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0 Subject: Predicting NHL Team Success (Loooooong post)

Posted by: KrazyKoalaBears
- Leader [517553018] Thu, Jan 01, 2004, 23:11

Some of you know that I've set up a computer formula to predict games in the Pick'ems game I run. It hasn't had much success, but, to be quite honest, the formula was not based on any kind of in-depth research or heavy number crunching. It was simply based on what I felt were important stats to consider.

It turns out that I may have been on the right path, just not looking at the right stats, or too many stats. Based on what you'll read below (if you continue), I've changed the formula and am interested to see what the results will be.

The idea of predicting team success has always interested me quite a bit and when I read about the topic in Moneyball, it further piqued my interest. For those of you who haven't read Moneyball, one of the ideas discussed is that there is a "stable relationship between season run totals and season wins." The concept was originated by Bill James and put into effect by Paul DePodesta for the Oakland A's. DePodesta figured out that the A's would have to score 135 more runs than they allowed in order to win 95 games. 95 wins is what DePodesta determined would be the number of wins needed to reach the playoffs.

So that got me thinking about scoring differential for other sports, particularly hockey, and what effect it had on team success. I played around with some of the numbers and stats for teams and compared them to how the teams did. At first, I focused on wins, but hockey is a bit more in-depth than that. When I started focusing on Points (which included ties and OTL), I found a fairly consistent correlation.

What I found was that, within about +/-5 points, you could predict a teams final season Points total by simply dividing the number of goals scored by the number of goals allowed and multiplying by the number of games played (82). I attempted to apply this idea to past seasons, but could only find accurate records for this season and the previous 2 seasons. So, admittedly, this idea has not been backed by years of data. But, the data I have is found below.

