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Top Pair of Forward - Contracts

I was wondering what teams generally pay for their top pairing forwards: the forwards who have the highest number of points per game, so I quickly made a table. The reason I was wondering is to see what sort of contract the Sedin's should qualify for as a pair as opposed to being two individuals. What it looks like is teams generally pay about $5 million per point/gp, so the Sedin pair average about 2 points per game are worth about $10 million per year. Of course you can see by the list, some teams pay more (Ottawa, New York) for their top players on a per point basis, but on average teams pay approximately $5 million. Some comments about the table above
<22 - is one of the top 2 players under 22 (in which case they may still be playing on entry level contract)
<26 - is one of the top 2 players under 26 (would be considered RFA's and have cheaper contracts)
<26$ - 0 if a player is <26 otherwise it is the team's price per point/gp
Sedin? - would the team have cap space and would be interested in paying $10+ million to sign Sedin's. Many teams already have a top pair they are happy with and have no interest in the Sedin's.

Long Term SPC

This article assumes that:

For players that the team has filed an LTI exception, the team is allowed to exceed the cap by up to the amount of the injured player's salary with as many replacement players as needed, provided that when the injured player is activated the team comes into compliance with the cap immediately.

In this article I am only referencing situations where the LTI (long term injury) is in fact a permanent injury where there is no possibility to return. This means that while the salary counts towards the cap it also increases the cap by the injured player’s salary, which is equivalent to the salary not counting towards the cap and the cap being unchanged (for permanent injury situation, which are not discussed in the CBA).

Why do teams sign long term contracts?

There have been a number of extremely long contracts signed in the NHL since the lockout largely due to salary cap rules. The Vancouver Sun had an interested article written about precisely that on June 19, 2009 (image to the left). There isn’t really an explanation why teams would sign these contracts or why these contracts are able to reduce the salary cap hit. The first long term contract was signed by New York Islanders and Charles Wang was criticized at length by fans and sports writers for such an irrationally long contract. Even after DiPietro’s significant injury(s?) other teams are now singing very similar contracts with their players. Why would teams do what many outside of the hockey business community think are irrational?

12-year vs. 1-year

Let’s assume a very simple world where two things are true: player has the options to sign a very long contract or a 1-year contract. And that there is no inflation, or no price changes from year to year. As a result if a player is just as good as they were last year then they will receive the same salary as they did last year.

Let’s work with the Sedin’s contract: As per the article attached the Sedin’s are willing to sign for 5.25 million per season for 12 years, this means that so long as the Sedin’s are willing to play for the Canucks (they do not retire) they will receive 5.25 million per year.

In contrast imagine if the Sedin’s decided to sign 1 year agreements for 12 years instead, how much they would require for the 1-year contract to be equivalent to the 12 year contract?

Now, before you jump to the conclusion that this amount would be the same as a 12-year contract imagine now that after 1 season one of the Sedin’s had a career ending injury. If the player had signed a 12 year contract he would continue to receive his annual salary, if the player had signed a 1 year contract instead his compensation would cease after 1 year and he would have significantly less money than if he had signed a 12 year contract.

Insurance

Of course both the player can choose to insure this lost income (so long as they can find a willing insurance company who wants to risk millions of dollars on a dangerous sport). The willing partner could insure the player lost income if the team chooses not to sign him due to injury. The player of course would have to pay a premium to do so, but could guarantee his income for 12 years as the long term contract did automatically. (Realistically a player would likely pay annual premium for $x million worth of future earning coverage, which would decrease every year – not sure if there’s a market for this though, however the example below will use a fixed payment insurance policy to simplify things).

Below I have attached a table that summarizes these two worlds:P(active) = probability the player is not injured
- Note I used a 5% chance the player has a career ending injury, this might be a little high, but it makes the numbers look better.

Money = Average amount of money paid by the team to that particular player.

CAP = Average cap hit to team as a result of this particular player + replacement player if injured

Diff = Average loss to player as a result of getting a career ending injury

Ins. = Insurance – The average cost associated with finding a replacement player when the player has a career ending injury.

In the 12-year contract the team pays both replacement player salary (if the signed player is injured) and the injured player’s salary. In the 1-year situation the team only pays the non-injured players salary, if the player wants to insure their earning that is their problem. To make both situations equivalent (player guaranteed $63 million after 12 years) the player would be requires to buy an insurance policy for their lost earnings.

