Because SV% is heavily influenced by the team more so than GAA is.
Do 'Expected' goals statistics suck?
- Thread starter Filthy Dangles
- Start date
Oilslick941611
Registered User
There’s nothing wrong with using multiple advanced stats to help inform decisions combined with decision making capabilities. This thread isn’t arguing that. It’s looking at specific advanced stats, in this case expected goals and using it as a basis for predicting goals. Which it isn’t, at least not on its own. The more fancy stats you build into a model the “better” it can be. But most don’t stand on their own.
Dr Pepper
Registered User
I've always felt it was more the opposite, likely due to the Jennings Trophy still being a thing.
Machinehead
Fox Mafia Consigliere
Not only that, but sometimes we can't even tell what direction it's going in.
Bad defense can raise save percentage through sheer volume.
Bear of Bad News
Now 25% more unBearable!
- Sep 27, 2005
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Ken Hitchcock is Exhibit A, B, and C of how team play impacts goaltenders' save percentages.
Either you can conclude that his coaching style focused on limiting high-danger scoring chances at the expense of higher-volume, low-danger shot attempts, or you can conclude that all goaltenders got better when they joined his teams and then got worse when they left.
Either you can conclude that his coaching style focused on limiting high-danger scoring chances at the expense of higher-volume, low-danger shot attempts, or you can conclude that all goaltenders got better when they joined his teams and then got worse when they left.
- Feb 10, 2010
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Goalies often get outsize credit and outsize blame for the defenses in front of them and the coaching schemes.
Depends on how you define "average" for a shot, but the median shot is actually far, far below 0.1 xG. The vast majority of shots have something like 0.01, 0.02, 0.03 xG. 0.1 xG would be classified as a medium danger shots, of which there are only a couple per game.
The main problem here is the assumption that percentages should be averaged additively, even though by the nature of how percentages work, they should be using multiplicative averages. If you do so, you'll find that the proper average is actually far lower than what you would expect.
Expected goals use an exponential distribution and in order to take a meaningful arithmetic mean, you would need to flatten them first. Or alternatively, use the pre-computed z scores for the gamma distribution(while individual expected goal samples follow the exponential distribution, their sum follows the gamma distribution).
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Djp
Registered User
Interesting. I feel there is a way to measure a hockey equiv of WAR in evaluating players.
another area would be how much is a center improving their linenates and how much is a winger driving play
I have problems in this without f as storing in shot/ chance wuality.
fir example you could have gotten 27 shots, then scored 3, sv Oct around 0.889.
When you see the game thr team had 5 odd man chances and 5 other high scoring chances.
Same stats from as different gamr where the D played strong. Thry got 3 PP goals and one shot was s point shot deflection
The rest of the chots were generally between fors as nd boards or ffg its sd nd blue line
It does not truly messurr thr goalie.
You could score s goalie based on quality saves vs quality scoring chances/ shots
Beezeral
Registered User
- Mar 1, 2010
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I'd bet an incredible amount of money that this convo didn't happen. Two people working in analytics willingly telling others that their job is completely worthless. No shot.
FerrisRox
"Wanna go, Prettyboy?"
I promise you this happened. Why on earth would make up a conversation like this? What would the point be?
Strong defenses deflate SV%. It's a whole complex thing, but to simplify it all teams essentially allow the same number high danger chances regardless of team defense.
Bounces R Way
Registered User
It's not about juicing numbers. It's about assigning a blanket value to a shooting event almost entirely based on from where the shooting event took place, and then deciding you can conclude how many goals you are expected to score based on that data. It's true that a 4th liner doesn't often get that many rebound chances but it does happen, and not all that rarely either. You can't dismiss these occurrences as not statistically significant and at the same time accept xG conclusions at their face value.
Expected goals, at least the publicly available models, don't sufficiently account for where the other players are on the ice. How one can possibly then call it a comprehensive appraisal of what has happened then?
So even more than 10x what an Ovechkin one timer from his office at the top of the circle is worth in the model then. Totally flawless definitely.
Could really do without the condescension of "well you must not understand it if you think it's bad". I understand the model just fine and it's because I understand it I don't think it's worth as much as many of the advanced stat zealots do. The entire premise is flawed in its current form and paints a woefully incomplete picture of what occurred during a game.
You're telling me you are applying shooter-dependent and goalie-dependant modifiers for every expected goals-value you come across? Is that what you're doing? Come on. Frankly ridiculous is right. That's no longer a stat that is useful if you have to do a bunch of stuff to it after it's been recorded to make it meaningful. That's not rocket science, merely common sense.
Well if we're accepting a baseline blanket 'expected goals' stat applicable to all players and all situations it really shouldn't matter who is taking the shot should it? But it does. I never argued the the elite players aren't generating the most volume either.
Since you all took issue with my initial scenario lets explore a couple more for how xG is calculated. These are common occurrences in NHL games.
*I know different sites use differing models and apply different filters and gradients etc but they are all at their basic form built upon something similar to the posted diagram above.*
1a) Kevin Rooney starts his shift in the DZ. Loses the faceoff and spends the next 73 seconds along with his linemates chasing the puck around under pressure from his opponents. His goalie bails him out several times. Finally the opponent's fwd line tire and go for a line change leaving Rooney's defenseman in the corner with the puck for an easy breakout with lots of open ice. He passes to Rooney while the rest of his line changes. Rooney, being the responsible and boiler plate nothing NHL player he is knows he must get the puck deep to allow for the next line to establish themselves on the ice. He takes the open ice and crosses the blueline with both opponent defenders in front of him. Rather than just dumping it in the corner Kev decides he should probably get at least one SoG this week so he wrists a 72mph shot at the goalie from just inside the blueline. Unless he shot some heroin between periods the goalie gloves it easily and sets the table for the weakside D to start a breakout.
