Shared cM to Relationship Predictor Excel Template
Shared cM Relationship Predictor Template
Organize shared cM data, compare possible relationship categories, and document your working relationship hypothesis in one structured DNA genealogy research spreadsheet.
Preview of the Shared cM Relationship Predictor research worksheet.
Shared centimorgans (cM) are one of the most useful pieces of information when evaluating an unknown DNA match. However, the same amount of shared DNA can be consistent with several different genealogical relationships.
For example, a shared cM value may fit more than one relationship category. A useful relationship worksheet therefore helps you compare possibilities rather than treating one cM number as a definitive relationship prediction.
Why Use a Shared cM Research Worksheet?
DNA testing companies provide relationship estimates, but those estimates are only one part of the research process. When you are working with an unknown match, it can be useful to record the DNA evidence alongside age information, family-tree clues, and your current research hypothesis.
- Keep shared cM information organized across multiple DNA matches.
- Compare several plausible relationship categories side by side.
- Record the longest shared segment when that information is available.
- Consider age and generational differences when evaluating possibilities.
- Separate a statistical possibility from your current genealogical hypothesis.
- Record what additional evidence is needed before accepting a relationship.
Who Is This Template For?
This spreadsheet is designed for genealogists researching unknown or uncertain DNA matches who want a structured way to evaluate possible relationships.
It can be useful for both newer DNA genealogists learning how to interpret shared cM and experienced researchers who want a consistent research log for larger numbers of matches.
Pre-Formatted Columns Included
The worksheet includes dedicated fields for recording the main evidence and reasoning used during relationship analysis:
- Match Name & Testing Company – Identify the DNA match and the platform where the match was found.
- Total Shared cM Value – Record the reported total amount of shared DNA.
- Longest Segment Length (cM) – Record the largest reported shared segment when available.
- Possible Relationship Categories – List relationship possibilities supported by the DNA evidence.
- Statistical Probability Range (%) – Record probability information from the relationship model or tool being used.
- Age Gap & Generational Alignment – Compare the match's age and likely generation with each relationship hypothesis.
- Working Research Hypothesis – Record the relationship you currently consider most plausible.
- Verification Requirements & Next Steps – Document the evidence still needed to test the hypothesis.
Best Use Cases for This Template
- Unknown DNA matches: Compare possible relationships when the genealogical connection is not yet known.
- Close-match research: Organize relationship possibilities before building or changing a family-tree hypothesis.
- Multiple possible relationships: Keep several plausible relationship categories visible instead of prematurely choosing one.
- Research planning: Record what additional information could help distinguish between competing hypotheses.
- DNA evidence documentation: Preserve the cM data and reasoning behind your conclusions for future research.
- Working with probability tools: Record outputs from established relationship probability tools and compare them with your broader genealogical evidence.
Important: Shared cM Does Not Identify a Relationship by Itself
Shared cM should be treated as evidence rather than as a definitive relationship label. A single cM value can be compatible with multiple relationships, especially when several generations or relationship pathways are possible.
Other evidence can help narrow the possibilities, including the match's age, known family relationships, shared matches, chromosome segments, family trees, geographic clues, surnames, and documented genealogical records.
Endogamy and pedigree collapse can also result in more shared DNA than might otherwise be expected for a particular relationship, so statistical estimates should always be interpreted in context.
Use this template to organize and evaluate evidence — not to replace genealogical verification.
Step-by-Step Relationship Research Workflow
- Record the DNA match. Enter the match name, testing company, total shared cM, and longest segment when available.
- List plausible relationships. Use an established relationship probability model or reference to identify relationship categories compatible with the shared DNA.
- Consider the generations. Compare the possible relationships with the ages of both people and any known generations in the family tree.
- Look for additional DNA evidence. Review shared matches, chromosome segments, triangulation opportunities, and other available genetic evidence.
- Compare the genealogy. Look for overlapping ancestors, surnames, locations, family clusters, and documentary evidence.
- Record your working hypothesis. Choose the relationship that currently best fits the evidence while keeping alternative possibilities documented.
- Define the next research step. Record what evidence would help confirm or reject the hypothesis.
Frequently Asked Questions
What is a shared cM relationship predictor?
A shared cM relationship predictor uses the amount of DNA two people share to identify relationship categories that may be compatible with that amount of DNA. It provides a range of possibilities rather than automatically identifying one exact relationship.
Can shared cM tell me exactly how two people are related?
No. The same shared cM amount can occur across multiple relationship types. Shared DNA is most useful when combined with age, family-tree information, shared matches, chromosome evidence, and traditional genealogical research.
Why should I record the longest shared segment?
The longest shared segment can provide additional context when evaluating a DNA match. It should be considered alongside total shared cM and the rest of the available evidence rather than interpreted on its own.
Why does age matter when evaluating a DNA relationship?
Age differences can help determine whether a possible relationship is genealogically plausible. For example, some relationship categories require different generational positions and are therefore more or less realistic depending on the ages of the people involved.
Should I record more than one possible relationship?
Yes. Keeping multiple plausible relationships visible can help prevent confirmation bias and make it easier to test competing hypotheses as new evidence becomes available.
Can this template be used with different DNA testing companies?
Yes. The template is designed as a general research worksheet and can be used with shared cM information from different testing platforms. The exact information available may vary between companies.
Is a cM probability result the same as proof of a relationship?
No. Probability estimates describe how well a relationship category fits the observed DNA amount under a particular model. They do not establish the genealogical relationship by themselves.
Ready to Analyze Your DNA Matches?
Download the free Shared cM Relationship Predictor Template and organize your DNA evidence, relationship possibilities, and next research steps in one place.
📥 Download the Free cM TemplateDNA Academy - Quick Answers
What formats are your free templates available in?
Our templates are available as downloadable Excel/Google Sheets files (for digital tracking).
How do I use a research log effectively?
A research log helps you track which records you’ve searched, what you found, and what’s still missing. We recommend filling it out as you go, it prevents duplicate searches and helps you identify patterns. Our template includes columns for date, source, location, and findings.
Are the templates available in languages other than English?
Currently, our templates are in English only. We are exploring translations into Swedish, Spanish, and German based on user requests. If you need a specific language, contact us and we’ll prioritize it.