2003-04 GP PTS GF GA GF/GA P PTS DIFF DIFF%
TORONTO 38 52 110 92 1.196 45 7 12.63%
DETROIT 40 51 132 95 1.389 56 -5 -8.98%
PHILADELPHIA 38 51 110 81 1.358 52 -1 -1.19%
VANCOUVER 38 50 111 87 1.276 48 2 3.03%
ST LOUIS 35 47 91 79 1.152 40 7 14.22%
NEW JERSEY 35 47 86 59 1.458 51 -4 -8.55%
CALGARY 36 44 83 72 1.153 42 3 5.68%
OTTAWA 36 44 113 76 1.487 54 -10 -21.65%
COLORADO 36 44 103 81 1.272 46 -2 -4.04%
SAN JOSE 38 44 94 85 1.106 42 2 4.49%
ATLANTA 40 43 120 121 0.992 40 3 7.75%
NY ISLANDERS 37 41 110 95 1.158 43 -2 -4.49%
MONTREAL 39 41 88 89 0.989 39 2 5.95%
LOS ANGELES 38 41 101 99 1.020 39 2 5.44%
BOSTON 38 41 91 96 0.948 36 5 12.14%
DALLAS 39 40 79 84 0.940 37 3 8.30%
NASHVILLE 36 38 88 93 0.946 34 4 10.36%
NY RANGERS 36 38 99 94 1.053 38 0 0.22%
MINNESOTA 38 38 83 80 1.038 39 -1 -3.75%
TAMPA BAY 35 37 79 77 1.026 36 1 2.95%
PHOENIX 37 37 92 105 0.876 32 5 12.38%
ANAHEIM 37 35 77 92 0.837 31 4 11.52%
FLORIDA 39 35 84 105 0.800 31 4 10.86%
BUFFALO 38 34 87 100 0.870 33 1 2.76%
CAROLINA 37 34 67 84 0.798 30 4 13.20%
EDMONTON 37 33 94 105 0.895 33 0 -0.38%
CHICAGO 39 29 73 106 0.689 27 2 7.38%
WASHINGTON 38 26 96 123 0.780 30 -4 -14.07%
PITTSBURGH 37 26 75 132 0.568 21 5 19.14%
COLUMBUS 37 25 74 103 0.718 27 -2 -6.33%
2002-03 GP PTS GF GA GF/GA P PTS DIFF DIFF%
OTTAWA 82 113 263 182 1.445 118 -5 -4.86%
DALLAS 82 111 245 169 1.450 119 -8 -7.10%
DETROIT 82 110 269 203 1.325 109 1 1.22%
NEW JERSEY 82 108 216 166 1.301 107 1 1.20%
PHILADELPHIA 82 107 211 166 1.271 104 3 2.59%
VANCOUVER 82 104 264 208 1.269 104 0 -0.07%
COLORADO 82 105 251 194 1.294 106 -1 -1.04%
ST LOUIS 82 99 253 222 1.140 93 6 5.61%
TORONTO 82 98 236 208 1.135 93 5 5.06%
ANAHEIM 82 95 203 193 1.052 86 9 9.21%
TAMPA BAY 82 93 219 210 1.043 86 7 8.05%
MINNESOTA 82 95 198 178 1.112 91 4 3.99%
WASHINGTON 82 92 224 220 1.018 83 9 9.25%
EDMONTON 82 92 231 230 1.004 82 10 10.48%
BOSTON 82 87 245 237 1.034 85 2 2.57%
NY ISLANDERS 82 83 224 231 0.970 80 3 4.20%
CHICAGO 82 79 207 226 0.916 75 4 4.93%
LOS ANGELES 82 78 203 221 0.919 75 3 3.43%
PHOENIX 82 78 204 230 0.887 73 5 6.76%
MONTREAL 82 77 206 234 0.880 72 5 6.25%
NY RANGERS 82 78 210 231 0.909 75 3 4.43%
CALGARY 82 75 186 228 0.816 67 8 10.81%
SAN JOSE 82 73 214 239 0.895 73 0 -0.58%
ATLANTA 82 74 226 284 0.796 65 9 11.82%
NASHVILLE 82 74 183 206 0.888 73 1 1.56%
BUFFALO 82 72 190 219 0.868 71 1 1.19%
FLORIDA 82 70 176 237 0.743 61 9 13.01%
COLUMBUS 82 69 213 263 0.810 66 3 3.75%
PITTSBURGH 82 65 189 255 0.741 61 4 6.50%
CAROLINA 82 61 171 240 0.713 58 3 4.22%
2001-02 GP PTS GF GA GF/GA P PTS DIFF DIFF%
DETROIT 82 116 251 187 1.342 110 6 5.12%
BOSTON 82 101 236 201 1.174 96 5 4.67%
TORONTO 82 100 249 207 1.203 99 1 1.36%
COLORADO 82 99 212 169 1.254 103 -4 -3.90%
SAN JOSE 82 99 248 199 1.246 102 -3 -3.22%
ST LOUIS 82 98 227 188 1.207 99 -1 -1.03%
PHILADELPHIA 82 97 234 192 1.219 100 -3 -3.03%
NY ISLANDERS 82 96 239 220 1.086 89 7 7.21%
CHICAGO 82 96 216 207 1.043 86 10 10.87%
NEW JERSEY 82 95 205 187 1.096 90 5 5.38%
PHOENIX 82 95 228 210 1.086 89 6 6.29%
LOS ANGELES 82 95 214 190 1.126 92 3 2.78%
VANCOUVER 82 94 254 211 1.204 99 -5 -5.01%
OTTAWA 82 94 243 208 1.168 96 -2 -1.91%
EDMONTON 82 92 205 182 1.126 92 0 -0.39%
CAROLINA 82 91 217 217 1.000 82 9 9.89%
DALLAS 82 90 215 213 1.009 83 7 8.03%
MONTREAL 82 87 207 209 0.990 81 6 6.65%
WASHINGTON 82 85 228 240 0.950 78 7 8.35%
BUFFALO 82 82 213 200 1.065 87 -5 -6.50%
NY RANGERS 82 80 227 258 0.880 72 8 9.82%
CALGARY 82 79 201 220 0.914 75 4 5.17%
MINNESOTA 82 73 195 238 0.819 67 6 7.97%
ANAHEIM 82 69 175 198 0.884 72 -3 -5.04%
NASHVILLE 82 69 196 230 0.852 70 -1 -1.27%
PITTSBURGH 82 69 198 249 0.795 65 4 5.50%
TAMPA BAY 82 69 178 219 0.813 67 2 3.41%
FLORIDA 82 60 180 250 0.720 59 1 1.60%
COLUMBUS 82 57 164 255 0.643 53 4 7.48%
ATLANTA 82 54 187 288 0.649 53 1 1.40%

The GF/GA column is obviously Goals For divided by Goals Against. The is the beginning of the formula. From there, the number is multiplied by Games Played (GP) to arrive at Projected Points (P PTS). The DIFF column shows the difference between actual Points and Projected Points and the DIFF% shows what percentage of actual points this DIFF is.

Though it is not displayed, the average DIFF for all teams listed is 2.38 Points and the average DIFF% is 3.48%. To me, a difference that basically amounts to just over 1 win for an entire season is pretty good.

So what does all this mean? It means that you should be able to predict team success with reasonable certainty before a game is played for the season or when changes occur during the season.

For instance, we all know that Mikka Kiprusoff just went down for Calgary. How will that affect the Flames? Let's try to find out.

We know that CGY's current GF/GA is 83/72, which is equal to 1.153. That roughly translates to 42 points on the season (they actually have 44). Kiprusoff had a GAA of 1.48. Lets assume that Kipper will be out 6 weeks (12/31-02/11) and Jamie McLennan will take over goaltending duties. That gives CGY 21 games to play (most in the NHL along with TAM) and if McLennan maintain his current GAA of 1.94, we can assume that CGY will allow about 41 goals during that time period.

However, let's assume that McLennan has been a bit lucky so far this season and will actually have a more reasonable GAA of 2.25. That results in CGY giving up about 47 goals over that time frame. To date, CGY has scored 2.31 GF/GP. Since there has been no change to the offense, let's assume that remains the same, yielding 49 goals for over the specified time frame.

