Centimorgans Explained: Reading Shared DNA to Understand Cousin Relationships

What Centimorgans Actually Measure

When a consumer DNA test returns your results, each match is accompanied by a centimorgan (cM) value. That number is the sum of every DNA segment you and your match share across all chromosomes. Think of your genome as a long string of beads: recombination — the shuffling that occurs each time DNA is passed from parent to child — breaks and re-joins that string in different places every generation. The longer the inherited pieces you still share with a relative, the higher your cM total will be.

Because recombination accumulates over generations, close relatives share long, abundant segments, while distant relatives share only short, scattered ones. A full sibling typically shares around 2,550 cM; a second cousin might share 230 cM; a fifth cousin might share as little as 15–20 cM, if anything detectable at all.

For a broader grounding in the terminology you'll encounter, see key terms every genetic genealogist should know.

Why the Same cM Value Can Point to Multiple Relationships

The most important concept to grasp is that DNA inheritance is probabilistic, not fixed. Two people who are first cousins on average share around 850 cM, but the empirically observed range runs from roughly 550 to 1,200 cM. That same upper portion of the range overlaps with half-siblings on the lower end and with grandparent–grandchild pairs in the middle. A cM value does not arrive with a label attached.

The Shared cM Project, a crowd-sourced research effort compiled by genealogist Blaine Bettinger, addressed this directly by gathering cM data from thousands of verified relationships and producing probability distributions for each category. The resulting reference charts — freely available and widely cited in the genealogical community — show not just an average but the full spread of values for each relationship type, along with the statistical likelihood of each interpretation for a given cM total.

When you receive a match, it's best to look up the cM value in one of these reference distributions and note every plausible relationship, then use your family tree and documentary records to eliminate impossible options. This combination of biological and documentary evidence is the standard the genealogical community relies on.

Reading cM Values at Different Relationship Distances

The table below summarizes approximate average cM values for common relationships. These are averages — real values will vary, and ranges overlap between categories.

Notice how the second-cousin range is especially wide. This reflects greater variability at more distant relationships, where recombination has had more generations to shuffle segments unpredictably. Third cousins may share no detectable DNA at all — roughly half of third-cousin pairs share nothing measurable — which is why the absence of a match never disproves a documented relationship.

For distant matches, grouping shared matches and looking for patterns is more productive than focusing on a single cM number. Our article on shared matches and clustering explains how to organize these systematically.

Using cM Data Alongside Documentary Evidence

Centimorgans are most powerful when treated as one layer of evidence, not a standalone answer. A cM value tells you the biological relationship is plausible; a birth certificate, census record, or marriage register tells you how that relationship came to be. Neither source is complete without the other.

A practical workflow looks like this: identify a match's cM value, list every plausible relationship, then open your family tree and cross-reference what documentary records exist for each candidate. Often you can eliminate two or three possibilities immediately because those ancestors lived in a different region or the timeline doesn't fit. What remains is a much narrower set of hypotheses you can test with further research.

Digitised historical records have made this cross-referencing faster and more reliable than ever. Learn how to combine these sources effectively in using online digitised records alongside DNA evidence.

It's also worth distinguishing cM-based match data from the ethnicity estimate section of your report — they draw on the same raw data but serve entirely different research functions. Ethnicity estimates vs. DNA matches explains why conflating the two leads to common research errors.

Once you've identified which chromosome segments correspond to specific ancestors, you can move toward chromosome mapping — a technique that assigns segments to particular family lines and strengthens your evidence considerably. See building a chromosome map for next steps.