Marathon Weekend 2018

[FFigawi]

Well, at least you know this one will stick around until January, so you have a long time to get used to it.

Now if only that @roxymama would change hers too

 

[mawatcha]

Hmm... is it ridiculous that I'm becoming determined to get placed in my previous corral?

I was in Corral B in 2016, but my half time since then has gone up around 5 to 7 minutes.

What's the latest they'll accept time changes? Now I'm gonna have to get properly training and find an August race!

 

[DVCFan1994]

Question, I've only ever had one POT that I entered for prior races. But this time, I may have a second to enter. I did a 10 miler yesterday, so I'd have something to get me moved up a bit. But I am hoping to get a better time at a race in August. Do you have to do anything different to replace one POT with another, or just repeat the same process?

 

[Dis_Yoda]

Hmm... is it ridiculous that I'm becoming determined to get placed in my previous corral?

I was in Corral B in 2016, but my half time since then has gone up around 5 to 7 minutes.

What's the latest they'll accept time changes? Now I'm gonna have to get properly training and find an August race!

October 3rd

 

[mawatcha]

October 3rd

Thanks! I found a mid-2016 race result that should help me qualify for my preferred corral too. Still, good to get training early I guess .

 

[courtneybeth]

Question, I've only ever had one POT that I entered for prior races. But this time, I may have a second to enter. I did a 10 miler yesterday, so I'd have something to get me moved up a bit. But I am hoping to get a better time at a race in August. Do you have to do anything different to replace one POT with another, or just repeat the same process?

I could be misreading this question, but you just go into your race registration and edit the POT submission area. But double-check as it can be 2-3 times of entering the data before it accepts it.

 

[FelisLachesis]

(sorry, I might lose a few of you with this message)

@DopeyBadger , I'm wondering about the McMillan calculator, and how it comes up with the results. Is the calculator simply a linear ratio of the change in distance? E.g. going from 10 miles to a marathon, it will just simply multiply the time by 2.62?

 

[Dis_Yoda]

(sorry, I might lose a few of you with this message)

@DopeyBadger , I'm wondering about the McMillan calculator, and how it comes up with the results. Is the calculator simply a linear ratio of the change in distance? E.g. going from 10 miles to a marathon, it will just simply multiply the time by 2.62?

The McMillan is not linear. It accounts for a slow down when mileage is increased.

 

[ZellyB]

Now if only that @roxymama would change hers too

So true!! I mean she HAS completed a half-marathon now with ease. Right, @roxymama?

 

[roxymama]

So true!! I mean she HAS completed a half-marathon now with ease. Right, @roxymama?

@FFigawi @ZellyB I can't be distracted right now from my "personal worst" 5k attempt in November. This is gonna need some serious training and dedication!!!

 

[Anisum]

This is unofficial based on the information runDisney provided next to the corral information

I knew you would have this.

Thanks for this! Now I have a goal pace I need to get to in order to meet my goal time

No problem!

 

[DopeyBadger]

(sorry, I might lose a few of you with this message)

@DopeyBadger , I'm wondering about the McMillan calculator, and how it comes up with the results. Is the calculator simply a linear ratio of the change in distance? E.g. going from 10 miles to a marathon, it will just simply multiply the time by 2.62?

@Dis_Yoda is correct. The relationship of the actual race times is not linear. Thus, you can't take mile PR time and multiply by 26.2 to get an estimated marathon finish time.

I think the confusion stems from this comment I made:

Whether it is a 10 miler or HM, it is converted to a marathon estimate using McMillan. Since most people's race times are not linear based on the mcmillan race equivalency calculator, this is why running a 10 miler is usually the most advantageous.

So this use of "linear" was not in description of the of the race times multiplied by a linear number, but rather the relationship when looking at the times on a race equivalency look up chart.

This is an example of a race equivalency chart (Daniels VDOT):



If the relationship were linear, then your race times would look like this:



This person can run a 5:56 mile, a 20:18 5k, and a 3:14:06 marathon. This is not common among recreational runners (I'll get back to this).

More common is a non-linear relationship like this:



This person runs a 6:17 mile, but they don't run a 3:24:39 marathon. Instead, they run a 4:34:59 marathon. Thus, the line connecting all of the data points is not linear, but shows a fade as the distance gets longer.

So, if a linear relationship is not common among recreational runners when using a race equivalency calculator, then where did the race equivalency calculator come from?

