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Full Scoreboard »» |
Detroit Red Wings 10-8-2, 22pts · 9th in Conference Est |
Player | # | POS | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | C/LW | 100.00 | 75 | 43 | 89 | 81 | 65 | 76 | 85 | 83 | 44 | 83 | 70 | 67 | 75 | 45 | 46 | 75 | 50 | 0 | 23 | 842,500$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 75 | 43 | 96 | 90 | 70 | 69 | 64 | 63 | 25 | 77 | 59 | 63 | 77 | 72 | 73 | 68 | 50 | 0 | 27 | 3,000,000$/2yrs | |||
![]() | 0 | C/LW | 100.00 | 77 | 54 | 83 | 83 | 70 | 74 | 96 | 67 | 95 | 77 | 71 | 81 | 63 | 74 | 77 | 76 | 50 | 0 | 31 | 2,375,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 69 | 53 | 84 | 84 | 73 | 76 | 99 | 76 | 44 | 81 | 84 | 80 | 61 | 80 | 87 | 82 | 50 | 0 | 33 | 4,450,000$/1yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 73 | 43 | 83 | 86 | 74 | 81 | 85 | 84 | 48 | 88 | 88 | 76 | 75 | 68 | 69 | 85 | 50 | 0 | 27 | 5,800,000$/3yrs | |||
![]() | 0 | RW | 100.00 | 94 | 99 | 39 | 84 | 86 | 76 | 73 | 70 | 36 | 72 | 87 | 73 | 25 | 74 | 78 | 80 | 50 | 0 | 28 | 5,166,667$/2yrs | |||
![]() | 0 | C/RW | 100.00 | 75 | 44 | 88 | 79 | 80 | 67 | 95 | 71 | 96 | 65 | 70 | 78 | 61 | 93 | 99 | 72 | 50 | 0 | 37 | 3,125,000$/2yrs | |||
![]() | 0 | C/RW | 100.00 | 87 | 58 | 80 | 86 | 65 | 81 | 99 | 84 | 97 | 83 | 78 | 73 | 60 | 73 | 75 | 81 | 50 | 0 | 29 | 5,625,000$/7yrs | |||
![]() | 0 | LW | 100.00 | 82 | 45 | 97 | 75 | 73 | 66 | 87 | 57 | 31 | 63 | 70 | 84 | 25 | 65 | 65 | 73 | 50 | 0 | 27 | 1,600,000$/2yrs | |||
![]() | 0 | C | 100.00 | 69 | 54 | 85 | 83 | 84 | 79 | 95 | 89 | 76 | 86 | 96 | 67 | 75 | 65 | 65 | 86 | 50 | 0 | 24 | 1,400,000$/1yrs | |||
![]() | 0 | C/LW | 100.00 | 75 | 64 | 79 | 76 | 77 | 63 | 88 | 58 | 91 | 63 | 60 | 86 | 25 | 66 | 69 | 68 | 50 | 0 | 30 | 1,750,000$/1yrs | |||
![]() | 0 | C/RW | 100.00 | 88 | 90 | 79 | 74 | 80 | 62 | 75 | 66 | 36 | 66 | 66 | 77 | 25 | 60 | 60 | 70 | 50 | 0 | 24 | 825,000$/1yrs | |||
![]() | 0 | D | 100.00 | 78 | 67 | 72 | 86 | 68 | 83 | 85 | 59 | 25 | 50 | 48 | 83 | 25 | 74 | 77 | 64 | 50 | 0 | 28 | 6,000,000$/1yrs | |||
![]() | 0 | D | 100.00 | 75 | 44 | 80 | 84 | 77 | 88 | 93 | 81 | 25 | 73 | 54 | 87 | 25 | 76 | 77 | 72 | 50 | 0 | 28 | 6,500,000$/8yrs | |||
![]() | 0 | D | 100.00 | 86 | 59 | 79 | 83 | 74 | 78 | 93 | 63 | 25 | 63 | 48 | 86 | 25 | 71 | 71 | 67 | 50 | 0 | 28 | 4,000,000$/3yrs | |||
![]() | 0 | D | 100.00 | 80 | 45 | 87 | 71 | 83 | 72 | 86 | 56 | 25 | 46 | 47 | 94 | 25 | 70 | 72 | 63 | 50 | 0 | 30 | 2,500,000$/2yrs | |||
![]() | 0 | D | 100.00 | 82 | 45 | 94 | 80 | 79 | 82 | 86 | 67 | 25 | 60 | 48 | 85 | 25 | 67 | 70 | 66 | 50 | 0 | 27 | 6,150,000$/8yrs | |||
![]() | 0 | D | 100.00 | 83 | 59 | 78 | 89 | 83 | 88 | 94 | 66 | 25 | 68 | 58 | 93 | 63 | 73 | 75 | 74 | 50 | 0 | 27 | 9,250,000$/8yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | C/RW | 100.00 | 79 | 84 | 67 | 78 | 84 | 70 | 72 | 65 | 80 | 58 | 65 | 72 | 62 | 64 | 64 | 68 | 50 | 0 | 27 | 750,000$/1yrs | |||
![]() | 0 | RW | 100.00 | 84 | 44 | 87 | 64 | 66 | 55 | 75 | 62 | 25 | 57 | 55 | 67 | 25 | 45 | 45 | 62 | 50 | 0 | 25 | 750,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 79 | 73 | 92 | 67 | 73 | 59 | 59 | 59 | 50 | 52 | 62 | 66 | 59 | 46 | 46 | 64 | 50 | 0 | 25 | 750,000$/1yrs | |||
![]() | 0 | D | 100.00 | 89 | 99 | 68 | 61 | 83 | 58 | 68 | 56 | 25 | 50 | 48 | 66 | 25 | 48 | 48 | 58 | 50 | 0 | 25 | 762,500$/2yrs | |||
TEAM AVERAGE | 100.00 | 80 | 60 | 81 | 79 | 76 | 73 | 84 | 68 | 48 | 67 | 65 | 77 | 46 | 67 | 69 | 72 | 50 | 0 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 100.00 | 75 | 82 | 79 | 76 | 75 | 75 | 83 | 75 | 79 | 75 | 75 | 63 | 64 | 77 | 50 | 0 | 27 | 3,500,000$/1yrs |
![]() | 0 | 100.00 | 69 | 67 | 65 | 83 | 74 | 65 | 86 | 71 | 71 | 69 | 85 | 52 | 52 | 71 | 50 | 0 | 30 | 1,100,000$/1yrs |
Scratches | ||||||||||||||||||||
![]() | 0 | 100.00 | 64 | 55 | 54 | 75 | 75 | 52 | 72 | 64 | 65 | 63 | 75 | 46 | 47 | 64 | 50 | 0 | 25 | 750,000$/1yrs |
