Parallel Paths


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.

  • positivebrontefan

    So much of the antipathy against advanced stats is nothing more than kneejerk anti-intellectual resentment.

    Willis, keep on rocking in the free world.

  • A time not ages ago, my girlfriend and I went out to lunch. Sitting next to us was a table of 5 boisterous Spaniards. As the meal went on, I became increasingly annoyed at the repetitive ‘bada-yada-mada-bada-bada-el-bada’ of what I perceived to be gibberish assaulting my ears. Imagine 5 grown men looking at each other and arguing loudly in baby-speak gibberish. It was distracting and annoying.

    Eventually they left us to a peaceful meal and I realized that though I was slightly annoyed at the volume, I was mostly annoyed because I didn’t understand Spanish. The constant bombardment of information I had no hope of understanding was overwhelming and thus annoying. Kind of like turning up a radio or TV to full volume and leaving it off station. It was full blown noise.

    I feel sometimes the same way when bombarded by statistics. All I wanted was to enjoy and discuss my hockey team and here we have all these strange symbols noisily ruining that for me.

    But, like the episode at the restaurant, it is mostly because I haven’t yet learned enough of the language to realize that it isn’t something to be annoyed about. It isn’t noise.

    Thanks JW for starting the process of understanding for some of us and explaining a few concepts such as Corsi, Fenwick, and Qualcomp. Now if you could just teach that ‘chef’ how to cook a steak right.

  • It’s all just added context. I’m not a pro scout and I dont have access to behind the scenes info. So why would I shun any kind of added info that’s available to me.

    Some of the info is presented poorly, IMO, for the average fan, but that’s why I appreciate your articles that try to marry those numbers with the things that we see on the ice in a more meaningful way.

    Anyone that gets angry at the stats is a goof. They dont have to agree with their relative importance compared to a mainstream stat, but how has getting more info ever hurt them?

  • book¡e

    Let me start by saying that I really believe stats are valuable.

    However, there is also a rigidity in them that sometimes is bested by the ability of humans to evaluate complex situations through combining rational (active) thought with intuition (the part of our brain that thinks without our active involvement). Intuition which is carefully combined with rational thought (including the use of stats) may be more effective than rational thought alone. With that said, many individuals who are ineffective at rational thought (and perhaps intuitive thought) are often poor at decision making, such as knowing which is the lucky slot machine

    Decision making for things like blackjack, tax investments, precise engineering and so on are most effectivly accomplished through very rational processes – intuitive thought tends to cause problems when brought into these realms.

    However, even relatively simple games, such as poker and Chess (simple when compared to many real world situations) often involve the use of intuitive thought alongside of carefully thought out rational strategies. Some of the best poker players in the world indicate that they rely on ‘gut instinct’ to identify if someone is bluffing or not. In actuality, these individuals are relying on their very effective intuitive ability to read other players – thousands of signals (blinks, sweat, eye movements, card movements, etc) all being observed and run through an intuitive evaluation process that results in a ‘gut feeling’. Most of us are not blessed with that intuition for reading other players (and have not developed it through practice) and as such, our gut instincts may be more harmful than helpful when we play poker – particularly if we let it overwhelm the logic of what our cards are telling us.

    I have seen this in rigid cost-benefit processes for contracts. A group will set rigid points based criteria for evaluating proposals for a project (such as the development of our Airport lands in Edmonton) and then they will assign points and then add everything up to come to THE answer. Then the result comes up and everyone is a bit shocked and feeling unsatisfied with the result. Pretty soon the discussion turns to how they must have weighted the criteria wrong. Then they start manipulating the weighting of the criteria until they get the result that ‘feels right’. Problem solved.

    So, I guess what I am saying is that stats are really important, but never count out that old pro that just seems to make the right decision all of the time – even if he can’t explain why with the use of advanced stats. Also, keep in mind that sometimes, you just have to go with your gut.

    btw – this is not in any way contradictory to JW who indicated that coaches and others inherently know things about their teams and their sport.

  • DK0

    Great article and I don’t have much to add other then cue the ‘HERP DERP BUT DID ADVANCED STATISTICS TELL YOU RYAN SMYTH WAS COMING BACK!?!/11?’ and ‘I have nothing to add so i’m going to personally attack Willis’ crowd. All you of you retards should move down to the southern states where you can celebrate your disdain for coherent thought and objective thinking with the other Neanderthals.

    • John Chambers

      Yep – I’m actually a big fan of the literature that gets published where the stats serve to offer a conclusion.

      I remember reading where Jay McClement and Mike Richards had the toughest QualityComp in the league and both pushed the puck up the ice in a positive direction. Definitely gives you new angles on guys outside of their boxcars.

      We all know these are quality centremen, but the stats can tell you something about changes in their performance before casual observers do. Like when the wheels fall off a good player, the stats could tell you well before Doug McLean is shouting in your face about in on Sportsnet. Same way that analysts began to downgrade RIM’s stock based on declining margins – they didn’t need to wait to see how slick the iPad 2 was to realize that that Playbooks would damage RIM’s profit-per-share.

