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Full Scoreboard »» |
Colorado Avalanche 15-4-2, 32pts · 2nd in Conference Ouest |
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 | 100.00 | 71 | 42 | 83 | 92 | 65 | 81 | 94 | 82 | 91 | 80 | 92 | 78 | 53 | 70 | 73 | 86 | 50 | 0 | 25 | 8,460,250$/2yrs | |||
![]() | 0 | RW | 100.00 | 67 | 42 | 91 | 79 | 71 | 73 | 75 | 81 | 53 | 57 | 86 | 67 | 75 | 50 | 50 | 76 | 50 | 0 | 22 | 1,562,500$/2yrs | |||
![]() | 0 | LW | 100.00 | 65 | 42 | 91 | 90 | 68 | 85 | 97 | 90 | 33 | 86 | 87 | 64 | 61 | 68 | 70 | 82 | 50 | 0 | 25 | 7,142,857$/4yrs | |||
![]() | 0 | C/RW | 100.00 | 63 | 64 | 73 | 84 | 72 | 75 | 95 | 76 | 78 | 76 | 71 | 63 | 47 | 75 | 76 | 72 | 50 | 0 | 29 | 5,000,000$/5yrs | |||
![]() | 0 | LW/RW | 100.00 | 59 | 41 | 91 | 87 | 69 | 76 | 90 | 74 | 59 | 78 | 71 | 75 | 70 | 72 | 76 | 74 | 50 | 0 | 28 | 5,400,000$/2yrs | |||
![]() | 0 | C/RW | 100.00 | 67 | 43 | 88 | 71 | 80 | 62 | 76 | 67 | 87 | 56 | 60 | 85 | 25 | 58 | 58 | 66 | 50 | 0 | 26 | 750,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 61 | 41 | 90 | 84 | 64 | 76 | 89 | 77 | 39 | 80 | 85 | 65 | 63 | 70 | 72 | 79 | 50 | 0 | 29 | 4,250,000$/2yrs | |||
![]() | 0 | RW | 100.00 | 76 | 44 | 93 | 80 | 72 | 73 | 71 | 59 | 31 | 72 | 62 | 77 | 25 | 64 | 65 | 69 | 50 | 0 | 26 | 2,166,667$/3yrs | |||
![]() | 0 | LW/RW | 100.00 | 99 | 99 | 60 | 77 | 85 | 70 | 87 | 68 | 44 | 67 | 60 | 77 | 25 | 76 | 78 | 70 | 50 | 0 | 31 | 3,100,000$/1yrs | |||
![]() | 0 | C/LW | 100.00 | 69 | 42 | 90 | 81 | 67 | 69 | 84 | 66 | 79 | 73 | 68 | 67 | 25 | 65 | 65 | 71 | 60 | 0 | 24 | 825,000$/1yrs | |||
![]() | 0 | C/RW | 100.00 | 59 | 41 | 90 | 82 | 68 | 81 | 90 | 85 | 25 | 84 | 84 | 63 | 56 | 65 | 65 | 80 | 50 | 0 | 25 | 1,450,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 79 | 44 | 95 | 88 | 69 | 72 | 80 | 72 | 26 | 75 | 70 | 66 | 37 | 75 | 82 | 73 | 50 | 0 | 31 | 6,000,000$/6yrs | |||
![]() | 0 | D | 100.00 | 76 | 45 | 73 | 90 | 81 | 89 | 83 | 89 | 25 | 66 | 61 | 87 | 25 | 73 | 74 | 74 | 50 | 0 | 26 | 7,500,000$/3yrs | |||
![]() | 0 | D | 100.00 | 86 | 88 | 76 | 77 | 82 | 78 | 86 | 61 | 25 | 47 | 50 | 89 | 25 | 75 | 75 | 65 | 50 | 0 | 29 | 4,400,000$/4yrs | |||
![]() | 0 | D | 100.00 | 76 | 45 | 88 | 81 | 84 | 80 | 94 | 59 | 25 | 57 | 50 | 90 | 75 | 66 | 68 | 67 | 50 | 0 | 27 | 3,166,667$/1yrs | |||
![]() | 0 | D | 100.00 | 71 | 43 | 85 | 83 | 71 | 86 | 84 | 64 | 25 | 53 | 48 | 90 | 25 | 77 | 80 | 65 | 50 | 0 | 29 | 6,000,000$/6yrs | |||
![]() | 0 | D | 100.00 | 81 | 44 | 86 | 78 | 70 | 74 | 82 | 61 | 25 | 53 | 50 | 80 | 25 | 59 | 60 | 64 | 50 | 0 | 23 | 1,400,000$/1yrs | |||
![]() | 0 | D | 100.00 | 65 | 53 | 84 | 83 | 78 | 85 | 93 | 64 | 25 | 64 | 48 | 86 | 80 | 73 | 75 | 66 | 50 | 0 | 27 | 4,025,000$/2yrs | |||
Scratches | ||||||||||||||||||||||||||
TEAM AVERAGE | 100.00 | 72 | 50 | 85 | 83 | 73 | 77 | 86 | 72 | 44 | 68 | 67 | 76 | 45 | 68 | 70 | 72 | 51 | 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 | 64 | 75 | 74 | 83 | 65 | 62 | 69 | 65 | 65 | 64 | 82 | 71 | 72 | 66 | 50 | 0 | 34 | 2,250,000$/1yrs |
![]() | 0 | 100.00 | 74 | 56 | 56 | 86 | 78 | 71 | 90 | 76 | 81 | 75 | 95 | 56 | 56 | 75 | 50 | 0 | 26 | 2,175,000$/1yrs |
Scratches | ||||||||||||||||||||
![]() | 0 | 100.00 | 59 | 54 | 54 | 70 | 65 | 52 | 83 | 62 | 65 | 59 | 95 | 56 | 57 | 63 | 50 | 0 | 27 | 5,000,000$/3yrs |
TEAM AVERAGE | 100.00 | 66 | 62 | 61 | 80 | 69 | 62 | 81 | 68 | 70 | 66 | 91 | 61 | 62 | 68 | 50 | 0 |
Player | # | POS | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | C/LW | 100.00 | 66 | 55 | 93 | 72 | 55 | 79 | 84 | 62 | 78 | 62 | 58 | 60 | 55 | 46 | 46 | 64 | 57 | 0 | 23 | 925,000$/1yrs | |||
![]() | 0 | C/LW | 100.00 | 80 | 56 | 82 | 65 | 62 | 58 | 85 | 60 | 65 | 62 | 58 | 79 | 25 | 58 | 59 | 65 | 50 | 0 | 23 | 800,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 77 | 70 | 94 | 70 | 70 | 77 | 82 | 59 | 50 | 47 | 67 | 65 | 64 | 45 | 45 | 66 | 57 | 0 | 22 | 795,000$/1yrs | |||