TEAM AVERAGE | 100.00 | 69 | 68 | 66 | 78 | 75 | 64 | 80 | 70 | 72 | 69 | 78 | 54 | 54 | 71 | 50 | 0 |
Player | # | POS | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | LW | 100.00 | 78 | 73 | 88 | 70 | 73 | 69 | 73 | 55 | 50 | 49 | 57 | 64 | 54 | 45 | 46 | 61 | 57 | 0 | 22 | 925,000$/1yrs | |||
![]() | 0 | C | 100.00 | 76 | 74 | 80 | 71 | 74 | 58 | 59 | 57 | 71 | 53 | 57 | 63 | 54 | 44 | 44 | 60 | 57 | 0 | 23 | 883,750$/1yrs | |||
![]() | 0 | C | 100.00 | 78 | 73 | 89 | 66 | 73 | 73 | 77 | 60 | 75 | 58 | 58 | 65 | 55 | 44 | 44 | 64 | 57 | 0 | 24 | 750,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 84 | 99 | 47 | 71 | 81 | 47 | 69 | 59 | 25 | 58 | 56 | 62 | 25 | 58 | 58 | 60 | 57 | 0 | 24 | 750,000$/1yrs | |||
![]() | 0 | LW | 100.00 | 79 | 45 | 91 | 70 | 77 | 56 | 78 | 62 | 42 | 61 | 60 | 75 | 25 | 48 | 49 | 66 | 57 | 0 | 24 | 750,000$/1yrs | |||
![]() | 0 | C | 100.00 | 67 | 57 | 90 | 68 | 57 | 66 | 67 | 63 | 79 | 64 | 59 | 60 | 56 | 44 | 44 | 63 | 57 | 0 | 22 | 766,667$/1yrs | |||
![]() | 0 | D | 100.00 | 79 | 77 | 83 | 73 | 77 | 73 | 78 | 56 | 25 | 46 | 52 | 65 | 49 | 45 | 45 | 61 | 57 | 0 | 23 | 883,750$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | C | 100.00 | 67 | 61 | 81 | 75 | 61 | 82 | 87 | 63 | 79 | 59 | 64 | 60 | 61 | 44 | 44 | 65 | 22 | 0 | 28 | 762,500$/2yrs | |||
![]() | 0 | C | 100.00 | 60 | 70 | 36 | 67 | 70 | 58 | 58 | 59 | 74 | 55 | 58 | 56 | 55 | 46 | 46 | 57 | 22 | 0 | 29 | 750,000$/1yrs |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 100.00 | 51 | 57 | 71 | 66 | 50 | 53 | 50 | 56 | 51 | 51 | 30 | 45 | 45 | 52 | 57 | 0 | 23 | 750,000$/1yrs | ||||||
Scratches |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
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General Manager | Jean Allaire |
---|
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | Player Name | Team Name | # | POS | GP | G | A | P | +/- | PIM | PIM5 | HIT | SHT | OSB | OSM | SHT% | SB | MP | AMG | PPG | PPA | PPP | PPM | PKG | PKA | PKP | PKM | GW | GT | FO% | FOT | GA | TA | EG | HT | P/20 | PSG | PSS |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Tage Thompson | 0 | C | 20 | 14 | 23 | 37 | 8 | 13 | 5 | 24 | 92 | 18 | 55 | 15.22% | 7 | 19.46 | 5 | 7 | 12 | 49 | 0 | 0 | 0 | 0 | 2 | 1 | 44.91% | 530 | 17 | 5 | 0 | 0 | 1.90 | 0 | 2 | ||
2 | Alex Killorn | 0 | LW/RW | 20 | 9 | 14 | 23 | 8 | 6 | 0 | 23 | 68 | 23 | 43 | 13.24% | 4 | 19.80 | 1 | 6 | 7 | 50 | 0 | 0 | 0 | 0 | 1 | 0 | 53.13% | 32 | 12 | 4 | 1 | 1 | 1.16 | 0 | 1 | ||
3 | Pavel Buchnevich | 0 | C/LW/RW | 21 | 10 | 11 | 21 | 15 | 8 | 0 | 34 | 54 | 25 | 39 | 18.52% | 15 | 18.43 | 3 | 3 | 6 | 50 | 0 | 0 | 0 | 11 | 5 | 1 | 50.00% | 20 | 21 | 6 | 0 | 0 | 1.09 | 0 | 1 | ||
4 | Vincent Trocheck | 0 | C/RW | 20 | 8 | 10 | 18 | 3 | 10 | 0 | 33 | 70 | 16 | 44 | 11.43% | 14 | 16.51 | 2 | 2 | 4 | 37 | 0 | 0 | 0 | 0 | 0 | 0 | 57.88% | 273 | 18 | 2 | 0 | 0 | 1.09 | 0 | 1 | ||
5 | Erik Haula | 0 | C/LW | 20 | 9 | 8 | 17 | 5 | 15 | 5 | 33 | 28 | 9 | 29 | 32.14% | 14 | 20.39 | 2 | 1 | 3 | 36 | 2 | 0 | 2 | 42 | 1 | 0 | 54.44% | 90 | 6 | 9 | 0 | 0 | 0.83 | 1 | 1 | ||
6 | Hampus Lindholm | 0 | D | 20 | 5 | 10 | 15 | 8 | 12 | 0 | 25 | 38 | 16 | 16 | 13.16% | 28 | 25.28 | 1 | 1 | 2 | 57 | 0 | 0 | 0 | 11 | 1 | 1 | 0.00% | 0 | 5 | 17 | 0 | 0 | 0.59 | 0 | 0 | ||
7 | Darnell Nurse | 0 | D | 21 | 0 | 8 | 8 | 13 | 12 | 0 | 43 | 35 | 4 | 9 | 0.00% | 25 | 22.98 | 0 | 1 | 1 | 44 | 0 | 1 | 1 | 21 | 0 | 0 | 0.00% | 0 | 4 | 19 | 0 | 0 | 0.33 | 0 | 0 | ||
8 | Tom Wilson | 0 | RW | 20 | 4 | 3 | 7 | -4 | 31 | 15 | 32 | 46 | 14 | 30 | 8.70% | 14 | 13.87 | 0 | 2 | 2 | 37 | 0 | 0 | 0 | 0 | 1 | 0 | 20.00% | 10 | 12 | 6 | 0 | 0 | 0.50 | 0 | 0 | ||
9 | Eric Robinson | 0 | LW | 20 | 3 | 4 | 7 | -3 | 0 | 0 | 14 | 24 | 2 | 7 | 12.50% | 4 | 11.97 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 27 | 0 | 1 | 26.67% | 15 | 1 | 5 | 0 | 0 | 0.59 | 0 | 0 | ||
