My statistics site was getting way too many columns that I found it necessary to make a few changes. The biggest change is that I grouped my statistics into two categories: one for goals and one for shots. At this time I also changed the code that is behind the scenes as it would make future changes easier. These changes made it possible to highlight the sorted column and also add/delete columns easily as I see fit. You will note these changes in the team pages as well as the forward and defense pages.
Another feature I decided to add is a items to display per page options. I have always only shown 30 items per page; now there is the option of showing more. Please only use ALL if you really need to see all the players as it can be a bit slow. I also allow users to sort by ice time per game, second assists (in the shooting statistics section).
I also added the requested column: average shot distance (only for even strength). You can also see how many shots/game each player gets (or shots/60 min)
If there are any problems with the site, please let me know.
December 30, 2007
December 20, 2007
Everything you wanted to know about the Shoot-out
Edmonton started the season going 10-1 in the shoot-out (now they are 10-2), this event brought about an interesting discussion on shootouts. I've been holding back posting anything about shoot-outs primarily due to lack of data, but after two seasons (plus a bit). It got me thinking: what led to Edmonton doing so well? Was it all luck or was skill a big part of it.
Looking at this without knowing any details it would appear that the shootout results are in fact perfectly random, you can sort of see some clustering in the middle, but other than that there are too many anomalies to make sense of anything. Let me however make a few key points:
1. LA: Lost Garon (80% shootout save percentage after 2005-2006)
2. Carolina: After the playoffs dumped Gerber and Ward has 1 win in three seasons
3. Florida: Lost Luongo
4. Philadelphia: switched to Niittymaki
5. Pittsburgh: started to use Fleury more often
6. San Jose: Toskala thankfully only played 1 shoot-out game in2006-2007 (0 wins in his career)
Remove the above points and you have a data set that has so much more structure. Of course I could probably think of good reasons to exclude every point on this graph, I'm simply trying to show that there are some key points that shouldn't be included because too much changed.
Since it appeared that Goalies were a big part of the shootout results. I figured I'd best compare goalie's save percentages in the shootout. Now the graph below BIG = BAD, small = GOOD. The graph below shows player's Z-scores. A Z-score of -2 means that only 2.5% of players will do better, a Z-score of -1 means that 16% of players will do better than that player. A score of 0 means that 50% of players are better, 50% are worse. A score of +1 means that 16% of players are worse and a score of +2 means that 2.5% of players are worse. [Very simplistic explanation]. These Z-scores are necessary because each goalie sees a different number of shots and it's easier to stop 100% of the shots if you only see three shots than it is to stop 100% of the shots when you see 100 shots. The main point I want to make is that having a Z-score of 2 one year suggests that you will have a Z-score of 1 the next (this is called a regression to the mean).
This regression to the mean is quite small, as it is saying that half of the average goalie's save percentage results are due to luck the other half come from skill (in a given season). [Individuals could be quite different]
In translation: Garon's 90% save percentage on the shootout, should be closer to (0.9-0.66)/2+0.66 = 78%r 78% (his career save percentage is: 46/58 = 79%).
Statistics by round:
1: 616 Shots. Shooting%: 0.3669
2: 616 Shots. Shooting%: 0.3344
3: 460 Shots. Shooting%: 0.2978
4: 83 Shots. Shooting%: 0.3494
5: 40 Shots. Shooting%: 0.3500
6: 24 Shots. Shooting%: 0.2917
7: 14 Shots. Shooting%: 0.286
8: 11 Shots. Shooting%: 0.364
9: 4 Shots. Shooting%: 0.250
10: 2 Shots. Shooting%: 0
11: 2 Shots. Shooting%: 0
12: 2 Shots. Shooting%: 0
13: 2 Shots. Shooting%: 0
14: 2 Shots. Shooting%: 1
15: 2 Shots. Shooting%: 0.5
Note Round 9+ 16 shots, 25% shooting percentage.
In general later rounds are easier to stop. So if a goalie plays until the 7th or 8th round his numbers should be better than a goalie who only sees the first two shooters.
On the surface it would appear that shooting percentage is all luck as there is no correlation between years. That being said, the graph below could just be the result of playing different opposition.
What is a guy like Garon worth in just the shootout. Well assuming average number of shootouts (10) he wins you an additional 1-2 points (or about $0.75M - 1.0M). [Based on this image , 35% shooting percentage and 80% save percentage]. Of course if you're Edmonton and discovered a way to get to the shootout 3x as often as expected, well then Garon is even more useful.
