When reading the Tableau chart below, please take into consideration the following:
- My machine learning (ML) algo (algorithm) removes outliers from the data set. For this reason, do not look at the absolute value of goals predicted, because players like Ovechkin (43.42) and Kucherov (32.9) may end up scoring many more.
- Everything is based on historical data – there is no eye test, human intervention, bias, or opinions accounted for in the ML algo.
How to Read?
In order to get the most value on the chart of predictions below, it is important to look at the following:
- Direction: has the ML algo predicted an increase in goals or decrease? This is represented by the shape of each bubble, where bigger bubbles represent larger differences. For example W. Karlsson (-18.6) and E. Staal (-14.4) see the biggest dips in goal scoring this year (buyer beware!). On the other hand, Burns (+10.8) and Tkachuk (+9.8) should see significant increases in goals.
- Relative Position: everything should be looked at relatively (or as a Rank). For example, Ovechkin and Laine are predicted to be the goal scoring leaders this year in NHL. However, the number of goals predicted may not actually be the actual goals scored.
- Chris Kreider (NYR)
- Max Pacioretty (WPG)
- Joe Pavelski (SJS)
- William Nylander (TOR)
- Correy Perry (ANA)
- William Karlsson (VGK)
- Kyle Connor (WPG)
- Eric Staal (MIN)
- Anze Kopitar (LA)
- Sean Couturier (PHI)
The rankings can be found here.