10 | Jeff Carter | 0 | C/RW | 20 | 1 | 5 | 6 | -2 | 0 | 0 | 12 | 31 | 18 | 32 | 3.23% | 4 | 13.46 | 0 | 0 | 0 | 7 | 0 | 1 | 1 | 20 | 1 | 0 | 52.63% | 114 | 10 | 2 | 0 | 0 | 0.45 | 0 | 0 | ||
11 | Ryan Pulock | 0 | D | 20 | 0 | 5 | 5 | 0 | 2 | 0 | 19 | 20 | 5 | 11 | 0.00% | 19 | 20.22 | 0 | 1 | 1 | 34 | 0 | 1 | 1 | 30 | 0 | 0 | 0.00% | 0 | 4 | 12 | 0 | 0 | 0.25 | 0 | 0 | ||
12 | Matt Dumba | 0 | D | 20 | 2 | 2 | 4 | 3 | 42 | 10 | 14 | 11 | 2 | 6 | 18.18% | 16 | 15.07 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 44 | 0 | 0 | 0.00% | 0 | 4 | 7 | 1 | 0 | 0.27 | 0 | 0 | ||
13 | Anthony Duclair | 0 | LW/RW | 20 | 1 | 3 | 4 | 0 | 0 | 0 | 14 | 37 | 7 | 22 | 2.70% | 4 | 13.45 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 14 | 0 | 0 | 25.00% | 8 | 6 | 2 | 0 | 0 | 0.30 | 0 | 1 | ||
14 | Tomas Nosek | 0 | C/LW | 20 | 2 | 2 | 4 | 3 | 6 | 0 | 12 | 22 | 6 | 5 | 9.09% | 8 | 10.08 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 45 | 0 | 0 | 65.31% | 49 | 1 | 4 | 0 | 0 | 0.40 | 0 | 0 | ||
15 | Patrik Nemeth | 0 | D | 20 | 0 | 3 | 3 | 1 | 0 | 0 | 11 | 13 | 5 | 5 | 0.00% | 9 | 15.35 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 53 | 0 | 0 | 0.00% | 0 | 1 | 6 | 0 | 0 | 0.20 | 0 | 0 | ||
16 | Nathan Bastian | 0 | C/RW | 20 | 0 | 3 | 3 | 0 | 2 | 0 | 21 | 19 | 1 | 12 | 0.00% | 5 | 7.67 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 75.00% | 4 | 7 | 2 | 0 | 0 | 0.39 | 0 | 0 | ||
17 | Jacob Peterson | 0 | C/LW | 20 | 2 | 0 | 2 | -1 | 2 | 0 | 14 | 27 | 11 | 23 | 7.41% | 2 | 12.06 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 20 | 0 | 0 | 27.27% | 11 | 10 | 4 | 0 | 0 | 0.17 | 0 | 1 | ||
18 | Jake McCabe | 0 | D | 20 | 0 | 1 | 1 | -1 | 21 | 5 | 25 | 22 | 4 | 6 | 0.00% | 35 | 20.16 | 0 | 0 | 0 | 34 | 0 | 0 | 0 | 30 | 0 | 0 | 0.00% | 0 | 2 | 11 | 0 | 0 | 0.05 | 0 | 0 | ||
Team Total or Average | 362 | 70 | 115 | 185 | 56 | 182 | 40 | 403 | 657 | 186 | 394 | 10.65% | 227 | 16.48 | 14 | 24 | 38 | 447 | 3 | 5 | 8 | 373 | 12 | 4 | 50.00% | 1156 | 141 | 123 | 2 | 1 | 0.62 | 1 | 8 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | Goalie Name | Team Name | GP | W | L | OTL | PCT | GAA | MP | PIM | SO | GA | SA | SAR | A | EG | PS % | PSA | ST | BG | S1 | S2 | S3 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Tristan Jarry | 10 | 5 | 4 | 1 | 0.908 | 2.98 | 604 | 0 | 0 | 30 | 326 | 166 | 0 | 0 | 0.000 | 2 | 10 | 10 | 1 | 0 | 1 | |
2 | Pheonix Copley | 3 | 1 | 2 | 0 | 0.906 | 3.02 | 179 | 0 | 0 | 9 | 96 | 53 | 1 | 0 | 0.000 | 0 | 3 | 18 | 0 | 0 | 0 | |
Team Total or Average | 13 | 6 | 6 | 1 | 0.908 | 2.99 | 783 | 0 | 0 | 39 | 422 | 219 | 1 | 0 | 0.000 | 2 | 13 | 28 | 1 | 0 | 1 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | VS Team | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | P | PCT | G | A | TP | SO | EG | GP1 | GP2 | GP3 | GP4 | SHF | SH1 | SP2 | SP3 | SP4 | SHA | SHB | Pim | Hit | PPA | PPG | PP% | PKA | PK GA | PK% | PK GF | W OF FO | T OF FO | OF FO% | W DF FO | T DF FO | DF FO% | W NT FO | T NT FO | NT FO% | PZ DF | PZ OF | PZ NT | PC DF | PC OF | PC NT | GF% | SH% | SV% | PDO | PDOBRK |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 3 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 10 | 10 | 0 | 3 | 0.500 | 10 | 18 | 28 | 0 | 0 | 2 | 3 | 5 | 0 | 96 | 34 | 33 | 29 | 2 | 114 | 43 | 23 | 54 | 5 | 2 | 40.00% | 9 | 2 | 77.78% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 60 | 35 | 72 | 28 | 52 | 24 | 50.0% | 10.4% | 91.2% | 101.6 | LUCKY | |
2 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 32 | 14 | 8 | 10 | 0 | 30 | 10 | 11 | 21 | 2 | 0 | 0.00% | 3 | 1 | 66.67% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 21 | 12 | 21 | 9 | 16 | 8 | 25.0% | 3.1% | 86.7% | 89.8 | Unlucky | |
3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 3 | 1 | 2 | 1.000 | 4 | 7 | 11 | 0 | 0 | 0 | 4 | 0 | 0 | 32 | 6 | 22 | 4 | 0 | 34 | 11 | 6 | 19 | 5 | 2 | 40.00% | 3 | 1 | 66.67% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 22 | 14 | 20 | 8 | 16 | 8 | 50.0% | 12.5% | 91.2% | 103.7 | LUCKY | |
