One of my passions obsessions
the past few years has been predicting free agent salaries. It's certainly not
an exact science, and I've whiffed big on some big names in past iterations. The
simplest method of predicting salary is to make a list of past comparable free
agents with similar statistics before their contracts expired and taking an
average of their new deals. This can prove wildly wrong with UFA players where
multiple teams are bidding against each other and driving up price, but for RFAs,
it is probably the closest approximation of what's happening in the negotiating
room or in arbitration.
I developed an algorithm to approximate Free Agent Value (as discussed in a blog post), which was consulted in this process. Its primary purpose is to approximating free agent value to judge how much they were over-under paid any given season. This was an important measure of value in my books about the best and worst contracts signed since the inception of the salary cap. The algorithm wasn't designed to predict term, or adjust itself higher/lower to compensate, as term absolutely affects salary size. Older players will take a lower salary for extra term, while young stars often only take long-term deals if they're getting a generous salary (especially when selling UFA seasons).
My algorithm for 2021 statistics was modified to include each player's 2019/20 output and averaged over 82 games. There were some flaws in this method at the lower end of the pay scale, but the algorithm values are just a guide which play a factor in my final decision. All of the estimates you are about to see are my own judgement call, not the monolithic results of what the algorithm says. The circumstances of this season are too unique to rely too heavily on historical data. Many of the predictions here are significantly lower than the algorithm value because of the Covid induced flat cap.
To view my
predictions for the 2020 free agency period, click here. My results were decent, but were
limited to 139 predictions (graph below). My correlation coefficient dropped by
10% from 2019 to 2020, so my Covid predictions were worse than the previous
season, especially when forecasting term (for which I was far too generous). I
did not bother making predictions for the lower end group, as I’ve considered
them too easy in the past. However, the more low-hanging fruit that’s included
here, the higher my correlation coefficient will be at the end. That’s why
you’re getting 460 predictions in this iteration.
There was an attempt in my 2020 predictions to account for the flat cap, as most salary estimates were significantly below what my algorithm and comparable averages recommended. All my metrics were telling me to go higher, but I bet the under in almost every case. It wasn’t enough. As you can see, my regression line passes through (8,7), meaning when I’m predicting $8M, the outcome is $7M. So for 2021, I’ll have to shave even more money off the sticker price.
The following predictions will be listed in 5 categories; UFA and RFA for both Forwards and Defense, plus goalies. There will be a final prediction list published just before free agency opens. These are simply my mid-term estimates and are subject to change.
UFA FORWARDS
RFA FORWARDS
RFA DEFENSE
GOALIES
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