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Caroline Hurricanes Team Overall:71 0-0-0, 0pts · 10th in Conférence Pat Burns |
# | Player | Position | Height | Weight | Age | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | Overall | Condition | Contract | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Scratches | ||||||||||||||||||||||||||
0 | ![]() | C | 6' 3" | 208 | 25 | 73 | 40 | 86 | 75 | 80 | 84 | 89 | 82 | 81 | 85 | 86 | 65 | 80 | 70 | 67 | 0 | 40 | 82 | 100.00 | 11,640,250$/3yrs | |
0 | ![]() | C/LW | 6' 1" | 216 | 32 | 76 | 40 | 81 | 78 | 88 | 78 | 93 | 78 | 90 | 84 | 78 | 68 | 57 | 88 | 93 | 0 | 40 | 81 | 100.00 | 11,000,000$/3yrs | |
0 | ![]() | C | 6' 3" | 195 | 36 | 71 | 40 | 72 | 76 | 74 | 80 | 84 | 78 | 76 | 88 | 74 | 65 | 74 | 89 | 61 | 0 | 40 | 79 | 100.00 | 6,100,000$/3yrs | |
0 | ![]() | C/LW | 6' 1" | 191 | 26 | 69 | 40 | 89 | 76 | 74 | 74 | 89 | 75 | 51 | 78 | 85 | 73 | 58 | 71 | 59 | 0 | 40 | 79 | 100.00 | 5,000,000$/3yrs | |
0 | ![]() | LW/RW | 6' 5" | 205 | 24 | 66 | 40 | 85 | 80 | 76 | 81 | 78 | 77 | 54 | 84 | 78 | 71 | 92 | 69 | 59 | 0 | 40 | 79 | 100.00 | 8,700,000$/3yrs | |
0 | ![]() | C/LW | 6' 4" | 214 | 24 | 73 | 64 | 65 | 79 | 82 | 80 | 89 | 75 | 76 | 82 | 76 | 67 | 91 | 68 | 59 | 0 | 40 | 78 | 100.00 | 6,000,000$/3yrs | |
0 | ![]() | LW/RW | 6' 1" | 185 | 31 | 71 | 40 | 88 | 77 | 71 | 76 | 87 | 71 | 54 | 79 | 76 | 71 | 70 | 79 | 72 | 0 | 40 | 77 | 100.00 | 5,000,000$/3yrs | |
0 | ![]() | C | 6' 2" | 204 | 23 | 71 | 40 | 83 | 81 | 80 | 70 | 86 | 69 | 62 | 77 | 73 | 67 | 54 | 65 | 59 | 0 | 40 | 75 | 100.00 | 2,300,000$/3yrs | |
0 | ![]() | LW/RW | 5' 11" | 195 | 38 | 76 | 40 | 85 | 66 | 79 | 74 | 92 | 64 | 56 | 72 | 71 | 74 | 59 | 94 | 79 | 0 | 40 | 74 | 100.00 | 3,034,500$/2yrs | |
0 | ![]() | C/LW/RW | 6' 0" | 196 | 30 | 80 | 64 | 74 | 66 | 78 | 73 | 89 | 64 | 66 | 76 | 66 | 75 | 54 | 72 | 68 | 0 | 40 | 73 | 100.00 | 1,800,000$/3yrs | |
0 | ![]() | C/LW | 6' 2" | 201 | 25 | 81 | 64 | 81 | 67 | 78 | 71 | 91 | 62 | 57 | 72 | 66 | 78 | 54 | 61 | 58 | 0 | 40 | 72 | 100.00 | 725,000$/2yrs | |
0 | ![]() | LW/RW | 6' 0" | 187 | 28 | 75 | 64 | 88 | 68 | 74 | 66 | 86 | 60 | 53 | 70 | 66 | 81 | 61 | 70 | 59 | 0 | 40 | 71 | 100.00 | 1,350,000$/2yrs | |
0 | ![]() | C/RW | 6' 0" | 186 | 26 | 70 | 68 | 85 | 71 | 73 | 70 | 80 | 62 | 79 | 78 | 59 | 79 | 54 | 60 | 58 | 0 | 40 | 71 | 100.00 | 1,700,000$/3yrs | |
0 | ![]() | RW | 6' 2" | 217 | 25 | 88 | 74 | 83 | 68 | 87 | 63 | 92 | 60 | 55 | 72 | 63 | 76 | 54 | 60 | 58 | 0 | 40 | 71 | 100.00 | 725,000$/2yrs | |
0 | ![]() | LW | 6' 1" | 215 | 26 | 89 | 81 | 72 | 67 | 87 | 59 | 77 | 58 | 56 | 72 | 59 | 68 | 54 | 63 | 59 | 0 | 40 | 69 | 100.00 | 2,750,000$/2yrs | |
0 | ![]() | RW | 6' 4" | 224 | 24 | 74 | 41 | 90 | 73 | 86 | 55 | 76 | 60 | 53 | 69 | 66 | 68 | 54 | 59 | 58 | 0 | 40 | 69 | 100.00 | 800,000$/3yrs | |