One of the first running calculators that I am aware of (and most commonly used today) was published in Runner's World in 1977 by Peter Reigel.

Reigel's formula is: t2 = t1 * (d2 / d1)^1.06
t= time
d= distance

So, as the distance increases by double, the pace declines by 6%.

Other formulas:
Reigel #2:
x = (av)^(1/(1-b))

Cameron:
a = 13.49681 - (0.000030363 * old_dist) + (835.7114 / (old_dist^0.7905))
b = 13.49681 - (0.000030363 * new_dist) + (835.7114 / (new_dist^0.7905))
new_time = (old_time / old_dist) * (a / b) * new_dist

Purdy:
P = A(Ts/Tp - B)
where P - is purdy points
Ts - Standard time from tables + time factor
Tp - Performance time to be compared
A, B - the scaling factors.

VO2max:
percent_max = 0.8 + 0.1894393 * e^(-0.012778 * time) + 0.2989558 * e^(-0.1932605 * time)
vo2 = -4.60 + 0.182258 * velocity + 0.000104 * velocity^2
vo2max = vo2 / percent_max

All of these formulas have something in common, they were written some time ago before the latest running boom. Which means much of the data used to generate these formulas was based on well trained athletes at the faster end of the pace spectrum. Sometimes based off world records.

Vickers made an attempt using real-world current data to come up with a better calculator. He takes into account training (using miles per week) as a first attempt at reworking the calculator at the crux of where most calculators fail: the marathon. In most cases, the race equivalency calculator assumes you are under ideal conditions and ideally trained. But for a portion of the running community, they are not well trained for the marathon and thus the calculator will fail in giving them a realistic goal/pacing strategy. Vickers attempted to fix that error in the calculators with his calculation based on several thousand self-reported results. I reviewed his paper back in November last year in my journal (link).

His forumla is:

Model 1:



Model 2:



This was my final conclusion on Vickers based on my interpretation of his paper:

There are 310 data points in their model 1 prediction (one other race) and 171 data points in the model 2 prediction. The data is further broken down into percentiles of 5%. So for model 1 that means 15 data points and for model 2 9 data points. Getting a lot smaller, right. So when evaluating the actual data I would conclude that the new model (1 and 2) is better than Riegel for everything in the top 67% of their data set, when evaluating the data as raw data. For model 1 that means everyone faster than a expected marathon of 3:52 should use the new calculator and for model 2 a 3:53. However, if you are slower than a 3:52 or 3:53, then the classic Riegel calculator is still better. If you want to say that avoiding a too fast start is the absolute paramount then the time cutoff is more like 4:11-4:14 (faster use the new calc, and slower use the classic calc). Now remember the NYC and Running in the USA averages? They were roughly 4:11-4:38. So essentially, the average runner should still use the classic calculator because the new calculator isn't as good at predicting average to slower times based on those completed in NYC or Running in the USA. Looks like to me they missed the mark with the original data set, and thus when they created a calculator it badly misjudges the times of those in the bottom 50% of marathon runners (but the classic can do those better, or at least according to the limited data set available in their original values).

But I do urge you to read the full synopsis I did because there was definitely some great things about the paper.

So, what is McMillan (as that was the original questions right? Ugh DopeyBadger and is really long winded answers...)

To determine, what he uses I did the following. I entered two random marathon times to see what HM output was generated. One generated output could be correct by chance, but having two match means they're very likely the same calculator.

McMillan -
3:00 marathon = 1:25:32 half marathon
5:25:36 marathon = 2:34:43 half marathon

Daniels VDOT -
3:00 marathon = 1:26:20 half marathon
5:25:36 marathon = 2:36:10 half marathon

Hansons -
3:00 marathon = 1:26:20 half marathon
5:25:36 marathon = 2:36:10 half marathon

Reigel -
3:00 marathon = 1:26:20 half marathon
5:25:36 marathon = 2:36:10 half marathon

From this, it shows that he uses a unique formula. This article (link) from Runner's World in 2014 confirms that it is his own proprietary calculation based on data from real-world samples (not world class).

Hope this helps!

 

[FelisLachesis]

I'm not quoting your message, @DopeyBadger . However, the main summary seems that the relationship between a known time for a distance and a different, unknown distance is an exponential regression. Finding the coefficient of exponentiation is the hard part, but there's loads of run times vs distances for people out there.

It comes down to standardizing the coefficient so the regression is standard for most people after inputting a known time and distance.