![]() | 0 | D | 100.00 | 68 | 73 | 56 | 66 | 73 | 76 | 83 | 48 | 25 | 40 | 41 | 57 | 39 | 45 | 45 | 51 | 57 | 0 | 23 | 750,000$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | LW/RW | 100.00 | 68 | 63 | 79 | 78 | 63 | 62 | 62 | 67 | 50 | 61 | 64 | 67 | 61 | 65 | 65 | 66 | 23 | 0 | 28 | 750,000$/1yrs | |||
![]() | 0 | D | 100.00 | 63 | 41 | 99 | 63 | 66 | 60 | 68 | 58 | 25 | 50 | 48 | 76 | 25 | 51 | 51 | 60 | 23 | 0 | 26 | 750,000$/1yrs |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Scratches |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
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General Manager | Kevin Meunier |
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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 |
# | 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 | Kyle Connor | 0 | LW | 21 | 12 | 22 | 34 | 16 | 0 | 0 | 25 | 101 | 22 | 56 | 11.88% | 8 | 21.21 | 1 | 8 | 9 | 68 | 0 | 0 | 0 | 1 | 4 | 0 | 13.89% | 36 | 37 | 11 | 0 | 0 | 1.53 | 0 | 1 | ||
2 | Sebastian Aho | 0 | C | 21 | 11 | 20 | 31 | 15 | 4 | 0 | 26 | 93 | 32 | 54 | 11.83% | 6 | 21.47 | 2 | 8 | 10 | 68 | 0 | 0 | 0 | 1 | 3 | 2 | 56.21% | 596 | 21 | 10 | 0 | 0 | 1.37 | 0 | 1 | ||
3 | Troy Terry | 0 | C/RW | 21 | 9 | 12 | 21 | 3 | 0 | 0 | 15 | 68 | 18 | 42 | 13.24% | 10 | 15.36 | 2 | 6 | 8 | 57 | 0 | 0 | 0 | 0 | 1 | 0 | 15.91% | 44 | 19 | 2 | 0 | 0 | 1.30 | 0 | 1 | ||
4 | Viktor Arvidsson | 0 | LW/RW | 21 | 9 | 10 | 19 | 10 | 2 | 0 | 14 | 51 | 8 | 33 | 17.65% | 7 | 19.18 | 5 | 4 | 9 | 54 | 0 | 0 | 0 | 0 | 2 | 0 | 60.00% | 20 | 11 | 10 | 1 | 0 | 0.94 | 0 | 0 | ||
5 | Aaron Ekblad | 0 | D | 21 | 3 | 13 | 16 | 6 | 18 | 0 | 45 | 45 | 25 | 26 | 6.67% | 34 | 26.99 | 3 | 3 | 6 | 78 | 0 | 0 | 0 | 20 | 0 | 0 | 0.00% | 0 | 14 | 21 | 0 | 0 | 0.56 | 0 | 0 | ||
6 | Teuvo Teravainen | 0 | LW/RW | 21 | 9 | 5 | 14 | 7 | 9 | 5 | 17 | 55 | 17 | 37 | 16.36% | 11 | 17.71 | 5 | 1 | 6 | 67 | 0 | 0 | 0 | 0 | 4 | 1 | 33.33% | 18 | 15 | 8 | 0 | 0 | 0.75 | 0 | 0 | ||
7 | Ryan Graves | 0 | D | 21 | 1 | 9 | 10 | 0 | 4 | 0 | 36 | 13 | 4 | 10 | 7.69% | 30 | 19.70 | 0 | 1 | 1 | 49 | 0 | 0 | 0 | 17 | 0 | 0 | 0.00% | 0 | 4 | 11 | 0 | 0 | 0.48 | 0 | 0 | ||
8 | Connor Murphy | 0 | D | 21 | 1 | 5 | 6 | 8 | 24 | 20 | 58 | 23 | 17 | 11 | 4.35% | 16 | 26.55 | 1 | 2 | 3 | 78 | 0 | 0 | 0 | 26 | 1 | 0 | 0.00% | 0 | 3 | 16 | 0 | 0 | 0.22 | 0 | 0 | ||
9 | Ondrej Palat | 0 | LW/RW | 21 | 1 | 5 | 6 | -3 | 0 | 0 | 29 | 49 | 13 | 28 | 2.04% | 13 | 14.23 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 24 | 0 | 0 | 23.08% | 26 | 12 | 4 | 0 | 0 | 0.40 | 0 | 0 | ||
10 | Kirill Marchenko | 0 | RW | 21 | 2 | 3 | 5 | -12 | 0 | 0 | 17 | 45 | 10 | 30 | 4.44% | 4 | 14.22 | 1 | 0 | 1 | 59 | 0 | 0 | 0 | 0 | 0 | 1 | 20.00% | 10 | 9 | 8 | 0 | 0 | 0.33 | 0 | 0 | ||
11 | Ryan Strome | 0 | C/RW | 21 | 3 | 2 | 5 | 4 | 21 | 15 | 26 | 34 | 11 | 21 | 8.82% | 7 | 14.74 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 10 | 0 | 0 | 53.50% | 243 | 8 | 2 | 0 | 0 | 0.32 | 0 | 0 | ||
12 | Mason Appleton | 0 | RW | 21 | 4 | 1 | 5 | -1 | 5 | 5 | 5 | 33 | 13 | 28 | 12.12% | 9 | 9.16 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 0 | 0 | 20.00% | 5 | 9 | 7 | 0 | 0 | 0.52 | 0 | 0 | ||
13 | Marcus Foligno | 0 | LW/RW | 21 | 3 | 1 | 4 | -2 | 9 | 5 | 30 | 40 | 12 | 25 | 7.50% | 7 | 9.27 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 13 | 0 | 0 | 50.00% | 4 | 9 | 2 | 0 | 0 | 0.41 | 0 | 0 | ||
14 | Kevin Stenlund | 0 | C/RW | 21 | 2 | 1 | 3 | -8 | 2 | 0 | 14 | 16 | 8 | 13 | 12.50% | 7 | 12.02 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 27 | 0 | 0 | 53.52% | 142 | 0 | 2 | 0 | 0 | 0.24 | 0 | 0 | ||
15 | Brett Pesce | 0 | D | 21 | 1 | 2 | 3 | 3 | 2 | 0 | 23 | 14 | 8 | 5 | 7.14% | 17 | 12.93 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0.00% | 0 | 2 | 5 | 0 | 0 | 0.22 | 0 | 0 | ||
