Flats are random?
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I think I tend to get more flats after recent heavy rains. All the water washes around debris towards the curb and leaves glass and wires pointing upwards in the pavement. That's my theory at least.
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I would propose n km before puncturing would be a more meaningful starting point. The idea would be that you'd have a 95% probability that the tire would go n km before going flat. That last 5% accounts for completely random behavior. But the closer you get to km n, themore likely you are to puncture!
There seems to be some point at which a tire breaks down and the flat rate goes up exponentially, but before you approach that point I don't think a flat is any more likely in the next 10 miles than it was in the first 10 miles.
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There's definitely something to that. Wet rubber is much, much easier to cut than dry rubber, and debris absolutely accumulates on the side of the road, making designated bike lanes flat tire factories.
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Also, small shards of glass are more likely to stick to a wet tire and then slowly work their way through it. Long time members of my club say that they get more flats on rides that happen on rainy days. That would explain why flats happen at the worst times, since rainy day is one of such worst times.
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The trouble here is that riding location is a huge factor in flats. I'm convinced that how many flats you get on your route has essentially no numerical correlation to how many flats I would get with the same tires on my route. Only by comparing two different tires on the same route do I trust the data.
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maybe this is just my experience, but,
0 flats in over 3years doesnt seem random to me
maybe you need to start using armored tires? or ride further out in the lane?
last time I replaced a tire, it was because the tread was wearing thin and threads were showing, yet it had never gotten punctured in its lifespan....
0 flats in over 3years doesnt seem random to me
maybe you need to start using armored tires? or ride further out in the lane?
last time I replaced a tire, it was because the tread was wearing thin and threads were showing, yet it had never gotten punctured in its lifespan....
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...uncontrolled variables... dominate the observations reported in this thread.
When uncontrolled variables dominate, you don't have an experiment worthy of the name. Next...!
When uncontrolled variables dominate, you don't have an experiment worthy of the name. Next...!
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Nonsense. Granted the variables are a bit uncontrolled, but given a large enough sample size order emerges from chaos. Besides, I never claimed there was even an experiment in progress, merely data analysis.
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Like many bike commuters, I have a tendency to obsess over flat tires. Like many bicyclists, I'm also a nerd. As a nerd who obsesses over flat tires, one of the things that intrigues me is the problem of understanding flat tire rates, particularly as it applies to comparing various tires.
It's well known among bike commuters that flat tires are essentially random events. You'll go eight months without getting a flat tire, then you'll get three in two weeks. It's just totally random, right? Well, I'm not giving up that easily.
One of the main problems with flats being random events is that it calls into question the possibility of comparing two different models of tires without using both for a long, long time. Nevertheless, as humans we all form opinions based on small sample sizes and can't be convinced otherwise. If I try tire A and get a bunch of flats then switch to tire B and don't get a bunch of flats you won't be able to convince me that tire A wasn't significantly more flat prone than tire B.
But is that really true?
That's one of the questions to which I wanted the answer. So, being a pseudo-scientific type, I set out to collect data. For the last three years I've been compulsively recording all information that seemed relevant about my flat tires -- the date, where I was riding, what the weather was like, how many miles were on the tire, front or rear, cause of the flat, etc. Now with three years worth of data, I'm starting some analysis.
So, I've got two tires, which I will call tire A and tire B. I used tire A for about 1900 miles and got 6 flats. I used tire B for 2000 miles and didn't get a single flat. Obviously tire B is more flat resistant, right? But how to quantify that?
What I decided is that I'd imagine a simplified probability model. I'd choose a somewhat arbitrary probability that I'd get a flat in any 10 miles of riding and then apply that probability to these two tires to see how well it would explain the data.
Let me say that I am aware of the crudity of this model. For one thing, the probability of getting a flat isn't actually consistent over time but seems to increase with tire wear. It also varies with weather and riding location. I'm ignoring these factors.
So, returning to my model, I made the guess that for any 10 miles of riding there was a 3% chance that I'd get a flat tire. Applying that (by means of the binomial formula), I find that in any given set of 200 10-mile trips, there is about a 60% chance that I'd get 6 or fewer flats, so that seems like a reasonable fit for tire A. However, with that probability, there is only a 0.2% chance that I would get zero flats in 200 10-mile trips. If both tires actually had this same probability of getting a flat, there would be about a 1 in 1000 chance that I would get more than 5 flats with tire A while getting no flats with tire B.
