> For the complete documentation index, see [llms.txt](https://matterhorn-doc.mometic.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://matterhorn-doc.mometic.com/find-opportunities/rankings-and-filters.md).

# Rankings and filters

Use Matterhorn company search, sector and market-cap filters, rankability, and sorting to create a focused stock research shortlist.

The ranking is a research queue. Use it to concentrate attention, then decide whether the evidence justifies further work. On Overview, **Detail >** beside **Top 10 Opportunities** explains the ordering without crowding the list.

![Companies table with search, sector, theme, market-cap and rankability filters](https://981865776-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FNOJXLd7UJBniObM136Nu%2Fuploads%2Fgit-blob-38a4a2259c7602a5137543dbd92743d4eed73c7e%2Fcompanies.png?alt=media)

## Make the universe useful

1. Open **Companies**.
2. Search by ticker or company name, or leave search blank to browse.
3. Choose a sector, economic theme, or market-cap band relevant to the question.
4. Use the rankability filter to understand evidence readiness.
5. Click a sortable column header; click again to reverse the order. Drag a header edge if you need more room.
6. Open a company row to inspect the case behind the number.

Filters combine. A company must match all active filters to remain visible. Filtering does not rebuild the model or turn the displayed rank into a new rank within your filtered subset.

## Read both rank and score

The standard dashboard's ordering uses an evidence-supported score with sector-standing, runway, sector-growth, and cash-quality adjustments. The raw weighted composite shown in a company breakdown is therefore not always sufficient to explain its place on the board. **Rank** and **Opp** are related, but they are not interchangeable. See [score layers](/understand-the-scores/understanding-scores.md).

In ML mode, the rank and ML score come from the same frozen beta bundle. A missing beta prediction stays unavailable. It does not inherit the score of a similarly named company or another share class.

## Use rankability as context

The tier describes whether the evidence record clears the configured coverage gates. It is not a credit rating or a probability of success. Use the evidence-readiness label shown in your installation. A company marked **Watchlist only** can still appear in the current standard ranked pool. **Excluded** and wholly unscorable companies are not admitted as ranked opportunities.

> **Pro Tip — Do not filter away your own blind spots.** Start with companies you can understand, then check the strongest candidates outside that group. A familiar ticker is easier to explain, but familiarity is not a score input.

For a manageable first shortlist, choose a few candidates with different strengths: one established compounder, one improving demand story, and one with strong business evidence but incomplete market confirmation. This is a research exercise, not a prescribed allocation.

Next: [compare candidates](/investigate-the-business/compare-companies.md), [understand missing evidence](/understand-the-scores/evidence-quality.md).