PREVIOUS: Part 2 (Methodology)
I truly despise the terms “weighted” and “adjusted” when it comes to numbers. To me, it just sounds like someone who’s discovered that they can mess around with numbers dishonestly to prove a point that’s not really defensible.
Understand that when I first started messing around with numbers to any real extent, it was 25 years ago and this is exactly what was happening in the mainstream. Player A scored 41 goals in 84 games – was this better or worse than someone who scored 36 goals in 74 games? If you just weight or adjust the numbers enough, maybe it becomes more clear or maybe it becomes more muddled. But wait, don’t forget that league scoring was higher in one year than in another, so that has to be accounted for….and the next thing you know, someone has inadvertently built a case that Ed Westfall was a better goal scorer than Mike Bossy. (I joke, but if you mess around long enough, goofy things like this can happen.)
And yet, I have to use something along these lines myself. The title of this section (“The Devil and J.J. Daigneault”) is so named for these reasons:
- It’s a nod to the famous short story “The Devil and Daniel Webster”, in which a farmer who sells his soul decides upon his death that, rather than simply accept what he agreed to, he’s going to have the famous lawyer Daniel Webster litigate on his behalf to avoid eternal damnation
- I despise “weighted” and “adjusted” when done lazily to such an extent that they might as well be the devil
- J.J. Daigneault is a (retired) longtime NHL defenseman
Why J.J. Daigneault?
Trivia time! Name the last two defensemen drafted out of the QMJHL who went in the top ten of the NHL Entry Draft.
They are Luc Bourdon (10th overall, 2005), and J.J. Daigneault (10th overall, 1984).
Daigneault was an unspectacular defenseman during his lengthy NHL career, and he was left unprotected in five separate NHL expansion drafts – a record for skaters.
Going into the last year of his hockey career (2000-01), Daigneault had played 898 NHL games. He signed as a free agent with the expansion Minnesota Wild, and played almost entirely with the IHL’s Cleveland Lumberjacks. He would play just a single game with the Wild (January 12, 2001 against Colorado), taking a cross-checking penalty.
Fast forward about 15 years, and somewhere online I stumbled across someone’s assessment of why the Wild’s first season was better than Atlanta’s the year prior or Nashville’s the year before that. Among other things, it was suggested that Minnesota had a huge advantage in NHL experience, and specifically mentioned Daigneault as an example of why.
Daigneault, who played one NHL game with the Wild that year, was specifically cited as an example of how his valuable NHL experience must have blah blah blah. I don’t recall where I found this assessment, and frankly I wouldn’t even bother referencing it today if not for the fact that an idea sprang from it which I’m using now. It was an asinine and completely nonsensical opinion in the first place. It also ignored the fact that Daigneault had played 35 games with Nashville in their first season just two years prior, but if you’re touting the experience of someone who plays one mid-season game against a vastly superior opponent, little things like “having the first iota of common sense” tend to be ignored completely.
When I looked at why Vegas was having unprecedented success by the All-Star break in their first season (2017-18), I dug into the experience factor with Vegas and with the nine most recent expansion teams. But rather than simply accept Daigneault’s experience, I multiplied it by the number of games that he played in the NHL that year – and then I did that for everyone and re-averaged it all back out. This allowed a more accurate picture of re-averaging to assess everything across the board without a single player (and one single game) skewing it very heavily. Again, we’re looking for illumination and clarity here, not for obfuscation and half-truths.
It’s not the end of the discussion over NHL experience, but I think that it creates a more accurate picture than suggesting that a guy who played one NHL game in a season was invaluable because it created a big advantage in experience.
How will it be used?
There are several applications of the J.J. Daigneault-inspired re-averaging that will take place over the duration of this project. Player aging discrepancies come immediately to mind, and will be tackled first in the next part of this series. But it has many further applications as we start really digging into player-related topics.
I’m also not claiming this to be some type of novel or new process. I’m simply explaining that it will be used as we progress, and why.