 

[Waiting2goback]

@Dis_Yoda is correct. The relationship of the actual race times is not linear. Thus, you can't take mile PR time and multiply by 26.2 to get an estimated marathon finish time.

I think the confusion stems from this comment I made:



So this use of "linear" was not in description of the of the race times multiplied by a linear number, but rather the relationship when looking at the times on a race equivalency look up chart.

This is an example of a race equivalency chart (Daniels VDOT):

View attachment 242264

If the relationship were linear, then your race times would look like this:

View attachment 242263

This person can run a 5:56 mile, a 20:18 5k, and a 3:14:06 marathon. This is not common among recreational runners (I'll get back to this).

More common is a non-linear relationship like this:

View attachment 242262

This person runs a 6:17 mile, but they don't run a 3:24:39 marathon. Instead, they run a 4:34:59 marathon. Thus, the line connecting all of the data points is not linear, but shows a fade as the distance gets longer.

So, if a linear relationship is not common among recreational runners when using a race equivalency calculator, then where did the race equivalency calculator come from?

One of the first running calculators that I am aware of (and most commonly used today) was published in Runner's World in 1977 by Peter Reigel.

Reigel's formula is: t2 = t1 * (d2 / d1)^1.06
t= time
d= distance

So, as the distance increases by double, the pace declines by 6%.

Other formulas:
Reigel #2:
x = (av)^(1/(1-b))

Cameron:
a = 13.49681 - (0.000030363 * old_dist) + (835.7114 / (old_dist^0.7905))
b = 13.49681 - (0.000030363 * new_dist) + (835.7114 / (new_dist^0.7905))
new_time = (old_time / old_dist) * (a / b) * new_dist

Purdy:
P = A(Ts/Tp - B)
where P - is purdy points
Ts - Standard time from tables + time factor
Tp - Performance time to be compared
A, B - the scaling factors.

VO2max:
percent_max = 0.8 + 0.1894393 * e^(-0.012778 * time) + 0.2989558 * e^(-0.1932605 * time)
vo2 = -4.60 + 0.182258 * velocity + 0.000104 * velocity^2
vo2max = vo2 / percent_max

All of these formulas have something in common, they were written some time ago before the latest running boom. Which means much of the data used to generate these formulas was based on well trained athletes at the faster end of the pace spectrum. Sometimes based off world records.

Vickers made an attempt using real-world current data to come up with a better calculator. He takes into account training (using miles per week) as a first attempt at reworking the calculator at the crux of where most calculators fail: the marathon. In most cases, the race equivalency calculator assumes you are under ideal conditions and ideally trained. But for a portion of the running community, they are not well trained for the marathon and thus the calculator will fail in giving them a realistic goal/pacing strategy. Vickers attempted to fix that error in the calculators with his calculation based on several thousand self-reported results. I reviewed his paper back in November last year in my journal (link).

His forumla is:

Model 1:

View attachment 242286

Model 2:

View attachment 242288

This was my final conclusion on Vickers based on my interpretation of his paper:

There are 310 data points in their model 1 prediction (one other race) and 171 data points in the model 2 prediction. The data is further broken down into percentiles of 5%. So for model 1 that means 15 data points and for model 2 9 data points. Getting a lot smaller, right. So when evaluating the actual data I would conclude that the new model (1 and 2) is better than Riegel for everything in the top 67% of their data set, when evaluating the data as raw data. For model 1 that means everyone faster than a expected marathon of 3:52 should use the new calculator and for model 2 a 3:53. However, if you are slower than a 3:52 or 3:53, then the classic Riegel calculator is still better. If you want to say that avoiding a too fast start is the absolute paramount then the time cutoff is more like 4:11-4:14 (faster use the new calc, and slower use the classic calc). Now remember the NYC and Running in the USA averages? They were roughly 4:11-4:38. So essentially, the average runner should still use the classic calculator because the new calculator isn't as good at predicting average to slower times based on those completed in NYC or Running in the USA. Looks like to me they missed the mark with the original data set, and thus when they created a calculator it badly misjudges the times of those in the bottom 50% of marathon runners (but the classic can do those better, or at least according to the limited data set available in their original values).

But I do urge you to read the full synopsis I did because there was definitely some great things about the paper.

So, what is McMillan (as that was the original questions right? Ugh DopeyBadger and is really long winded answers...)

To determine, what he uses I did the following. I entered two random marathon times to see what HM output was generated. One generated output could be correct by chance, but having two match means they're very likely the same calculator.

