Course Routes

Data

  • Race distance (latitude and longitude points)

  • Elevation

  • Elevation change (gain and loss)

  • Slope

  • Aspect ratio

  • Canopy (tree cover)

  • Land cover

Primary Source(s)

  • GPX files created by race organizers

Secondary Source(s)

  • GPX files created by third-parties we deem credible via our verification process. (Importantly, we don’t use GPX files that were generated by a race participant using a watch — at least not yet. The relative inaccuracy of GPS watches is well-documented)

  • GPX files created by us

Uses

Course-related data is the meat and potatoes of Turnsheet. Most of the uses are familiar to trail runners — reporting the high and low points of a race, for instance. A race’s difficulty score is driven primarily by its route specifics. No matter how many aid stations a race might have, if it has 38,000 feet of elevation gain, it’s going to be tough.

Something Cool

We use CalTopo to visualize and analyze our GPX files. Like most of the tools you’ll read about here, we highly recommend it. While CalTopo offers a very capable free version that should meet the majority of the average runner’s needs, we happily pay for a “Pro” subscription. Pro grants us access to two additional (and powerful) features:

  • Resample data — This allows us, as CalTopo states, “to get more accurate [elevation gain and loss] numbers.” It’s certainly not perfect, but it’s a step in the right direction

  • Export data to CSV — This allows us to pull the point-by-point latitude/longitude data that sits behind a GPX file out of CalTopo and perform additional, more detailed analyses. We can, for example, crosswalk the canopy and elevation data to find high points of a race with limited tree cover. These points, we’ve come to find, are a surprisingly good predictor of what we call “big views.” Here is an example of the CSV output.


Weather COnditions

Data

  • Daytime (2:00pm) temperature

  • Nighttime (3:00am) temperature

  • Precipitation

  • Sunrise and sunset

  • Cloud cover

  • Humidity

  • UV index

Primary Source(s)

  • Dark Sky — If you aren’t familiar with Dark Sky, we suggest you check them out. (Their mobile app is first rate). The MA-based company launched in 2011 with the idea of of predicting weather with “down-to-the-minute precision.” It’s cool

Secondary Source(s)

  • None

Uses

We collect five years of historical weather data on each race to help runners understand what conditions will potentially look like on race day. Depending on the race distance — and, by extension, how long it takes to finish — we may report the weather at different locations at different times. That’s why we collect both daytime and nighttime temperatures. The weather conditions at night at Bighorn, for example, are wildly different from the weather conditions at the height of the day.

Something Cool

We have a particular interest in the variability of weather. We believe the increased likelihood of variability in the weather — year to year, hour to hour — makes a race more difficult. If you know with 100% certainty it’s going to be 62 degrees and cloudy on race day, then you know with 100% certainty how to prepare. If there’s a 33% chance of afternoon thunderstorms followed by a 20-degree drop in the temperature — well, ah, pack a coat?


RACE REsults

Data

  • Race name

  • Race date

  • Race distance

  • Race location

  • Runner name (first, last)

  • Runner age

  • Runner gender

  • Runner location (city, state, country)

  • Runner start/finish status (finish, did not finish, did not start)

  • Runner finishing time

  • Runner place

  • Runner gender place

Primary Source(s)

  • Whenever possible, we pull race data directly from a race website. We find these data are the most accurate and comprehensive

Secondary Source(s)

  • If a race does not post results directly on its website, we’ll follow their links to third-party platforms, like UltraSignup (USA!) and Raceday (Canada!). To be fair, these third-party platforms are often primary sources because many events choose to outsource their results reporting

Uses

TBD…

Something Cool

There are lot of ultra-runners out there and, chances are, you’re similar to a few. TBD…


Runner Profiles

Data

  • Name (first, last)

  • Birthday

  • Gender

  • Location (city, state, country)

  • Email

  • Favorite race(s)

  • “Bucket list” race(s)

Primary Source(s)

  • When you create an account with Turnsheet, you’ll be asked to provide this information. You’ll be able to update it as you see fit, when you see fit. (Oh, and you can delete your entire profile at any time — no hoops and no questions asked)

Secondary Source(s)

  • None

Uses

TBD…

Something Cool

TBD…