16 | Jonas Brodin | 0 | D | 21 | 0 | 1 | 1 | -1 | 4 | 0 | 20 | 21 | 7 | 10 | 0.00% | 29 | 20.41 | 0 | 1 | 1 | 49 | 0 | 0 | 0 | 23 | 0 | 0 | 0.00% | 0 | 1 | 14 | 0 | 0 | 0.05 | 0 | 1 | ||
17 | Timothy Liljegren | 0 | D | 21 | 1 | 0 | 1 | 3 | 0 | 0 | 26 | 12 | 6 | 4 | 8.33% | 17 | 13.48 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 11 | 0 | 0 | 0.00% | 0 | 0 | 7 | 1 | 0 | 0.07 | 0 | 0 | ||
18 | Sam Steel | 0 | C/LW | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0.00% | 1 | 10.53 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0.00% | 4 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | ||
Team Total or Average | 358 | 72 | 112 | 184 | 48 | 104 | 50 | 426 | 714 | 231 | 433 | 10.08% | 233 | 16.96 | 21 | 34 | 55 | 637 | 0 | 0 | 0 | 194 | 15 | 4 | 50.70% | 1148 | 174 | 140 | 2 | 0 | 0.61 | 0 | 4 |
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 | Adin Hill | 16 | 12 | 2 | 2 | 0.933 | 1.99 | 964 | 0 | 1 | 32 | 481 | 266 | 3 | 0 | 0.667 | 3 | 16 | 5 | 1 | 1 | 2 | |
2 | James Reimer | 5 | 3 | 2 | 0 | 0.915 | 2.41 | 299 | 0 | 0 | 12 | 141 | 86 | 0 | 0 | 0.000 | 0 | 5 | 16 | 1 | 0 | 0 | |
Team Total or Average | 21 | 15 | 4 | 2 | 0.929 | 2.09 | 1264 | 0 | 1 | 44 | 622 | 352 | 3 | 0 | 0.667 | 3 | 21 | 21 | 2 | 1 | 2 |
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 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | -1 | 0 | 0.000 | 2 | 4 | 6 | 0 | 0 | 1 | 1 | 0 | 0 | 44 | 16 | 16 | 12 | 0 | 32 | 11 | 2 | 22 | 2 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 21 | 12 | 22 | 8 | 16 | 7 | 40.0% | 4.5% | 90.6% | 95.2 | Unlucky | |
2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 0 | 1 | 2 | 0 | 33 | 17 | 7 | 9 | 0 | 26 | 18 | 2 | 15 | 5 | 2 | 40.00% | 1 | 1 | 0.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 22 | 12 | 19 | 8 | 18 | 9 | 50.0% | 9.1% | 92.3% | 101.4 | LUCKY | |
3 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 4 | 5 | -1 | 2 | 0.500 | 4 | 6 | 10 | 0 | 0 | 0 | 3 | 1 | 0 | 77 | 28 | 28 | 21 | 0 | 55 | 16 | 7 | 37 | 11 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 46 | 26 | 39 | 17 | 34 | 18 | 44.4% | 5.2% | 90.9% | 96.1 | Unlucky | |
4 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 1 | 5 | 2 | 1.000 | 6 | 10 | 16 | 0 | 0 | 3 | 1 | 2 | 0 | 37 | 12 | 12 | 13 | 0 | 23 | 8 | 16 | 11 | 3 | 2 | 66.67% | 4 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 23 | 13 | 18 | 8 | 18 | 8 | 80.0% | 16.2% | 95.7% | 111.9 | LUCKY | |
5 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 4 | -2 | 0 | 0.000 | 2 | 4 | 6 | 0 | 0 | 1 | 1 | 0 | 0 | 42 | 10 | 10 | 22 | 0 | 38 | 16 | 2 | 14 | 4 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 22 | 14 | 20 | 8 | 16 | 8 | 33.3% | 4.8% | 89.5% | 94.2 | Unlucky | |
6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 3 | 2 | 2 | 1.000 | 5 | 7 | 12 | 0 | 0 | 0 | 3 | 2 | 0 | 36 | 9 | 15 | 12 | 0 | 27 | 17 | 9 | 24 | 5 | 2 | 40.00% | 2 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 21 | 12 | 20 | 9 | 17 | 8 | 50.0% | 13.9% | 88.9% | 102.8 | FUN | |
7 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 3 | 2 | 1.000 | 3 | 5 | 8 | 0 | 1 | 1 | 1 | 1 | 0 | 30 | 10 | 14 | 6 | 0 | 36 | 15 | 0 | 18 | 2 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 19 | 11 | 21 | 9 | 18 | 9 | 100.0% | 10.0% | 100.0% | 110.0 | LUCKY | |
8 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 2 | 2 | 2 | 1.000 | 4 | 7 | 11 | 0 | 0 | 0 | 1 | 3 | 0 | 34 | 12 | 6 | 16 | 0 | 30 | 12 | 2 | 16 | 4 | 3 | 75.00% | 1 | 1 | 0.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 20 | 11 | 22 | 8 | 17 | 8 | 50.0% | 11.8% | 93.3% | 105.1 | LUCKY | |