In my example, a 12-year contract results in the team having to pay:

$63 million to Signed player

$14.7 million to replacement player due to injuries.

-------

$77.7 million net cost of signing.

However, the $14.7 million would not matter in terms of cap concerns though…

In my example, a 1-year contract results in the team having to pay:

$63 million to signed player

$19.2 million to replacement player due to injuries.

-------

$82.2 million net cost, but entire amount counts towards the cap.

The team who chooses the longer term contract not only pays essentially the same total cost for player salaries, but in the long term contract the injury replacement do no effect the cap, whereas the replacement do effect the cap in the short term contracts. The difference is essentially who is buying the insurance. If the team pays for the insurance it is not charged against the cap, whereas if the player buys the insurance it is charged against the cap. I’m not sure if players actually buy these injury insurance policies or if they just self insure the risk.

So if anyone ever asks you why teams would sign such long term contracts the answer is simple: insurance is part of the cap for short term contracts and is not part of the cap in the long term contracts.

My Opinion

My belief is that these contracts are bad for the NHL in general. I think it create stagnation in teams. These rules make teams boring as there is very little change. It means that the stars will stay in one place for a long time without the possibility of going to a different team. Player’s however benefit significantly from these agreements: they have guaranteed wages and know where they will be living for the few years and can settle down (buy and house, move kids to a new school they might graduate in). That’s not to say players wouldn’t be nervous about these contracts. Specifically they would worry about management changing priorities and the being stuck in the NHL’s worst team for 12 years.

I still think the costs associated with these contracts are a turn off for many General Managers. Unless the General Manager has an unlimited budget it’s hard to a owner asking to sign off on a $63 million dollar contract (that could backfire).

I think there should be enough natural disincentives to these contracts to keep them becoming the norm, but teams who sign them will be rewarded with the extra cap space they need to sign better players.

Some goalie statistics...

I have been compiling data since 2003-2004 and felt now was a good time to join it all together in one large database so I can produce statistics that you see below. The tables below include data from playoffs and regular season from 2003-2004 2005-2006 to 2008-2009 (excluding the 2003-2004 playoffs). The database contains over 300,000 shots in over 6000 games.

Top 10 - Total Shots Against.

N Name SQN SV S G EG D 1 Miikka Kiprusoff 0.907 0.912 9208 808 830 22 2 Roberto Luongo 0.917 0.919 8923 723 835 112 3 Martin Brodeur 0.912 0.918 8223 678 738 60 4 Ryan Miller 0.902 0.913 8201 717 705 -12 5 Henrik Lundqvist 0.916 0.916 8060 680 778 98 6 Tomas Vokoun 0.919 0.921 7513 597 709 112 7 Marc-andre Fleury 0.905 0.909 7505 682 688 6 8 Marty Turco 0.903 0.905 7500 713 707 -6 9 Cam Ward 0.909 0.905 7329 693 728 35 10 Tim Thomas 0.916 0.919 7167 580 665 85

Top 10 - Goals Prevented.

N Name SQN SV S G EG D 1 Tomas Vokoun 0.919 0.921 7513 597 709 112 2 Roberto Luongo 0.917 0.919 8923 723 835 112 3 Henrik Lundqvist 0.916 0.916 8060 680 778 98 4 Tim Thomas 0.916 0.919 7167 580 665 85 5 Cristobal Huet 0.916 0.919 5454 444 507 63 6 Martin Brodeur 0.912 0.918 8223 678 738 60 7 Dominik Hasek 0.918 0.915 3898 332 390 58 8 Jonas Hiller 0.927 0.926 2303 171 225 54 9 J.S. Giguere 0.910 0.913 6738 588 630 42 10 Niklas Backstrom 0.913 0.922 5030 391 431 40

Top 10 - Save Percentage (+3000 shots)

