Snapshot of the standings morning of December 1st:
In this month’s instalment, I take a look at another
statistic that contains some luck and further reveals unsustainable paces, both
high and low. Individual Points Percentage (IPP) is defined as the percentage
of goals scored while a player is on the ice that he had a point on. Now, I’m
not going to get too carried away with looking at straight IPP numbers.
Naturally, we would expect some players to factor into a lot more goals when
they’re on the ice than others. Even adjusting for position, we would expect
some forwards to factor into more goals than others; some players are just
better at hockey than others.
Still, when it comes specifically to second assists, there’s
a bunch of stuff that happens after a player has touched the puck that he has
nothing to do with. It is for this reason that I have created the STAB ratio
(Stefan’s Second Assists to Blanks ratio, where “second” is designated by a “T”
for “two”, cause otherwise it looks like a misspelling of a Swedish car).
How is STAB calculated?
Divide points by IPP to get the total number of goals that
the player was on the ice for. Subtract points to get the total number of goals
that the player was on the ice for but did not factor in on, as far as the
scoresheet is concerned (blanks). The ratio is then second assists to blanks,
and we can derive a percentage by dividing second assists by the overall total
(blanks + second assists).
Team
|
STAB
|
STAB effect
|
Patrik
Stefans
|
34.43%
|
12.26
|
G-Phil's
Flyers
|
32.35%
|
6.30
|
Moilers
|
31.93%
|
5.44
|
Joshfrey
Krupuls
|
31.43%
|
5.84
|
Schizzarks
|
31.41%
|
5.28
|
Milan
Micahleks
|
30.41%
|
3.42
|
Vanrooser
Canicks
|
30.00%
|
1.76
|
Los
Amjawors Kings
|
29.72%
|
2.26
|
Winter
Claassics
|
29.41%
|
1.43
|
Quebec
Rordiques
|
28.24%
|
-0.53
|
WBS
Parkers
|
28.08%
|
-0.83
|
Mackhawks
|
27.40%
|
-2.59
|
Dicklas
Lidstroms
|
26.13%
|
-5.01
|
Teeyotes
|
22.73%
|
-7.82
|
Magnus
Faajarvis
|
22.47%
|
-10.99
|
Powder
Rangers
|
22.22%
|
-13.88
|
The table above lists KL teams by their STAB percentages.
Individual STABs were not calculated for each player, but rather, second assist
and blank totals were tallied for entire rosters first, and then the overall percentage
was calculated. The STAB effect represents the points gained or lost in the KL
so far on account of players getting more or fewer second assists than
probability would dictate they should.
The NHL STAB average across all players so far this season
is just under 30%, which makes good sense. When 5 players are on the ice for
one team and they score a goal, one is awarded a second assist, while two get
“blanked”; if every goal scored had two assists, we would expect a STAB of
33.33% across the league, but of course, there are also goals that are
unassisted or have only one other contributor than the scorer himself. Therefore,
we would expect a slightly smaller overall percentage. The numbers for the KL
are consistent with this; our league average is 28.64%.
There will continue to be differences between our teams’
STAB percentages. As the sample size increases, the variability will decrease,
but it will always exist. Chance will remain a factor in this imperfect world,
where all other things are not considered equal. But, what if they were? Below is how
our standings would look. Four teams would be within a single point of the
lead, six within 6 pts, and nine within 17! I maintain that this season we will
see the closest battle ever for the Krusell Cup.
Team
|
Adj TTL
|
PBL
|
|
|
248
|
0
|
|
|
248
|
0
|
|
|
247
|
1
|
|
|
247
|
1
|
Dicklas Lidstroms
|
245
|
3
|
|
|
242
|
6
|
Schizzarks
|
236
|
12
|
|
|
234
|
14
|
|
|
231
|
17
|
|
|
218
|
30
|
|
|
208
|
40
|
|
|
206
|
42
|
|
|
195
|
53
|
|
|
187
|
61
|
|
|
179
|
69
|
|
|
167
|
81
|
Limitations
As always, my models have deficiencies. I can point out two
that could distort the picture here. First, all roster players have been
included, not just scoring roster players. I’ve done this partly out of
laziness, but also because fringe roster players are relevant considerations; a
team’s 10th or 11th forward might have deflated totals
and could or should be on the scoring roster. Second, I haven’t considered all
on-ice situations. I mentioned last month that for whatever reason,
stats.hockeyanalysis.com doesn’t allow visitors of the site to view cumulative
totals, but instead, provides breakdowns separately for every game situation
(5on5, 5on4, etc). I have done my best to include power play situations this
time around, but unfortunately the site also only provides stats for players
who have played over 50 minutes for a given situation. Not surprisingly, many
KL players have seen time on the powerplay, but not in excess of 50 mins at
this point in the season. Their PP numbers are therefore excluded. Not withstanding
how that may affect a team’s overall STAB, I think the two limitations just
mentioned could be seen to offset with respect to the effect size.
In the process of running these numbers, I got to see how
many players on each squad had PP time over 50 mins. I find the totals to be
rather telling:
Team
|
PPlayers
|
Patrik
Stefans
|
17
|
Mackhawks
|
14
|
Winter
Claassics
|
13
|
Magnus
Faajarvis
|
13
|
Moilers
|
12
|
Dicklas
Lidstroms
|
12
|
Joshfrey
Krupuls
|
11
|
Schizzarks
|
11
|
Milan
Micahleks
|
11
|
Powder
Rangers
|
11
|
G-Phil's
Flyers
|
9
|
Los
Amjawors Kings
|
9
|
Quebec
Rordiques
|
7
|
WBS
Parkers
|
6
|
Teeyotes
|
5
|
Vanrooser
Canicks
|
4
|
Power Rankings? I've changed my mind on providing them every month, partly cause I don't think much has changed over the course of November, and I kind of want to stand by my predictions from last month. I've also taken note that readership has fallen off in Malaysia, South Korea, and Namibia, so there's a bit of cost-benefit analysis going on.
I will provide two further fun tidbits in closing, though. The KL's poorest STAB victim is Dion Phaneuf, who should have about 5 more points than he does. Conversely, the player doing the most bludgeoning so far is Jacub Voracek, benefiting with 6 points more than he should have.
PREYDE-KIRSHENBLAT