4 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 0 | 1 | 2 | 0 | 33 | 7 | 18 | 8 | 0 | 33 | 12 | 4 | 23 | 3 | 1 | 33.33% | 2 | 0 | 100.00% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 23 | 14 | 19 | 8 | 17 | 9 | 66.7% | 9.1% | 97.0% | 106.1 | LUCKY | |
5 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 4 | -2 | 0 | 0.000 | 2 | 3 | 5 | 0 | 0 | 0 | 2 | 0 | 0 | 25 | 5 | 10 | 10 | 0 | 33 | 11 | 8 | 13 | 5 | 1 | 20.00% | 4 | 1 | 75.00% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 19 | 10 | 23 | 9 | 16 | 8 | 25.0% | 8.0% | 87.9% | 95.9 | Unlucky | |
6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 3 | 5 | 2 | 1.000 | 8 | 14 | 22 | 0 | 0 | 3 | 1 | 4 | 0 | 43 | 10 | 15 | 18 | 0 | 33 | 10 | 18 | 20 | 4 | 0 | 0.00% | 4 | 2 | 50.00% | 1 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 23 | 13 | 19 | 7 | 17 | 9 | 88.9% | 18.6% | 90.9% | 109.5 | FUN | |
7 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | 4 | -1 | 1 | 0.500 | 3 | 6 | 9 | 0 | 0 | 2 | 1 | 0 | 1 | 30 | 12 | 7 | 9 | 9 | 32 | 14 | 6 | 23 | 1 | 0 | 0.00% | 3 | 0 | 100.00% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 20 | 11 | 26 | 10 | 18 | 8 | 42.9% | 10.0% | 87.5% | 97.5 | FUN | |
8 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 4 | 5 | -1 | 0 | 0.000 | 4 | 6 | 10 | 0 | 0 | 2 | 0 | 2 | 0 | 36 | 16 | 12 | 8 | 0 | 27 | 13 | 24 | 29 | 8 | 3 | 37.50% | 2 | 0 | 100.00% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 24 | 15 | 18 | 8 | 17 | 8 | 16.7% | 11.1% | 81.5% | 92.6 | FUN | |
9 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 4 | 3 | 4 | 1.000 | 7 | 14 | 21 | 0 | 0 | 1 | 3 | 3 | 0 | 63 | 16 | 19 | 28 | 0 | 71 | 27 | 6 | 38 | 8 | 2 | 25.00% | 3 | 1 | 66.67% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 41 | 23 | 45 | 19 | 33 | 16 | 62.5% | 11.1% | 94.4% | 105.5 | LUCKY | |
10 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 4 | -2 | 0 | 0.000 | 2 | 3 | 5 | 0 | 0 | 1 | 0 | 1 | 0 | 31 | 18 | 7 | 6 | 0 | 32 | 10 | 6 | 6 | 2 | 1 | 50.00% | 3 | 2 | 33.33% | 1 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 21 | 13 | 23 | 8 | 15 | 7 | 33.3% | 6.5% | 87.5% | 94.0 | Unlucky | |
11 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 3 | 3 | 2 | 1.000 | 6 | 8 | 14 | 0 | 0 | 2 | 2 | 2 | 0 | 39 | 19 | 8 | 12 | 0 | 33 | 17 | 4 | 16 | 3 | 2 | 66.67% | 2 | 1 | 50.00% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 24 | 15 | 19 | 7 | 16 | 8 | 66.7% | 15.4% | 90.9% | 106.3 | FUN | |
12 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 3 | 6 | -3 | 0 | 0.000 | 3 | 5 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 70 | 19 | 21 | 30 | 0 | 73 | 13 | 33 | 40 | 10 | 0 | 0.00% | 4 | 1 | 75.00% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 43 | 25 | 42 | 18 | 33 | 17 | 37.5% | 4.3% | 91.8% | 96.1 | DULL | |
13 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 5 | 5 | 4 | 1.000 | 10 | 14 | 24 | 0 | 0 | 2 | 4 | 4 | 0 | 70 | 15 | 23 | 32 | 0 | 54 | 23 | 18 | 27 | 6 | 2 | 33.33% | 9 | 2 | 77.78% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 40 | 23 | 42 | 19 | 37 | 17 | 72.7% | 14.3% | 90.7% | 105.0 | FUN | |
14 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 5 | -2 | 0 | 0.000 | 3 | 5 | 8 | 0 | 0 | 1 | 2 | 0 | 0 | 35 | 8 | 14 | 13 | 0 | 41 | 8 | 4 | 15 | 2 | 1 | 50.00% | 2 | 1 | 50.00% | 1 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 20 | 11 | 21 | 9 | 18 | 9 | 33.3% | 8.6% | 87.8% | 96.4 | Unlucky | |
15 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 4 | 2 | 1.000 | 5 | 9 | 14 | 0 | 0 | 1 | 1 | 3 | 0 | 34 | 6 | 9 | 19 | 0 | 27 | 6 | 4 | 18 | 0 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 23 | 15 | 19 | 8 | 17 | 8 | 83.3% | 14.7% | 96.3% | 111.0 | LUCKY | |
_Vs Division | 9 | 2 | 6 | 0 | 0 | 0 | 0 | 1 | 21 | 29 | -8 | 5 | 0.278 | 21 | 36 | 57 | 0 | 0 | 5 | 7 | 9 | 0 | 287 | 97 | 97 | 93 | 2 | 315 | 99 | 85 | 157 | 27 | 5 | 18.52% | 25 | 7 | 72.00% | 1 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 190 | 112 | 202 | 81 | 152 | 74 | 42.1% | 7.3% | 90.8% | 98.1 | Unlucky | |