N Name SQN SV S G EG D 1 Niklas Backstrom 0.913 0.922 5030 391 431 40 2 Tomas Vokoun 0.919 0.921 7513 597 709 112 3 Cristobal Huet 0.916 0.919 5454 444 507 63 4 Roberto Luongo 0.917 0.919 8923 723 835 112 5 Tim Thomas 0.916 0.919 7167 580 665 85 6 Martin Brodeur 0.912 0.918 8223 678 738 60 7 Henrik Lundqvist 0.916 0.916 8060 680 778 98 8 Dominik Hasek 0.918 0.915 3898 332 390 58 9 Manny Fernandez 0.913 0.915 3557 304 334 30 10 Ilja Bryzgalov 0.905 0.914 5635 487 495 8

Top 10 - Shot Quality Neutral Save Percentage (+3000 shots)

N Name SQN SV S G EG D 1 Tomas Vokoun 0.919 0.921 7513 597 709 112 2 Dominik Hasek 0.918 0.915 3898 332 390 58 3 Roberto Luongo 0.917 0.919 8923 723 835 112 4 Cristobal Huet 0.916 0.919 5454 444 507 63 5 Henrik Lundqvist 0.916 0.916 8060 680 778 98 6 Tim Thomas 0.916 0.919 7167 580 665 85 7 Niklas Backstrom 0.913 0.922 5030 391 431 40 8 Manny Fernandez 0.913 0.915 3557 304 334 30 9 Martin Brodeur 0.912 0.918 8223 678 738 60 10 J.S. Giguere 0.910 0.913 6738 588 630 42

All the data for all goalies can be found here.
SQN - shot quality neutral save percentage - a save percentage that adjusts for the difficulty of the shots (If a goalie faces a lot of easier shots then their SQN will be lower than their save percentage. Similarly, if a goalie faces more difficult shots (rebounds, powerplay, etc.) they will have a higher SQN than their Save percentage
SV - Save percentage = 1-Goals/Shots
S - Shots against
G - Goals against
EG - Expected goals - The number of goals that should be scored against a goalie given how difficult the shot is to stop.
D = EG - G - Goals Prevent - how many goals a goalie stopped compared to how many you would expect him to stop.

UPDATE: As per a request Even Strength statistics:

N name D SQN SV S G 1 Tomas Vokoun 86 92.3 93.2 5761 394 2 Roberto Luongo 66 91.8 93.0 6507 454 3 Tim Thomas 60 91.8 92.9 5548 393 4 Henrik Lundqvist 54 91.6 92.5 6038 451 5 Dominik Hasek 52 92.6 93.3 2819 188 6 J Giguere 46 91.7 92.8 4854 349 7 Martin Brodeur 39 91.3 92.6 6371 469 8 Kari Lehtonen 36 91.5 92.5 4757 359 9 Cristobal Huet 30 91.5 92.7 4021 294 10 Rick Dipietro 21 91.2 92.0 4252 340 11 Manny Fernandez 18 91.3 92.4 2727 207 12 Miikka Kiprusoff 17 90.9 92.4 6715 508 13 Ilja Bryzgalov 15 91.0 92.4 4357 330 14 Niklas Backstrom 15 91.1 92.7 3948 289 15 Chris Osgood 10 90.9 92.0 3459 278 16 Cam Ward 9 90.8 91.4 5535 475 17 Ray Emery 9 90.9 91.8 3287 268 18 Nikolai Khabibulin 8 90.8 91.4 4502 388 19 Martin Gerber 6 90.8 91.8 3922 323 20 Marc-andre Fleury 5 90.7 92.1 5562 440 21 Carey Price 4 90.8 92.1 2469 195 22 Chris Mason 3 90.7 92.0 3753 299 23 Ty Conklin 0 90.6 92.1 2137 169 24 Mathieu Garon -1 90.6 91.7 3274 271 25 Manny Legace -2 90.5 91.6 2497 209 26 Jason Labarbera -6 90.3 91.5 2037 174 27 Alexander Auld -6 90.3 91.3 2510 218 28 Ed Belfour -7 90.2 91.3 2148 187 29 Evgeni Nabokov -8 90.4 91.8 5058 414 30 Ryan Miller -8 90.4 92.4 6288 481 31 Brent Johnson -8 90.1 91.5 2025 173 32 Martin Biron -9 90.4 91.9 4870 396 33 Pascal Leclaire -9 90.2 91.6 2402 202 34 Dwayne Roloson -11 90.4 91.6 5316 444 35 Marty Turco -12 90.4 91.8 5631 463 36 Mike Smith -12 89.9 92.0 2014 162 37 Vesa Toskala -15 90.2 91.3 4167 361 38 Peter Budaj -18 90.0 91.3 3683 320 39 Curtis Joseph -21 89.7 90.8 2720 251 40 Johan Hedberg -22 89.5 90.8 2225 204 41 Antero Niittymaki -25 89.7 90.8 3264 299 42 Marc Denis -29 89.0 90.2 2071 203 43 Olaf Kolzig -30 89.7 91.2 3788 333 44 John Grahame -31 88.9 90.1 2018 199 45 Jose Theodore -37 89.6 90.8 4144 380 46 Andrew Raycroft -42 89.0 90.4 3047 294

