On bias-confirming video and the definition of objective analysis

Every video analysis article ever has received the same comment: “I could collect clips of ten bad plays [insert team’s best player] made and argue he’s the worst player on the team.”

I’m sure you could – but that’s not how analysis works.

It is almost impossible for humans to turn off their biases and look at something old like they’d never seen it before. As a result, it is extremely difficult to take an unbiased and objective look at a player. But what does “objective” even mean?

From the Cambridge Dictionary:

So, to get back to the opening quote, if you just take ten bad plays and argue the involved player is bad at hockey, that’s neither objective nor valuable. Yet, writers – including myself – write entirely one-sided pieces again and again, and we have the guts to call the result “objective analysis.”

And there’s a reason for that.

Let’s assume a team’s defenceman sticks out with bad possession numbers. Upon further research, his failure to exit the defensive zone with control seems to be a significant reason for it, although he’s known as a strong skater and puck-mover. Does that mean the numbers are lying and stats are stupid or are they accurate, and if so, can these assertions be supported with video?

This, precisely, is what video coaches exist for, and it is what writers like myself aim to provide the public. So, we dive into video of maybe five or ten games from the past few weeks and look at every breakout said defenceman has made.

Maybe we find the player spent most of his ice time with replacement-level players who don’t get open properly. Perhaps he is frequently matched up against opposing teams’ best forechecking lines, who are too good at shutting down the offensive blue line and the neutral zone. Or maybe the video reveals a lack of awareness, vision, or passing skill.

Whatever our findings may be, we now want to present them to you. Or, in a video coach’s case, to the head coach and the player.

And this is where things get tricky. We don’t want to let our biases rule our thoughts and resulting work, and come up with an entirely negative video package, only because it’s what we wanted to find. We don’t want to include plays we might not have picked up as negative had they been made by a different player but use them anyway because they make this player look bad.

But at the same time, there is absolutely no point in showing you the one time the defender played a perfect stretch pass for a breakaway or the time he fooled a forechecker with a quick fake when he still only breaks out of the D-zone successfully 40 percent of the time.

We shouldn’t go into video analysis thinking “I’m going to make this guy look bad at hockey.” But there is absolutely nothing wrong with looking at statistics and thinking “I am going to find the reasons for this player’s numbers.” In fact, NHL clubs hire people to do precisely this.

Being objective does not equal showing some good and some bad clips of a player. Being objective means going into video analysis open to being proven wrong. But if we are proven right, there is nothing wrong with wrapping that up in a one-sided piece that focuses on nothing but examples of bad plays.

The goal is to dive into video and look out for trends, while shutting off biases as much as humanly possible. What matters isn’t the one time a player did something surprising. What matters are all the times he did the same thing, and what results from those plays.

If our struggling defenceman shows examples of excellent breakouts and clearly displays the skill-set to provide that on a consistent basis, the goal would still be to find out why it hasn’t been working for him. And in a next step, the coaches and the player himself could use the wrong examples to focus on using his skill-set more efficiently and successfully.

So, the next time you get angry about that negative article about a player you like, maybe consider that even an entirely negative thing can be objective analysis.