9 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 4 | 1 | 2 | 1.000 | 5 | 8 | 13 | 0 | 0 | 4 | 0 | 1 | 0 | 34 | 17 | 9 | 8 | 0 | 41 | 11 | 4 | 16 | 2 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 21 | 13 | 21 | 8 | 17 | 7 | 55.6% | 14.7% | 90.2% | 104.9 | FUN | |
10 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 3 | 2 | 2 | 1.000 | 5 | 8 | 13 | 0 | 0 | 0 | 2 | 3 | 0 | 31 | 6 | 13 | 12 | 0 | 22 | 13 | 7 | 22 | 5 | 1 | 20.00% | 1 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 21 | 11 | 19 | 8 | 18 | 10 | 57.1% | 16.1% | 86.4% | 102.5 | FUN | |
11 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 2 | -1 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 1 | 0 | 0 | 31 | 13 | 7 | 11 | 0 | 26 | 10 | 0 | 18 | 7 | 1 | 14.29% | 0 | 0 | 0.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 21 | 12 | 20 | 9 | 17 | 9 | 0.0% | 3.2% | 92.3% | 95.5 | DULL | |
12 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 2 | -1 | 1 | 0.500 | 1 | 2 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 30 | 12 | 11 | 7 | 3 | 24 | 9 | 0 | 23 | 6 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 23 | 13 | 19 | 9 | 21 | 11 | 33.3% | 3.3% | 91.7% | 95.0 | DULL | |
13 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 0 | 1 | 2 | 0 | 36 | 9 | 17 | 10 | 0 | 24 | 10 | 2 | 28 | 5 | 1 | 20.00% | 1 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 21 | 12 | 20 | 9 | 17 | 9 | 66.7% | 8.3% | 95.8% | 104.2 | DULL | |
14 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 2 | 2 | 2 | 1.000 | 4 | 5 | 9 | 0 | 0 | 0 | 0 | 4 | 0 | 32 | 7 | 8 | 17 | 0 | 39 | 19 | 5 | 18 | 3 | 2 | 66.67% | 0 | 0 | 0.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 20 | 10 | 22 | 8 | 17 | 8 | 50.0% | 12.5% | 94.9% | 107.4 | LUCKY | |
15 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 4 | 2 | 1.000 | 5 | 9 | 14 | 0 | 0 | 2 | 2 | 1 | 0 | 32 | 9 | 15 | 8 | 0 | 17 | 7 | 14 | 30 | 4 | 2 | 50.00% | 2 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 24 | 13 | 18 | 9 | 17 | 8 | 75.0% | 15.6% | 94.1% | 109.7 | LUCKY | |
16 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 3 | 1 | 2 | 1.000 | 4 | 7 | 11 | 0 | 0 | 0 | 1 | 3 | 0 | 40 | 8 | 10 | 22 | 0 | 40 | 12 | 11 | 20 | 1 | 1 | 100.00% | 3 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 19 | 11 | 23 | 9 | 17 | 8 | 50.0% | 10.0% | 92.5% | 102.5 | LUCKY | |
17 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 | 3 | -1 | 1 | 0.500 | 2 | 2 | 4 | 0 | 0 | 0 | 1 | 1 | 0 | 21 | 2 | 12 | 7 | 0 | 35 | 4 | 6 | 28 | 2 | 1 | 50.00% | 3 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 21 | 11 | 20 | 8 | 18 | 9 | 25.0% | 9.5% | 91.4% | 101.0 | LUCKY | |
18 | 3 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 13 | 4 | 9 | 6 | 1.000 | 13 | 21 | 34 | 0 | 0 | 5 | 3 | 5 | 0 | 109 | 30 | 45 | 34 | 0 | 87 | 31 | 15 | 79 | 10 | 3 | 30.00% | 5 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 69 | 42 | 59 | 26 | 51 | 26 | 71.4% | 11.9% | 95.4% | 107.3 | LUCKY | |
_Vs Division | 6 | 4 | 2 | 0 | 0 | 0 | 0 | 0 | 18 | 14 | 4 | 8 | 0.667 | 18 | 27 | 45 | 0 | 0 | 0 | 8 | 10 | 0 | 210 | 69 | 64 | 77 | 0 | 177 | 74 | 23 | 113 | 30 | 8 | 26.67% | 4 | 1 | 75.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 130 | 75 | 125 | 53 | 104 | 54 | 43.5% | 8.6% | 92.1% | 100.7 | DULL | |
_Vs Conference | 15 | 9 | 4 | 0 | 0 | 1 | 0 | 1 | 47 | 36 | 11 | 20 | 0.667 | 47 | 75 | 122 | 0 | 0 | 8 | 17 | 22 | 0 | 527 | 153 | 181 | 193 | 3 | 455 | 170 | 66 | 321 | 60 | 14 | 23.33% | 18 | 1 | 94.44% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 328 | 192 | 311 | 132 | 264 | 136 | 48.5% | 8.9% | 92.1% | 101.0 | Unlucky | |
_Since Last GM Reset | 21 | 15 | 4 | 0 | 0 | 1 | 0 | 1 | 72 | 45 | 27 | 32 | 0.762 | 72 | 117 | 189 | 0 | 1 | 18 | 23 | 31 | 0 | 729 | 227 | 255 | 247 | 3 | 622 | 239 | 104 | 439 | 81 | 21 | 25.93% | 28 | 2 | 92.86% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 461 | 269 | 431 | 186 | 371 | 189 | 54.3% | 9.9% | 92.8% | 102.6 | LUCKY | |