_Vs Conference | 16 | 8 | 7 | 0 | 0 | 0 | 0 | 1 | 54 | 49 | 5 | 17 | 0.531 | 54 | 91 | 145 | 0 | 0 | 13 | 19 | 22 | 0 | 531 | 160 | 188 | 183 | 2 | 534 | 183 | 157 | 290 | 58 | 14 | 24.14% | 46 | 13 | 71.74% | 2 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 342 | 203 | 348 | 145 | 274 | 135 | 52.6% | 10.2% | 90.8% | 101.0 | FUN | |
_Since Last GM Reset | 20 | 10 | 8 | 0 | 0 | 0 | 0 | 2 | 71 | 62 | 9 | 22 | 0.550 | 71 | 119 | 190 | 0 | 0 | 19 | 25 | 27 | 1 | 669 | 205 | 226 | 236 | 11 | 667 | 228 | 175 | 362 | 64 | 17 | 26.56% | 55 | 15 | 72.73% | 3 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 430 | 257 | 435 | 181 | 343 | 170 | 53.5% | 10.6% | 90.7% | 101.3 | FUN | |
Total | 20 | 10 | 8 | 0 | 0 | 0 | 0 | 2 | 71 | 62 | 9 | 22 | 0.550 | 71 | 119 | 190 | 0 | 0 | 19 | 25 | 27 | 1 | 669 | 205 | 226 | 236 | 11 | 667 | 228 | 175 | 362 | 64 | 17 | 26.56% | 55 | 15 | 72.73% | 3 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 430 | 257 | 435 | 181 | 343 | 170 | 53.5% | 10.6% | 90.7% | 101.3 | FUN |
Puck Time | |
---|---|
Offensive Zone | 21 |
Neutral Zone | 17 |
Defensive Zone | 21 |
Puck Time | |
---|---|
Offensive Zone Start | 421 |
Neutral Zone Start | 286 |
Defensive Zone Start | 443 |
Puck Time | |
---|---|
With Puck | 30 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 578 |
Faceoffs Lost | 572 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 10.3 | 9.57 |
2nd Period | 21.6 | 20.31 |
3rd Period | 33.4 | 30.68 |
Overtime | 33.9 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 1.0 | 0.64 |
2nd Period | 2.2 | 1.65 |
3rd Period | 3.6 | 2.67 |
Overtime | 3.6 | 2.83 |
Even Strenght Goal | 51 |
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PP Goal | 17 |
PK Goal | 3 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 6 | 4 |
Lost | 5 | 3 |
Overtime Lost | 1 | 1 |
PP Attempt | 64 |
---|---|
PP Goal | 17 |
PK Attempt | 55 |
PK Goal Against | 15 |
Home | |
---|---|
Shots For | 33.5 |
Shots Against | 33.4 |
Goals For | 3.6 |
Goals Against | 3.1 |
Hits | 18.1 |
Shots Blocked | 11.4 |
Pim | 8.8 |
Projected Total Cap Hit | 78,721,667$ |
Projected Cap Space | 3,778,333$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 20,382,985$ |
Players In Salary Cap | 25 |
LTIR Players | 0 |
Red Wings Roster | Pos | Age | Cap Hit | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 | 2030-31 |
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Alex Killorn ![]() | LW/RW | 33 | 4,450,000$ | 4,450,000$ | |||||||
Anthony Duclair ![]() | LW/RW | 27 | 3,000,000$ | 3,000,000$ | 3,000,000$ | ||||||
Carson Meyer ![]() | RW | 25 | 750,000$ | 750,000$ | |||||||
Darnell Nurse ![]() | D | 27 | 9,250,000$ | 9,250,000$ | 9,250,000$ | 9,250,000$ | 9,250,000$ | 9,250,000$ | 9,250,000$ | 9,250,000$ | 9,250,000$ |
Dennis Gilbert ![]() | D | 25 | 762,500$ | 762,500$ | 762,500$ | ||||||
Eric Robinson ![]() | LW | 27 | 1,600,000$ | 1,600,000$ | 1,600,000$ | ||||||
Erik Haula ![]() | C/LW | 31 | 2,375,000$ | 2,375,000$ | |||||||
Erik Kallgren ![]() | G | 25 | 750,000$ | 750,000$ | |||||||
Hampus Lindholm ![]() | D | 28 | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ |
Jacob Peterson ![]() | C/LW | 23 | 842,500$ | 842,500$ | |||||||
Jake McCabe ![]() | D | 28 | 4,000,000$ | 4,000,000$ | 4,000,000$ | 4,000,000$ | |||||
Jeff Carter ![]() | C/RW | 37 | 3,125,000$ | 3,125,000$ | 3,125,000$ | ||||||
John Hayden ![]() | C/RW | 27 | 750,000$ | 750,000$ | |||||||
Joona Luoto ![]() | LW/RW | 25 | 750,000$ | 750,000$ | |||||||
Matt Dumba ![]() | D | 28 | 6,000,000$ | 6,000,000$ | |||||||
Nathan Bastian ![]() | C/RW | 24 | 825,000$ | 825,000$ | |||||||
Patrik Nemeth ![]() | D | 30 | 2,500,000$ | 2,500,000$ | 2,500,000$ | ||||||
Pavel Buchnevich ![]() | C/LW/RW | 27 | 5,800,000$ | 5,800,000$ | 5,800,000$ | 5,800,000$ | |||||
Pheonix Copley ![]() | G | 30 | 1,100,000$ | 1,100,000$ | |||||||
