Per my annual tradition, here are NBA playoff odds generated using the model that I shared last year, the year before, and the year before that.
Who made it in, who will make it in next year, and how borderline are some of our favourite not-yet-eligible players?
I'm not here to gloat. Or at least, not about the Raptors. I'm here to gloat about my predictions.
I love how this literature, and our entire understanding of probability, has either been about predicting rainfall of profiting through gambling.
A lot of these teams are really dragged down by having a few weak players, especially if they're expected to play significant minutes.
Next year could go in many directions, since there are no sure-fire NHL candidates. There's no Martin Brodeur or Teemu Selanne. The most accomplished player might not be an NHLer, since it looks like Hayley Wickenheiser is eligible. This gives the committee a lot of room to reconsider players it overlooked in the past.
Some of these teams will be much better than expected, and some will be much worse, but right now we don't know which.
We can fit the data perfectly, but we shouldn’t. This is what’s known as the bias-variance trade-off. The more precise we try to be in fitting the data at hand, the more likely we memorize effects that are due to random variation in the training data that do not generalize to other datasets.
I love lists, and I love arguing, so here are five players who should be on the top 100, and who they could take off.
All this talk about the NHL's Greatest 100 got me thinking about what goes into hockey greatness. I always lamented how there wasn't a Hockey Hall of Fame model like basketball-reference's model. So I thought I would go about predicting both things.