      It’s amazing to me that some GM’s would fail to adopt this information into their analysis. It’s what makes contracts like Huselius’ and to a greater extent Kovalchuk’s so mind-boggling.

  • Chris.

    @ Jon Willis:

    Don’t be stupid Willis. People like me who never played hockey at a high level; sit 34 rows away from the ice; consume vast amounts of alcohol during the game while gawking at the cheerleaders, smooch cam, blackberry, and my bag of popcorn… all the while blaahbabablahing to some random neighbor about the shi**y powerplay… We saw em good! We saw em real good!

    You take back everything you said about the casual observer! You owe us an apology sir!

    *Lips pressed tight waiting for his apology.*

  • OB1 Team Yakopov - F.S.T.N.F

    there is a man who lives alone in a building. one day he decides to leave. so he packs up all his things, waters the plants, and turns off all the lights never to come back again. his actions resulted in the death of 6 men, why

    willis i like your stuff and statistical approach to things and i find it very informative, but it hurts and clearly makes me think of riddles. so here is a riddle.

      • Oilers4ever

        bravo bravo, well done sir. extract the crap and you get the relevant, and voila the answer.

        i agree about the enjoyment of riddles. they serve to prove/dis-prove my intelligence at any given moment.

  • ChiliChunk

    JW – Nice article to put the advanced stats into proper context.

    For any of the anti advanced stats guys, if they still don’t see the value after having you laying it out like this, then I assume that they are just mentally lazy. Definitely, it is more fun to be in the ‘saw him good’ camp and as you point out, I’m sure that competent coaching staffs know alot of this intuitively from seeing how their players perform in the different situations that they are placed into.

    However, seeing comparative data, even for the coaching staff, can clear some of the decision making fog. This is valuable, because, as human’s, we are not immune to making irrational choices – even when presented with perfectly ordered data (exhibit A: lottery and casino players).

    • I agree stats are helpful data in decisions. However, 14 teams still finish out of the playoffs, even with all the data coaching staffs have. If the data was the be all and end all, why do we have almost 50% of the teams not making it.

      Statistically, that is the case, however reality means most data really can’t help you beat the odds that half the teams fail.

      50% of marriages fail, yet 100% of people enter into then to succeed. Are we mentally lazy to marry, ignoring we might just fail, or is human nature the true predicter of the future. Will Penner be a duff in LA, or do his stats say he will be a 30 goal scoring and lead the team in hard work?

      • positivebrontefan

        Point one; 30 team league, 16 make the playoffs, wouldn’t make a difference if all the teams operated the same.

        Point two; people are imperfect.

      • ChiliChunk

        I’m going to go out on a limb here and say it’s becuase only 16 tems are allowed to make the playoffs.

        The real questions should be:

        1) which teams conistently make it into the playoffs and which ones consistently fail to make it into the playoffs and why?;

        2) why are there successful marriages succeed and why do others fail?

  • John Chambers

    It becomes painful at times when we always predict the future based on probabilities. Human nature tends to blow most predictions south. How many donairs did Penner eat before the pending game? How late did Eberle stay out chasing his probably pending mate? I find every year probabilities are less than probable and it comes down to wins/ losses and the collection of a series of unfortunate events.

    It is probable the Oilers will not make the playoffs next year comparing them to this and that, but then we bring in all variables across the league, the Oilers might just get two playoff dates come next spring. Probably not, but perhaps likely.

  • John Chambers

    In the end, most NHL players I would think are only moderately victims or beneficiaries of quality of linemates, quality of opposition, and quality of zonestarts. On home ice, coaches might prefer to match lines (although some at the NHL level don’t during the regular season), but everything gets brought back to the mean, more or less, once the road games pile up.

    I doubt regression analysis plays a huge role in a team’s self-evaluation or pro scouting of players. Maybe this is because hockey GM’s are usually former hockey players instead of math or statistics majors, but probably it’s because they rely on their instinctive analysis of the game, rather than advanced stats; a dalliance reserved for hockey nerds like you and I.

    Is Kovalchuk responsible in his own end? No. Is Dustin Penner too fat to play Centre? Yes. Marc Andre Bergeron has a big cannon and is a lousy defenseman. Basically everone who follows the game could tell you these things without referencing Corsi ratings or zone starts. Coaches evaluate the defensive abilities of players and play them on the penalty kill. That’s why they get paid or canned as NHL coaches.

    Meanwhile Dany Heatley makes a career banging in powerplay goals, and if he doesn’t get pp time he sulks like a child, but stats have a hard time explaining it.

    • John Chambers

      And yet, more and more teams are hiring guys or using software to analyze data, including Calgary.

      I don’t think computers hsould be picking players at teh end of the day (though in some cases it may be a good idea), but I think the real value si in separating players who are otherwise too close in ability to be judged through simple observation.

  • Number 94 Is FIST In My Heart

    Good read. To simplify, pretend you’re looking at the path of say Sidney Crosby and Ryan Jones. Now they both start miles apart from each other, yet progress at the exact same rate…this is all hypothetical…so at the end of the parallel path Sidney Crosby is the much better player, but both have progressed in the same fashion