Location: Burnaby Lake, CW
Distance: 11.1 km
Weather: High cloud, a little sun
Temp: 15ºC
Wind: moderate to strong
Calories burned: 787
Average pace: 4:49/km <– personal record
Total distance to date: 1392.58 km
Ran: Piper Mill Trail.
With the cloud cover and strong wind it was actually a bit chilly heading out on the run today — par for the course when it comes to June weather. By about the halfway point my hands and arms finally started warming up, though they got cold again on the walk home after.
The cottonwood snowfall continued today, with the wind whipping off billions and billions of seed-covered twigs, littering them about the trails. There is something ridiculous and sad about seeing a black slug covered in cottonwood seeds. Many a slug was so decorated today.
I ran clockwise to mix things up and felt a little creaky to start but still tied my fastest pace for the first 1K at 4:37. The left shin behaved itself and was not a factor. Annoyingly the left foot was hurting more but again it did not slow me down. In general I feel like I am riding an edge where I get through these various ailments or one of them turns for the worse. I am hoping for the former, obviously.
I felt like my pace was going decently but not spectacularly. Specifically it felt like I was maybe lagging a bit in the middle and I resolved to put in a little more effort for the final km. This resulted in my fastest finish ever — 4:45/km and brought down my average pace to another personal record, 4:49/km, the first time I’ve dipped under 4:50 and three seconds off my previous best. The finish actually built up from the 8K mark where my times actually reversed and got faster instead of slower. I apparently hit my stride.
I am especially happy with the strong finish, particularly with the crankiness I was experiencing with the foot. Legs and feet are both feeling better now, which makes me cautiously optimistic.
Also, the new Nike+ site went live today (no more Flash, woo) and my early impression is that it’s much more improved over the previous iteration. I can even cut and paste my run times like so:
4’37″/km
4’45″/km
4’49″/km
4’51″/km
4’49″/km
4’49″/km
4’51″/km
4’54″/km
4’53″/km
4’52″/km
4’45″/km
Now if I could figure out a way to conveniently convert that data into my ongoing table I’d be set.
Chart:
| km | Jun 6 | Jun 4 | Jun 1 | May 30 |
|---|---|---|---|---|
| 1 | 4:37 | 4:37 | 4:42 | 4:37 |
| 2 | 4:45 | 4:42 | 4:46 | 4:45 |
| 3 | 4:49 | 4:45 | 4:49 | 4:48 |
| 4 | 4:51 | 4:47 | 4:51 | 4:49 |
| 5 | 4:49 | 4:49 | 4:51 | 4:50 |
| 6 | 4:49 | 4:51 | 4:52 | 4:50 |
| 7 | 4:51 | 4:52 | 4:53 | 4:51 |
| 8 | 4:54 | 4:53 | 4:54 | 4:52 |
| 9 | 4:53 | 4:53 | 4:55 | 4:52 |
| 10 | 4:52 | 4:54 | 4:56 | 4:53 |
| 11 | 4:45 | 4:54 | 4:56 | 4:52 |
