Last season I started a new project using advanced stats to evaluate Montreal Canadiens players on the fly every 20 or so games, or every quarter of the season. The methodology changed as the season went on and as I refined my knowledge of what stats were most relevant and why.
I believe that I’ve settled on a model now that is fairly easily digestible, but at the same time helps you learn and understand each player’s tendencies, strengths and weaknesses. The biggest hurdle was always collecting the data, then finding a way to make the data interesting and relevant for all readers.
The first two editions at the quarter and half marks of the season were overlong reads with a ton of information thrown at you, so I split it up into positions at the third quarter review. Now I’m going to split it up further, and have each player get their own post. This will allow me to be more expansive on the analysis side of things, while making each post a quicker read.
Because it’s already September, I’ll only be reviewing players who will still be in the Canadiens organization in 12-13. I doubt many people will care that there won’t be a post about Chris Campoli though.
For this post what I want to do is explain each stat I’ll be using, and what they bring to the table for analysis. As before, I’ll be splitting stats up into even strength, powerplay and shorthanded situations. You can also look at our glossary of terms for advanced stats. I’ll also be using a graphic that will show how each player played last year compared to the rest of their career.
EVEN STRENGTH
Time on Ice [TOI/60] – will show how much a player is relied upon in any given situation. This will be displayed in minutes played per 60 minutes of game time. The more a player plays in any given situation, the more likely they’re playing well, and relied on by the coaching staff.
Score Close Shot, Fenwick, Corsi Percentage – are all proxies for possession. While some would argue that possession during tied situations has less trouble with score effects, but the increased sample size has its advantages as well. Last season we expressed these numbers as out of a factor of 1000, but this year we’re just going to use a decimal and express the percentage to make it easier to understand at a glance.
Corsi Relative [Corsi Rel] – is a possession statistic from all of even strength play, relative to a player’s teammates. Using this statistic allows us to eliminate the noise of team effects on possession. On a great team like the Detroit Red Wings, nearly everyone has positive possession, but not everyone is a great player. We can see who is strong and who is weak using this statistic. Expressed as a +/- number per 60 minutes of even strength play, for example if a player is -5, his team is outshot by 5 shots every 60 minutes he’s on the ice.
Offensive Zone Start Percentage [Off Zone Start %] – allows us to see how a coach deploys his players. Who gets defensive responsibilities, who isn’t trusted to play in their own zone, who is used in an exploitation role to generate offense?
Offensive Zone Finish Percentage [Off Zone Finish %] – shows which players push the play from their own zone into the opponent’s zone. Finishing in the offensive zone more often than you start there is a positive, although ending your shifts in the offensive zone more than 50% of the time is always positive.
Corsi Relative Quality of Competition [Corsi Rel QoC] – using the weighted possession metrics of the opponents of each player, we can see the typical competition they face. The stat is by no means flawless, but tells us a lot about which players are used in a tough role, and is especially applicable to defensemen.
Corsi Relative Quality of Teammates [Corsi Rel QoT] – is a stat that we haven’t used in the reviews before, but I’ve mentioned it a few times. It’s the same idea as quality of competition, but measures the kind of support a player has from the players he’s usually deployed with.
On Ice Shooting and Save Percentages [On Ice SH and SV%] – measure the average shooting% of the team while the player is on the ice, along with the average save% the player receives from the goaltenders he plays in front of. These numbers are very transient from season to season and large outliers from the norm are due to random variance that isn’t likely to continue.
PDO – As discussed before, PDO is just on ice shooting and save percentages added together and multiplied by 10 to get an expression out of 1000. PDO trends close to 1000 for all players over time, although players can have slightly inflated or deflated PDO’s as a team if they play in front of an excellent or terrible goaltender.
Scoring Chances For/Against – scoring chances are any shot or missed shot within the home plate area. They are recorded by our very own Olivier Bouchard on his site En Attendant Les Nordiques en Français. Scoring chances are a great way to measure a player’s performance via generating offense as well as limiting offense from the opponent.
Scoring Chance Differential – is simply scoring chance +/- per 60 minutes of play.
Penalty Differential [Pen Diff] – is a stat I whipped up last year to give some context to penalties, as it is a measure of how many penalties a player takes for each one he draws. This shows the value of players who antagonize the other team, get lots of penalties, but draw even more.
Risk/Reward – is our own Christopher Boucher’s stat from his website Boucher Scouting which analyses how many positive events a player is involved in per minute of ice time, minus how many negative events a player is involved in per minute. The higher the risk/reward number, the more effective the player is.
Goals, Assists, Points and Shots per 60 – is simply each stat per 60 minutes played at even strength.
True Plus/Minus – is a +/- statistic that eliminates the noise of inherently random events like empty net and shorthanded scoring. Only even strength play is counted.
SPECIAL TEAMS
Corsi, Corsi Quality of Competition, Corsi Quality of Teammates – is used for special teams because I don’t think there are enough minutes played by each player to make relative statistics that significant. Also there are fewer lower end players who play on special teams, also making relative statistics less significant.
*Special note: There were questions last year about the grades given to players. Each player is graded based on the expectations of their position. It’s subjective, and you’re free to disagree.
With the explanations out of the way, we can get on to the Review/Preview later today!
