How to Read a blue Score
What the numbers actually mean — and how to act on them.
The composite score
Every stock gets a score from 0 to 100 and a letter grade from A to F. Think of it like a job performance review: an A means the company is firing on all cylinders across the board. An F means something is seriously wrong. Most stocks land somewhere in between — a C is average, a B is solid, an A is genuinely exceptional.
A score tells you the condition of the business today — not whether you should buy it.
The five categories
blue breaks the composite score into five areas, each worth a different percentage: Growth (25%) measures whether the business is expanding. Value (15%) measures whether you're paying a fair price. Quality (30%) measures how well-run the business is. Risk (20%) measures financial safety. Momentum (10%) measures near-term tailwinds. Quality and Risk together make up half the score because they're the most reliable long-term signals.
What score to target
A B grade (70+) is a solid starting filter. A-rated stocks are rare and sometimes already expensive because everyone else has noticed. C is average. D and F are warning signs worth understanding before going further. Don't chase the highest score blindly — look for companies with consistently strong fundamentals across multiple categories, especially Quality and Risk.
Like a home inspection report: it tells you the condition, not whether you should make the offer.
How to use it in your workflow
Use the score as your first filter, not your final answer. A strong score means the numbers look healthy — that earns the company a spot on your research list. From there, you still need to understand the business, check for a competitive moat, and decide if the price makes sense for your situation. blue does the heavy quantitative lifting. The qualitative judgment is yours.
Open any stock's analysis page. Look at all five category scores — which ones are strongest? Which are weakest? That breakdown tells the real story.
Try it →Knowledge Check
1. Which two categories together make up 50% of the composite blue score?
2. What does a blue score actually tell you?
3. How should you use a strong blue score in your research process?