Stanley Cup Final

DET PIT # G EG S% G EG SV% Game 1: 3 2.0 96.7 1 3.0 85.0 Game 2: 3 2.2 96.8 1 3.1 86.4 Game 3: 2 2.4 81.3 4 1.6 91.7 Game 4: 2 3.5 85.2 4 2.7 94.3 Game 5: 5 3.3 100 0 1.2 84.8 Game 6: 1 2.2 93.1 2 2.9 95.5 Series [3-3] 16 15.6 92.4 12 14.5 89.7

Game 1: If Detroit plays like that for the entire series they probably wont be able to win.
Game 2: Much of the same. Excellent chances for Pittsburgh, but too many goal posts.
Game 3: That was closer to what I was expecting this series to be like.
Game 4: ?
Game 5: Detroit certainly is better with Datsyuk.

DET PIT Winner Even Strength GF 3.01 2.99 EGF 2.69 2.35 GA 2.57 2.53 EGA 2.31 2.38 SV% 88.9% 89.4% Power Play GF 9.94 8.34 EGF 9.04 7.27 GA 0.48 1.37 EGA 0.67 0.84 SV% 87.8% 90.4%

Not exactly sure when Detroit's injuries will recover. If they all recover Detroit should win this series, otherwise it's anyone's series.

Western Confernece Final

DET CHI # G EG S% G EG SV% Game 1: 5 3.9 94.4 2 3.6 89.7 Game 2: 3 3.2 93.9 2 3.3 90.6 Game 3: 3 2.4 84.0 4 2.5 87.5 Game 4: 6 3.6 96.0 1 2.5 83.3 Game 5: 2 4.6 96.4 1 2.8 95.7 Series [4-1] 19 17.7 93.2 10 14.7 89.8

Game 1: Chicago hung in there until the end.
Game 2: I was expecting OT to go a little longer. It appears Chicago can beat Detroit, they just haven't accomplished that yet.
Game 3: Chicago isn't making this easy for themselves.

DET CHI Winner Even Strength GF 3.01 2.8 EGF 2.69 2.63 GA 2.57 2.16 EGA 2.31 2.44 SV% 88.9% 91.1% Power Play GF 11.24 9.22 EGF 10.59 6.72 GA 0.73 0.62 EGA 0.61 0.71 SV% 87.8% 90.8%

Detroit will look to score themselves out of problems, but Chicago has much better goaltending and this matchup could turn out to be Ducks Part II. Looks to be another close series.

Eastern Conference Final

PIT CAR # G EG S% G EG SV% Game 1: 3 3.0 90.9 2 2.2 90.0 Game 2: 7 3.6 82.6 4 2.3 83.3 Game 3: 6 4.6 94.1 2 3.4 89.1 Game 4: 4 2.0 97.1 1 3.4 85.0 Series [4-0] 20 13.2 92.0 9 11.3 87.1

Game 1: Well executed by Pittsburgh.
Game 2: For a moment there I thought Carolina would tie it up again.

PIT CAR Winner Even Strength GF 2.99 2.45 EGF 2.35 2.6 GA 2.53 2.37 EGA 2.38 2.55 SV% 89.4% 90.7% Power Play GF 7.41 6.91 EGF 7.89 7.14 GA 1.96 0.96 EGA 0.7 0.99 SV% 90.4% 90%

Can Carolina's defense hold off Pittsburgh's offense. They did it in Boston, why not again.