Ryan Pulock ![]() | D | 27 | 6,150,000$ | 6,150,000$ | 6,150,000$ | 6,150,000$ | 6,150,000$ | 6,150,000$ | 6,150,000$ | 6,150,000$ | 6,150,000$ |
Tage Thompson ![]() | C | 24 | 1,400,000$ | 1,400,000$ | |||||||
Tom Wilson ![]() | RW | 28 | 5,166,667$ | 5,166,667$ | 5,166,667$ | ||||||
Tomas Nosek ![]() | C/LW | 30 | 1,750,000$ | 1,750,000$ | |||||||
Tristan Jarry ![]() | G | 27 | 3,500,000$ | 3,500,000$ | |||||||
Vincent Trocheck ![]() | C/RW | 29 | 5,625,000$ | 5,625,000$ | 5,625,000$ | 5,625,000$ | 5,625,000$ | 5,625,000$ | 5,625,000$ | 5,625,000$ |
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Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | VS Team | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | P | PCT | G | A | TP | SO | EG | GP1 | GP2 | GP3 | GP4 | SHF | SH1 | SP2 | SP3 | SP4 | SHA | SHB | Pim | Hit | PPA | PPG | PP% | PKA | PK GA | PK% | PK GF | W OF FO | T OF FO | OF FO% | W DF FO | T DF FO | DF FO% | W NT FO | T NT FO | NT FO% | PZ DF | PZ OF | PZ NT | PC DF | PC OF | PC NT | GF% | SH% | SV% | PDO | PDOBRK |
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1 | 3 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 10 | 10 | 0 | 3 | 0.500 | 10 | 18 | 28 | 0 | 0 | 2 | 3 | 5 | 0 | 96 | 34 | 33 | 29 | 2 | 114 | 43 | 23 | 54 | 5 | 2 | 40.00% | 9 | 2 | 77.78% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 60 | 35 | 72 | 28 | 52 | 24 | 50.0% | 10.4% | 91.2% | 101.6 | LUCKY | |
2 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 32 | 14 | 8 | 10 | 0 | 30 | 10 | 11 | 21 | 2 | 0 | 0.00% | 3 | 1 | 66.67% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 21 | 12 | 21 | 9 | 16 | 8 | 25.0% | 3.1% | 86.7% | 89.8 | Unlucky | |
3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 3 | 1 | 2 | 1.000 | 4 | 7 | 11 | 0 | 0 | 0 | 4 | 0 | 0 | 32 | 6 | 22 | 4 | 0 | 34 | 11 | 6 | 19 | 5 | 2 | 40.00% | 3 | 1 | 66.67% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 22 | 14 | 20 | 8 | 16 | 8 | 50.0% | 12.5% | 91.2% | 103.7 | LUCKY | |
4 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 0 | 1 | 2 | 0 | 33 | 7 | 18 | 8 | 0 | 33 | 12 | 4 | 23 | 3 | 1 | 33.33% | 2 | 0 | 100.00% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 23 | 14 | 19 | 8 | 17 | 9 | 66.7% | 9.1% | 97.0% | 106.1 | LUCKY | |
5 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 4 | -2 | 0 | 0.000 | 2 | 3 | 5 | 0 | 0 | 0 | 2 | 0 | 0 | 25 | 5 | 10 | 10 | 0 | 33 | 11 | 8 | 13 | 5 | 1 | 20.00% | 4 | 1 | 75.00% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 19 | 10 | 23 | 9 | 16 | 8 | 25.0% | 8.0% | 87.9% | 95.9 | Unlucky | |
6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 3 | 5 | 2 | 1.000 | 8 | 14 | 22 | 0 | 0 | 3 | 1 | 4 | 0 | 43 | 10 | 15 | 18 | 0 | 33 | 10 | 18 | 20 | 4 | 0 | 0.00% | 4 | 2 | 50.00% | 1 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 23 | 13 | 19 | 7 | 17 | 9 | 88.9% | 18.6% | 90.9% | 109.5 | FUN | |
7 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | 4 | -1 | 1 | 0.500 | 3 | 6 | 9 | 0 | 0 | 2 | 1 | 0 | 1 | 30 | 12 | 7 | 9 | 9 | 32 | 14 | 6 | 23 | 1 | 0 | 0.00% | 3 | 0 | 100.00% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 20 | 11 | 26 | 10 | 18 | 8 | 42.9% | 10.0% | 87.5% | 97.5 | FUN | |
8 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 4 | 5 | -1 | 0 | 0.000 | 4 | 6 | 10 | 0 | 0 | 2 | 0 | 2 | 0 | 36 | 16 | 12 | 8 | 0 | 27 | 13 | 24 | 29 | 8 | 3 | 37.50% | 2 | 0 | 100.00% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 24 | 15 | 18 | 8 | 17 | 8 | 16.7% | 11.1% | 81.5% | 92.6 | FUN | |
9 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 4 | 3 | 4 | 1.000 | 7 | 14 | 21 | 0 | 0 | 1 | 3 | 3 | 0 | 63 | 16 | 19 | 28 | 0 | 71 | 27 | 6 | 38 | 8 | 2 | 25.00% | 3 | 1 | 66.67% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 41 | 23 | 45 | 19 | 33 | 16 | 62.5% | 11.1% | 94.4% | 105.5 | LUCKY | |
