NYSSRA races are fun, but we all know that ski racers are a competitive bunch. They are always looking to ski faster and do better with each race. And, they are always scanning the results sheet to see how they did compared to the rest of the field. It is easy to look at overall place or age-group placing to evaluate your race. But, is finishing 3rd in the Reindeer Roundup require the same effort as finishing 3rd in the NYSEF Season Opener? Skiers know that some races are tougher than others. What makes one race more competitive than the other? If a race has lots of fast skiers that all finish within seconds of each other, then that is a tough field to compete against!
One way to determine the quality of the race field is to look at how fast the skiers were. Simply put, if the skiers are fast, then the race was competitive. To determine the “relative competitiveness” of NYSSRA races, look at how the top seven skiers did in the race. This group of skiers includes all of the medal winners and represents the pace of the head of the field. Chances are good that these skiers were in the lead for the majority of the race, and set the pace for the pack to follow. Using the average speed of the top 7 skiers as a measure, the first NYSSRA races of the year stack up as follows:
| NYSEF_opener_10M |
|
00:02:48 |
| NYSEF_opener_5M |
|
00:03:22 |
| NYSEF_opener_10F |
|
00:03:23 |
| Rochester1_10M |
|
00:04:05 |
| Reindeer_Roundup_10M |
|
00:04:13 |
| NYSEF_opener_5F |
|
00:04:17 |
| Osceola_Xmas_5M |
|
00:04:21 |
| Rochester1_5M |
|
00:04:48 |
| Rochester1_10F |
|
00:05:06 |
| Osceola_Xmas_5F |
|
00:05:15 |
| Reindeer_Roundup_10F |
|
00:05:47 |
Using this measure, the NYSEF 10 km men’s race was the fastest. The problem with using this to evaluate competitiveness is that ski race speeds are notoriously influenced by snow and weather conditions. The Reindeer Roundup took place during a massive snowstorm. And, typically, top male skiers are faster than top female skiers. The NYSEF women skied the exact same course and distance as the men. To eliminate this gender and weather variable, evaluate the %back of the top racers. The %back statistic does a good job of eliminating variables like distance, course difficulty and weather. If you analyze this season’s races using the average % back of the top 7 finishers it looks like this.
| NYSEF_opener_10F |
|
3.75% |
| NYSEF_opener_10M |
|
3.96% |
| Rochester1_10M |
|
5.21% |
| Osceola_Xmas_5M |
|
5.91% |
| Reindeer_Roundup_10M |
|
6.62% |
| Rochester1_10F |
|
10.35% |
| Osceola_Xmas_5F |
|
13.81% |
| Rochester1_5M |
|
14.21% |
| NYSEF_opener_5F |
|
16.69% |
| NYSEF_opener_5M |
|
17.65% |
| Reindeer_Roundup_10F |
|
33.69% |
Now, the NYSEF women’s 10 k is the most competitive. The top 7 skiers in the field were very close to one another at the finish. The skiers were fast, and the top skiers were equally fast. However, the field size was much smaller in the NYSEF women’s race, there were half as many skiers as there were in the men’s race. If a race field is bigger, then a skier is more likely to be skiing against tough competition, especially to place in the top half of the field. If you look at the average number of skiers that the top 7 had to beat to be better than the middle of the pack, it looks like this:
| NYSEF_opener_10M |
|
18.5 |
| Osceola_Xmas_5M |
|
18 |
| Osceola_Xmas_5F |
|
8.5 |
| NYSEF_opener_10F |
|
8 |
| Reindeer_Roundup_10M |
|
5.5 |
| Rochester1_10M |
|
3.5 |
| NYSEF_opener_5M |
|
1.5 |
| Reindeer_Roundup_10F |
|
0.5 |
| Rochester1_5M |
|
-0.5 |
| Rochester1_10F |
|
-0.5 |
| NYSEF_opener_5F |
|
-0.5 |
The top 7 skiers in the Osceola Xmas Mens 5 km race and the NYSEF opener mens 10 km race had to beat an average of 18 other good skiers just to be in the top half of the field. Typically, in a NYSSRA race, more skiers means more traffic and tougher race conditions. However, just beating alot of skiers does not automatically make it a challenging race.
To get a full picture of the “competitive nature” of a NYSSRA race, you need to look at a composite of the speed of the race, the % back of the race and the size of the field. Of these values, %back should carry the highest weight.
So I have devised the competitive index value for NYSSRA races. For each racer, subtract the %back from 110 (the winners would have given 110%!) Then add the number of skiers that he/she beat to be in the top half of the field. Finally, subtract the number of minutes per km. Find the average competitive index for the top 7 skiers and you have a number that describes how competitive the race field was. Our first set of NYSSRA races looks like this:
| Race |
|
Average of competitive_index_value |
| NYSEF_opener_10M |
|
115.17 |
| Osceola_Xmas_5M |
|
112.91 |
| NYSEF_opener_10F |
|
110.11 |
| Rochester1_10M |
|
106.37 |
| Reindeer_Roundup_10M |
|
103.49 |
| Osceola_Xmas_5F |
|
100.22 |
| Rochester1_10F |
|
99.19 |
| Rochester1_5M |
|
95.34 |
| NYSEF_opener_5M |
|
92.96 |
| NYSEF_opener_5F |
|
92.88 |
| Reindeer_Roundup_10F |
|
76.32 |
So, the NYSEF 10 km mens race has been the most competitive of the season. This was thanks in large part to the St. Lawrence University ski team who really “upped the ante” for this race. Of course, you can use this stat to evaluate an individual’s race performance which takes into account %back, size of field and speed. Using our race data, our top performing NYSSRA skiers have been as follows:
| Day, Chad 2929 |
Osceola_Xmas_5M |
120.33 |
| |
Rochester1_10M |
113.09 |
| Izzo, Elizabeth 3421 |
Osceola_Xmas_5F |
115.56 |
| Bencze, Charlie 3383 |
Osceola_Xmas_5M |
118.61 |
| |
NYSEF_opener_5M |
112.13 |
| Johnson, Carl 2587 |
Osceola_Xmas_5M |
114.21 |
| Stevens, Dan 3482 |
Reindeer_Roundup_10M |
114.09 |
| Wynn, Michael 3413 |
Reindeer_Roundup_10M |
111.85 |
| Wynn, Carly 3976 |
Reindeer_Roundup_10F |
111.57 |
| Sapp, Maile 3715 |
NYSEF_opener_5F |
110.35 |
| Swayze, Adam 4978 |
Rochester1_5M |
110.07 |
This is just another way for competitive NYSSRA skiers to evaluate their races and to see how they really stack up against the competition.