Eastern Conference Semi - Boston vs. Carolina

BOS CAR # G EG S% G EG SV% Game 1: 4 2.7 94.4 1 1.8 85.2 Game 2: 0 3.2 84.6 3 1.3 100 Game 3: 2 2.7 91.7 3 3.6 92.6 Game 4: 1 1.9 87.1 4 3.1 94.7 Game 5: 4 3.6 100 0 1.7 88.9 Game 6: 4 2.0 94.3 2 3.5 80.0 Game 7: 2 3.6 90.9 3 3.3 94.4 Series [3-4] 17 19.7 91.8 16 18.3 91.4

Game 1: Boston won this game in every area: goaltending, offense, defense. Tough game for Ward.
Game 2: Carolina won, but they were completely outplayed. Good game Ward.
Game 3: Carolina was actually able to outplay Boston for a change. Maybe I was wrong. After being shut down in the first couple games Carolina plays hard at home to win convincingly (albeit in OT)
Game 4: Man I feel like an idiot. From my vantage point it looks as though Boston isn't even trying anymore. They now have a large hill to climb and it's quite unlikely they will pull it off.
Game 5: Carolina still has 2 chances. Much better game by Boston.
Game 6: Watching the game I thought Boston was dominating, however, the numbers above tell a different story. Boston has shown over the last couple games why they got the most points in the east.
Game 7: Carolina proved they're at least as good as Boston, this should be a good conference finals...

BOS CAR Winner Even Strength GF 2.84 2.45 EGF 2.34 2.6 GA 1.95 2.37 EGA 2.4 2.55 SV% 91.9% 90.7% Power Play GF 10.12 6.97 EGF 8.1 8.27 GA 1.2 1.23 EGA 0.56 0.78 SV% 91.7% 90%

Has there ever been a more lopsided series? Boston has better scoring, defense, goaltending & special teams. I'll be curious how many people pick the Hurricanes to win. Just look at the season series (18 GF Boston, 6 GF Carolina)

Updated: [the comments below indicated more discussion might be necessary]

Boston

Offense:
I’ve felt all season that Boston has been outperforming all scoring expectations. Whether you look at the players they have or based on their expected scoring rates, Boston has either been one lucky team or proving day in and day out that expected scoring rates and analysis is worthless. I’d be the first to say that, I would rather Boston be a lucky team than a good team. If they’re a good team it means my research is wrong. That said, even with all the analysis I’ve done, goal differential is still essentially the most important indicator of a good team and Boston has that!

Defense:
This is Boston’s bread and butter. I know they have a great goalie, but really Chara really is the most important player to this team. They had the fewest goals against in the league this year and didn’t do too poorly last year.

Goaltending:
I liked Thomas the first season I saw him. I knew with his size and skill that he would be a successful goalie. However, I never expected he would be this successful. Personally I feel Thomas is a .915 goalie (Luongo is a 0.920 goalie for example). They theoretical limit for an NHL goaltender is about .920 (these are all shot quality neutral metrics) with a minimum around 0.880. 0.915 is excellent, but this season Thomas has outperformed his historical averages and came in around 0.930 (1.5% better than I’d expect), 1.5% might seem like a small amount, but it’s equivalent to about 30 goals against over the course of a season. However, just because he was lucky all season doesn’t mean his luck is going to run out tomorrow.

Carolina

Offense:
Carolina met expectation in terms of scoring. They actually have the worst scoring record of all remaining teams and they’re up against a team that has great goaltending and defense. Adding Eric Cole at the trade deadline was huge for this team, during the period he was on the team average goals for per game jumped from 2.6 to 3.7. That being said, Eric Cole didn’t seem to be an important player in the first round.

Defense:
I wouldn’t exactly call this one of Carolina’s strengths and they were lucky to have another bad offensive team to play against in the first round. Pitkanen is the only real name (although I’ve really come to like Gleason – first round pick). Corvo always was a great offensive defenseman for Ottawa, but not exactly defensively minded. Seidenberg is steady, but no all star. (as you can see I know very little about Carolina).

Goaltending:
I was never a fan of Ward in the playoff run on 2005-2006. What frustrated me was that the team in front of him was playing so well it didn’t matter too much how he played, he just had to be better than Martin Gerber. However, in 2005-2006 he was 22 now he’s 25, which for goalies is when they begin to peak. I still think of Ward as an average starting goalie, he’s not amazing (he has been lately). In the long run his numbers should hover around .900.