Conversly, in order to get as much as a 1 in 4 chance that I could have used tire B for 2000 miles without getting a flat, I have to assign a probability of 0.7% for a flat in any given 10 mile trip. Applying that value to tire A, there would be a 99.7% chance that I'd get fewer than 6 flats. This yields less than a 1 in 1000 chance that I would get more than 5 flats with tire A while getting no flats with tire B.
So, my conclusion is that given two tires both used for 2000 miles in similar conditions if one tires gets 6 flats while the other gets 0 flats then I can, in fact, trust my belief that the tire that got no flats has better flat protection.
The next thing I'd like to know is how many flat tires you need to get before you can conclusively say that a tire is not as flat-resistant as another tire that got no flats.
Yes, I have too much time on my hands.
It's well known among bike commuters that flat tires are essentially random events. You'll go eight months without getting a flat tire, then you'll get three in two weeks. It's just totally random, right? Well, I'm not giving up that easily.
One of the main problems with flats being random events is that it calls into question the possibility of comparing two different models of tires without using both for a long, long time. Nevertheless, as humans we all form opinions based on small sample sizes and can't be convinced otherwise. If I try tire A and get a bunch of flats then switch to tire B and don't get a bunch of flats you won't be able to convince me that tire A wasn't significantly more flat prone than tire B.
But is that really true?
That's one of the questions to which I wanted the answer. So, being a pseudo-scientific type, I set out to collect data. For the last three years I've been compulsively recording all information that seemed relevant about my flat tires -- the date, where I was riding, what the weather was like, how many miles were on the tire, front or rear, cause of the flat, etc. Now with three years worth of data, I'm starting some analysis.
So, I've got two tires, which I will call tire A and tire B. I used tire A for about 1900 miles and got 6 flats. I used tire B for 2000 miles and didn't get a single flat. Obviously tire B is more flat resistant, right? But how to quantify that?
What I decided is that I'd imagine a simplified probability model. I'd choose a somewhat arbitrary probability that I'd get a flat in any 10 miles of riding and then apply that probability to these two tires to see how well it would explain the data.
Let me say that I am aware of the crudity of this model. For one thing, the probability of getting a flat isn't actually consistent over time but seems to increase with tire wear. It also varies with weather and riding location. I'm ignoring these factors.
So, returning to my model, I made the guess that for any 10 miles of riding there was a 3% chance that I'd get a flat tire. Applying that (by means of the binomial formula), I find that in any given set of 200 10-mile trips, there is about a 60% chance that I'd get 6 or fewer flats, so that seems like a reasonable fit for tire A. However, with that probability, there is only a 0.2% chance that I would get zero flats in 200 10-mile trips. If both tires actually had this same probability of getting a flat, there would be about a 1 in 1000 chance that I would get more than 5 flats with tire A while getting no flats with tire B.
Conversly, in order to get as much as a 1 in 4 chance that I could have used tire B for 2000 miles without getting a flat, I have to assign a probability of 0.7% for a flat in any given 10 mile trip. Applying that value to tire A, there would be a 99.7% chance that I'd get fewer than 6 flats. This yields less than a 1 in 1000 chance that I would get more than 5 flats with tire A while getting no flats with tire B.
So, my conclusion is that given two tires both used for 2000 miles in similar conditions if one tires gets 6 flats while the other gets 0 flats then I can, in fact, trust my belief that the tire that got no flats has better flat protection.
The next thing I'd like to know is how many flat tires you need to get before you can conclusively say that a tire is not as flat-resistant as another tire that got no flats.
Yes, I have too much time on my hands.
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You have proven mathematically that the tire with no flats has a lower probability of getting a flat than the tire with more flats. Brilliant! (using Guiness ad voice). Seriously though, it would seem that you cannot assign any probability to getting a flat w/ tire B, since you have not had a flat with it, i.e. the current probability is simply 0 - unless you use data outside your current data set. Also, you don't mention if these tires are on the same back, or whether both tires are both being used in front or rear.
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I can't assign a probability to tire B, but I can (and did) examine the probability that I would get no flats in 2000 miles if the actual probability were some value P. I didn't crunch the numbers, but I suspect that if tire A had only gotten 3 flats, for instance, then the math would have told me the results were inconclusive.
