As mentioned before, the data includes ultra-marathons, trail-runs, etc.  In an effort to extract those to get only road races I’ve filtered the data to include only those races with at least 200 participants (male/female so 200 male participants at least or 200 female participants).  Still there are some non-road races in the data that have 200+ participants, but far less than before.  So, is the data totally “cleaned” of these races, no.  But, I think this gets us closer to the finishing time(s) people are running to win “normal” marathon road races.

The average time for Female winners is around 3:02:00 for the last 10 years.  Again, much lower time than had we included all races in the data set without some filtering.

These graphs were only of races in the US.  In general, without having personal knowledge of the race, (terrain, temperature, organization, etc.) marathon difficulty is difficult to measure objectively.  I don’t know of any “difficulty index” for marathons (let me know if you know of one), which is why starting with the winning times of races is a good place to start when considering racing with the potential to win.