Advanced Special Teams Percentage
There’s a stat that I previously analyzed but didn’t name – STP. My definition of STP is Special Teams Percentage – the basic stat that combines both the power play and penalty kill percentage. Teams over a total of 100% do well on special teams, scoring more goals than they give up, while teams under 100% have their special teams hurting them.
But while that stat is simple enough to give a rough overview of how well a team generally performs on special teams, it does not include short-handed goals, which is an important part in any special teams play. Emotionally, it can either be a rallying point or a deflator. Stats-wise, it makes the power play less effective and the penalty kill more effective.
Thus, in what seems like a far too simple formula, I have designed a metric for how effective special teams are in a general sense while including SHG and SHGA. It is not adjusted for odd kinds of special teams situations, like 5-on-3 or 4-on-3, but it still is a bit more accurate than just relying on a combination of PP and PK percentages. The formula is as follows:
![[([(PPG-SHGA)/PP Opp] + [(TS-PPGA+SHG)/TS])/GP]*82](http://img87.imageshack.us/img87/315/astpformula2.png)
A team with an even aSTP would get a 1.000 – meaning that not only does the team score as many goals as they prevent on the power play, but that the shorthanded goals scored and allowed are even. Anything over 1.000 means that the combination of offense and defense for special teams benefits the team, and under a 1.000 means that it’s detrimental.
| Team | PP Opp | PPG | PP% | SHGA | TS | PPGA | PK% | SHG | STP | STP Rank | aSTP | aSTP Rank | Change |
| PHI | 316 | 71 | 22.5 | 1 | 393 | 67 | 83 | 16 | 105.5 | 5 | 1.092 | 1 | 4 |
| MIN | 328 | 66 | 20.1 | 6 | 291 | 36 | 87.6 | 9 | 107.7 | 1 | 1.090 | 2 | -1 |
| SJS | 360 | 87 | 24.2 | 11 | 306 | 51 | 83.3 | 12 | 107.5 | 2 | 1.084 | 3 | -1 |
| BOS | 313 | 74 | 23.6 | 7 | 306 | 54 | 82.4 | 8 | 106 | 3 | 1.064 | 4 | -1 |
| STL | 351 | 72 | 20.5 | 8 | 357 | 58 | 83.8 | 10 | 104.3 | 6 | 1.048 | 5 | 1 |
| DET | 353 | 90 | 25.5 | 4 | 327 | 71 | 78.3 | 6 | 103.8 | 7 | 1.045 | 6 | 1 |
| WSH | 337 | 85 | 25.2 | 11 | 387 | 75 | 80.6 | 7 | 105.8 | 4 | 1.044 | 7 | -3 |
| BUF | 358 | 75 | 21 | 5 | 336 | 61 | 81.8 | 7 | 102.8 | 9 | 1.035 | 8 | 1 |
| ANA | 309 | 73 | 23.6 | 8 | 385 | 78 | 79.7 | 6 | 103.3 | 8 | 1.023 | 9 | -1 |
| OTT | 339 | 66 | 19.5 | 5 | 346 | 64 | 81.5 | 8 | 101 | 13 | 1.018 | 10 | 3 |
| MTL | 374 | 72 | 19.2 | 11 | 370 | 65 | 82.4 | 10 | 101.6 | 12 | 1.014 | 11 | 1 |
| CHI | 363 | 70 | 19.3 | 6 | 330 | 64 | 80.6 | 10 | 99.9 | 17 | 1.013 | 12 | 5 |
| NJD | 307 | 58 | 18.9 | 4 | 324 | 65 | 79.9 | 12 | 98.8 | 20 | 1.012 | 13 | 7 |
| LAK | 360 | 69 | 19.2 | 8 | 362 | 62 | 82.9 | 4 | 102.1 | 10 | 1.009 | 14 | -4 |
| VAN | 357 | 67 | 18.8 | 5 | 371 | 69 | 81.4 | 7 | 100.2 | 15 | 1.007 | 15 | 0 |
| NYR | 346 | 48 | 13.9 | 14 | 329 | 40 | 87.8 | 9 | 101.7 | 11 | 1.004 | 16 | -5 |
| CAR | 374 | 70 | 18.7 | 9 | 301 | 59 | 80.4 | 8 | 99.1 | 19 | 0.994 | 17 | 2 |
| FLA | 308 | 51 | 16.6 | 9 | 311 | 54 | 82.6 | 7 | 99.2 | 18 | 0.985 | 18 | 0 |
| NYI | 320 | 54 | 16.9 | 5 | 361 | 73 | 79.8 | 12 | 96.7 | 22 | 0.984 | 19 | 3 |
| NSH | 318 | 50 | 15.7 | 8 | 338 | 59 | 82.5 | 9 | 98.2 | 21 | 0.984 | 20 | 1 |
| PIT | 360 | 62 | 17.2 | 13 | 347 | 60 | 82.7 | 7 | 99.9 | 16 | 0.983 | 21 | -5 |
| CGY | 358 | 61 | 17 | 15 | 349 | 58 | 83.4 | 6 | 100.4 | 14 | 0.979 | 22 | -8 |
| ATL | 357 | 69 | 19.3 | 10 | 366 | 88 | 76 | 13 | 95.3 | 25 | 0.960 | 23 | 2 |
| COL | 318 | 50 | 15.7 | 8 | 318 | 64 | 79.9 | 4 | 95.6 | 24 | 0.943 | 24 | 0 |
| TBL | 343 | 61 | 17.8 | 9 | 405 | 89 | 78 | 4 | 95.8 | 23 | 0.942 | 25 | -2 |
| DAL | 351 | 54 | 15.4 | 4 | 327 | 70 | 78.6 | 2 | 94 | 28 | 0.934 | 26 | 2 |
| CBJ | 322 | 41 | 12.7 | 12 | 346 | 62 | 82.1 | 8 | 94.8 | 26 | 0.934 | 27 | -1 |
| TOR | 330 | 62 | 18.8 | 7 | 308 | 78 | 74.7 | 6 | 93.5 | 29 | 0.933 | 28 | 1 |
