There are lots of ways the NHL rewards failure and punishes excellence, like the player draft, ever shrinking salary caps, and the half-win award for participating in overtime, but even the way in which playoff pairings are decided has a perverse incentive.
There are three rewards to doing well in the NHL regular season:
- 1. Going to the playoffs,
-
2. A favorable first round pairing
in said playoffs,
-
3. Home team advantage for playoff
games more often.
Here I argue that the first-round pairings
are not as favorable as they could be.
I’ve talked about the consequences of this
in general sport in the previous article “Draft Pairing Tournament Format”, but
in this post I talk numbers and the case of the 2019 President’s Trophy
winners, the Tampa Bay Lightning.
Every small advantage matters
In a best-of-7 series, being paired with a
team you can beat more than 50% of the time matters a LOT. Every 1% of chance
of beating an opponent in a single game translates into roughly 2% of chance in
a series.
Figure 1: Every 1% of win chance in a game translates to roughly 2% in a best-of-7. |
If you want to incentivize
people to always play to win, you have to give the best rewards to the highest
ranked teams at the end of the season. So you take the best team, and you
reward them for winning the most by putting them up against the weakest
opponent among the qualifiers. That would give that highest ranked team the
best chance at progressing to the second round if NHL teams were like this in Figure 2
Figure 2: Four teams of different strength, but otherwise identical. |
But hockey isn’t one skill, it’s a
collection of many, so reality is closer to this:
Figure 3: Four teams of different strength, as well as specific weak and strong areas. |
In that top bracket, that Squirtle is
hosed. He played the best the regular season, and what does he get for it? THE
LEAST FAVORABLE MATCHUP. To maximize his chances at the second round, he would
rather play either of the other two opponents, but instead the system meant to
help him has done the opposite. Bulbasaur gets a free pass again.
Being in the top seed, that Squirtle
probably made it into the playoffs with a few wins to spare. Tactically, it
would have been better to lose a few of those on purpose near the end, if that
particular matchup was looking likely.
So how do we fix this? We let the Squirtle pick their
opponent. The remaining two can
fight each other.
Advantages:
-
ALWAYS an incentive to aim for
a higher seed, to either get a better pick, or avoid being picked by your
counter.
-
More entertainment when a team
picks to play an unusually high seed. If a team avoids picking the lowest
ranked available seed, we can ask “what do they know and fear?”.
Both good and bad:
-
Adds more analytical depth.
Disadvantage:
-
“Teams aren’t Pokémon, yo. You’re
just a big fat nerd trying to ruin another sport.”
-
It gives the first team too much
power.
-
Teams that try to avoid being
picked early by being as costly to beat as possible. See Figure 4.
“Teams aren’t Pokemon…”
Look upon your Lightning, they mighty, and
despair. They won over 70% their regular season games, and played against a
50/50 team. They had home team advantage. Don't worry though, lightning will always be dangerous on the golf course.
How likely was this? Would they have done
better against any of the other 6 opponents they could have faced? To find
this, first find each team’s offensive and defensive ability, which we’ll do
with a classic Poisson regression, which yields:
Parameter
|
Value
|
Rank (League)
|
Baseline
|
0.854
|
|
Home Adv.
|
0.102
|
|
TB Offense
|
0.478
|
1st
|
TB Defense
|
-0.118
|
7th
|
CBJ Offense
|
0.252
|
11th
|
CBJ Defense
|
-0.081
|
9th
|
Effects are additions to an exponent, so a
baseline of 0.854 means a baseline team (Anaheim) scores exp(0.854) = 2.349
goals per hour. A team at home scores exp(0.102) = 1.107 times as much as a
visiting team. Tampa Bay scores exp(0.478) = 1.613 times as much as the
baseline team.
All of this translates to…
Goals per hour
|
In Tampa
|
In Columbus
|
TB Goals per hour
|
3.861
|
3.488
|
CBJ Goals per hour
|
2.686
|
2.974
|
Chance of TB Win
|
70.4%
|
59.3%
|
Which translates to a series win chance of
82% before we consider the rock-paper-scissors aspect.
For the rock-paper-scissors (RPS) part, we’re
going to use a simplified version of the analysis in “Modeling Intransitivity
in Matchup and Comparison Data” by Shuo Chen and Thorsten Joachims to give each
team a position on a clock. If a team is clockwise of an opponent, we will
model them as having an advantage, with the greatest advantage happening at 90
degrees and for teams that are both far from the centre. In mathematical terms,
we are taking the magnitude of the cross product of the teams’ locations.