Using the numbers above, CGY's GF/GA number drops from 1.153 to 1.043. Is this significant? Well, with 21 games played, that would be the difference between 24 points and 22 points, or one win.

If we go further and say that McLennan will revert to his career GAA of 2.61 (55 GA during 21 GP), CGY's GF/GA number drops from 1.152 to 0.891. During those same 21 games, their Projected Points drop from 24 to 19.

So who cares? I really don't know. I simply found this and thought it was interesting. It could help when looking at whether or not people think teams are over or under-performing. For instance, does a positive DIFF mean a team is over-performing? Does a negative mean their under-performing? Can/Will that change easily? For instance, ANA finished the season at +9 last year while DAL finished at -8. Could that have been a sign of things to come?

And what about offseason moves? In the book Moneyball, they talk about DePodesta looking at the contributions of each individual player and then determining how many Runs For and Runs Against the team expects to have for the year. DePodesta figured that the 2002 Oakland A's would score 800-820 runs and allow 650-670 runs. They ended up scoring 800 and allowing 653. Can the same thing be done with hockey and then translated into team Points? Could/Would that help drafting for fantasy teams?

All things that could be discussed, which I guess is why I'm posting this. :)

1bookie
      ID: 364442220
      Fri, Jan 02, 2004, 10:03
KKB.. Moneyball, great book, solid theoretical stuff, although I'm not completely sold on the full application of the theories... While it has been uncanny how close DePodesta's numbers have been to actual results, I'm still a little old school about all things baseball.. It's pitching and Defense that get you to the dance and it's the little fundamental things, throwing to the right base, moving runners up, etc that win in the end... The A's are getting to the dance because of their pitching and defense, but since they do not bunt, steal, etc, they continue to fall short in October....

Now to carrying the statistical analysis to hockey. While, using the GF and GA for an entire team, should be able to give you a fair statistal analysis of season point totals, I'm not sure that you can take the next step and throw the goaltenders GAA into the mix to extrapolate points in a given stretch of time. It will be interesting to see over time, how your theory pans, who knows you could become hockey's version of Bill James...
2ukula
      ID: 1503429
      Fri, Jan 02, 2004, 10:46
KKB - I did some similar analysis on hockey a few years back and have years and years of data stored away somewhere. I'll see if I can dig it up. My goal at the time was to predict individual games and compare my result to see where the vegas line was skewed. I was also interested in putting a value on home ice advantage for the league and for each team. Unfortunately at the time my computer wasn't up to speed with the number crunching and I put the project on the shelf. I guess now would be a good time to dust it off eh?
3KrazyKoalaBears
      Leader
      ID: 517553018
      Fri, Jan 02, 2004, 13:28
ukula, I too looked towards some sort of home-ice advantage, but for the time being, I simply continue to use GF and GA. However, for predicting games, I use home and away GF and GA for the respective teams with the idea that these should show any home-ice advantage for the home team, or the extent to which playing on the road doesn't matter for the away team. I still have quite a ways to go before anything meaningful will come from the game predictions until I start going back and looking at old data. If you have something along these lines, I'd be willing to help in any way possible to help scrape the dust off.

bookie, I tend to believe the book when it comes to the playoffs and think that the playoffs are basically a crapshoot. They take a game that plays 162 games a season and squeeze it down to a 5-game series followed by 2 7-game series'. When you consider that Hockey, with an 82-game season, uses 5, 7, 7, and 7-game series' and Basketball, also with an 82-game season, uses 4 7-game series', it's kind of ludicrous that Baseball plays the same number of games.

In other words, Baseball's season is designed to weed out luck and produce the truly best teams in the league, but their playoffs are the equivalent of their season ending at the ASB. Because of this, baseball's playoffs introduce an unnatural amount of luck compared to the regular season.

But, let's look at the Oakland A's in the playoffs last year game by game:

Game 1: OAK 5 - 4 BOS
OAK actually had 2 SB and, for some unknown reason, Hatteberg was caught stealing. This is the same Scott Hatteberg that has 1 SB and 4 CS for his career. Why he was running in the playoffs is anybody's guess. There are some interesting numbers for the stats that have been determined that a pitcher can directly control (BB, K, HR).

BOS: 10 BB, 10 K, 0 HR
OAK: 7 BB, 11 K, 3 HR

Now the 3 OAK HR's weren't huge because there was a total of 1 man on base for all 3. The biggest thing that stands out to me is the BB/K ratio, especially considering Pedro (4 BB/3 K) was on the mound for BOS.

Interestingly enough, OAK took the game to extra innings by playing their version of "small ball". The inning started with a R.Hernandez flyout, followed by a McMillon BB (Byrnes runned). Then, Singleton was HBP and Ellis K'd. Durazo then singled in McMillon and Chavez grounded out to end the inning. That's the way OAK plays and it worked for them.

What was even further interesting was that OAK won the game on a bunt single by R.Hernandez in the 12th with 2 outs: "R Hernandez reached on bunt single to third, E Chavez scored, S Hatteberg to third, T Long to second."