Few other notes:
Carolina had the lead for 82 minutes in the entire 7 game series against N.J. Sure wins are all that matters in the end, but winning in the final seconds of a hockey game doesn’t give me confidence in a team’s abilities to win hockey games (it isn’t something that is generally repeatable).

Conclusion:
Boston’s goaltending is certainly better than Carolina’s
Boston has better defense than Carolina (who would you rather have Chara or Pitkanen?)
Offensively I think the teams are reasonably equal.

Overall though, I have a hard time seeing Carolina live through this series.

Western Conference Semi - Detroit vs. Anaheim.

DET ANA # G EG S% G EG SV% Game 1: 3 3.5 88.2 2 1.7 91.4 Game 2: 3 4.5 89.2 4 3.7 93.3 Game 3: 1 4.4 93.5 2 3.1 97.7 Game 4: 6 3.6 87.5 3 2.4 86.1 Game 5: 4 3.3 90.0 1 1.0 90.9 Game 6: 1 3.2 93.1 2 2.9 96.9 Game 7: 4 3.6 90.0 3 3.0 88.9 Series [4-3] 22 26.1 90.4 17 17.8 92.3

Game 1: We all knew Detroit would be a offensive powerhouse in this series. Hiller just needs to play a little better. Unlike San Jose, Detroit knows they have to get the puck up to score on Hiller.
Game 2: That's one long game. Looks like Anaheim's strategy is to stay out of the box. The few penalties they had were considered non-calls by NBC.
Game 3: Hiller!
Game 4: Did you really think Detroit would only win 1 game. Don't worry Anaheim's stifling defense will be back.
Game 5: Now that's the Detroit we've been missing!
Game 6: Classic Ducks hockey...
Game 7: Luck wasn't on the Ducks this season. Great game 7 action.

DET ANA Winner Even Strength GF 3.01 2.49 EGF 2.69 2.59 GA 2.57 2.33 EGA 2.31 2.43 SV% 88.9% 90.4% Power Play GF 11.45 11.46 EGF 10.17 9.94 GA 0.36 0.99 EGA 0.51 0.54 SV% 87.8% 90.2%

Detroit gets another shot at the 2007 Conference Final match up where Anaheim defeated Detroit. However, the tables have turned slightly since then, Anaheim was in 2nd in the Conference and now they're in 8th. But they were able to beat the President's Trophy winners.

Osgood has a amazing first round, but Anaheim should be a handful for the Detroit Red Wings. They're goaltending will frustrate the Wings. Sounds like a fun series.

Eastern Conference Semi - Washington vs. Pittsburgh

WSH PIT # G EG S% G EG SV% Game 1: 3 2.6 91.7 2 2.4 88.5 Game 2: 4 2.7 91.7 3 3.6 85.2 Game 3: 2 2.1 91.2 3 3.4 90.5 Game 4: 3 1.8 84.8 5 3.3 83.3 Game 5: 3 2.3 88.9 4 3.6 87.0 Game 6: 5 1.7 87.9 4 3.3 70.6 Game 7: 2 1.9 80.0 6 3.0 89.5 Series [3-4] 22 15.1 88.1 27 22.6 85.4

Game 1: Close game, but Washington takes the first win.
Game 2: Ovechkin vs. Crosby - TIE, but Washington as a team won.
Game 3: Washington now has 6 playoff OT losses in a row! Pittsburgh pulled this one out of the fire, but they did manage to completely outplay Washington.
Game 4: Pittsburgh really took this one to them. And it's another chance for Washington tomorrow (I hate back-to-back in the playoffs).
Game 5: I always thought Pittsburgh would win this series (easy to say it now...)
Game 6: That was dominant Pittsburgh win, but they still couldn't keep the puck out of their own net.
Game 7: Amazing win by Pittsburgh. Two second round "upsets", two to go...

WSH PIT Winner Even Strength GF 2.77 2.99 EGF 2.63 2.35 GA 2.42 2.53 EGA 2.18 2.38 SV% 88.9% 89.4% Power Play GF 10.17 7.62 EGF 8.05 7.26 GA 1.43 1.39 EGA 1.07 0.82 SV% 88.8% 90.4%

Who doesn't love Ovechkin vs. Crosby! Should be a good series, and probably full of scoring (for those people who play pools). Also it looks like a close series (6-7 games?)