Analytics was always designed to be nothing more than and add-on tool to be used as a drill down option to get a better determination of a player or teams play but not determine wins and losses overall.
Hockey analytics 101: Introduction to core concepts
Expected Goals
Expected goal models assign a value to shots based on their location and other factors such as whether the shot was a rebound, one-timer, etc. The concept of expected goals in hockey is based on the concept that some shots are more valuable than others based on how likely they are to result in goals.
Anyone who has played the game, even in a casual setting, or has watched it intently can attest to the fact that not all shots are created equal. A shot taken from the slot or right on the doorstep is far more likely to go in than a shot taken from a bad angle at the half-boards or a shot taken outside the offensive zone.
Just like Corsi and Fenwick (and other stats), we can measure the expected goals (xG) for a player, line, pairing or team, whether it’s for (xGF) or against (xGA).
This makes xGF% a valuable tool in discerning the quality of shots that occur when a player is on the ice and helps us gain a better understanding of how sound their play is with and without the puck.
Concepts and stats related to expected goals for and against include:
Scoring Chances For/Against (SCF and SCA) and
High-Danger Corsi For/Against (HDCF and HDCA) follow these same principles.
NOTE: They're using xGF% by a player to determine
"how sound his play is with and without the puck" it says nothing at all about predicting game outcome and scores based off it because that would be ridiculous to make that jump and conclusion as you can't control the outcome of the shot. This is simply the analytics truthers misrepresenting the data for a purpose other than its intended use.