In both cases I was using the same model tire front and rear. They were used on different, but very similar bikes.
In both cases I was using the same model tire front and rear. They were used on different, but very similar bikes.
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It would seem that each flat is an independent event, considering your tires don't touch the same stretch of road ever again on a ride.
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OK, I don't see the point of trying to draw causal correlations from "data" that is drawn from uncontrolled experiments, or non-experiments. Have fun!
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I've concluded that the black tires get more flats than blue tires and I didn't have to work nearly has hard at it as you.
This is of course no help if your bike is red because the blue tires would clash. Imagine the horror if you did get a flat in a blue tire that was mounted on a red bike. I bet no one would stop to help you.
This is of course no help if your bike is red because the blue tires would clash. Imagine the horror if you did get a flat in a blue tire that was mounted on a red bike. I bet no one would stop to help you.
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Flat tires have nothing to do with tubes, tires, protection, etc... they're directly attributable to the Bike Gremlins that accompany all of us
on every ride, waiting to pounce and muck up a perfectly good ride. Good relations with the bike gods, and good karma in general help
alleviate the chaos and misfortune a puncture (or several) can create...
Alan
on every ride, waiting to pounce and muck up a perfectly good ride. Good relations with the bike gods, and good karma in general help
alleviate the chaos and misfortune a puncture (or several) can create...
Alan
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Flat tires have nothing to do with tubes, tires, protection, etc... they're directly attributable to the Bike Gremlins that accompany all of us
on every ride, waiting to pounce and muck up a perfectly good ride. Good relations with the bike gods, and good karma in general help
alleviate the chaos and misfortune a puncture (or several) can create...
Alan
on every ride, waiting to pounce and muck up a perfectly good ride. Good relations with the bike gods, and good karma in general help
alleviate the chaos and misfortune a puncture (or several) can create...
Alan
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Like many bike commuters, I have a tendency to obsess over flat tires. Like many bicyclists, I'm also a nerd. As a nerd who obsesses over flat tires, one of the things that intrigues me is the problem of understanding flat tire rates, particularly as it applies to comparing various tires.
It's well known among bike commuters that flat tires are essentially random events. You'll go eight months without getting a flat tire, then you'll get three in two weeks. It's just totally random, right? Well, I'm not giving up that easily.
One of the main problems with flats being random events is that it calls into question the possibility of comparing two different models of tires without using both for a long, long time. Nevertheless, as humans we all form opinions based on small sample sizes and can't be convinced otherwise. If I try tire A and get a bunch of flats then switch to tire B and don't get a bunch of flats you won't be able to convince me that tire A wasn't significantly more flat prone than tire B.
But is that really true?
That's one of the questions to which I wanted the answer. So, being a pseudo-scientific type, I set out to collect data. For the last three years I've been compulsively recording all information that seemed relevant about my flat tires -- the date, where I was riding, what the weather was like, how many miles were on the tire, front or rear, cause of the flat, etc. Now with three years worth of data, I'm starting some analysis.
So, I've got two tires, which I will call tire A and tire B. I used tire A for about 1900 miles and got 6 flats. I used tire B for 2000 miles and didn't get a single flat. Obviously tire B is more flat resistant, right? But how to quantify that?
What I decided is that I'd imagine a simplified probability model. I'd choose a somewhat arbitrary probability that I'd get a flat in any 10 miles of riding and then apply that probability to these two tires to see how well it would explain the data.
Let me say that I am aware of the crudity of this model. For one thing, the probability of getting a flat isn't actually consistent over time but seems to increase with tire wear. It also varies with weather and riding location. I'm ignoring these factors.
So, returning to my model, I made the guess that for any 10 miles of riding there was a 3% chance that I'd get a flat tire. Applying that (by means of the binomial formula), I find that in any given set of 200 10-mile trips, there is about a 60% chance that I'd get 6 or fewer flats, so that seems like a reasonable fit for tire A. However, with that probability, there is only a 0.2% chance that I would get zero flats in 200 10-mile trips. If both tires actually had this same probability of getting a flat, there would be about a 1 in 1000 chance that I would get more than 5 flats with tire A while getting no flats with tire B.