So who says they don't "manufacture" runs? However, because they did it in extra innings, a factor of luck should be considered. Why did this set of plays work in this inning and not any other? Typically, no team bunts with 2 outs anyhow, so why did it work this time?

Game 2: OAK 5 - 1 BOS
OAK got all the runs they scored in the bottom of the 2nd. The inning went as follows:
-S Hatteberg grounded out to first.
-J Guillen walked.
-J Guillen to second on passed ball by D Mirabelli.
-R Hernandez singled to right, J Guillen scored.
-J Dye hit by pitch, R Hernandez to second.
-E Byrnes doubled to left, R Hernandez and J Dye scored.
-M Ellis walked.
-E Durazo grounded out to first, E Byrnes to third, M Ellis to second.
-E Chavez safe at second on throwing error by second baseman T Walker, E Byrnes and M Ellis scored.
-M Tejada flied out to center.

Not once in that inning did they play small ball, yet they managed 5 runs, in the playoffs no less.

Game 3: OAK 1 - 3 BOS
There are 3 reasons OAK lost this game...
Hits: 6
BB: 2
HR allowed: 1

OAK was only on base a total of 8 times. That's a failure of OAK's system. Their system tries to maximize men on base through OBP. It's not surprising that the 2 "Mr. Swing at Anything's" (Tejada and Chavez) were a combined 0-for-9 with 1 BB. The only hits OAK got were from the bottom 4 players in their lineup. That's not going to work for ANY team except maybe the Yankees.

Now, realistically BOS didn't do much better (7 hits, 4 BB), but the game winner was an 11th inning HR off of Rich Harden. That's something Harden could control and he didn't. Still, OAK lost in extra innings, which again introduces the luck factor.

Game 4: OAK 5 - 4 BOS
Again, Chavez and Tejada are nowhere to be found. A combined 1-for-8, with 0 BB, and 5 men LOB. Again, the majority of hits come from the bottom 4 players in the lineup. Again, the game comes down to a late-inning HR (2-run by Ortiz in the 8th) that is in the control of the pitcher (Rincon). Again, you have to consider the luck of it all. Rincon is no slouch, as I'm sure you read in the book. In 55.1 IP last season, he gave up just 4 HR. That he gave up 2 in 4 IP in the playoffs simply points to the luck of it all.

Game 5: OAK 4 - 3 BOS
Again, where in the heck are Tejada and Chavez. A combined 1-for-4 with 0 BB. At least Tejada managed an RBI. But, realistically, the game came down to BOS's 6th inning. Here it is:
-J Varitek homered to left.
-J Damon walked.
-N Garciaparra fouled out to first.
-T Walker hit by pitch, J Damon to second.
-M Ramirez homered to left, J Damon and T Walker scored.
-D Ortiz struck out swinging.
-K Millar popped out to second.

The one thing you'll notice is that all the players who scored were a result of actions that were directly controlled by the pitcher: BB, HBP, and HR. Again, OAK's pitching failed them. Those were the only HR's that Zito gave up in 2 games, but they were costly. He gave up 19 in 231.2 regular season IP, but then gave up 2 in 13 IP in the playoffs, almost double his regular season rate.

So games 3, 4, and 5 all came down to pitching mistakes. Could those mistakes have been offset by more offense? Sure, but Tejada and Chavez did exactly what they weren't supposed to do: make outs. Combined, for games 3, 4, and 5, Tejada and Chavez were 2-for-25, with 1 BB. That's not OAK baseball and I doubt that's going to work for any team in baseball.

When questioning OAK's abilities, I also look back to their 2002 playoffs when they scored 26 runs in 5 games. Remember Ray Durham saying, "I don't see a lot of playoff games where the score is 8-5. It's always 1-0 and 2-1," when he was trying to talk about how important it is to steal bases? The average score of the MIN/OAK series was 7.6-3.0. That' doesn't look very close to 1-0 or even 2-1 to me and that was the point. People think the playoffs are about small ball, but it's actually a microcosm of the game with more luck than usual added in because of the short series'. Do you think that if the playoffs were twice as long as they current are that Tejada and Chavez would continue to hit a combined .080? I wouldn't think it. The more games played, the more the averages return to the averages.

And while people say OAK can't win in the playoffs, they seemingly forget that they were up 2-0 on the Yankess and then had luck strike against them in the final 3 games.

Game 3 had 1 run: A Posada HR off of Zito. OAK had a combined 6 hits and 1 BB. Again, not OAK's way of playing.

OAK simply got destroyed in Game 4 and lost Game 5 mostly because of 3 errors. Both teams had 3 ER allowed. Without the errors, it could have been a completely different game, series, and playoffs. Again, the games coming down to luck.

-------------------------------

Okay, enough of baseball, this is a hockey forum! ;)

I'm not sure that you can take the next step and throw the goaltenders GAA into the mix to extrapolate points in a given stretch of time.