0 | ![]() | C/RW | 6' 2" | 200 | 22 | 72 | 42 | 85 | 71 | 76 | 59 | 77 | 59 | 79 | 71 | 59 | 69 | 54 | 58 | 57 | 0 | 40 | 68 | 100.00 | 1,050,833$/3yrs | |
0 | ![]() | RW | 5' 7" | 191 | 23 | 57 | 58 | 68 | 64 | 60 | 66 | 63 | 64 | 54 | 63 | 64 | 60 | 64 | 58 | 55 | 0 | 40 | 64 | 100.00 | 750,000$/3yrs | |
0 | ![]() | RW | 6' 2" | 194 | 20 | 57 | 59 | 64 | 62 | 65 | 68 | 64 | 62 | 55 | 62 | 63 | 61 | 56 | 54 | 53 | 0 | 40 | 64 | 100.00 | 925,000$/1yrs | |
0 | ![]() | LW | 6' 6" | 230 | 24 | 56 | 59 | 62 | 60 | 77 | 66 | 65 | 59 | 55 | 57 | 61 | 65 | 54 | 60 | 56 | 0 | 40 | 63 | 100.00 | 995,833$/2yrs | |
0 | ![]() | C/RW | 5' 11" | 170 | 27 | 54 | 61 | 67 | 63 | 57 | 67 | 65 | 61 | 55 | 59 | 61 | 57 | 54 | 66 | 59 | 0 | 40 | 62 | 100.00 | 750,000$/3yrs | |
0 | ![]() | LW/RW | 6' 2" | 195 | 22 | 56 | 53 | 67 | 60 | 65 | 65 | 63 | 57 | 55 | 57 | 58 | 58 | 54 | 57 | 54 | 0 | 40 | 61 | 100.00 | 1,208,333$/1yrs | |
0 | ![]() | C | 5' 10" | 185 | 21 | 55 | 55 | 66 | 57 | 60 | 63 | 61 | 56 | 70 | 55 | 58 | 59 | 54 | 55 | 53 | 0 | 40 | 59 | 100.00 | 875,000$/2yrs | |
0 | ![]() | C/RW | 5' 11" | 185 | 22 | 55 | 54 | 67 | 55 | 60 | 56 | 56 | 55 | 70 | 55 | 56 | 60 | 57 | 57 | 54 | 0 | 40 | 58 | 100.00 | 910,833$/1yrs | |
0 | ![]() | D | 6' 2" | 193 | 28 | 66 | 65 | 78 | 95 | 74 | 94 | 79 | 70 | 40 | 85 | 66 | 86 | 61 | 69 | 59 | 0 | 40 | 81 | 100.00 | 4,875,000$/1yrs | |
0 | ![]() | D | 5' 11" | 180 | 26 | 65 | 66 | 83 | 87 | 71 | 88 | 82 | 68 | 40 | 79 | 65 | 73 | 58 | 65 | 59 | 0 | 40 | 76 | 100.00 | 5,000,000$/1yrs | |
0 | ![]() | D | 6' 2" | 199 | 23 | 83 | 64 | 82 | 75 | 77 | 83 | 88 | 60 | 40 | 72 | 62 | 88 | 54 | 59 | 58 | 0 | 40 | 75 | 100.00 | 880,000$/3yrs | |
0 | ![]() | D | 6' 2" | 216 | 28 | 76 | 40 | 88 | 73 | 86 | 86 | 90 | 62 | 40 | 75 | 60 | 83 | 54 | 68 | 59 | 0 | 40 | 75 | 100.00 | 6,150,000$/3yrs | |
0 | ![]() | D | 6' 0" | 195 | 23 | 73 | 66 | 77 | 71 | 78 | 83 | 83 | 67 | 40 | 77 | 64 | 83 | 54 | 58 | 58 | 0 | 40 | 75 | 100.00 | 1,700,000$/3yrs | |
0 | ![]() | D | 6' 1" | 200 | 32 | 76 | 64 | 72 | 67 | 79 | 80 | 84 | 61 | 40 | 74 | 62 | 86 | 54 | 80 | 66 | 0 | 40 | 74 | 100.00 | 3,000,000$/1yrs | |
0 | ![]() | D | 6' 0" | 204 | 30 | 75 | 66 | 78 | 88 | 83 | 70 | 73 | 55 | 40 | 68 | 57 | 85 | 54 | 61 | 58 | 0 | 40 | 72 | 100.00 | 2,250,000$/2yrs | |
0 | ![]() | D | 6' 2" | 210 | 27 | 78 | 40 | 74 | 60 | 83 | 72 | 75 | 57 | 40 | 72 | 59 | 82 | 54 | 65 | 59 | 0 | 40 | 71 | 100.00 | 800,000$/2yrs | |
0 | ![]() | D | 6' 5" | 229 | 27 | 85 | 73 | 91 | 60 | 95 | 79 | 74 | 60 | 35 | 70 | 60 | 63 | 51 | 67 | 69 | 0 | 40 | 70 | 100.00 | 750,000$/3yrs | |
0 | ![]() | D | 6' 2" | 186 | 23 | 69 | 40 | 77 | 65 | 70 | 69 | 71 | 58 | 40 | 74 | 58 | 76 | 54 | 58 | 58 | 0 | 40 | 69 | 100.00 | 850,000$/3yrs | |
0 | ![]() | D | 6' 0" | 193 | 23 | 59 | 51 | 72 | 63 | 66 | 66 | 61 | 58 | 40 | 63 | 57 | 65 | 54 | 58 | 56 | 0 | 40 | 63 | 100.00 | 925,000$/1yrs | |