Total | 21 | 15 | 4 | 0 | 0 | 1 | 0 | 1 | 72 | 45 | 27 | 32 | 0.762 | 72 | 117 | 189 | 0 | 1 | 18 | 23 | 31 | 0 | 729 | 227 | 255 | 247 | 3 | 622 | 239 | 104 | 439 | 81 | 21 | 25.93% | 28 | 2 | 92.86% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 461 | 269 | 431 | 186 | 371 | 189 | 54.3% | 9.9% | 92.8% | 102.6 | LUCKY |
Puck Time | |
---|---|
Offensive Zone | 21 |
Neutral Zone | 17 |
Defensive Zone | 20 |
Puck Time | |
---|---|
Offensive Zone Start | 517 |
Neutral Zone Start | 316 |
Defensive Zone Start | 384 |
Puck Time | |
---|---|
With Puck | 30 |
Without Puck | 29 |
Faceoffs | |
---|---|
Faceoffs Won | 610 |
Faceoffs Lost | 607 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 10.8 | 9.57 |
2nd Period | 23.0 | 20.31 |
3rd Period | 34.7 | 30.68 |
Overtime | 34.9 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.9 | 0.64 |
2nd Period | 2.0 | 1.65 |
3rd Period | 3.4 | 2.67 |
Overtime | 3.4 | 2.83 |
Even Strenght Goal | 51 |
---|---|
PP Goal | 21 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 7 | 8 |
Lost | 3 | 1 |
Overtime Lost | 0 | 2 |
PP Attempt | 81 |
---|---|
PP Goal | 21 |
PK Attempt | 28 |
PK Goal Against | 2 |
Home | |
---|---|
Shots For | 34.7 |
Shots Against | 29.6 |
Goals For | 3.4 |
Goals Against | 2.1 |
Hits | 20.9 |
Shots Blocked | 11.4 |
Pim | 5.0 |
Projected Total Cap Hit | 82,023,941$ |
Projected Cap Space | 476,059$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 21,354,290$ |
Players In Salary Cap | 21 |
LTIR Players | 0 |
Avalanche Roster | Pos | Age | Cap Hit | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 | 2030-31 |
---|---|---|---|---|---|---|---|---|---|---|---|
Aaron Ekblad ![]() | D | 26 | 7,500,000$ | 7,500,000$ | 7,500,000$ | 7,500,000$ | |||||
Adin Hill ![]() | G | 26 | 2,175,000$ | 2,175,000$ | |||||||
Brett Pesce ![]() | D | 27 | 4,025,000$ | 4,025,000$ | 4,025,000$ | ||||||
Cal Petersen ![]() | G | 27 | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | |||||
Connor Murphy ![]() | D | 29 | 4,400,000$ | 4,400,000$ | 4,400,000$ | 4,400,000$ | 4,400,000$ | ||||
James Reimer ![]() | G | 34 | 2,250,000$ | 2,250,000$ | |||||||
Jonas Brodin ![]() | D | 29 | 6,000,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | ||
Kevin Stenlund ![]() | C/RW | 26 | 750,000$ | 750,000$ | |||||||
Kirill Marchenko ![]() | RW | 22 | 1,562,500$ | 1,562,500$ | 1,562,500$ | ||||||
Kyle Connor ![]() | LW | 25 | 7,142,857$ | 7,142,857$ | 7,142,857$ | 7,142,857$ | 7,142,857$ | ||||
Marcus Foligno ![]() | LW/RW | 31 | 3,100,000$ | 3,100,000$ | |||||||
Mason Appleton ![]() | RW | 26 | 2,166,667$ | 2,166,667$ | 2,166,667$ | 2,166,667$ | |||||
Ondrej Palat ![]() | LW/RW | 31 | 6,000,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | ||
Ryan Graves ![]() | D | 27 | 3,166,667$ | 3,166,667$ | |||||||
Ryan Strome ![]() | C/RW | 29 | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | |||
Sam Steel ![]() | C/LW | 24 | 825,000$ | 825,000$ | |||||||
Sebastian Aho ![]() | C | 25 | 8,460,250$ | 8,460,250$ | 8,460,250$ | ||||||
Teuvo Teravainen ![]() | LW/RW | 28 | 5,400,000$ | 5,400,000$ | 5,400,000$ | ||||||
Timothy Liljegren ![]() | D | 23 | 1,400,000$ | 1,400,000$ | |||||||
Troy Terry ![]() | C/RW | 25 | 1,450,000$ | 1,450,000$ | |||||||
Viktor Arvidsson ![]() | LW/RW | 29 | 4,250,000$ | 4,250,000$ | 4,250,000$ |
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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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | -1 | 0 | 0.000 | 2 | 4 | 6 | 0 | 0 | 1 | 1 | 0 | 0 | 44 | 16 | 16 | 12 | 0 | 32 | 11 | 2 | 22 | 2 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 21 | 12 | 22 | 8 | 16 | 7 | 40.0% | 4.5% | 90.6% | 95.2 | Unlucky | |
2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 0 | 1 | 2 | 0 | 33 | 17 | 7 | 9 | 0 | 26 | 18 | 2 | 15 | 5 | 2 | 40.00% | 1 | 1 | 0.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 22 | 12 | 19 | 8 | 18 | 9 | 50.0% | 9.1% | 92.3% | 101.4 | LUCKY | |
