8 Dimensions · 15K Paths
Smart top-pick frequency ranking
Interactive · adjust weights live
Drag the dimensions you value — watch the ranking change.
Weights
The total is auto-normalized
Live ranking
Based on your weights (normalized) × each dimension's average score
- 1AI Applications & Data Services7.91 / 10
- 2Enterprise Software & Automation7.40 / 10
- 3Green & Energy Materials7.23 / 10
- 4Healthcare & Devices7.02 / 10
- 5Advanced Manufacturing6.92 / 10
Note: this component is a quick teaching re-rank; the formal report runs a full Monte Carlo + counter-scenarios.
Win Frequency
Top-pick frequency under default weights.
Note: a high top-pick frequency ≠ a recommendation to enter. Combine it with personal fit, capital access, exit paths, and due-diligence conclusions.
Rank Robustness
Across 15,000 samples, each track's probability of different ranks.
| Track | #1 | #2 | #3 | #4 | #5 |
|---|---|---|---|---|---|
| AI Applications & Data Services | 80.0% | 14.3% | 4.3% | 1.1% | 0.3% |
| Enterprise Software & Automation | 11.5% | 43.2% | 27.4% | 13.1% | 4.8% |
| Advanced Manufacturing | 0.9% | 6.8% | 15.3% | 29.3% | 47.6% |
| Green & Energy Materials | 6.0% | 24.7% | 32.0% | 22.7% | 14.6% |
| Healthcare & Devices | 1.7% | 11.0% | 20.9% | 33.7% | 32.7% |
Methodology
Methodology
8-dimension scoring + Gaussian sampling + weighted sum → top-pick frequency over N samples
- Weights can be tuned to founder preference; this model is exported with the default configuration
- Gaussian parameters (mu, sigma) represent industry consensus and uncertainty
- Top-pick frequency ≠ a recommendation to enter; combine it with personal fit and due diligence