0 | ![]() | D | 6' 1" | 190 | 24 | 55 | 55 | 65 | 60 | 63 | 67 | 65 | 59 | 40 | 59 | 57 | 61 | 54 | 61 | 56 | 0 | 40 | 62 | 100.00 | 750,000$/3yrs | |
0 | ![]() | D | 6' 6" | 240 | 24 | 57 | 54 | 59 | 60 | 77 | 68 | 67 | 58 | 40 | 58 | 55 | 62 | 54 | 61 | 56 | 0 | 40 | 62 | 100.00 | 750,000$/3yrs | |
0 | ![]() | D | 6' 4" | 215 | 27 | 56 | 55 | 64 | 58 | 71 | 66 | 64 | 56 | 40 | 56 | 55 | 61 | 54 | 65 | 59 | 0 | 40 | 61 | 100.00 | 762,500$/1yrs | |
0 | ![]() | D | 6' 4" | 208 | 22 | 57 | 54 | 63 | 60 | 69 | 65 | 63 | 57 | 40 | 57 | 56 | 61 | 54 | 57 | 54 | 0 | 40 | 61 | 100.00 | 894,167$/1yrs |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | Goalie | Height | Weight | Age | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | Overall | Condition | Contract |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Scratches | ||||||||||||||||||||||||
0 | ![]() | 6' 4" | 224 | 26 | 71 | 89 | 89 | 69 | 85 | 86 | 60 | 55 | 0 | 40 | 80 | 100.00 | 925,000$/1yrs | |||||||
0 | ![]() | 6' 5" | 209 | 25 | 76 | 72 | 71 | 81 | 80 | 71 | 58 | 56 | 0 | 40 | 78 | 100.00 | 750,000$/2yrs | |||||||
0 | ![]() | 6' 2" | 190 | 27 | 78 | 67 | 65 | 73 | 85 | 91 | 59 | 55 | 0 | 40 | 78 | 100.00 | 800,000$/2yrs | |||||||
0 | ![]() | 6' 2" | 174 | 22 | 59 | 65 | 64 | 65 | 72 | 69 | 56 | 53 | 0 | 40 | 67 | 100.00 | 910,833$/1yrs | |||||||
0 | ![]() | 6' 4" | 205 | 21 | 54 | 54 | 54 | 54 | 54 | 54 | 54 | 54 | 0 | 40 | 54 | 100.00 | 925,000$/2yrs |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Mike Sullivan | 84 | 90 | 91 | 87 | 81 | 75 | 68 | USA | 54 | 1 | 525,000$ |
General Manager | Richard Proulx |
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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 |
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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 |
# | 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 |
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Projected Total Cap Hit | 0$ |
Projected Cap Space | 91,500,000$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 0$ |
Players In Salary Cap | 44 |
LTIR Players | 0 |
Player Name | Pos | Age | Cap Hit | 2022-2023 | 2023-2024 | 2024-2025 | 2025-2026 | 2026-2027 | 2027-2028 | 2028-2029 | 2029-2030 |
---|---|---|---|---|---|---|---|---|---|---|---|
Akil Thomas ![]() | C/RW | 22 | 910,833$ | 910,833$ | |||||||
Alec Regula ![]() | D | 22 | 894,167$ | 894,167$ | |||||||
Auston Matthews ![]() | C | 25 | 11,640,250$ | 11,640,250$ | 11,640,250$ | 11,640,250$ | |||||
Ben Gleason ![]() | D | 24 | 750,000$ | 750,000$ | 750,000$ | 750,000$ | |||||
Brendan Lemieux ![]() | LW | 26 | 2,750,000$ | 2,750,000$ | 2,750,000$ | ||||||
Brock McGinn ![]() | LW/RW | 28 | 1,350,000$ | 1,350,000$ | 1,350,000$ | ||||||
Carl Dahlstrom ![]() | D | 27 | 750,000$ | 750,000$ | 750,000$ | 750,000$ | |||||
Dan Vladar ![]() | C | 25 | 750,000$ | 750,000$ | 750,000$ | ||||||