To find these “clock positions”, we’re
going to take a hierarchical approach. Keep these attack and defense values
from before as fixed, and estimate the “clock positions” by finding which set of
31 positions best predicts the winners of each of the regular season’s 1271
games. This is done using the optim() function in a similar fashion to what was
done in the “optim Quick and Dirty“ article here http://www.stats-et-al.com/2015/07/using-optim-to-get-quick-and-dirty.html
We get these positions, shown below in
Figure 5. The farther from the middle a team is, the more specialized it is. For
example, Anaheim, Pittsburgh, and Tampa Bay are all-rounders that have no
particular strength or weakness against particular teams. On the other hand,
Boston has an advantage over Toronto, which has an advantage over St. Louis,
which has an advantage over Columbus, which in turn has an advantage over
Boston.
To get a sense of the effect, notice that
the series win chance against CBJ has dropped from 82% to 78%, and that the RPS
advantage is small and negative. Boston may be a stronger overall team, but TB
seems to be able to get around that, this the RPS advantage against Boston is
larger and positive.
Opponent
|
TB “RPS” advantage
|
TB wins at home
|
TB wins away
|
TB wins series
|
CBJ
|
- 0.291
|
68.2%
|
58.3%
|
78.4%
|
BOS
|
+0.870
|
70.8%
|
56.3%
|
79.7%
|
TOR
|
- 0.327
|
67.5%
|
57.3%
|
77.0%
|
WSH
|
- 0.836
|
65.3%
|
56.8%
|
74.2%
|
CAR
|
+1.211
|
74.5%
|
61.9%
|
86.5%
|
NYI
|
- 0.041
|
66.8%
|
56.3%
|
75.5%
|
PIT
|
+ 0.186
|
71.3%
|
59.2%
|
82.0%
|
There are two teams which the President’s
Trophy winners would have a distinctly larger advantage over than the opponents
they were ‘rewarded’ with. That 8% of a series win they would have been given
for choosing to play against Carolina isn’t nothing; 8% of a second round is
like 1% of a Stanley Cup, thrown down the toilet.
This gives too much power to the first team.
What if the 2nd seed has a late-season
injury or suspension of their star player? Then the 1st seed might
elect to play them before the player returns, to avoid facing them later at full
strength. Such a match up would reward the 1st seed, but that 2nd
seed also did well in the regular season, they don’t deserve this.
To fix this, professor Tim Swartz suggests
a more restricted draft: Seeds 1-4 choose from seeds 5-8, in order of rank.
This has the added advantage that every
team knows before the draft whether they will be picking an opponent or be
picked. It’s also a smaller change for those skeptical of the pairing draft, while
preventing perverse incentives. Teams in seeds 1-4 always want to be a higher
rank to choose first, and teams in seeds 5-8 cannot benefit from losing the
last game or two of the season to try for a favorable higher seed pairing.
Technically, seed 4 isn’t choosing because
they’re left with the one remaining opponent among seeds 5-8, but they still
benefit by not being in the pool of draftees to begin with.
Follow-up: How big is that home team advantage?
Surely THAT reward is worth something.
Not really, not when it’s 4 games out of 7.
Let’s radically simplify this down to a +
or - % of winning. For example, if a team has a 50% chance of winning on
neutral ice and the home team advantage is a +/- 6%, then they will win 56% of
home games and 44% of away games.
Across all teams and all games in the NHL, the
home team wins 56-57% of the time, but in case there are other effects in the
playoffs, let’s consider a variety of levels of advantage from 0 to 10%.
Result:
Home Team Adv. (+/-)
|
Game Win Pr. (of top seed)
|
.45
|
.5
|
.55
|
.60
|
.65
|
.00
|
.392
|
.500
|
.608
|
.710
|
.800
|
|
.02
|
.398
|
.506
|
.614
|
.716
|
.805
|
|
.04
|
.404
|
.513
|
.621
|
.722
|
.810
|
|
.06
|
.409
|
.519
|
.627
|
.728
|
.816
|
|
.08
|
.415
|
.525
|
.634
|
.735
|
.822
|
|
.10
|
.421
|
.532
|
.641
|
.742
|
.829
|
Behold.
No reasonable amount of home team advantage
is going to give the top seed the upper hand if they are also the weaker team
somehow. The real reward for being the top seed in the regular season is the
pairing.
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