Conversly, in order to get as much as a 1 in 4 chance that I could have used tire B for 2000 miles without getting a flat, I have to assign a probability of 0.7% for a flat in any given 10 mile trip. Applying that value to tire A, there would be a 99.7% chance that I'd get fewer than 6 flats. This yields less than a 1 in 1000 chance that I would get more than 5 flats with tire A while getting no flats with tire B.
So, my conclusion is that given two tires both used for 2000 miles in similar conditions if one tires gets 6 flats while the other gets 0 flats then I can, in fact, trust my belief that the tire that got no flats has better flat protection.
The next thing I'd like to know is how many flat tires you need to get before you can conclusively say that a tire is not as flat-resistant as another tire that got no flats.
Yes, I have too much time on my hands.
It's well known among bike commuters that flat tires are essentially random events. You'll go eight months without getting a flat tire, then you'll get three in two weeks. It's just totally random, right? Well, I'm not giving up that easily.
One of the main problems with flats being random events is that it calls into question the possibility of comparing two different models of tires without using both for a long, long time. Nevertheless, as humans we all form opinions based on small sample sizes and can't be convinced otherwise. If I try tire A and get a bunch of flats then switch to tire B and don't get a bunch of flats you won't be able to convince me that tire A wasn't significantly more flat prone than tire B.
But is that really true?
That's one of the questions to which I wanted the answer. So, being a pseudo-scientific type, I set out to collect data. For the last three years I've been compulsively recording all information that seemed relevant about my flat tires -- the date, where I was riding, what the weather was like, how many miles were on the tire, front or rear, cause of the flat, etc. Now with three years worth of data, I'm starting some analysis.
So, I've got two tires, which I will call tire A and tire B. I used tire A for about 1900 miles and got 6 flats. I used tire B for 2000 miles and didn't get a single flat. Obviously tire B is more flat resistant, right? But how to quantify that?
What I decided is that I'd imagine a simplified probability model. I'd choose a somewhat arbitrary probability that I'd get a flat in any 10 miles of riding and then apply that probability to these two tires to see how well it would explain the data.
Let me say that I am aware of the crudity of this model. For one thing, the probability of getting a flat isn't actually consistent over time but seems to increase with tire wear. It also varies with weather and riding location. I'm ignoring these factors.
So, returning to my model, I made the guess that for any 10 miles of riding there was a 3% chance that I'd get a flat tire. Applying that (by means of the binomial formula), I find that in any given set of 200 10-mile trips, there is about a 60% chance that I'd get 6 or fewer flats, so that seems like a reasonable fit for tire A. However, with that probability, there is only a 0.2% chance that I would get zero flats in 200 10-mile trips. If both tires actually had this same probability of getting a flat, there would be about a 1 in 1000 chance that I would get more than 5 flats with tire A while getting no flats with tire B.
Conversly, in order to get as much as a 1 in 4 chance that I could have used tire B for 2000 miles without getting a flat, I have to assign a probability of 0.7% for a flat in any given 10 mile trip. Applying that value to tire A, there would be a 99.7% chance that I'd get fewer than 6 flats. This yields less than a 1 in 1000 chance that I would get more than 5 flats with tire A while getting no flats with tire B.
So, my conclusion is that given two tires both used for 2000 miles in similar conditions if one tires gets 6 flats while the other gets 0 flats then I can, in fact, trust my belief that the tire that got no flats has better flat protection.
The next thing I'd like to know is how many flat tires you need to get before you can conclusively say that a tire is not as flat-resistant as another tire that got no flats.
Yes, I have too much time on my hands.
I can't comment on your dataset since you haven't published it but I don't think the binomial model is the correct one to use. I think you should model it as a Poisson distribution as the of a flat per unit mile (or 10 miles if you want to stick with that), then you can compare the lambda of each different tire and I think that would give you a much better indication of its flat resistance.
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Some flats are random bad luck. However, there are many factors that increase the probability of getting flats, including:
- Running tires with too low pressure, which leads to pinch flats if you hit bumps, potholes, etc. I pump my tires before every ride to help avoid those.
- Riding in the "crud line" of gravel, glass, etc. that accumulates on the edge of roads and at intersections. This, I am convinced, is one of the main reasons why some cyclists get a lot of flats. They are afraid to take the lane, hug the edge of the road, and pay dearly for it.
