Top 100 MRCA Scoreboard
How It works# | Name | Points |
---|---|---|
1 | Michele Cragg | 1260 |
2 | Jill Schell | 1131 |
3 | K Williams | 979 |
4 | Terry Fitzgerald | 719 |
5 | James Smith | 678 |
6 | Max Gerald Heffler | 637 |
7 | Paul Rakow | 624 |
8 | Ruth Laverne Cattles | 564 |
9 | Samuel Boylan | 339 |
10 | Tony Allegra | 314 |
11 | Erik Granstrom | 287 |
12 | Douglas Husemann | 279 |
13 | Andreas West | 254 |
14 | Evelyn Vinson | 228 |
15 | Kenneth Louis Jordan Jr | 208 |
16 | Peggy Jude | 205 |
17 | Rodney Merrill | 203 |
18 | Deborah Dixon Walker | 202 |
19 | Tony Norris | 197 |
20 | Joseph Lawrence | 183 |
21 | Pamela E Culy | 177 |
22 | Angela Townsend | 157 |
23 | Steven Coker | 156 |
24 | Marjorie Anderson | 131 |
25 | Ricardo Roffiel | 127 |
26 | Veronica Williams | 124 |
27 | James Arnold | 121 |
Angel Tai | 121 | |
29 | John Roberts | 115 |
30 | Robin Babou | 112 |
31 | Christy Jordan-Frank | 100 |
32 | Lynne Williamson | 92 |
33 | Mike Alexander | 66 |
34 | Carrie Loranger | 63 |
35 | David Cheney Conroyd | 61 |
Robert Warthen | 61 | |
37 | Tim Janzen | 59 |
38 | Lisa Marley | 55 |
39 | P Donley | 53 |
Christine Diaz | 53 | |
41 | Chase Clift | 48 |
42 | Pam Pennington | 43 |
43 | Jane Chapman | 36 |
44 | Marion Boyd | 32 |
Stephanie Payne | 32 | |
46 | William Harvey | 31 |
47 | Shari Jamieson | 30 |
48 | Sandra Wilson | 21 |
49 | JOHN WILKES | 20 |
50 | Lynda Crackett | 19 |
51 | Zachary Kiyak | 18 |
52 | Vernon Smith | 15 |
53 | Lisa L. | 14 |
54 | Robert Ralston | 12 |
Bryanna Hines | 12 | |
56 | Patrick Callaghan | 11 |
57 | Elisabeth Oosterink | 10 |
58 | Angie Kennedy | 9 |
Anneli Ighil | 9 | |
60 | Anna Castle-Byrne | 7 |
Irwin Goldberg | 7 | |
62 | Loretta Reich Rippee | 6 |
Gail Wilson | 6 | |
Carrol Fish | 6 | |
65 | Anthony Cassidy | 5 |
66 | Karin Betts | 4 |
William Canavan | 4 | |
68 | James MacDonald | 3 |
Jarod Perry (Winters) | 3 | |
Michael Echter | 3 | |
Toni Vitale | 3 | |
Melinda Culpon | 3 | |
Shawn Heyse | 3 | |
74 | Betty Graham | 2 |
Arianna Day-Clevenger | 2 | |
Linda Merckx | 2 | |
Joanna Douglas | 2 | |
78 | Vanessa Ebert | 1 |
Sigurður Eysteinsson | 1 | |
John Matthews | 1 | |
William Walton | 1 | |
jaden turnley | 1 | |
Steve Gent | 1 | |
michelle Bordonaro | 1 | |
James Marx | 1 | |
Mel Green | 1 | |
Luiz Henrique Santana Souza | 1 | |
Ken Waters | 1 |
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.