Honestly, I don't know if you can do this either. I kind of made this one up as I went along and I think I was wrong. It seems that GAA will vary vastly from year to year for goalies.

Looking at GAA and Sv% compared to career averages, I found something interesting. In order to ensure relavent stats, I only used years where goalies started more than 40 games, except for this year, where I allowed stats as long as the goalie has started 30 games.

Martin Broduer has seen jumps as much as 113% (1994) and 80% (2003) off his career GAA. But, what remains the same, or at least consistent enough to bare further looking into, is his Sv%. The biggest deviation from his career Sv% that Brodeur has had is 102% (1996,2003) and 99% (1994,1998,2000,2001).

But let's look at a goalie who maybe isn't viewed as being quite as stable as Brodeur. Sean Burke has seen jumps as much as 140% (1992) and 77% (2000,2001) off his career GAA. Meanwhile, the biggest deviation from his career Sv% is 102% (2000,2001) and 97% (1988,1992).

Let's look at someone like Ron Tugnutt. Because of his career, I'll include all years where Tugnutt started at least 30 games. Again, we find wide variances in GAA, from 151%, 132%, and 132% off his career average in 1989-1991 to a GAA as low as 59% of his career average in 1998. But, again, his Sv% only varies as high as 103% in 1998 and as low as 96% in 1989. The difference between '98 and '89? Tugnutt went from 32.76 SOG/60min in '89 to 24.04 SOG/60min in '98.

Now this may seem obvious, that the more SOG a goalie faces, the more goals he'll give up. But I don't recall ever giving Sv% as much of a look as GAA when considering how good goalies are or which goalies to draft. Through the limited data I've been able to process this morning and into the afternoon, it looks like Sv% could be a much bigger determination of who is a good goalie and who is not than GAA could ever attempt to come close to. Again, this is interesting to me because all we ever hear about and all that is usually ever focused on is GAA. It's like the Oakland A's focusing on OBP instead of AVG.

Now, let's revisit McLennan. It should now not be surprising that his Sv% this year is 102% of his career average while his GAA is 74%. Apparently, he has quite a defense in front of him that is preventing shots and this would also help explain Kipper (103% of his career Sv%, 61% of his career GAA). So, when substituting McLennan for Kipper, really we should just have to compare Sv%. If there is a large difference, we can break down the numbers further. McLennan has a career Sv% of .898 and Kipper has a career Sv% of .909. That's a 99% difference for McLennan, which suggests there should be little to no drop off with McLennan in net compared to Kipper. This means that CGY should come closer to the 24 points in 21 games that would be expected while Kipper was in net, barring any major injuries in defensemen or other major players for CGY.

I'm really not sure what I may have stumbled upon, but it seems to be something that hasn't been looked at much considering how much attention is given to GAA.

4KrazyKoalaBears
      Leader
      ID: 517553018
      Fri, Jan 02, 2004, 14:26
For fun, I'm about to take a lot of what I've posted in the 2 LONG posts above and see what could happen if the assumptions made are correct. The two assumptions I'll work with are:

  1. GF/GA predicts team success. Further, (GF/GA)*GP can predict a team's Points.
  2. A goalie's Sv% does NOT vary greatly from year to year and can remain constant even when changing teams.

With those assumptions in mind, I want to see how CBJ, who just fired their coach, could be different if they had a different goalie. Let's swap Marc Denis (.904 career Sv%) for Roberto Luongo (.918 career Sv%). In the 27 games that Denis has started, CBJ has 19 points. Their GF/GA is 51/71, or 0.718 (exact same as their total GF/GA), with 791 SOG. The 0.718 times 27 games yields 19 points, right on par with what has actually happened.

If we put Luongo and his .918 career Sv% in place of Denis, it yields a GA of 65 and a GF/GA of 51/65, or .785. Multiplying by 27 games, that gives us 21 points, or 1 extra win.

How is this useful? It could tell CBJ that they don't need to worry about their goaltending position. Even inserting one of the best career Sv% goalies in the league won't help but for about 1 win over the course of half a season. They need to either build more offense or build a defense that stifles SOG. Again, it sounds straight forward, but doesn't seem to be put on the minds of those making the decisions.

And then the question becomes, which is easier to build? A high-powered offense or a low-SOG defense? Further, which is cheaper? Can a team get by with minimal offense while allowing fewer SOG than normal? My GF/GA research suggests there's a limit, but if a team like CBJ could manage their same 74 GF, while allowing an average SOG more like NJD's 23.9 SOG/Gm instead of 30.4 SOG/Gm, they might be able to end up on the positive side.

If Denis had started all 37 games (an assumption just for these purposes) and only faced 23.9 SOG/Gm, CBJ would have a translated GA of 83 using Denis' career Sv%. Using this year's Sv%, they would have a GA of 75. Those numbers translate to a GF/GA of .892 and .987, or team Points of 33 and 37.

As the standings are today, 37 points would be just 3 points out of the playoffs behind DAL at 40 with 39 GP. At a rate of .987 GF/GA, CBJ would have 38 points after 39 GP, leaving them just 2 points shy of a playoff spot.