10 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 4 | -2 | 0 | 0.000 | 2 | 3 | 5 | 0 | 0 | 1 | 0 | 1 | 0 | 31 | 18 | 7 | 6 | 0 | 32 | 10 | 6 | 6 | 2 | 1 | 50.00% | 3 | 2 | 33.33% | 1 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 21 | 13 | 23 | 8 | 15 | 7 | 33.3% | 6.5% | 87.5% | 94.0 | Unlucky | |
11 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 3 | 3 | 2 | 1.000 | 6 | 8 | 14 | 0 | 0 | 2 | 2 | 2 | 0 | 39 | 19 | 8 | 12 | 0 | 33 | 17 | 4 | 16 | 3 | 2 | 66.67% | 2 | 1 | 50.00% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 24 | 15 | 19 | 7 | 16 | 8 | 66.7% | 15.4% | 90.9% | 106.3 | FUN | |
12 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 3 | 6 | -3 | 0 | 0.000 | 3 | 5 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 70 | 19 | 21 | 30 | 0 | 73 | 13 | 33 | 40 | 10 | 0 | 0.00% | 4 | 1 | 75.00% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 43 | 25 | 42 | 18 | 33 | 17 | 37.5% | 4.3% | 91.8% | 96.1 | DULL | |
13 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 5 | 5 | 4 | 1.000 | 10 | 14 | 24 | 0 | 0 | 2 | 4 | 4 | 0 | 70 | 15 | 23 | 32 | 0 | 54 | 23 | 18 | 27 | 6 | 2 | 33.33% | 9 | 2 | 77.78% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 40 | 23 | 42 | 19 | 37 | 17 | 72.7% | 14.3% | 90.7% | 105.0 | FUN | |
14 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 5 | -2 | 0 | 0.000 | 3 | 5 | 8 | 0 | 0 | 1 | 2 | 0 | 0 | 35 | 8 | 14 | 13 | 0 | 41 | 8 | 4 | 15 | 2 | 1 | 50.00% | 2 | 1 | 50.00% | 1 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 20 | 11 | 21 | 9 | 18 | 9 | 33.3% | 8.6% | 87.8% | 96.4 | Unlucky | |
15 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 4 | 2 | 1.000 | 5 | 9 | 14 | 0 | 0 | 1 | 1 | 3 | 0 | 34 | 6 | 9 | 19 | 0 | 27 | 6 | 4 | 18 | 0 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 23 | 15 | 19 | 8 | 17 | 8 | 83.3% | 14.7% | 96.3% | 111.0 | LUCKY | |
_Vs Division | 9 | 2 | 6 | 0 | 0 | 0 | 0 | 1 | 21 | 29 | -8 | 5 | 0.278 | 21 | 36 | 57 | 0 | 0 | 5 | 7 | 9 | 0 | 287 | 97 | 97 | 93 | 2 | 315 | 99 | 85 | 157 | 27 | 5 | 18.52% | 25 | 7 | 72.00% | 1 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 190 | 112 | 202 | 81 | 152 | 74 | 42.1% | 7.3% | 90.8% | 98.1 | Unlucky | |
_Vs Conference | 16 | 8 | 7 | 0 | 0 | 0 | 0 | 1 | 54 | 49 | 5 | 17 | 0.531 | 54 | 91 | 145 | 0 | 0 | 13 | 19 | 22 | 0 | 531 | 160 | 188 | 183 | 2 | 534 | 183 | 157 | 290 | 58 | 14 | 24.14% | 46 | 13 | 71.74% | 2 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 342 | 203 | 348 | 145 | 274 | 135 | 52.6% | 10.2% | 90.8% | 101.0 | FUN | |
_Since Last GM Reset | 20 | 10 | 8 | 0 | 0 | 0 | 0 | 2 | 71 | 62 | 9 | 22 | 0.550 | 71 | 119 | 190 | 0 | 0 | 19 | 25 | 27 | 1 | 669 | 205 | 226 | 236 | 11 | 667 | 228 | 175 | 362 | 64 | 17 | 26.56% | 55 | 15 | 72.73% | 3 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 430 | 257 | 435 | 181 | 343 | 170 | 53.5% | 10.6% | 90.7% | 101.3 | FUN | |
Total | 20 | 10 | 8 | 0 | 0 | 0 | 0 | 2 | 71 | 62 | 9 | 22 | 0.550 | 71 | 119 | 190 | 0 | 0 | 19 | 25 | 27 | 1 | 669 | 205 | 226 | 236 | 11 | 667 | 228 | 175 | 362 | 64 | 17 | 26.56% | 55 | 15 | 72.73% | 3 | 201 | 421 | 47.74% | 223 | 443 | 50.34% | 154 | 286 | 53.85% | 430 | 257 | 435 | 181 | 343 | 170 | 53.5% | 10.6% | 90.7% | 101.3 | FUN |
Puck Time | |
---|---|
Offensive Zone | 21 |
Neutral Zone | 17 |
Defensive Zone | 21 |
Puck Time | |
---|---|
Offensive Zone Start | 421 |
Neutral Zone Start | 286 |
Defensive Zone Start | 443 |
Puck Time | |
---|---|
With Puck | 30 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 578 |
Faceoffs Lost | 572 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 10.3 | 9.57 |
2nd Period | 21.6 | 20.31 |
3rd Period | 33.4 | 30.68 |
Overtime | 33.9 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 1.0 | 0.64 |
2nd Period | 2.2 | 1.65 |
3rd Period | 3.6 | 2.67 |
Overtime | 3.6 | 2.83 |
Even Strenght Goal | 51 |
---|---|
PP Goal | 17 |
PK Goal | 3 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 6 | 4 |
Lost | 5 | 3 |
Overtime Lost | 1 | 1 |
PP Attempt | 64 |
---|---|
PP Goal | 17 |
PK Attempt | 55 |
PK Goal Against | 15 |
Home | |