| EDM | 354 | 60 | 17 | 8 | 338 | 76 | 77.5 | 3 | 94.5 | 27 | 0.931 | 29 | -2 |
| PHX | 344 | 50 | 14.5 | 4 | 293 | 68 | 76.8 | 5 | 91.3 | 30 | 0.919 | 30 | 0 |
Teams highlighting in gray made the playoffs last season.
Note that all the numbers are from last season, so the rankings will likely change pretty drastically when this season starts. I included each team’s STP as well, to give a comparison, as well as all the stats that I used to compile aSTP. Things to note:
The inclusion of SHG really helped the New Jersey Devils, who rose from a below-average STP to a slightly above-average aSTP because of a defensively-minded power play (only 4 SHGA) and a good amount of offense on thier penalty kill (12 SHG). The Philadelphia Flyers rose to the top of the league because of the 16 SHG they scored and the single SHGA they allowed.
Conversely, the Calgary Flames were hurt by the nine fewer SHG they scored than they allowed. The New York Rangers, Pittsburgh Penguins, and Los Angeles Kings were also hurt
What’s interesting to me is that the Minnesota Wild are so highly ranked despite not making the playoffs. Same with Buffalo and Ottawa – it suggests that a lot of their success stems from special teams, while they have problems while playing 5-on-5. And then the Columbus Blue Jackets are the fourth-worst team, and yet made the playoffs pretty comfortably. The trend is definitely that playoff teams tend to have above 1.000 aSTPs, but with four playoff teams with sub-1.000s and four non-playoff teams with above 1.000 aSTPs it suggests that special teams aren’t necessarily the make-or-break aspect of a team’s success.
Disclaimer: I literally worked this out during history class, so sorry if the math somehow turns out to be wrong. I checked the formula several times, but there’s always a chance for human error. Stats retrieved from NHL.com.
| Tags: its hockey time, stats | 6 Comments |
Fools and Sages was created as an outlet for photoshopping, web design, and hockey rants. I currently attend school in Southern California, but do not hesitate to yell "BEAT LA!" As a Sharks fan, I will defend Patrick Marleau to the death. I have stats, and I'm not afraid to use them.

6 Responses to “Advanced Special Teams Percentage”
September 22nd, 2009 saat: 8:49 pm
Sweet. I once attempted to make a metric for either hockey or baseball. All the “stats” didn’t make sense or they were useless…
September 22nd, 2009 saat: 9:44 pm
I have another idea for special teams differential. As I don’t have a blog I’m willing to link, email me sometime and we can discuss. You should have my address now.
September 23rd, 2009 saat: 11:09 am
I have no idea how you’re able to come up with stuff to do this, but it’s amazing.
I do wonder how our numbers would have looked during RW’s tenure. The power play was cited as being hideously stagnant. It’d be interesting to see the changes in eras.
September 23rd, 2009 saat: 7:08 pm
@CTGray-
Haha, thanks. I was really bored in history, and you know how it goes – with great boredom comes great inspiration, lol.
And now you’ve given my inspiration for the next post. I might even go back to the Darryl Sutter era if NHL.com has those numbers.
September 25th, 2009 saat: 7:13 pm
Percentages can be misleading if there is an imbalance between PP and PK, i.e., if you’re on the PK much more than the PP, then a good PK might still mean that you’re giving up more special teams goals than you are getting.
Why not compute net goals/game for special teams, as well as net goals/game even-strength, to see if teams are positive or negative for each metric, and then how they rank in each metric against other teams?
September 25th, 2009 saat: 7:18 pm
Also, I would contend that even-strength play is more important, particularly for the playoffs, when refs tend to “swallow their whistles” and not call as many penalties. You can’t ever count on being on the PP, but you are surely going to be even-strength for most of the game…
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