3 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 4 | 5 | -1 | 2 | 0.500 | 4 | 6 | 10 | 0 | 0 | 0 | 3 | 1 | 0 | 77 | 28 | 28 | 21 | 0 | 55 | 16 | 7 | 37 | 11 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 46 | 26 | 39 | 17 | 34 | 18 | 44.4% | 5.2% | 90.9% | 96.1 | Unlucky | |
4 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 1 | 5 | 2 | 1.000 | 6 | 10 | 16 | 0 | 0 | 3 | 1 | 2 | 0 | 37 | 12 | 12 | 13 | 0 | 23 | 8 | 16 | 11 | 3 | 2 | 66.67% | 4 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 23 | 13 | 18 | 8 | 18 | 8 | 80.0% | 16.2% | 95.7% | 111.9 | LUCKY | |
5 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 4 | -2 | 0 | 0.000 | 2 | 4 | 6 | 0 | 0 | 1 | 1 | 0 | 0 | 42 | 10 | 10 | 22 | 0 | 38 | 16 | 2 | 14 | 4 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 22 | 14 | 20 | 8 | 16 | 8 | 33.3% | 4.8% | 89.5% | 94.2 | Unlucky | |
6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 3 | 2 | 2 | 1.000 | 5 | 7 | 12 | 0 | 0 | 0 | 3 | 2 | 0 | 36 | 9 | 15 | 12 | 0 | 27 | 17 | 9 | 24 | 5 | 2 | 40.00% | 2 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 21 | 12 | 20 | 9 | 17 | 8 | 50.0% | 13.9% | 88.9% | 102.8 | FUN | |
7 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 3 | 2 | 1.000 | 3 | 5 | 8 | 0 | 1 | 1 | 1 | 1 | 0 | 30 | 10 | 14 | 6 | 0 | 36 | 15 | 0 | 18 | 2 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 19 | 11 | 21 | 9 | 18 | 9 | 100.0% | 10.0% | 100.0% | 110.0 | LUCKY | |
8 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 2 | 2 | 2 | 1.000 | 4 | 7 | 11 | 0 | 0 | 0 | 1 | 3 | 0 | 34 | 12 | 6 | 16 | 0 | 30 | 12 | 2 | 16 | 4 | 3 | 75.00% | 1 | 1 | 0.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 20 | 11 | 22 | 8 | 17 | 8 | 50.0% | 11.8% | 93.3% | 105.1 | LUCKY | |
9 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 4 | 1 | 2 | 1.000 | 5 | 8 | 13 | 0 | 0 | 4 | 0 | 1 | 0 | 34 | 17 | 9 | 8 | 0 | 41 | 11 | 4 | 16 | 2 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 21 | 13 | 21 | 8 | 17 | 7 | 55.6% | 14.7% | 90.2% | 104.9 | FUN | |
10 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 3 | 2 | 2 | 1.000 | 5 | 8 | 13 | 0 | 0 | 0 | 2 | 3 | 0 | 31 | 6 | 13 | 12 | 0 | 22 | 13 | 7 | 22 | 5 | 1 | 20.00% | 1 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 21 | 11 | 19 | 8 | 18 | 10 | 57.1% | 16.1% | 86.4% | 102.5 | FUN | |
11 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 2 | -1 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 1 | 0 | 0 | 31 | 13 | 7 | 11 | 0 | 26 | 10 | 0 | 18 | 7 | 1 | 14.29% | 0 | 0 | 0.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 21 | 12 | 20 | 9 | 17 | 9 | 0.0% | 3.2% | 92.3% | 95.5 | DULL | |
12 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 2 | -1 | 1 | 0.500 | 1 | 2 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 30 | 12 | 11 | 7 | 3 | 24 | 9 | 0 | 23 | 6 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 23 | 13 | 19 | 9 | 21 | 11 | 33.3% | 3.3% | 91.7% | 95.0 | DULL | |
13 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 0 | 1 | 2 | 0 | 36 | 9 | 17 | 10 | 0 | 24 | 10 | 2 | 28 | 5 | 1 | 20.00% | 1 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 21 | 12 | 20 | 9 | 17 | 9 | 66.7% | 8.3% | 95.8% | 104.2 | DULL | |
14 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 2 | 2 | 2 | 1.000 | 4 | 5 | 9 | 0 | 0 | 0 | 0 | 4 | 0 | 32 | 7 | 8 | 17 | 0 | 39 | 19 | 5 | 18 | 3 | 2 | 66.67% | 0 | 0 | 0.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 20 | 10 | 22 | 8 | 17 | 8 | 50.0% | 12.5% | 94.9% | 107.4 | LUCKY | |
15 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 4 | 2 | 1.000 | 5 | 9 | 14 | 0 | 0 | 2 | 2 | 1 | 0 | 32 | 9 | 15 | 8 | 0 | 17 | 7 | 14 | 30 | 4 | 2 | 50.00% | 2 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 24 | 13 | 18 | 9 | 17 | 8 | 75.0% | 15.6% | 94.1% | 109.7 | LUCKY | |