---|---|
Shots For | 33.5 |
Shots Against | 33.4 |
Goals For | 3.6 |
Goals Against | 3.1 |
Hits | 18.1 |
Shots Blocked | 11.4 |
Pim | 8.8 |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
78,721,667$ | 0$ | 78,721,667$ | 3,778,333$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | Little Caesars Arena | |
City | Detroit | ||
Capacity | 18000 | ||
Season Ticket Holders | 40% |
Arena Capacity - Ticket Price Attendance - % | |||||
---|---|---|---|---|---|
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Arena Capacity | 6000 | 5000 | 2000 | 4000 | 1000 |
Ticket Price | 100$ | 60$ | 35$ | 25$ | 200$ |
Attendance | 67721 | 57016 | 22918 | 45368 | 11436 |
Attendance PCT | 94.06% | 95.03% | 95.49% | 94.52% | 95.30% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
29 | 17038 - 94.66% | 612,705$ | 7,352,463$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
78,721,667$ | 78,721,667$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
20,382,985$ | 78,721,667$ | 20,382,985$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
17,768,452$ | 142 | 410,009$ | 58,221,278$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
63,103,162$ | 78,721,667$ | -507,185,714$ | -552,520,424$ |
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Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
---|---|---|---|---|---|---|---|
2024 | |||||||
2025 | |||||||
2026 | |||||||
2027 | |||||||
2028 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
---|---|---|---|---|---|
1 ballo det 2023 | |||||
Adam Gaudette | Link | ||||
Aku Raty | 2019 | 158 | |||
Alexander Nikishin | 2020 | 28 | |||
Alexandre Fortin | |||||
Angus MacDonell | 2023 | 192 | |||
Anttoni Honka | 2019 | 85 | |||
Arsenii Sergeev | 2021 | 178 | |||
Ben Jones | Link | ||||
Brandon Kruse | 2018 | 138 | |||
Brendan Lepsic | |||||
Brian Zanetti | 2021 | 113 | |||
Bryce Misley | |||||
Carson Bantle | 2020 | 139 | |||
Carson Rehkopf | 2023 | 64 | |||
Cedrick Guindon | 2022 | 108 | |||
Christoffer Ehn | |||||
Daniel Torgersson | 2020 | 63 | |||
David Cotton | |||||
David Edstrom | 2023 | 41 | |||
Domenic Divincentiis | 2022 | 203 | |||
Filip Cederqvist | 2019 | 147 | |||
Frederik Nissen | 2019 | 136 | |||
Gabriel Gagné | |||||
Gustav Berglund | 2019 | 167 | |||
Gustav Olhaver | |||||
Helge Grans | 2020 | 40 | |||
Henrik Tikkanen | 2020 | 205 | |||
Hudson Elynuik | 2016 | 71 | |||
Hugo Ollas | 2020 | 174 | |||
Ivan Fedotov | |||||
Jack Becker | |||||
Jackson Kunz | 2020 | 112 | |||
Jake Kupsky | |||||
Jakob Stenqvist | 2016 | 166 | |||
Jakub Galvas | 2017 | Link | |||
Jermaine Loewen | 2018 | 192 | |||
Joel L'Esperance | Link | ||||
Joel Ratkovic | 2022 | 204 | |||
Joni Jurmo | 2020 | 95 | |||
Kalle Kossila | |||||
Kevin Korchinski | 2022 | 12 | |||
Kevin Reidler | 2022 | 139 | |||
Kyle Rau | Link | ||||
Liam Gorman | 2018 | 151 | |||
Linus Karlsson | 2018 | 81 | |||
Luca Delbelbelluz | 2022 | 43 | |||
Lukas Cormier | 2020 | 43 | |||
Lukas Jasek | |||||
Luke Stevens | |||||
Marek Alscher | 2022 | 99 | |||
Maskim Berezkin | 2020 | 133 | |||
Ole Bjorgvik Holm | 2020 | 143 | |||
Oskar Jellvik | 2021 | 145 | |||
Petr Hauser | 2022 | 142 | |||
Philip Kemp | |||||
Philippe Desrosiers | |||||
Remi Elie | 2013 | Link | |||
Rudy Guimond | 2023 | 160 | |||
Ryan Collins | |||||
Samu Tuomaala | 2021 | 56 | |||
Samuel Helenius | 2021 | 49 | |||
Santeri Hatakka | 2019 | 178 | Link | ||
Sebastian Bradshaw | 2023 | 224 | |||
Shawn Boudrias | 2018 | 153 | |||
Simon Forsmark | 2022 | 107 | |||
Simon Lundmark | 2019 | 54 | |||
Stephen Halliday | 2022 | 100 | |||
Tobias Geisser | |||||
Tomas Mazura | 2019 | 168 | |||
Topi Ronni | 2022 | 55 | |||
Ty Gallagher | 2021 | 209 | |||
Tyson Kozak | 2021 | 177 | |||
Ville Ottavainen | 2021 | 103 | |||
Vilmer Alriksson | 2023 | 107 | |||
William Trudeau | 2021 | 115 | |||
Xavier Bouchard | 2018 | 171 | |||
Yevgeni Volokhin | 2023 | 128 | |||
ryan olsen |
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