neroxs.blogg.se

Finishtime
Finishtime




finishtime

RELATED : How to Use Heart-Rate Training Zones for TriathlonĪnother trick is to look at past race results from the event you’re targeting to give a sense of whether a course might be slower or faster than you anticipate. In the build-up to a big event, race simulations provide a testing ground where those zones can be refined and translated into pace, power numbers, and times.

finishtime finishtime

“These athletes often struggle to break down mental barriers to let themselves physically push their bodies to the limits during fitness tests or hard training sessions, making it hard to predict what they ’re truly capable of,” she said.Īs a general rule of thumb, Dietzel expects that most age-group athletes can hold a zone 2 heart rate or effort for an Ironman, zone 3 for a 70.3, zone 4 for an Olympic, and high zone 4 to zone 5 for a sprint. On the other hand, middle-of-the-pack age-groupers or beginners might not be accustomed to the intensity that comes with racing and may not really have similar efforts or results to compare. They also have previous performances that can be analyzed to create more accurate estimates. Olivia Dietzel, owner of LivFit Coaching, explains that finishing times for pros or elite age-group athletes will be much more predictable, because these athletes regularly push themselves during testing and in hard training sessions. This might consist of purposeful long rides and runs at goal pace or key interval sessions for shorter races.Īnother factor to consider is your level of triathlon experience. Instead, it ’s best to base estimates on training sessions or workouts that target race-specific intensity.

finishtime

“You should be able to point to training sessions or other races as evidence to support your estimates otherwise, you ’re just guessing,” said Russell Cox, a triathlon coach and data expert, who has crunched the numbers on thousands of age-group finishes. The first thing to keep in mind is that your times will differ from regular training and a triathlon estimate shouldn ’t be based on your best race times for each stand-alone sport. Even if you pick a reasonable average from your single sport workouts to base your estimation upon, you likely weren ’t doing all three events back-to-back, which can lead to fatigue and slower overall times. Plus, many athletes make the mistake of basing their estimate on best times or PRs achieved during training, which results in a predicted finisher ’s time that might be an unlikely best-case scenario. Total distance is another factor that not only affects speed, but also the extra time that must be added for transitions. Weather conditions and terrain play a big part in pacing on race day. However, there are many variables that make this challenging. If you know how fast you swim, bike, and run, it stands to reason that you could estimate how long it might take you to finish the race. So you’re wondering, based on all your workouts, how long will the race take you? How can you estimate your triathlon finish time? Maybe you want to give your spectator squad an idea about where and when they can cheer you on. Maybe you’ve done one before, but want to try a new distance. Find a way to make that an actual column in your table1, then index it, and you'll be a happy camper.Heading out the door? Read this article on the new Outside+ app available now on iOS devices for members!Ĭongratulations! You ’ve signed up for a triathlon. Just wanted to give a starting point.Īgain, I'm fairly certain your issue is that SCN_TO_TIMESTAMP function. If anyone else wants to edit this and make it better, feel free. WHERE SCN_TO_TIMESTAMP(ora_rowscn) BETWEEN ( SELECT starttime Taskid -Best if you're going to be using multiple taskIDs Here's the CTE anyway, but I doubt it will be much of a performance improvement. However, I think your REAL problem is that you're using a function (SCN_TO_TIMESTAMP) in your where clause, and it's ignoring any indexing on the ora_rowscn column. That's probably the error you're getting. In your second query, your where clause has 1 column trying to compare to TWO columns in your subquery.






Finishtime