16 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 3 | 1 | 2 | 1.000 | 4 | 7 | 11 | 0 | 0 | 0 | 1 | 3 | 0 | 40 | 8 | 10 | 22 | 0 | 40 | 12 | 11 | 20 | 1 | 1 | 100.00% | 3 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 19 | 11 | 23 | 9 | 17 | 8 | 50.0% | 10.0% | 92.5% | 102.5 | LUCKY | |
17 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 | 3 | -1 | 1 | 0.500 | 2 | 2 | 4 | 0 | 0 | 0 | 1 | 1 | 0 | 21 | 2 | 12 | 7 | 0 | 35 | 4 | 6 | 28 | 2 | 1 | 50.00% | 3 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 21 | 11 | 20 | 8 | 18 | 9 | 25.0% | 9.5% | 91.4% | 101.0 | LUCKY | |
18 | 3 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 13 | 4 | 9 | 6 | 1.000 | 13 | 21 | 34 | 0 | 0 | 5 | 3 | 5 | 0 | 109 | 30 | 45 | 34 | 0 | 87 | 31 | 15 | 79 | 10 | 3 | 30.00% | 5 | 0 | 100.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 69 | 42 | 59 | 26 | 51 | 26 | 71.4% | 11.9% | 95.4% | 107.3 | LUCKY | |
_Vs Division | 6 | 4 | 2 | 0 | 0 | 0 | 0 | 0 | 18 | 14 | 4 | 8 | 0.667 | 18 | 27 | 45 | 0 | 0 | 0 | 8 | 10 | 0 | 210 | 69 | 64 | 77 | 0 | 177 | 74 | 23 | 113 | 30 | 8 | 26.67% | 4 | 1 | 75.00% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 130 | 75 | 125 | 53 | 104 | 54 | 43.5% | 8.6% | 92.1% | 100.7 | DULL | |
_Vs Conference | 15 | 9 | 4 | 0 | 0 | 1 | 0 | 1 | 47 | 36 | 11 | 20 | 0.667 | 47 | 75 | 122 | 0 | 0 | 8 | 17 | 22 | 0 | 527 | 153 | 181 | 193 | 3 | 455 | 170 | 66 | 321 | 60 | 14 | 23.33% | 18 | 1 | 94.44% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 328 | 192 | 311 | 132 | 264 | 136 | 48.5% | 8.9% | 92.1% | 101.0 | Unlucky | |
_Since Last GM Reset | 21 | 15 | 4 | 0 | 0 | 1 | 0 | 1 | 72 | 45 | 27 | 32 | 0.762 | 72 | 117 | 189 | 0 | 1 | 18 | 23 | 31 | 0 | 729 | 227 | 255 | 247 | 3 | 622 | 239 | 104 | 439 | 81 | 21 | 25.93% | 28 | 2 | 92.86% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 461 | 269 | 431 | 186 | 371 | 189 | 54.3% | 9.9% | 92.8% | 102.6 | LUCKY | |
Total | 21 | 15 | 4 | 0 | 0 | 1 | 0 | 1 | 72 | 45 | 27 | 32 | 0.762 | 72 | 117 | 189 | 0 | 1 | 18 | 23 | 31 | 0 | 729 | 227 | 255 | 247 | 3 | 622 | 239 | 104 | 439 | 81 | 21 | 25.93% | 28 | 2 | 92.86% | 0 | 256 | 517 | 49.52% | 194 | 384 | 50.52% | 160 | 316 | 50.63% | 461 | 269 | 431 | 186 | 371 | 189 | 54.3% | 9.9% | 92.8% | 102.6 | LUCKY |
Puck Time | |
---|---|
Offensive Zone | 21 |
Neutral Zone | 17 |
Defensive Zone | 20 |
Puck Time | |
---|---|
Offensive Zone Start | 517 |
Neutral Zone Start | 316 |
Defensive Zone Start | 384 |
Puck Time | |
---|---|
With Puck | 30 |
Without Puck | 29 |
Faceoffs | |
---|---|
Faceoffs Won | 610 |
Faceoffs Lost | 607 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 10.8 | 9.57 |
2nd Period | 23.0 | 20.31 |
3rd Period | 34.7 | 30.68 |
Overtime | 34.9 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.9 | 0.64 |
2nd Period | 2.0 | 1.65 |
3rd Period | 3.4 | 2.67 |
Overtime | 3.4 | 2.83 |
Even Strenght Goal | 51 |
---|---|
PP Goal | 21 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 7 | 8 |
Lost | 3 | 1 |
Overtime Lost | 0 | 2 |
PP Attempt | 81 |
---|---|
PP Goal | 21 |
PK Attempt | 28 |
PK Goal Against | 2 |
Home | |
---|---|
Shots For | 34.7 |
Shots Against | 29.6 |
Goals For | 3.4 |
Goals Against | 2.1 |
Hits | 20.9 |
Shots Blocked | 11.4 |
Pim | 5.0 |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
82,023,941$ | 0$ | 82,023,941$ | 476,059$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | Ball Arena | |
City | Colorado | ||
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 | 57389 | 47820 | 18771 | 37414 | 9506 |
Attendance PCT | 95.65% | 95.64% | 93.86% | 93.54% | 95.06% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
31 | 17090 - 94.94% | 617,184$ | 6,171,835$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