This is deemed worthy of 0.03 xGs.
1b) Cale Makar starts his shift in the OZ. MacKinnon wins the faceoff and the winger gets it back to Makar. Makar controls the puck and fakes sending it back down low to open up the middle of the ice. He walks the blueline as layers of traffic gather in front of his opponent's net. The goalie can't see the puck through the traffic and stands taller in his perimeter stance to try to find it. Makar sees this and sees an opening through the moving bodies. With no windup he wrists a 72mph shot from just inside the blueline. The shot is well placed and he scores under the goalie's glove. Goalie never saw it and curses his winger for missing his assignment and not blocking the point shot.
This is deemed worthy of 0.03 xGs.
2a) Ryan Lomberg takes a pass with speed in the NZ after some nice work by his other winger to win a high board battle. He has some room so he takes the defender wide and executes some respectable net drive by keeping his feet moving. He's by himself as his linemates are busy picking fleas off each other by the bench. He takes a contested shot along the ice from in tight to the net, the goalie has the angle covered easily and the shot bounces harmlessly to the corner.
This is deemed worthy of 0.3 xGs.
2b) Patrick Kane vacating his defensive responsibilities as he senses the puck is about to turn over creeps past the mouth breathing weakside defenseman still standing on the blueline trying to keep the pressure on. Sure enough Kane's center wins the puck along the boards and lifts a nice outlet area pass to center ice. Kane grabs the puck and is in alone on the goalie. He fakes going high glove and freezes our poor tender before making a move to the backhand and then crossbar down roofs it.
This is deemed worthy of 0.3 xGs.
Go ahead and handwave away these differences if you want but to me they are not reconcilable. It's not that xG models tell us nothing or aren't worth considering, it's that they are incomplete and aren't actually providing what they are claiming to. Over season long samples they can definitely be useful and predictive but stuff like the deserve-to-win'o'meter or NST's charting for individual games just isn't that useful without the context of seeing the game happen. It's not one or the other eye test vs advanced stats, it should be considering both as parts of an overall picture.
Exactly! The worst defensive teams still know how to take the middle of the ice away. Bad defense results in a lot of time spent in the d zone and as a result the volume of low danger chances is the result of bad defense. Goals are scored from low danger chances too. The more low danger chances a team willfully gives up means more goals. However SV% also raises as a result.
High danger chances come from bad mistakes that are one off type plays. Falling down at the blue line, or a bad pass, or a broken stick are where HD chances come from. HD chances are very random at times.
Machinehead
Fox Mafia Consigliere
You're operating under the assumption that xG operates solely based on distance. Here, just as an example, is the list of variables used in Moneypuck's model.
1.) Shot Distance From Net
2.) Time Since Last Game Event
3.) Shot Type (Slap, Wrist, Backhand, etc)
4.) Speed From Previous Event
5.) Shot Angle
6.) East-West Location on Ice of Last Event Before the Shot
7.) If Rebound, difference in shot angle divided by time since last shot
8.) Last Event That Happened Before the Shot (Faceoff, Hit, etc)
9.) Other team's # of skaters on ice
10.) East-West Location on Ice of Shot
11.) Man Advantage Situation
12.) Time since current Powerplay started
13.) Distance From Previous Event
14.) North-South Location on Ice of Shot
15.) Shooting on Empty Net
Based on those parameters, the Rooney and Makar shots are two completely different plays.
The Lomberg and Kane plays are more similar, but Kane going to the backhand changes #5, #6, #10, and probably #4 too if he's completely unfettered as you described.
The potential issue with xG models on certain plays, is that it doesn't factor in ability level when two players take very similar shots. You have not described very similar shots at all.
Hellebuyck only faces shots from 4th liners and that's pumping up his GSAX?
This thread has been pretty interesting.
Bounces R Way
Registered User
Well again, this is the basic model that these other ones such as MoneyPuck are built off of. That basic xG model would record the xG statistic described in my scenarios exactly as I've stated it would. I realize I have not described similar shots at all, that was kind of the point. Even after we apply all those 15 other variables and modifiers to it, the initial data the model is working off of I would judge as flawed and incomplete. Maybe others have a lower bar but I feel if you're going to claim to have proven how many goals a hockey team should have scored in a game you shouldn't have easily picked apart holes in the concept. I also have my doubts all those variables in MoneyPuck's model are recorded and collated accurately as their site looks like it's from 2006, but that's besides the point.
xG operates on two basic parameters to determine the shot quality. Shot distance and shot angle. That's literally it. Do those two basic parameters seem to provide a complete picture of how dangerous a shot is to you?
There's been huge advances recently in the NBA and NFL using statistic modeling that has provided a brief competitive advantage.
MLB has famously been using these ideas going much further back than those two.
Why is the NHL the one league that it wont work for?
Machinehead
Fox Mafia Consigliere
I think you're putting too much weight on it in a sense. Nobody is saying "should have scored." It's a measure of who's dictating the play. It does that pretty well. Out of all the Cup winners since they started measuring xG, all but one of them were good at it.
That's more than enough to at least treat it with some validity, and yet it has to pass more purity tests than people's random opinions based on viewings.
You described two very different events, and like, the models would treat them differently, so I don't know what the point is.
Also, it always gets into this "it's just shot distance" discussion, and whether that's true or not, yeah, distance is the most important variable!
Breakaways, tips, and rebounds go in a hell of a lot more often than seeing eye shots from the point.