McMillan -
3:00 marathon = 1:25:32 half marathon
5:25:36 marathon = 2:34:43 half marathon

Daniels VDOT -
3:00 marathon = 1:26:20 half marathon
5:25:36 marathon = 2:36:10 half marathon

Hansons -
3:00 marathon = 1:26:20 half marathon
5:25:36 marathon = 2:36:10 half marathon

Reigel -
3:00 marathon = 1:26:20 half marathon
5:25:36 marathon = 2:36:10 half marathon

From this, it shows that he uses a unique formula. This article (link) from Runner's World in 2014 confirms that it is his own proprietary calculation based on data from real-world samples (not world class).

Hope this helps!

I'm not quoting your message, @DopeyBadger . However, the main summary seems that the relationship between a known time for a distance and a different, unknown distance is an exponential regression. Finding the coefficient of exponentiation is the hard part, but there's loads of run times vs distances for people out there.

It comes down to standardizing the coefficient so the regression is standard for most people after inputting a known time and distance.

Where is @Keels, I thought there was no math allowed?

 

[Sailormoon2]

I'm not quoting your message, @DopeyBadger . However, the main summary seems that the relationship between a known time for a distance and a different, unknown distance is an exponential regression. Finding the coefficient of exponentiation is the hard part, but there's loads of run times vs distances for people out there.

It comes down to standardizing the coefficient so the regression is standard for most people after inputting a known time and distance.

I applaud anyone who actually understands this...I mean I can read all the individual words, but together they don't really make any sense

 

[FelisLachesis]

I applaud anyone who actually understands this...I mean I can read all the individual words, but together they don't really make any sense

Ok, in English:

Say you can run a 10 mile race in a pace of 10 minutes per mile, so 1:40:00 for the entire race. Yes, I'm using nice round numbers for the sake of this argument. If you were going to just jog one mile, that was your goal right now before dinner, would you run it in just 10 minutes? No. Chances are, you can run that single mile faster than that, say 7. Now going back to 10 miles, can you run that 10 miler in 70 minutes? No. Now to make a chart for this hypothetical you, here's your times at various distances:

1 mile - 7 minutes
2 miles - 14 1/2 minutes
3 miles - 22 1/2 minutes
4 miles - 31 minutes

(math nerds, yes, my second derivative is constant, I'm lazy, doesn't affect my example)

and so forth

The fact is, for each additional distance you add, it takes a little more time to finish the next mile than it took the mile before it. The formulas that @DopeyBadger and I are talking about try to mimic that little bit of slowdown everyone faces. However, as the amount of distance increases, the amount of time to that next mile goes up and up, until a point where you are physically exhausted, which causes that last mile to technically take infinite time (as you never actually complete it).

The first formulas used had only compared professional runners, which caused longer times to be a bit underestimated. As more casual runners make more data, the calculations usually get better.

In short, this is why Disney allows 10 milers to be used for PoT, as they take into account the extra time used. But Dopeybadger says that most calculations still underestimate marathon times, so that's why using a 10 miler as PoT is usually your best bet.

Real world example: Usain Bolt's World Record time for the 100 metres is 9.58s. If he could maintain that speed for an entire marathon, he'd finish 26.2 miles in 1:07:19 The world record marathon time is 2:02:57, set by Dennis Kimetto. Surely, there's no way Usain could keep his speed through an entire road race like that.

 

[FFigawi]

Where is @Keels, I thought there was no math allowed?

She's busy making our preparations for DATW

 

[CanadianPaco]

Question checking in for WDW Marathon, I understand that your are asked for ID? Do they ask for photo ID or emailed proof of registration?

 

[FFigawi]

Question checking in for WDW Marathon, I understand that your are asked for ID? Do they ask for photo ID or emailed proof of registration?

As it says on the website,

• You must pick up your own participant packet which includes your event-issued bib number and timing device) during regularly scheduled hours. Individuals will no longer be able to pick up participant packets on behalf of others.
• Download and complete your personalized race waiver online (available approximately two weeks prior to event).
• Visit the Expo at ESPN Wide World of Sports to pick up your Race Packet.
• You must have a valid ID in order to pick up your packet (driver's license, passport, Military ID, Government issued ID.)
• If you do not have a valid photo ID we cannot issue you your race bib. No exceptions will be made.

 

[Dis_Yoda]

Where is @Keels, I thought there was no math allowed?

Math is always allowed as math is fun

Dis_Yoda - Aerospace Engineer & Math Tutor