82,023,941$ | 82,023,941$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
21,354,290$ | 82,023,941$ | 21,354,290$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
19,132,688$ | 142 | 427,208$ | 60,663,536$ |
Team Total Estimate | |||
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Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
63,584,719$ | 82,023,941$ | -499,710,791$ | -544,162,822$ |
Left Wing | Center | Right Wing | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Defense #1 | Defense #2 | Goalie | |||||||||||||||||||||||||||||||||
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Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
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2024 | |||||||
2025 | |||||||
2026 | |||||||
2027 | |||||||
2028 |
Priority | Type | Description |
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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 col 2023 | |||||
ALexei Lipanov | |||||
Aatu Jamsen | 2020 | 192 | |||
Adam Ollas Mattson | |||||
Adam Sykora | 2022 | 42 | |||
Alexander Peters | |||||
Andrew Nielsen | |||||
Arno Tiefensee | 2023 | 152 | |||
Axel Andersson | 2018 | 56 | |||
Benjamin Baumgartner | 2020 | 161 | |||
Blake Hillman | |||||
Bobby Brink | Link | ||||
Brad Morrison | |||||
Brandon Saigeon | 2018 | 155 | |||
Brennan Menell | |||||
Brett Stapley | 2018 | 202 | |||
Brock Faber | 2020 | 68 | |||
Brody Lamb | 2021 | 114 | |||
Carson Latimer | 2021 | 131 | |||
Carter Mazur | 2021 | 68 | |||
Chad Krys | 2016 | 62 | |||
Colby Barlow | 2023 | 13 | |||
Cole Knuble | 2023 | 119 | |||
Cole Spicer | 2022 | 119 | |||
Connor Kelley | 2021 | 210 | |||
Connor Levis | 2023 | 199 | |||
Danil Karpovich | 2023 | 185 | |||
David Tendeck | 2018 | 169 | |||
Deamont Hunt | 2020 | 75 | |||
Domenick Fensore | 2019 | 96 | |||
Dominik Masin | |||||
Drew Fortescue | 2023 | 99 | |||
Eetu Liukas | 2021 | 162 | |||
Ethan Bowen | 2020 | 207 | |||
Fabian Lysell | 2021 | 20 | |||
Felix Nilsson | 2023 | 56 | |||
Filip Lindberg | 2019 | 204 | |||
Francesco Pinelli | 2021 | 34 | |||
Ian McCoshen | |||||
Isak Rosen | 2021 | 22 | |||
Jack Devine | 2022 | 223 | |||
Jack Gorniak | 2018 | 140 | |||
Jakub Vondras | 2022 | 171 | |||
James Clark | 2023 | 216 | |||
Jared Wright | 2022 | 168 | |||
Jaroslav Chmelar | 2021 | 152 | |||
John Farinacci | 2019 | 90 | |||
Josef Korenar | Link | ||||
Josh Anderson | 2016 | 91 | |||
Josh Davies | 2022 | 183 | |||
Josh Ho Sang | |||||
Karel Plasek | 2019 | 183 | |||
Kasper Puutio | 2020 | 155 | |||
Kirill Tankov | 2021 | 220 | |||
Leevi Aaltonen | 2019 | 142 | |||
Linus Sjodin | 2022 | 215 | |||
Logan Stankoven | 2021 | 39 | |||
Mackie Samoskevich | 2021 | 33 | |||
Manix Landry | 2021 | 146 | |||
Marcus Hogberg | Link | ||||
Maskim Zukhov | |||||
Matt Copponi | 2023 | 204 | |||
Nate Thompson | Link | ||||
Nicholas Boka | |||||
Nicholas Porco | 2019 | 154 | |||
Nikita Quapp | 2021 | 195 | |||
Nils Juntorp | 2022 | 192 | |||
Noah Ellis | 2020 | 186 | |||
Noel Gunler | 2020 | 52 | |||
Nolan Collins | 2022 | 173 | |||
Oliver Tarnstrom | 2020 | 103 | |||
Petr Kvaca | |||||
Philip Svedeback | 2021 | 126 | |||
Ryan Conmy | 2023 | 195 | |||
Ryan Hofer | 2022 | 172 | |||
Ryan Lohin | 2016 | 210 | |||
Ryan Murphy | Link | ||||
Seamus Casey | 2022 | 41 | |||
Sebastian Aho | Link | ||||
Sergei Ivanov | 2022 | 151 | |||
Thomas Milic | 2023 | 115 | |||
Timur Ibragimov | 2019 | 173 | |||
Tomas Machu | 2021 | 222 | |||
Trenton Bourque | |||||
Ty Voit (C/LW) | 2021 | 158 | |||
Ty Young | 2022 | 136 | |||
Tyler Muszelik | 2022 | 122 | |||
Viktor Neuchev | 2022 | 87 | |||
Warren Clark | 2023 | 184 | |||
Will Cranley | 2020 | 163 | |||
William Stromgren | 2021 | 50 | |||
William Wallinder | 2020 | 33 | |||
Zakary Karpa | 2022 | 198 |
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