Team winning percentage
The first thing I looked at was year over year comparisons:
Looking at this without knowing any details it would appear that the shootout results are in fact perfectly random, you can sort of see some clustering in the middle, but other than that there are too many anomalies to make sense of anything. Let me however make a few key points:
1. LA: Lost Garon (80% shootout save percentage after 2005-2006)
2. Carolina: After the playoffs dumped Gerber and Ward has 1 win in three seasons
3. Florida: Lost Luongo
4. Philadelphia: switched to Niittymaki
5. Pittsburgh: started to use Fleury more often
6. San Jose: Toskala thankfully only played 1 shoot-out game in2006-2007 (0 wins in his career)
Remove the above points and you have a data set that has so much more structure. Of course I could probably think of good reasons to exclude every point on this graph, I'm simply trying to show that there are some key points that shouldn't be included because too much changed.
Since it appeared that Goalies were a big part of the shootout results. I figured I'd best compare goalie's save percentages in the shootout. Now the graph below BIG = BAD, small = GOOD. The graph below shows player's Z-scores. A Z-score of -2 means that only 2.5% of players will do better, a Z-score of -1 means that 16% of players will do better than that player. A score of 0 means that 50% of players are better, 50% are worse. A score of +1 means that 16% of players are worse and a score of +2 means that 2.5% of players are worse. [Very simplistic explanation]. These Z-scores are necessary because each goalie sees a different number of shots and it's easier to stop 100% of the shots if you only see three shots than it is to stop 100% of the shots when you see 100 shots. The main point I want to make is that having a Z-score of 2 one year suggests that you will have a Z-score of 1 the next (this is called a regression to the mean).
This regression to the mean is quite small, as it is saying that half of the average goalie's save percentage results are due to luck the other half come from skill (in a given season). [Individuals could be quite different]In translation: Garon's 90% save percentage on the shootout, should be closer to (0.9-0.66)/2+0.66 = 78%r 78% (his career save percentage is: 46/58 = 79%).
Save percentage By Round
Now there are a few things to keep in mind:Statistics by round:
1: 616 Shots. Shooting%: 0.3669
2: 616 Shots. Shooting%: 0.3344
3: 460 Shots. Shooting%: 0.2978
4: 83 Shots. Shooting%: 0.3494
5: 40 Shots. Shooting%: 0.3500
6: 24 Shots. Shooting%: 0.2917
7: 14 Shots. Shooting%: 0.286
8: 11 Shots. Shooting%: 0.364
9: 4 Shots. Shooting%: 0.250
10: 2 Shots. Shooting%: 0
11: 2 Shots. Shooting%: 0
12: 2 Shots. Shooting%: 0
13: 2 Shots. Shooting%: 0
14: 2 Shots. Shooting%: 1
15: 2 Shots. Shooting%: 0.5
Note Round 9+ 16 shots, 25% shooting percentage.
In general later rounds are easier to stop. So if a goalie plays until the 7th or 8th round his numbers should be better than a goalie who only sees the first two shooters.
Shooters:
On the surface it would appear that shooting percentage is all luck as there is no correlation between years. That being said, the graph below could just be the result of playing different opposition.
What is a guy like Garon worth in just the shootout. Well assuming average number of shootouts (10) he wins you an additional 1-2 points (or about $0.75M - 1.0M). [Based on this image , 35% shooting percentage and 80% save percentage]. Of course if you're Edmonton and discovered a way to get to the shootout 3x as often as expected, well then Garon is even more useful.
December 19, 2007
Brad Stuart
It's hard to miss Brad Stuart. A lot of good things have, been said about him. But he seems to have been involved in a lot of bad trades recently (Stuart being the bad part).
Traded from a losing San Jose team (to a losing) Boston team for Joe Thornton. Many people might point to Thornton as the reason San Jose made the playoffs, but it appears that the loss of a key defenseman wasn't too big of a problem. (Boston ended up with 74 points)
From Boston, Stuart (along with Primeau) was traded for a 1st round draft pick, Kobasew and a solid defender: Andrew Ference. Interestingly, after the trade Calgary struggled and just squeezed themselves into a play-off spot
Stuart is now playing for a team that, as of last year, appeared to only need a goaltender: Los Angeles. Labarbera has provided the goaltending, but now the team lacks any sort of defense. Allowing over 30 shots per hour at even strength and the shots that hit the net are almost 20% more difficult to stop.
Stuart may not be the worst on the team in terms of plus-minus, but he certainly is up there with his -10 (and another -2 vs Detroit tonight).
Looking at a short window of history, Stuart may have just signed and been traded to bad teams, his record in the previous 187 games is appalling: 42% winning percentage.
"[Brad Stuart] is prone to mistakes in pressure situations, which has led him into the coach's doghouse in the past. Doesn't use his size effectively enough." - Sportsnet.ca, what more can I really say...