- Fragile tires. Some tires just get a lot more flats. They are made for racing, speed and light weight. Tires like Vittoria Corsa CXs or other racing versions. I don't buy these kind of tires.
- Riding on wet roads. Unfortunately, this is hard to avoid if you commute, but it is a well-know phenomenum that you get more flats when it's raining or wet roads because glass will stick to your tires easier and debris gets washed into the roadways.
- Reinstalling tires that flat without thoroughly examining them for glass, wire, rocks that are stuck in the tread. This is the leading cause of repeated flats on the same wheel. If you keep getting flats on the same tire, turn it inside out and closely examine the inside of the tread. Run your fingers along it. Examine the outer tread real closely. Chances are very likely that something is stuck in the tread. Sometimes it's a small piece of wire or glass that is barely visible.
- Old tubes with valves that are wearing out. This is probably the most common cause of flats for me because I repair my flatted tubes and sometimes use them for years. Eventually the valves get worn out and they can't be repaired.
BTW, I don't use heavy thick tires like Schwalb Marathons. I use reasonably light but durable tires like Continental GP 4000s, Michelin Pro Races, Vittoria Rubinos. I get several flats a year but I also ride 7,000-8,000+ miles a year. I enjoy riding too much to use heavy, poor handling tires with high rolling resistance. I would much rather fix a few flats than have to slog up all the hills on heavy tires.
- Running tires with too low pressure, which leads to pinch flats if you hit bumps, potholes, etc. I pump my tires before every ride to help avoid those.
- Riding in the "crud line" of gravel, glass, etc. that accumulates on the edge of roads and at intersections. This, I am convinced, is one of the main reasons why some cyclists get a lot of flats. They are afraid to take the lane, hug the edge of the road, and pay dearly for it.
- Fragile tires. Some tires just get a lot more flats. They are made for racing, speed and light weight. Tires like Vittoria Corsa CXs or other racing versions. I don't buy these kind of tires.
- Riding on wet roads. Unfortunately, this is hard to avoid if you commute, but it is a well-know phenomenum that you get more flats when it's raining or wet roads because glass will stick to your tires easier and debris gets washed into the roadways.
- Reinstalling tires that flat without thoroughly examining them for glass, wire, rocks that are stuck in the tread. This is the leading cause of repeated flats on the same wheel. If you keep getting flats on the same tire, turn it inside out and closely examine the inside of the tread. Run your fingers along it. Examine the outer tread real closely. Chances are very likely that something is stuck in the tread. Sometimes it's a small piece of wire or glass that is barely visible.
- Old tubes with valves that are wearing out. This is probably the most common cause of flats for me because I repair my flatted tubes and sometimes use them for years. Eventually the valves get worn out and they can't be repaired.
BTW, I don't use heavy thick tires like Schwalb Marathons. I use reasonably light but durable tires like Continental GP 4000s, Michelin Pro Races, Vittoria Rubinos. I get several flats a year but I also ride 7,000-8,000+ miles a year. I enjoy riding too much to use heavy, poor handling tires with high rolling resistance. I would much rather fix a few flats than have to slog up all the hills on heavy tires.
Last edited by tarwheel; 04-25-12 at 07:43 AM.
#46
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I doubt the extra mass of "heavy" tires is holding you back as much as you seem to think, but rolling resistance certainly is a critical parameter no matter what the riding condition.
#47
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I can't comment on your dataset since you haven't published it but I don't think the binomial model is the correct one to use. I think you should model it as a Poisson distribution as the of a flat per unit mile (or 10 miles if you want to stick with that), then you can compare the lambda of each different tire and I think that would give you a much better indication of its flat resistance.
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I occasionally e-mail the local roads department and ask them to sweep the bike lane somewhere or other. They usually tell me they'll put in a request but that it gets done on a regular schedule anyway. The thing is, in the winter there's usually a very clearly defined line that shows you where the street sweeper stopped, and it's usually very close to the line marking the bike lane. On the plus side, they sometimes actually clean the bike lane when I ask.
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#49
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I have no doubt that heavy tires don't make a significant difference in the actual speed of a bike, and maybe not even its acceleration, but they feel a lot different. If the tire is also hard that's even worse. I don't really care how fast I'm going so much as I care about how much I'm enjoying the ride.
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