“Watch the games!” they yell. “Numbers can’t tell you everything!” they argue.
No, numbers can’t tell you everything and paying attention to analytics doesn’t mean actually watching hockey games isn’t necessary. Few intelligent people will believe in either of those points.
Analytics, statistics and numbers can’t possibly tell you the whole story. But heart, grit, leadership and “tough to play against” don’t tell you everything either. Both are needed.
“They’re studying hockey’s granular events — odd-man rushes, zone entries, shots taken early and late in a shift — and uncovering information that complements intelligence gathered by traditional scouting.
Cracks exist in the latter method. One scout, for example, might prefer to conduct viewings on an AHL player on a Sunday, after he’s played road games on Friday and Saturday. The scout is trying to determine how the player performs when he’s tired to gauge his competitiveness. Another scout might ignore the Sunday viewing as garbage because of fatigue. This centers on a scout’s preferences.
Analytics is about sealing every crack. It’s not accurate enough to look at a goalie’s save percentage. It has to be adjusted for variables such as shot location, quality of competition, and save frequency. This requires math. The adjusted save percentage gives teams a more accurate depiction of a goalie’s skills.”
The key phrase there is “uncovering information that complements intelligence gathered by traditional scouting.”
And the next paragraph?
“The point, after all, is to find value. Teams regularly err by giving fat contracts to players who don’t deserve such plumpness (think four years, $13.5 million to Rob Scuderi). The smart clubs, with analytics as one of their tools, target players whose warts make them unworthy elsewhere”
Some people question why analytics are important and how they can help teams coaches, general managers and organizations succeed. That’s a valid question. Here is how that article attempts to answer it:
“The point is also to adjust game strategy and roster composition to mesh with the data. If teams board the analytics train, coaches will pull their goalies earlier to erase deficits. Forwards will leave a shot alone instead of blocking it. GMs will consider a roster with weight diversity — some 220-pounders with some 175-pound water bugs — instead of body uniformity. Coaches will not dress an enforcer who plays four minutes and chases the puck. Organizations will invest in forwards and goalies more than defensemen.
Such tweaks will require courage. They run counter to generations of hockey tradition. But people with lots of letters after their names will tell you that data doesn’t lie.”
You may be unsure of how much value to place on analytics and you may be uncertain as to how they help your favorite team. That’s perfectly understandable. But completely ignoring “fancy stats” really isn’t at this point. They’re useful. Period. You just need to know when and how they’re useful and how and where to apply them. Or at least you should hope that the team you cheer for understands.
“Player tracking and the information it provides won’t be the magic bullet. Unlike baseball, hockey isn’t a neat chain of static events. Players play offense and defense simultaneously. Substitutions happen on the fly. Goals aren’t scored regularly. A winger can be just as critical to a faceoff win as a center. Teams will need smart hockey people to eliminate the statistical noise.
Perhaps above all else, analytics gets people thinking. Good information validates some theories. It nixes others. But it prompts us to consider ideas we might otherwise classify as foolish. In hockey, that’s a neat and novel approach.”