Objects on a parallel course give us an interesting example of unification and divergence. On the one hand, they are travelling along the same path, moving towards a common destination, and they never diverge from that path. On the other hand, they never converge; that is to say that despite all the similarities of their path they remain as far apart from each other at the end of their course as they did at the beginning.
What on Earth am I talking about here?
The funny thing about advanced statistics is that the ones I find most useful – the ones I consult frequently when evaluating players – are representative of items that any qualified, diligent observer would pick up just from watching a lot of games.
Take Quality of Competition and Quality of Teammates. There probably isn’t a fan of the game that fails to understand the relative value of playing with Ales Hemsky versus the relative value of playing with Steve MacIntyre. It’s an axiomatic truth: line-mates impact performance. Similarly, down through hockey history there has always been a certain cachet that comes with shadowing top players. Don Cherry preached it as a coach and it goes back well before his day.
What QualComp and QualTeam do is put a number to these values. This is important, for a couple of different reasons. The first is that the average fan isn’t especially good at picking out who plays top opposition, all by themselves. For years now – certainly the entirety of the post-lockout era, probably longer – power vs. power (where the top players face each other) has been the preferred matchup for most NHL coaches. Despite this, fans have persisted in identifying third-line as the guys facing the stars. Sometimes it’s true, especially in the past – Todd Marchant held the role for a time in Edmonton, while Anaheim and New Jersey have both had extended periods where they used a checking line – but as a rule it doesn’t happen. Carefully watching matchups is one way of doing it, and in my experience the matchups rather closely mirror QualComp.
The second reason is that even if a fan is careful about watching how a coach runs his lines, it is all but impossible to watch enough games to properly evaluate all 30 teams, particularly as injuries start accumulate and lineups get jigged around.
QualComp is a help in both areas – it serves as a sanity check for personal observations on a team one follows closely, and it provides data for teams that one person simply doesn’t have time to follow in-depth. It shouldn’t be regarded as something alien: it simply condenses a task that any competent observer should be doing in the first place.
Zone Starts are a similar statistic. A competent observer who watches a lot of games can generally tell you which players are relied on for shifts in their own end, and which players get used in a lot of offensive situations. He knows that these things matter – players on the ice in their own end a lot not only have a higher chance of getting scored on (especially off a lost faceoff) but to get a scoring chance of their own they must travel 200 feet, penetrating increasingly sophisticated defensive schemes, all the while knowing that every deke and every pass could be picked off and lead to a chance against. A player having a perfect shift might spend 30 seconds chasing the puck in his own end and 10 seconds getting the puck up ice, but be forced to dump it in to get the line change. He just played a perfect shift but never got an opportunity to score.
The reverse is true as well. A player starting in the offensive zone has a higher chance of scoring a goal (especially following a successful faceoff), and even if his team loses possession he now has 200 feet to reclaim the puck, and any mistake by the opposition can lead to a scoring chance. Off a won faceoff, this player could spend 30 seconds moving the puck around the offensive zone but never threatening, chase it up ice for 10 seconds, and then get the change while the other team is changing – his line played a miserable shift, but they got away with it because the centre won an offensive zone faceoff.
These contextual statistics matter a lot when it comes to evaluating players. Coaches know them without needing to glance at numbers – they’re the ones deciding when and where to use these players. Competent observers that watch a lot of games involving one team know them too, and appreciate the difficulty or ease of the role each player plays – and they probably have a very good idea for teams in the same division and a good idea of teams in the same conference. A casual fan, the guy who watched 15 games this year and was sober for the first period (special exemption for fans of the Oilers/Leafs, where the games encourage drunkenness as a lifestyle choice), probably doesn’t have a clue.
Corsi and Fenwick are a little more esoteric, but they do fit with something coaches have been doing for decades: collecting scoring chances. Even coaching staffs that don’t physically count scoring chances (and these days, I suspect those are rare indeed) consciously evaluate a player’s two-way game. In a battle between Corsi and scoring chances, I’ll always defer to scoring chances, but the fact is we simply don’t have scoring chance data for every team – and both Corsi (shots, missed shots and blocked shots for minus the same against) and Fenwick (shots and missed shots for minus the same against) closely mirror scoring chances – something that’s been shown time and again.
All those fancy numbers really boil down to a very simple concept, something coaches have been doing since the game turned professional – evaluating a player’s two-way game and noting context while doing so.
Getting back to the introduction, I find a lot of the ‘advanced stats vs. watching the game’ style discussions to be unhelpful and rather pointless. If one watches the game closely, think there’s more to playing hockey than scoring goals and adding assists, and believe that how a coach uses a player has a big impact on how successful he is, they won’t disagree with the statistics on much – at most, it will probably be a stylistic argument, on the relative value of hitting and fighting in today’s game, or an argument of degree (‘sure X played tough minutes, but he still ought to have produced more’), or an argument about specific situations (‘Y is a good player generally, but can’t elevate his game when it counts’).
Are those important distinctions? Yes. However, in the main, proponents of both schools are looking for the same thing.