Interesting to think about.

5KrazyKoalaBears
      Leader
      ID: 517553018
      Fri, Jan 02, 2004, 14:35
Okay, I'm starting to think about this too much. :)

I don't recall ever seeing a stat for something like SOG Allowed While on Ice. There's always a focus on +/-, but if we can show that GA are a factor of SOG, does +/- really matter, or is it more of a function of the goalies Sv% combined with allowing SOG?

In other words, wouldn't a stat that shows how many SOG a team faces compared to how many SOG a team takes while a player is on the ice be a better sign of how that player helps/hurts his team?

For instance, let's say that while Player A is on the ice, his team allows an average of 10 SOG and takes an average of 8 SOG. Let's call that a new -2. Let's say that while Player B is on the ice, his team allows an average of 8 SOG and takes 12 SOG. Let's call that a new +4. Given those situations, it's possible that both players could be +, -, or even opposite +/- of their SOG +/- depending on the goalie behind them and the goalie in front of them. However, (again, as long as goalie success is indeed tied to SOG) SOG would be more descriptive of scoring opportunities. The rest would simply be the luck of when the goalie allows the goals he would be expected to allow.

Food for thought.

6ukula
      ID: 19032212
      Fri, Jan 02, 2004, 15:01
KKB - I'm not sure I agree with the GF/GA formula as being the best predictor of a team's points. I've used that formula in the past but have switched to a more accurate (IMO) stat of margin-of-victory.

I've put the last 23 years of data on a spreadsheet comparing the "kkb ratio" versus the "margin of victory" ratio. The correlation is "slightly" better using the "margin of victory" ratio. The greater accuracy is found in the extremes (the really good teams and the really bad teams).

Give me your email address and I'll send it to you.

ukula
7KrazyKoalaBears
      Leader
      ID: 517553018
      Fri, Jan 02, 2004, 15:18
admin@kafenatid.net
8bookie
      ID: 364442220
      Fri, Jan 02, 2004, 15:30
OK.. I'll stay away from Baseball and go right to hockey...

This slight change in your formula to look at Save% and put it in with the team in question is quite interesting... In fact there was an article in the Philly paper in which Clarke eluded to a very similar philosophy on netminding... IIRC, he basically said that you don't win games because of your goaltender (He did make an exception for Broduer), instead you win because the rest of the team plays solid fundamental hockey... Your extrapolation on CBS, validates his ramblings... Although, I must say, I'm not the biggest Clarke fan in the Philly area, but with your example it seems to make some sense... ;->

Very interesting stuff..
9bookie
      ID: 364442220
      Fri, Jan 02, 2004, 15:33
OK, I can't stay away from baseball.. While I agree that any team in the league could beat any other in a 5 or 7 game series due to a variety of factors, I stand by my feeling that when it is such a "crapshoot" the team that plays the most fundamentally sound, both offensively and defensively (and that includes doing the little things, bunting, etc) will more times than not win in a short series....
10KrazyKoalaBears
      Leader
      ID: 517553018
      Fri, Jan 02, 2004, 15:44
bookie, I'm definitely going to look into the Sv% and SOG part. It's piqued my interest enough to give it a lot more thought.

As for baseball, you're right that "plays the most fundamentally sound, both offensively and defensively will more times than not win in a short series", but I disagree that it involves the small stuff as heavily as most people think. To me, playing fundamentally sound is not making errors, getting on base, and not giving up HR's, all of which OAK failed to do in their final 3 games last year and throughout their playoff failures in previous years. In fact, consider that both OAK and BOS had 3 steals. Also, OAK was the only team that had a Sacrifice. Neither team played small ball, yet one still won. Would playing small ball have helped? It didn't seem to hurt BOS, so who's to say it would have?

11KrazyKoalaBears
      Leader
      ID: 517553018
      Fri, Jan 02, 2004, 19:34
ukula, got the file, but haven't had a chance to look at it yet.

--------------------------------

I've managed to look at 291 goalie seasons going back to the 1995 season and have found some interesting stats regarding GAA, SV%, and SA/60min. I started my research with goalies who, in their career, had at least 2 40-start seasons. That gave me 49 goalies (ranging from Biron to Roy to Giguere to Fuhr and so on) and 622 seasons of stats start with.

Once I gathered all of those goalies stats, I narrowed my focus and only looked at the seasons where the goalie actually started 40 or more games. In some cases, Yahoo did not have the number of starts a goalie made in earlier seasons (like the 80's), so I used a threshold of 40 or more games played for those particular seasons. This gave me the 292 seasons that I worked with.

Comparing seasonal GAA to career GAA, there was a minimum percentage difference of 63.9% (Tom Barrasso, '97, PIT) and a maximum percentage difference of 144.9% (Byron Dafoe, '95, LOS). The average percentage difference was 99.1%, which is to be expected since these seasons represent the "major" seasons (over 40 games started) of the goalies' careers and will have more impact on their career averages.

