Top 100 MRCA Scoreboard
How It works| # | Name | Points |
|---|---|---|
| 1 | Michele Cragg | 2428 |
| 2 | Jay Fletcher | 1095 |
| 3 | Paul Rakow | 912 |
| 4 | Jill Schell | 905 |
| 5 | Terry Fitzgerald | 901 |
| 6 | Samuel Boylan | 718 |
| 7 | Douglas Husemann | 517 |
| 8 | Tony Allegra | 496 |
| 9 | Ruth Laverne Cattles | 491 |
| 10 | Peggy Jude | 408 |
| 11 | Tim Janzen | 391 |
| 12 | Erik Granstrom | 385 |
| 13 | Andreas West | 324 |
| 14 | Max Gerald Heffler | 300 |
| 15 | Tony Norris | 291 |
| 16 | Rodney Merrill | 267 |
| 17 | James Smith | 237 |
| 18 | K Williams | 213 |
| 19 | John Roberts | 192 |
| 20 | Joseph Lawrence | 191 |
| 21 | Marjorie Anderson | 166 |
| Evelyn Vinson | 166 | |
| 23 | Kenneth Louis Jordan Jr | 133 |
| 24 | Pamela E Culy | 129 |
| 25 | Steven Coker | 122 |
| 26 | James Arnold | 119 |
| 27 | Veronica Williams | 108 |
| 28 | Chase Clift | 91 |
| 29 | Robin Babou | 86 |
| 30 | Angela Townsend | 74 |
| 31 | P Donley | 69 |
| 32 | Ricardo Roffiel | 55 |
| 33 | Lynne Williamson | 53 |
| 34 | Lisa L. | 36 |
| 35 | Angie Kennedy | 32 |
| 36 | William Harvey | 28 |
| 37 | Pam Pennington | 27 |
| 38 | David Cheney Conroyd | 25 |
| Stephanie Payne | 25 | |
| 40 | Carrie Loranger | 23 |
| 41 | Robert Warthen | 22 |
| 42 | william Watson | 21 |
| 43 | Deborah Dixon Walker | 17 |
| 44 | Shari Jamieson | 16 |
| 45 | Angel Tai | 13 |
| 46 | Elisabeth Oosterink | 10 |
| 47 | Patrick Callaghan | 9 |
| 48 | Lynda Crackett | 7 |
| Mike Alexander | 7 | |
| 50 | Joanna Douglas | 6 |
| 51 | Anna Castle-Byrne | 5 |
| 52 | Loretta Reich Rippee | 4 |
| 53 | Alfred Anheier | 3 |
| Shawn Heyse | 3 | |
| 55 | Susan Stoddard | 2 |
| Zachary Kiyak | 2 | |
| Kaitlyn Parker | 2 | |
| Robert Ralston | 2 | |
| Laura Barnes | 2 | |
| Carrol Fish | 2 | |
| 61 | Franz Oster | 1 |
| Lisa Marley | 1 | |
| Teneshia Baker-Lane | 1 | |
| Bryanna Hines | 1 | |
| Luiz Henrique Santana Souza | 1 | |
| John Matthews | 1 | |
| michelle Bordonaro | 1 | |
| Miriam Engstrom | 1 | |
| Jo Anderson | 1 | |
| Alice Rockefeller | 1 | |
| Dave Lyons | 1 | |
| Vanessa Ebert | 1 | |
| H Z | 1 | |
| Michelle Stella | 1 | |
| 75 | David Wagner | 0 |
| 76 | Betty Graham | -2 |
| 77 | Christy Jordan-Frank | -39 |
Here's how "Common Ancestor Points" work:
* Identify each Most Recent Common Ancestor (MRCA) between two of your DNA matches or between a DNA match and yourself. The MRCA is the person or couple through whom two DNA matches (or you and a DNA match) are related.
Examples:- In a parent/child relationship, the parent is the MRCA as the DNA to the child came through the parent. This is the easiest MRCA to identify.
- For full siblings, the MRCAs are the parents. For half-siblings, the MRCA is the parent from whom all half-siblings are descending.
- For 1st cousins, the MRCA is the grandparent couple from whom both cousins are descending. For 2nd cousins, it's the great-grandparent couple, and so on.
When we identify MRCAs for DNA matches in a triangulated group (TG), we know that the DNA has been inherited through the MRCA (single person), or for MRCA couples, we know that the DNA has come through one of them. As we add more MRCAs, we're collecting more evidence that the DNA was indeed inherited along this path and not any other possible path (especially important in endogamous relationships).
The "Common Ancestor Points" are calculated as follows:
For each DNA kit under your user profile, we identify all TGs with an assigned MRCA and give one point for each.
Example:You have 2 DNA kits under your user profile, and they have 17 TGs with 28 MRCAs assigned to them. The CAP will be 28 in this case.
Remember, if both DNA kits are in a TG together, we won't double count this TG. Also, there are more MRCAs than TGs as we haven't identified how all MRCAs in the TGs are related to each other.
Lastly, it's crucial to research the ancestors of ALL DNA matches in a TG! Every DNA match in a TG has inherited the same ancestral piece of DNA from an unknown common ancestor. By identifying MRCAs, we're collecting evidence as to who this common ancestor might have been.