Does McDavid lose out for having missed games to injury?
[TBODY] [/TBODY]
Rank Team Points (Skaters) Points (Goalies) Points (Total) 1 Toronto Maple Leafs 93.48 17.57 111.05 2 Pittsburgh Penguins 93.72 16.82 110.54 3 Dallas Stars 91.42 16.31 107.73 4 New Jersey Devils 94.24 11.2 105.44 5 Colorado Avalanche 91.36 13.22 104.58 6 Columbus Blue Jackets 88.48 12.6 101.08 7 San Jose Sharks 85.23 14.79 100.02 8 Minnesota Wild 83.68 15.65 99.33 9 Vegas Golden Knights 82.17 17 99.17 10 Chicago Blackhawks 82.98 14.99 97.97 11 Anaheim Ducks 82.46 14.38 96.84 12 Washington Capitals 79.44 17.29 96.73 13 New York Rangers 80.75 15.25 96 14 Carolina Hurricanes 74.47 21.29 95.76 15 Philadelphia Flyers 81.09 14.38 95.47 16 Montreal Canadiens 79.9 15.22 95.12 17 Seattle Kraken 79.67 15.44 95.11 18 Arizona Coyotes 81.55 12.75 94.3 19 Calgary Flames 80.93 13.36 94.29 20 Detroit Red Wings 78.77 15.11 93.88 21 Ottawa Senators 79.69 13.42 93.11 22 Nashville Predators 81.44 11.55 92.99 23 Los Angeles Kings 75.47 17.22 92.69 24 Boston Bruins 77.02 15.63 92.65 25 Florida Panthers 77.58 14.91 92.49 26 St. Louis Blues 76.08 15.68 91.76 27 Winnipeg Jets 77.81 13.53 91.34 28 Edmonton Oilers 77.98 12.1 90.08 29 Tampa Bay Lightning 78.46 11.09 89.55 30 Vancouver Canucks 78.54 10.94 89.48 31 New York Islanders 71.71 12.39 84.1 32 Buffalo Sabres 62.14 13.93 76.07
lelCan't be right. Devils would be top 3 on both Panda and Latvian scores with a backup like Dell
imo Devils are bottom 5 lottery team... I was aiming for a top 5 pick for Lafreniere/Byfield/Stutzle because I assumed this was a keepers league
Not a fan of the charts honestly.
Not nearly enough importance on Defensive players.
I like this much more!1 BOS
2 TBL
3 PIT
4 COL
5 VEG
6 EDM
7 STL
8 PHI
9 CAR
10 WPG
11 TOR
12 VAN
13 NYR
14 FLA
15 ARI
16 DAL
17 NYI
18 NSH
19 MTL
20 CBJ
21 WSH
22 CHI
23 CGY
24 MIN
25 BUF
26 SJS
27 NJD
28 ANA
29 DET
30 OTT
31 LAK
^^
Real
1 BOS
2 TBL
3 PIT
4 COL
5 VEG
6 EDM
7 STL
8 PHI
9 CAR
10 WPG
11 TOR
12 VAN
13 NYR
14 FLA
15 ARI
16 DAL
17 NYI
18 NSH
19 MTL
20 CBJ
21 WSH
22 CHI
23 CGY
24 MIN
25 BUF
26 SJS
27 NJD
28 ANA
29 DET
30 OTT
31 LAK
^^
Real
and you're aware that this is actual NHL teams where Pettersson is a Canuck, Crosby a Penguin, and so on?I like this much more!
Don't get me wrong panda, I think your fancy stats things is amazing, I just feel it's not a great indicator on how well teams draft.
You are still great
1) this is strength of squads after trade deadlineAwful
Everyone knows LAK > OTT, DET
Look at the real life standings and let me know what you think about them.
I didn't apply positional scarcity to things like DFF and xGoals for defencemen, but could do so.top 5 ok, 6-31 is interesting. Clearly defense personnel is not as heavily weighted as some others
Thats the jokeand you're aware that this is actual NHL teams where Pettersson is a Canuck, Crosby a Penguin, and so on?
okayThats the joke
okay
but to clarify
you are okay with the real life rankings but hate the fantasy rankings even though they use the exact same ranking algorithm?
the suggestion is that if you find the real life rankings largely agreeable, then you should find the fantasy hockey rankings largely agreeable as they operate off the same algorithmThe issue is Pettersson isn't on Vancouver he's on Vegas now
1) this is strength of squads after trade deadline
2) it does not account for injuries as all stats are prorated
3) algorithm is strength of squad's top 12 forwards and top 6 defencemen so depth is not a thing
NHL Injury Viz: 2019/20 team injury breakdowns (at suspension)
Detroit actually had really bad injury problems this year but no one talks about it
Major update. Complete rosters.
I did a series of correlation studies to see how the different PandaRankings categories correlated to win percentage and goal differential. I did this using the real standings with real teams with real rosters, i.e. what you actually see when you look up the league standings.
PandaScores, which grade players, have a ~0.78 r-value for win percentage and ~0.8 r-value for goal differential.
PandaRankings, after a series of tweaks for just how to weight the different rankings, achieved a 0.854 r-value for win percentage and 0.887 r-value for goal differential. Given that these values were derived using my battery of statistics, this is phenomenal. That's right: PandaRankings have a 0.854 r-value for real-life win percentage.
My correlation started off at 0.74, and through a series of different techniques for weighting, I was able to get it this high. What's interesting, though, is how far some teams fell. As always, it's not perfect...but it's pretty f***ing good. Los Angeles is a major victim of the changes, but that's life.
Your charts are probably about as close as you can get to judging teams based solely off numbers. But it's still a secondary tool to me.the suggestion is that if you find the real life rankings largely agreeable, then you should find the fantasy hockey rankings largely agreeable as they operate off the same algorithm
yes, I know, teammates chemistry usage all the classics etc etc etc