Comparing seasonal SV% to career SV%, there was a minimum percentage difference of 96.2% (Patrick Roy, '85, MON) and a maximum percentage difference of 103.4% (Tom Barrasso, '97, PIT). The average percentage difference was 100.1%, again as was to be expected.

It is no small wonder that Barrasso's '97 season shows up in both areas. It is, statistically, a complete anomoly. Outside of '97, his SV% was never more than 101.1% and never less than 98.0% of his career average (0.892). Yet, in '97, he managed a SV% of .922, or 103.4% of his career average.

As I mentioned at the beginning of this post, I also looked at SA/60min to see how that affected goalie performance. If it is true that SV% varies little and can be used to predict/determine goalie success, then a rise in SA/60 compared to a goalies career SA/60 should translate to a higher GAA, and vice versa.

Out of 291 seasons of data, there were 79 seasons (27.1%) where a goalies' GAA was 90%, or less, than their career GAA. If the assumption above is correct, we would expect a decline in SA/60 for those 79 seasons. Out of those 79 seasons, 70 were accompanied by a decline in SA/60.

Now, let's look at the reverse. Out of the 291 seasons of data, there were 62 seasons (21.3%) where a goalies' GAA was 110%, or more, than their career GAA. Again, if the assumption is correct, we would expect a rise in SA/60 for those 62 seasons. Out of the 62 seasons, 52 were accompanied by a rise in SA/60.

It looks like this might be well on the way to showing that SV% is far more important of a stat than GAA. It further begins to show that a significant rise/decline in GAA is almost always the result of a decline/rise in SA/60.

I haven't worked backwards from SA/60 to see what significant changes result in, but I have a feeling that it's going to be directly tied to GAA.

And back to the team aspect of this, it is becoming more and more clear that teams that can stop SOG will be more successful than those who can't. Again, this may seem like a "duh" concept, but if it is, it's certainly not one that many teams seem to grasp.

BTW, I will make the Excel spreadsheet available after I have worked with it some more.

12KrazyKoalaBears
      Leader
      ID: 517553018
      Fri, Jan 02, 2004, 19:41
Forgot to mention the following. If the statistics hold true, it appears that you can expect a significant decline (90% or lower) or rise (110% or higher) from a goalies' career GAA about 48.4% of the time. Again, this is significant in itself because GAA is held up to be such an important stat in determining goalie greatness. If it can fluctuate that much that often, does it really show that much?

By comparison, you can expect a 98%, or less, decline or 102%, or more, increase in a goalies' SV% about 7.9% of the time, or 23 out of 291 seasons.

13bookie
      ID: 364442220
      Fri, Jan 02, 2004, 22:31
Great analysis KKB... I wish I had your patience to dig through the numbers... I can't believe Bob Clarke may actually be on to something....
14KrazyKoalaBears
      Leader
      ID: 517553018
      Fri, Jan 02, 2004, 23:02
bookie, no matter what people think of Bob Clarke, he's put a winning team on the ice for quite some time. In fact, PHI hasn't had less than 93 Points in a full regular season since '93-'94.

As for the numbers, what I'm really wishing I had was some numbers to work out that SOG +/- I was mentioning earlier. I really think it might be worth looking into. In the meantime, I think ukula and I might be on to something regarding predicting team success. I'm also going to look deeper into goalie success to see if any of these ideas hold true when you go WAY back into the history of the NHL. Further, I want to see if there's a translation from the minors to the NHL so that you could accurately predict goalie success based on minor league (or college or European) success.

So much to do, so few hours in the day. :)

15bookie
      ID: 364442220
      Fri, Jan 02, 2004, 23:23
My frustration with Clarke is the same as everyone else's.. he's always put together a contender, but he can't seem to win the cup... And yes, like baseball there is some part of a crapshoot in the playoffs, but without winning the big one, you'll never the credit you may otherwise deserve....
16KrazyKoalaBears
      Leader
      ID: 517553018
      Sat, Jan 03, 2004, 16:50
More data. Oh yippee! ;)

I've expanded the goalie research as much as Yahoo will allow. The new raw data now includes 58 goalies and 695 seasons. As I mentioned in my last post, Yahoo does not include GS for earlier years. Because of that, I have changed my filter for seasons to research to 41 GP and am now ignoring GS. With this new filter, I now have 325 seasons of goalie info to work with. Not much more than before, but still more.

FINDINGS

Season/Career Comparison Findings
As was mentioned before, GAA varies greatly from a goalies' career average. There were 67 seasons (20.6%) when a goalie's GAA was 110% or more over his career GAA. There were 87 seasons (26.8%) when a goalie's GAA was 90% or less under his career GAA. The low percentage difference was 58.7% (Tugnutt, '98, OTT) and the high percentage difference was 144.9% (Dafoe, '95, LOS).

Again, as was mentioned before, there is far less variance in a goalies' SV% compared to career SV%. There were 14 seasons (4.3%) when a goalies' SV% was 102% or more over his career SV%. There were 11 seasons (3.4%) when a goalies' SV% was 98% or less under his career SV%. The low percentage difference was 96.2% (Roy, '85, MON) and the high percentage difference was 103.4% (Barrasso, '97, PIT).