Traded from a losing San Jose team (to a losing) Boston team for Joe Thornton. Many people might point to Thornton as the reason San Jose made the playoffs, but it appears that the loss of a key defenseman wasn't too big of a problem. (Boston ended up with 74 points)
From Boston, Stuart (along with Primeau) was traded for a 1st round draft pick, Kobasew and a solid defender: Andrew Ference. Interestingly, after the trade Calgary struggled and just squeezed themselves into a play-off spot
Stuart is now playing for a team that, as of last year, appeared to only need a goaltender: Los Angeles. Labarbera has provided the goaltending, but now the team lacks any sort of defense. Allowing over 30 shots per hour at even strength and the shots that hit the net are almost 20% more difficult to stop.
Stuart may not be the worst on the team in terms of plus-minus, but he certainly is up there with his -10 (and another -2 vs Detroit tonight).
Looking at a short window of history, Stuart may have just signed and been traded to bad teams, his record in the previous 187 games is appalling: 42% winning percentage.
"[Brad Stuart] is prone to mistakes in pressure situations, which has led him into the coach's doghouse in the past. Doesn't use his size effectively enough." - Sportsnet.ca, what more can I really say...
West continues to dominate East
West vs. East (This season)
30 Wins
24 Losses
4 OTW or SOW
2 OTL or SOL
Winning percentage = 30/54 = 56%
185 GF
163 GA
Pythagorean percentage = 1852/(1852+1632) = 56%
What's interesting is that it has stayed so consistent over the last few years.
30 Wins
24 Losses
4 OTW or SOW
2 OTL or SOL
Winning percentage = 30/54 = 56%
185 GF
163 GA
Pythagorean percentage = 1852/(1852+1632) = 56%
What's interesting is that it has stayed so consistent over the last few years.
December 16, 2007
Buy low - Sell high
I haven't said much (if anything) about Lupul, I was curious whether he would rebound or disappear. Also, I didn't know much about Lupul so it was best I kept my mouth shut. I didn't even realize that Lupul was in fact draft 7th overall.
I decided to create a short list of players who were drafted 7th and had a bad season in their early 20's.
1990: Sydor 24 - 58 GP: 12 Points
1993: Arnot 24 - 70 GP: 33 Points
1995: Doan 22 - 79 GP: 22 Points
1996: Rasmussen 23 - 67 GP: 14 Points
1997: Mara 23 - 75 GP: 24 Points
1998: Malhotra 22 - 59 GP: 10 Points
1999: Beech - 14 GP: 4 Points in 2 years
2001: Komisarek 23 - 71 GP: 6 Points
2002: Lupul 81 GP: 28 Points (-29)
Often, if you look at past players, teams will trade these players during or right after their bad seasons. However, teams are quickly disappointed as their high draft pick succeeds in their new environment. What's interesting is that Edmonton didn't like Lupul because of his bad plus minus, so the team picked up Souray (ranked second last in plus minus) and Pitkanen (ranked fourth last in plus minus).
The point I'm trying to make is that all players have bad seasons (often early in their careers) and teams view this as a good predictor of future performance, when draft position is probably a better prediction of future performance than one season. Anaheim was smart to see a player who had done better than expected one year and got a great deal for him (sell high). However Edmonton, after one bad season, dumped this 1st round draft pick (plus their captain) for Philadelphia's trash.
In conclusion, don't give up on a player after one bad season. Also, don't get too excited by one great year either.
I decided to create a short list of players who were drafted 7th and had a bad season in their early 20's.
1990: Sydor 24 - 58 GP: 12 Points
1993: Arnot 24 - 70 GP: 33 Points
1995: Doan 22 - 79 GP: 22 Points
1996: Rasmussen 23 - 67 GP: 14 Points
1997: Mara 23 - 75 GP: 24 Points
1998: Malhotra 22 - 59 GP: 10 Points
1999: Beech - 14 GP: 4 Points in 2 years
2001: Komisarek 23 - 71 GP: 6 Points
2002: Lupul 81 GP: 28 Points (-29)
Often, if you look at past players, teams will trade these players during or right after their bad seasons. However, teams are quickly disappointed as their high draft pick succeeds in their new environment. What's interesting is that Edmonton didn't like Lupul because of his bad plus minus, so the team picked up Souray (ranked second last in plus minus) and Pitkanen (ranked fourth last in plus minus).
The point I'm trying to make is that all players have bad seasons (often early in their careers) and teams view this as a good predictor of future performance, when draft position is probably a better prediction of future performance than one season. Anaheim was smart to see a player who had done better than expected one year and got a great deal for him (sell high). However Edmonton, after one bad season, dumped this 1st round draft pick (plus their captain) for Philadelphia's trash.
In conclusion, don't give up on a player after one bad season. Also, don't get too excited by one great year either.
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