You can hide them in the minors, but that only gives you minimal relief. A quick recap: this is our third year doing contract projections for the NHL offseason.

There are some very bad contracts around the NHL. For a given contract, we ensure that we also have each player’s age, draft round/position, height/weight, etc. This rule gets elasticized in training camp, and preseason games are often full of AHL-contracted loaners. Luckily this actually did yield better results and was not for nothing. Matthews had the third-bestselling jersey last season. So the AHL-contracted players on the Marlies are not going to suddenly show up on the Leafs. So right away, algorithms that work well with linear/normal distributions like ordinary least squares regression (“linear regression”) will likely not be ideal. But the downside to this is that we still inevitably have hard cutoffs between the tiers. We’ve chosen to include a “known” contract’s term as a feature in our cap percentage model. They can be renewed, however. Of course, the prior year is still the most important, but this was something that we found quite interesting. And this, my friends, presents quite the problem (that imbalanced dataset thing I mentioned above).

While these seem somewhat commonplace, the skewed distribution of classes presents numerous problems.

With the first part of our final model (term) complete, we move onto the cap percentage model. Try-out deals, nearly always called ATOs and PTOs (A is for amateur and P is for professional) are short-term deals that pay a per-diem and expire after 25 games played. The Leafs signed free agent John Tavares last year and extended the contracts of its own young studs, Auston Matthews and Mitch Marner, in 2019. To go from the AHL to the NHL, the player has to be signed to an NHL SPC. There have been somewhat rare events where NHL-contracted players are loaned to an AHL team affiliated with another NHL club. Here's a look at the best deal on each team heading into the 2019-20 season. I won’t cover all of them (acquiring more data, changing the evaluation metric, etc), but one of the best ways to deal with imbalanced data is to explore different algorithms. Finally (I think this is the last thing although I’m sure we’ll get yelled for something we’ve missed), we do not have anything that deals with arbitration.

We then remove the ‘07-08, ‘08-09, and ‘09-10 seasons. There is another capped amount for rookies, who are players who have played less than 25 professional games.

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