Again looking at SA/60 for the seasons where a goalies' GAA rose more than 110% or declined more than 90% off their career GAA, I found the numbers from above continued to hold true. In the 67 seasons that a goalies' GAA rose by 110% or more, it was accompanied by a rise in SA/60 over their career average 57 times, or 85.1%. In the 87 seasons that a goalies' GAA declined by 90% or less, it was accompanied by a decline in SA/60 under their career average 74 times, or 85.1%.

Now for the new info. I decided to look at a year-by-year comparison of GAA and SV% along with SA/60. Because I'm still only using 41-GP seasons, it actually means a comparison between a goalies' 41-GP season and their previous 41-GP season. For most goalies, there is not more than a 1-year gap between any 2 41-GP seasons, so this should not be a concern.

Looking at year-by-year GAA, the average change is 99.3%. The high percentage change was 152.5% (Kidd, '97, CAR to '00, FLA). The low percentage change was 55.7% (Tugnutt, '90, COL to '97, CBJ). The high percentage change for 2 back-to-back years for the same team was 149.2% (Dafoe, '98, BOS to '99, BOS). The low percentage change for 2 back-to-back years for the same team was 68.7% (McLean, '90, VAN to '91, VAN). Not surprisingly, 3 of the 4 seasons were accompanied by a significant corresponding rise/decline in SA/60 between the years compared:
Kidd ('97 to '00): 112.1%
Tugnutt ('90 to '97): 67.0%
Dafoe ('98 to '99): 99.2%
McLean ('90 to '91): 92.6%

Dafoe essentially saw little change in his SA/60, yet still managed to lower both his GAA and his SV%. This goes against the other data and shows that it is possible for a goalie to break outside of his career SV%. It's just not very likely.

Looking at year-by-year SV%, the average change is 100.1%. The high percentage change was 103.9% (McLean, '90, VAN to '91, VAN). The low percentage change was 96.0% (Dafoe, '98, BOS to '99, BOS). These both also take care of back-to-back seasons for the same team.

Looking at significant change, there were 62 seasons when a goalies' GAA was 110% or more over their previous season's GAA. Of these 62 seasons, 51 (82.3%) were accompanied by an increase in SA/60 from the previous season. There were 76 seasons when a goalies' GAA was 90% or less under their previous season's GAA. Of thse 76 seasons, 57 (75.0%) were accompanied by a decrease in SA/60 from the previous season. This simply verifies what the previous data showed.

Looking at significant change for SV%, there were 26 seasons where a goalie's SV% was 102% or more over their previous season's SV%. Not surprisingly, 22 of those seasons were accompanied by a decrease in GAA of 90% or less under the previous season. There were 13 seasons where a goalie's SV% was 98% or less under their previous season's SV%. Again, not surprisingly, 12 of those seasons were accompanied by an increase in GAA of 110% or more over the previous season.

So now we're back to, "what does it all mean?" I think I might be getting closer to drawing some conclusions. The initial ones are as follows:

  • A goalie's SV% will tend to remain close to their career SV% and their previous season's SV%.
  • A goalie's GAA will vary widely, both compared to career GAA and a previous season's GAA.
  • Career and previous season's SA/60 and SV% may be the biggest determining factors for what a goalie's GAA will be in a season.

So again, why is this important? Because we've had GAA shoved down our throat since we started following hockey. Every time I watch a game, SV% is usually either never talked about or rarely talked about. According to these stats, it should be the ONLY thing, maybe along with SA/60, that is talked about.

And let's look at the Vezina Trophy. According to NHL.com, "the Vezina Trophy is an annual award given to the goalkeeper adjudged to be the best at this position as voted by the general managers of all NHL clubs."

Last year, the award went to Martin Brodeur. 2nd place was Turco, followed by Belfour. Given that, and what has been outlined above, who would you say is the best goalie of the following:

  • A: 2.26 GAA, .922 SV%, 7 SO, 29.1 SA/60
  • B: 1.72 GAA, .932 SV%, 7 SO, 25.5 SA/60
  • C: 2.02 GAA, .914 SV%, 9 SO, 23.4 SA/60
  • D: 1.83 GAA, .925 SV%, 6 SO, 24.5 SA/60
  • E: 2.30 GAA, .920 SV%, 8 SO, 28.9 SA/60

Personally, I would give it to either goalie B, A, or D. Those guys are Turco, Belfour, and Cechmanek. C is Brodeur and E is Giguere. I just don't see Brodeur as the best goalie on that list. All he really did was play more games and win more games, something that is not completely in his control like the stats above (with the exception of SA/60).

All in all, I think I'm going to start giving SV% and a team's SA/60 a lot more consideration when looking at goalies to pick. From the data above, GAA should follow those other 2 stats and, if what ukula and I have found with regard to team success holds true, Wins should follow from the GAA compared to the team's offensive capabilities.

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