Shut up and show me the dashboard
I've had an interesting use case over the winter.
Next week I'm competing at the Quebec Winter Triathlon. It's my first one. I've spent almost as much time looking at last year's results as I have training. And as I'm looking at last year's results I can't help but compare my current training to the field and figure out how I'll fair (spoiler - not great).
And I don't think this is a totally crazy use case of analytics- looking at a dataset and wanting to input your own data.
Let's see what that might look like.
First - the winter triathlon.
It's a 25 KM race that involves Snowshoeing, Skating and Skiing - in that order.
There's an elite and an age class category. Obviously I'm not elite, so let's look at the Age Class. Last year there were 75 racers, the majority were men and somewhat surprisingly the 40-60 year olds dominate.
I took a look at each of the disciplines to see how people ranked compared to their overall finish time. A fun side note - the finish time also includes transition time, so Snow+Skate+Ski not = to Finish time. Which threw me for a long loop when doing data validation.
Somewhat interesting is that the Ski is most correlated to the finish. But that kind of makes sense considering it takes the longest to complete.
I can only spend so much time looking at this before selfishly thinking of myself. How would I have finished based on these results. Where do I rank in last year's race.
In Tableau you need a row in order to do anything. With this database I got lucky as they have a dummy participant's row. So I've simply hijacked that. What you can also do with Tableau's unions, is join a blank txt or csv file which will generate a new row.
My first bit of code is replacing the dummy row
IF CONTAINS([Name],"Tirage au Sort")
then [Name Param]
So if it's the dummy row, then replace it with the variable name, otherwise use the name. And you need to do this for every field where you have a field you want to import. For me it looks like this
And now to enter my abysmal times. The Snowshoe and Ski are easy. My snowshoe is brutal and I'm coming in at about 31 minutes. Hopefully that's due to my courses and fatigue or else I'll be starting well back. The Ski is significantly more competitive, I did 11 K the other day in 39 minutes which translates to a 33:10 9K. The Skate I have no idea. I've been skating but it's hard to do 11K on a 200 meter track in a thick crowd. But I used to be good at skating so I'll generously give myself a mid pack time of 29:30.
So those times put me 13th. Which is ludicrous. But a couple of things that I'm sure you're noticing as well:
It doesn't include transition time, which is why my distance ranks seem funky compared to the overall. That could easily tack on 5 minutes.
I haven't factored in fatigue of doing the three events back to back, which will surely be significant.
With this kind of format you can play with it as much as you want, tweaking your inputs to see how you compare to a field. It's a very interesting way to compare your current results to a historical dataset. .