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Monday, December 16, 2013

It's All About the Matchup - Full Fantasy Hockey Team Matchup Rankings for ESPN Roto Leagues 2013

Welcome to Puck Numbers!

As a life-long hockey fan, I've decided to try my hand at fantasy hockey this year and have been loving every minute of it. Having played fantasy football, I was surprised to see a lack of quality match-up statistical analyses, as in any sport the quality of a player's opponent is often as important as the quality of the player himself. Curious, I took the plunge into the statistical void and have returned with some great data! I'll be updating this data daily with short and long-term breakdowns to identify which teams are winning and which are losing.

The inaugural post here is a full-breakdown of each NHL team and how generous or stingy they've been in each statistical category. To start, I've broken down the numbers for the ESPN Standard Roto stat categories, which consists of Goals, Assists, Plus/Minus, Penalties in Minutes, Power Play Points, Average Time On Ice, and Shots on Goal. I've also completed a breakdown of the goalie statistics: Wins, Save Percentage and Goals Against Average.

To keep things as straightforward as possible, I've done a simple recording of the total stats so far without getting into advanced statistics, which have been proven to be more predictive. More on that analysis in future posts.

Now, on to the data! Before you look, I'll explain how each column was tabulated.

Most of these stats were mined directly from NHL.com. However, some were less straightforward. You'll notice the Average Time on Ice is split into two categories: PP and PK. The PP column is a measurement of the amount of time the opposing team spent on the power-play compared to the average team. For the Penalty Kill, I investigated how much time opposing teams spent a man or more down compared to the average. 

One of the more difficult stats to tabulate was opposing goaltender GAA, which I calculated by subtracting each team's Total Empty Net Goals by their Total Goals For, then dividing by total games played to better approximate the data. Ok, for real this time, on to the data!


NORMALIZED TEAM MATCHUP DATA

TEAMGA+/-PIMPPSOGATOI-PPATOI-PKWSV%GAA
ANA-0.21-0.21-0.770.470.02-1.145:235:33-0.1565-0.00940.4859
BOS-0.58-0.58-0.67-1.32-0.15-1.045:204:24-0.166-0.00450.0331
BUF0.270.271.120.220.034.265:325:170.28850.0291-1.0578
CGY0.510.510.52-1.530.01-0.345:115:400.1067-0.00530.0028
CAR0.040.040.21-2.1500.865:245:180.08890.0088-0.3662
CHI0.080.08-0.89-1.41-0.06-2.645:265:20-0.166-0.02090.9851
COL-0.32-0.32-0.65-1.540.171.364:325:13-0.1768-0.00650.0702
CBS0.120.120.24-0.080.010.365:214:490.0764-0.004-0.1184
DAL0.260.26-0.161.070.072.364:586:060.016800.167
DET-0.13-0.130.03-2.9-0.04-0.846:125:360.07210.0034-0.0855
EDM0.760.760.830.470.020.965:286:080.1864-0.0035-0.057
FLA0.450.450.471.150.19-0.844:515:540.14770.0139-0.3956
LAK-0.7-0.7-0.650.85-0.05-2.546:396:03-0.14640.0024-0.0427
MIN-0.44-0.44-0.09-1.30.11-3.745:325:14-0.04220.0078-0.457
MON-0.58-0.58-0.090.45-0.180.165:405:39-0.07080.0035-0.1712
NSH0.060.060.48-1.35-0.120.165:355:010.01580.006-0.3002
NJD-0.29-0.290.15-4.24-0.2-5.445:345:050.1183-0.0021-0.3074
NYI0.770.770.71-0.820.280.364:535:310.23590.0105-0.2191
NYR0.040.040.620.23-0.17-1.044:505:240.03010.0165-0.3956
OTT0.480.480.120.880.284.166:316:050.11830.00450.1338
PHI0.030.030.334.590.090.467:026:220.07640.0103-0.4215
PHX0.420.42-0.13-0.950.173.465:365:15-0.0619-0.00970.4261
PIT-0.46-0.46-0.29-0.15-0.25-3.044:535:16-0.1758-0.010.3691
SJS-0.31-0.31-0.550.5-0.12-2.444:226:42-0.10540.00090.4876
STL-0.32-0.32-0.844.91-0.03-4.445:575:35-0.209-0.02770.7799
TBL-0.25-0.25-0.210.1-0.06-0.746:025:55-0.0751-0.0045-0.0578
TOR0.210.2102.880.286.466:235:220.0006-0.0130.1044
VAN-0.35-0.35-0.290.39-0.29-1.645:174:58-0.07080.00260.1716
WSH0.210.210.243.470.015.165:395:42-0.0448-0.0090.3967
WPG0.180.180.15-2.2701.366:055:380.08890.0097-0.1603


RANKING BREAKDOWN PER STATISTICAL CATEGORY - SKATERS

TEAMScoring+/-PIMPP ScoringSOGATOI-PPATOI-PK
ANA19281112221915
BOS28272225202130
BUF71151031521
CAR15112716101820
CBS12101715132029
CGY352514162310
CHI13302422261719
COL232526672925
DAL820696244
DET1815291919513
EDM2210119163
FLA575418278
LAK30268202526
MIN2617217281424
MON2918122715911
NJD21133028301326
NSH1462324141227
NYI13193122616
NYR1641426212817
OTT41472435
PHI178281112
PHX61920551123
PIT27231829272522
SJS222492324301
STL242911829814
TBL202116211777
TOR916411418
VAN25221330232228
WPG111228178612
WSH1093132109

RANKING BREAKDOWN PER STATISTICAL CATEGORY - GOALIES

WSV%GAATEAM
252527ANA
262118BOS
111BUF
976CAR
111912CBS
72217CGY
272930CHI
292319COL
141622DAL
121213DET
31815EDM
434FLA
241416LAK
1782MIN
211110MON
5177NJD
1598NSH
249NYI
1325NYR
61021OTT
1053PHI
192626PHX
282724PIT
231528SJS
303029STL
222014TBL
162820TOR
201323VAN
8611WPG
182425WSH

The numbers here show how much below or above average teams have performed against each of these teams. For all stats except GAA, the larger, positive numbers are better. Edmonton and the New York Islanders are each allowing nearly a goal more than the average team and nearly a goal and a half more than the LA Kings, the stingiest team so far for scoring.

No big surprises here, save for Toronto and Washington ranking quite highly as favorable match-ups for skaters.

Take these numbers as a rough guide, as there is much more work to be done. For example, I plan to investigate whether teams allow assists at a near-equal rate, which I'll address in a future post. Addtionally, overtime minutes for goalies should be accounted for when calculating Goals Against Average is calculated by Goals Allowed per 60 on-ice minutes. Despite these shortcomings, this guide should suffice.

For my next post, I'll take a closer look at which teams have been the most generous match-ups across the board. I'll keep ya posted. Until next time, best of luck!

For those interested in the raw numbers, shoot me an e-mail at Jaywillyfantasy@gmail.com

Also, for those who are looking for a break from setting the same players in their line-ups everyday, check out DraftKings.com and enter one of their daily NHL Fantasy Drafts. I've found it especially satisfying whenever I try to pick up a player only to find another team scooped them up. Playing here helps me keep my blog going and the great data flowing for you. See you there!

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