The NY Marathon is a borderline absurd phenomena. Over 40,000 runners enter each year from around 70 different countries. Here I have compiled some of the data from the 2009 race.

Male and Female Age Group Data:

In this section, I have divided the finishers by gender and age.

 Male Average Place by Age 

 Female Average Place by Age 

These chart shows the Average time by Age group for male and female runners. It seems that the ideal running age is about 24 for men and about 22 for women. 

 Male Time Variance by Age 

 Female Time Variance by Age 

These chart shows the time distribution by place for male and female runners with age in the frame series. Notice that the distribution is skewed low in both cases.

Country and State Comparison:

This section will attempt to show which regions dominate the race.

 Average Place by Country 

This chart shows the average time for each country. As expected, Kenya and Ethiopia are ranked 1st and 2nd.

 Average Place by State 

This chart shows the state by state time averages.

Time Splits vs. Overall Finish:

Pace is an integral part of distance running. Some runners like to build up their speed as they go through the race, some like to start strong and try to hold a high pace for as long as they can, and some runners try to keep a consistent pace throughout. This section will examine how different pacing methods worked in terms of overall performance.

 0k to 5k time vs place 

 5k to 10k time vs place 

 10k to 15k time vs Place 

 15k to 20k time vs place 

 20k to 25k time vs place 

 25k to 30k time vs place 

 30k to 35k time vs place 

 35k to 40k time vs place 

This chart shows the 5k time splits vs overall finish. It seems that there is a very loose correlation between the first 5k time and finish. The runners with better latter splits tend to be doing better in the overall placing. This is evidenced by the tightening of the correlation as you progress through the race. This falls apart in the last 5k. This is attributable to the infamous "kick" that a runner puts in when he knows that he is close to the finish.

 Total Time vs Place 

This chart shows the final time vs place distribution. Notice that there is a very tight logarithmic relationship between place and total time. This is the opposite time distribution that you would see for cycling. It seems that elite runners actually have a higher delta time between places than normal runners. 

Citation:

http://www.ingnycmarathon.org/