Every number on a card has a reason. This page explains the principles, the six stats, and the line we draw between rigour and theatre.
The retail investor's problem isn't lack of data — it's the opposite. Free tools, paid terminals and finance Twitter all flood the same person with metrics, ratios and opinions. What's missing is a way to read a portfolio at a glance: spot what's strong, what's weak, and what each holding actually does for the team.
Wall Street Cards turns each stock into a card with six stats — the same six for every stock, computed the same way every time. The promise is simple: if you understand the stats on one card, you understand them on every card. The card is the interface; the methodology below is the engine underneath it.
A stat of 95 doesn't mean "top 5% of the entire market" — it means top 5% within the company's sector. We use the Global Industry Classification Standard (GICS), the same taxonomy that institutional investors rely on, and we compute each stat as a percentile inside that sector.
Why this matters: comparing a software company's growth to a utility's growth is meaningless. They live in different worlds, with different cost structures, capital cycles and investor expectations. A 90 in Growth for an Energy major and a 90 in Growth for a Software firm aren't the same number, but they tell you the same useful thing — this company is growing fast relative to its peers. That's the comparison that actually informs a decision.
An Oil major showing Moat 95 is one of the most defensible businesses in Energy — not necessarily one of the most defensible in the whole market. A reader who doesn't get this would compare a "95 Moat" oil stock against a "95 Moat" tech stock and mistake them for equivalents. We make the sector context explicit on every card.
Every card carries six stats. They follow the convention used in modern football simulators (PAC, SHO, PAS, DRI, DEF, PHY) so the football metaphor stays clean, but each one maps to a real financial concept:
How the stock has performed recently. A "fast" card has been in form; a slow one has lagged or fallen.
How fast the underlying business is expanding. Revenue and earnings are the headline; forward expectations weigh in too.
How reliably the business delivers what it promises. Earnings surprises, predictability, low operational volatility.
How good the business is on the inside — margins, returns on the capital it deploys, how much it reinvests in itself.
How well the business defends itself in a downturn. Balance-sheet strength, cash generation, resistance to drawdowns.
How big the company is in the league. Market cap, revenue scale, share of its sector.
The OVR is a weighted average of the six stats, where the weights depend on the company's profile. A growth-oriented business naturally leans more on Growth and Momentum; a defensive business leans on Moat and Consistency. The weighting is sector-aware — what counts as "balanced" for Tech is not what counts as "balanced" for Consumer Staples. Exact weights are not published here (that's the calibration we keep private), but the principle is: the OVR reflects what good looks like for a company of that type.
There are two kinds of card in the system, and they behave differently on purpose.
The card you generate for any ticker you own — that's a Standard card. The six stats come straight from the calculation, with the sector percentile applied. No adjustments, no boosts, no editorial sweetening. If a popular consumer brand has a Quality score of 76 by the numbers, the card shows 76. The same input always produces the same output.
A small set of cards belong to higher tiers — Icon and Legend — typically reserved for companies whose stature in the market goes beyond what a pure financial-ratio calculation captures (think of brand value, historical impact, decades of consistent dominance). These cards can receive a boost on top of their base stats. The rules of the boost are strict:
A purely data-driven model would produce some uncomfortable results — a household-name icon that happens to be going through a soft year would rate around 85, which feels wrong to anyone who understands the brand. A purely vibes-driven model would invite ridicule from anyone who actually reads financials. Model B keeps the base scoring fully rigorous, and gives icon-class companies a clearly-labelled adjustment — so the rigour stays intact and the recognisable greats stay recognisable. Theatre is allowed; opacity is not.
We're upfront about where the numbers come from today:
A scheduled job runs every Monday: it downloads the latest data for the entire universe, recomputes every stat (percentile-normalised within sector), and updates the cards. That weekly recalc is also what powers the Match Report — the weekly briefing that tells you why a card went up or down in form. The card you own is a living card: it changes when the underlying company does. The card in your collection (a drop) is a sealed card: its stats are frozen at the moment of issuance, like a trading card, and never change. That duality is intentional.
No. Wall Street Cards is an educational entertainment product. The stats describe how a company looks across six dimensions — they don't say "buy this" or "sell that". Reading a card is reading a company, not getting a tip.
The six stats each capture one dimension (Momentum, Growth, Consistency, Quality, Moat, Size). The OVR is a weighted average of those six, where the weights depend on the company's profile — a growth business gives more weight to Growth and Momentum, a defensive business to Moat and Consistency. So a 90 OVR isn't "the average of the six stats" — it's "the right average for what this company is".
Because the format is instantly readable for anyone who's spent time with modern football simulators — and most of our target audience has. The codes are familiar; what they map to (Momentum, Growth, etc.) is what the page makes explicit. The format is the hook; the meaning is what we owe the reader.
Once a week, every Monday. The scheduled job recomputes every card in the universe with the latest data. That weekly cadence is also what produces the Match Report — the briefing that explains what changed in your squad and why.
Because comparing a Software company to a Utility on the same absolute scale is misleading. A 90 in Growth should mean "this company is growing fast" — and what "growing fast" means is very different for a Tech firm than for a Consumer Staples brand. Sector-relative makes the comparison meaningful, the way player ratings compare a striker to other strikers and not to goalkeepers.
Not in public — that's the part we keep as know-how, and the calibration is what we continue to refine. What we publish is the principles, the data sources, and the financial concepts each stat draws from. If the methodology says "Moat is fed by net debt / EBITDA, FCF yield, drawdown and beta", you can sanity-check whether the number on a card lines up with what you'd expect — even if you don't know the exact weights.
Both, and we say so. An Icon card carries the same six base stats as any Standard card (calculated the same way). On top of that, it can carry one transparent boost — capped at +5, applied to a single stat, with the source cited on the card itself. So a high Icon rating is "real numbers + clearly-shown adjustment". You can always subtract the boost in your head and see the underlying score.
The universe is built on demand. When a user adds a ticker that hasn't been pre-computed, the stats are calculated on-the-fly the first time, and from then on the ticker joins the weekly recalc like any other. The catalogue grows with what people actually want to track — not with a fixed list.