Getting into the Nitty-Gritty of Nationals Splits
Alright, so I spent some time recently digging into the splits from the nationals. It wasn’t for anything super official, just my own curiosity, really. You watch these events, and you hear commentators talk about pacing, but I wanted to see it laid out, you know? See the actual numbers for myself.
First thing was getting the data. Man, that was a bit of a pain. You’d think it would be straightforward, but the official results page was, let’s say, not the easiest to work with. It wasn’t like a nice clean table I could just grab. Had to do a lot of copy-pasting, and even then, things were messy. Some numbers were squished together, others had weird formatting. Spent a good hour or two just cleaning things up in a basic spreadsheet. Felt like I was wrestling with the computer half the time.
Once I had the times somewhat organized – basically, the time at each marker for a bunch of the competitors – I started doing the simple math. Just subtracting the previous time point from the current one to get the split for that section. Nothing fancy, just basic arithmetic. Did this row by row, athlete by athlete.
Looking for Patterns
This is where it got interesting. Staring at all those numbers, patterns started to pop out.
- Some folks went out like a rocket, absolutely blazing fast in the first part, but then you could see them slowing down considerably later on.
- Others had a more even pace, just clicking off consistent times section after section.
- Then you had the strong finishers, the ones whose last split was noticeably faster than their middle ones.
I started comparing athletes directly. Put the splits for the top few finishers side-by-side. It was pretty clear how different strategies played out. One person might gain a lot early, another would reel them back in towards the end. It wasn’t always the fastest starter who won, that’s for sure.
I even looked at some folks who didn’t finish on the podium, just to see their approach. Sometimes you’d see someone try a really aggressive strategy that just didn’t pay off. It kind of humanized the whole thing, seeing the numbers behind the effort and the different ways people tackled the same challenge.
Honestly, the whole process was pretty manual. Just me, a spreadsheet, and a lot of patience. No complicated software or anything. But it felt good to actually work through the data myself instead of just reading summaries. You get a much better feel for the flow of the competition that way. It definitely confirmed some things I suspected about pacing and showed me a few surprises too. Was it tedious? Yeah, a bit. But worth it to satisfy my own curiosity and see the story the numbers told.
