TripleJ Hottest 100 Predictions 2016 Edition
Justin’s Hottest 100 Predictions for 2016. Read More
Justin’s Hottest 100 Predictions for 2016. Read More
Justin explains why some of his predictions were so wrong last year. Read More
Predicting the Hottest 100 for 2015 once again! Read More
Today is the day for the Hottest 100 of 2014. Lots of eager listeners will be waiting to see if anything by Taylor Swift makes it into the countdown, including me. Sadly, work and other commitments have kept me away from the detailed statistics I’d have liked to run on… Read More
I leave the country for a few days, and look what happens! The whole country is up in arms (and down in legs) about whether or not a Taylor Swift song will get enough votes to be in the Hottest100 this year. As some of you may know, the past… Read More
Now that we have the official results, let’s take a look at how we did! All models are wrong, some are useful. Firstly, my model picked 85 songs as being in the top 100, so we missed 15. So did the Warmest 100 list. We got 4 exactly right, as… Read More
I hooked up my MooresCloud Holiday to the stereo today so that I could sync up the light display with TripleJ’s Hottest 100 countdown. The Hottest 100 is a bit of a tradition for me; I’ve listened to it every year since 1993, and I have a few other personal… Read More
This is my last revised list for the Hottest 100. This list is generated using a more sophisticated method (yet again) after a discussion over Twitter I had with @chrisjrn about the kinds of bias there might be in the sample. I refined the list with three techniques. Firstly, I… Read More
I’ve done another couple of data matching runs, and I think I might have a more accurate one than the previous list. There are a couple of significant differences, which I think is due to the way the partial matching Nilsimsa hash works. Basically I’ve tuned the Nilsimsa hash cutoff… Read More
I’ve replicated the methods used by the Warmest 100 crew to check their results. I managed to collect 15,588 total votes compared with their 17,800, so my list will be slightly less accurate, thought I’ve used a slightly more complex matching technique than what @flossinspace did, so that might help… Read More