This week I am going to take a break from individual scoring chances and look at the team as a whole. I wrote over at WaPo that this is just a string of bad luck and wanted to go a little more in depth. As you probably know by now, I use a specific definition of what I consider a scoring chance based on shot quality data and log everyone who is on the ice at the time using the script from Vic Ferrari. You can find the spreadsheet online that summarizes each week, and I promise I will get it up to date in the next few days.
First, I want everyone to see how the Caps have been converting their scoring chances to goals. Or rather how they haven’t. Convert percentage is simply goals-for divided by scoring chances-for. I’ll use a 10-game moving average to help smooth out the highs and lows. Period one on the chart is the average conversion percentage of games 1 through 10, while period two is the average of games 2 through 11, and so on. Stats from the Nov 27 game vs CAR are not included due to NHL.com errors.
Complaining about officiating is an unmistakable sign of a poor sport. Only a terrible sportsman blames the referees, but let’s get real: the Caps are getting screwed on penalties against the Pittsburgh Penguins. I’m not here to spread conspiracy theories or accuse officials of malpractice; I’ve just got some cold, hard facts that may blow your mind.
Biostatistician and devoutly “warped” Caps fan, Stevie K, is gifted with numbers in a way that I am not. Whereas my girlfriend does not permit me to keep score at Scrabble, K has performed a statistical analysis to ascertain how soon, in a perfect situation, the Washington Capitals can secure the Presidents’ Trophy (hereafter “The Prez”) for the first time in the team’s history.
What follows is a peek into a disturbed mind, wherein the machinations of p-values and standard deviations are comprehended with ease. Abandon all hope, ye who read on, of understanding what Stevie K now lays at your feet; let the numbers wash over you and ease you into a narcotic stupor. Trip the light fantastic amidst a really big spreadsheet. I promise to bold the important stuff that makes sense to normal human beings.
There’s a lot riding on tonight’s appointment with the Bruins, and it all merits serious discussion. Unfortunately, the Russian Machine is staffed by morons, so we’re going to swap genuine gravitas with overblown stupidity.
If the Caps win tonight, they will break the team’s record for consecutive games won (10, by the 83-84 Caps). They will also break the Bruins’ record for consecutive games lost (8, by the 56 Bruins). The Caps team is playing at their acme right now, whereas the Bruins are hoping they’ve already hit rock bottom. What does this portend for tonight’s game?
Well, if you flip a coin, your chances of getting heads are the same from one toss to another. Ideally, all binary competitions (one winner and one loser) would be like this. If the principle could be extended to sports, the Caps would likely win tonight just because they are the better team objectively. But first we much deal with a few others factors, and also, we must maul intelligent statistical theory until the results please us. Please join us behind the jump.
Chris Clark and Milan Jurcina in a Blue Jackets Uniform. Weird.
The Washington Capitals made a trade this week, picking up Jason Chimera from the Columbus Blue Jackets for Chris Clark and Milan Jurcina. Given that I spent all weekend putting together a spreadsheet trying to approximate the Goals Versus Threshold that Puck Prospectus uses to give an idea of a player’s contributions, I thought it would be a good time to put it to use. I wasn’t able to match their GVT exactly, but I got close enough to make the thing potentially viable.
First, on what GVT is:
“To explain in terms already familiar to sports statisticians, GVT is very similar to VORP in baseball: it is the value of a player, in goals, above what a replacement player would have contributed. The fact that GVT is measured in goals is crucial: statistics that divide up “Win Shares”, so that the ratings of a team’s players sum to that team’s number of wins, are very erratic and non-linear, since wins don’t increase or decrease linearly with team caliber. While hockey is ultimately about winning or losing, players’ contributions always come down to scoring goals and preventing them. A player cannot “win” a game, even though he may be put in a situation where scoring a goal or making a key save would create or conserve a win. Each player’s role, no matter his position, is to try and increase the goal differential in favor of his team. An offensive player who scores a hat trick only to see his teammates allow 4 goals against has nevertheless done his job; a goaltender who stops 39 of 40 shots only to lose 1-0 has likewise performed well. Using this standard, all players can be compared by the same yardstick: how much did they help (or harm) their team’s goal differential?…
GVT is measured in goals. This makes it a convenient unit that hockey fans are already comfortable with.
GVT compares hockey players of all positions and over any period of time.
GVT only uses statistics that lead directly to goals. You cannot incorporate goaltender wins into GVT, because they are not a measurement of goals prevented. However, if you can rationally explain what are the odds of a faceoff win (or loss) leading to a goal or goal against, it would be possible to incorporate faceoff wins and losses into GVT, though I have not done so.
GVT has built-in accounting. The sum of player GVTs on a team equals that team’s GVT plus the replacement level. This is essential, as player statistics often come with caveats. “Kovalchuk scored 43 goals, but he doesn’t play defense and his team isn’t good”. This makes it much easier to measure “how good would this team be replacing player A with player B?” It is also essential in that player success is correlated with team success, which after all is the entire point of the sport.
GVT automatically normalizes for the strength of the league…
GVT does not measure a player’s talent. The statistic measures a player’s contribution to his team’s goal differential. A goaltender that faces zero shots will have a value of zero, regardless of whether he is Patrick Roy or Andrew Raycroft. Likewise, a player that is injured or gets little ice time will see his GVT reduced accordingly. It also does not take into account environment: a player will score more with better linemates, and I make no attempt to adjust for that…
GVT does not measure intangibles. Things like leadership do exist in hockey, and they do help to make your teammates better. However, there is no way to measure this through statistics, and any attempt to quantify it is futile. In effect, we are not trying to see what information is “hidden” in the statistics; we are simply trying to better characterize the information that is at hand”