Dillon Heatherington ![]() | D | 27 | 762,500$ | 762,500$ | |||||||
Dylan Sikura ![]() | C/RW | 27 | 750,000$ | 750,000$ | 750,000$ | 750,000$ | |||||
Evgeni Malkin ![]() | C | 36 | 6,100,000$ | 6,100,000$ | 6,100,000$ | 6,100,000$ | |||||
Filip Chytil ![]() | C | 23 | 2,300,000$ | 2,300,000$ | 2,300,000$ | 2,300,000$ | |||||
Gustav Lindstrom ![]() | D | 23 | 850,000$ | 850,000$ | 850,000$ | 850,000$ | |||||
Jake Christiansen ![]() | D | 23 | 925,000$ | 925,000$ | |||||||
Jake Evans ![]() | C/RW | 26 | 1,700,000$ | 1,700,000$ | 1,700,000$ | 1,700,000$ | |||||
Jared McCann ![]() | C/LW | 26 | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | |||||
John Tavares ![]() | C/LW | 32 | 11,000,000$ | 11,000,000$ | 11,000,000$ | 11,000,000$ | |||||
Jordan Martinook ![]() | C/LW/RW | 30 | 1,800,000$ | 1,800,000$ | 1,800,000$ | 1,800,000$ | |||||
Julien Gauthier ![]() | RW | 24 | 800,000$ | 800,000$ | 800,000$ | 800,000$ | |||||
Karel Vejmelka ![]() | D | 26 | 925,000$ | 925,000$ | |||||||
Keaton Middleton ![]() | D | 24 | 750,000$ | 750,000$ | 750,000$ | 750,000$ | |||||
Keean Washkurak ![]() | C | 21 | 875,000$ | 875,000$ | 875,000$ | ||||||
Keegan Kolesar ![]() | RW | 25 | 725,000$ | 725,000$ | 725,000$ | ||||||
Kevin Lankinen ![]() | D | 27 | 800,000$ | 800,000$ | 800,000$ | ||||||
Lukas Dostal ![]() | C/LW | 22 | 910,833$ | 910,833$ | |||||||
Martin Fehervary ![]() | D | 23 | 880,000$ | 880,000$ | 880,000$ | 880,000$ | |||||
Mike Matheson ![]() | D | 28 | 4,875,000$ | 4,875,000$ | |||||||
Nico Daws ![]() | D | 21 | 925,000$ | 925,000$ | 925,000$ | ||||||
Patrik Laine ![]() | LW/RW | 24 | 8,700,000$ | 8,700,000$ | 8,700,000$ | 8,700,000$ | |||||
Pierre-Luc Dubois ![]() | C/LW | 24 | 6,000,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | |||||
Radim Simek ![]() | D | 30 | 2,250,000$ | 2,250,000$ | 2,250,000$ | ||||||
Rasmus Kupari ![]() | C/RW | 22 | 1,050,833$ | 1,050,833$ | 1,050,833$ | 1,050,833$ | |||||
Reilly Smith ![]() | LW/RW | 31 | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | |||||
Riley Tufte ![]() | LW | 24 | 995,833$ | 995,833$ | 995,833$ | ||||||
Robert Hagg ![]() | D | 27 | 800,000$ | 800,000$ | 800,000$ | ||||||
Ryan Pulock ![]() | D | 28 | 6,150,000$ | 6,150,000$ | 6,150,000$ | 6,150,000$ | |||||
Sampo Ranta ![]() | LW/RW | 22 | 1,208,333$ | 1,208,333$ | |||||||
Sean Durzi ![]() | D | 23 | 1,700,000$ | 1,700,000$ | 1,700,000$ | 1,700,000$ | |||||
Tony DeAngelo ![]() | D | 26 | 5,000,000$ | 5,000,000$ | |||||||
Travis Hamonic ![]() | D | 32 | 3,000,000$ | 3,000,000$ | |||||||
Trey Fix-Wolansky ![]() | RW | 23 | 750,000$ | 750,000$ | 750,000$ | 750,000$ | |||||
Tyson Foerster ![]() | RW | 20 | 925,000$ | 925,000$ | |||||||
Yakov Trenin ![]() | C/LW | 25 | 725,000$ | 725,000$ | 725,000$ | ||||||
Zach Parise ![]() | LW/RW | 38 | 1,500,000$ | 1,500,000$ | 1,500,000$ |
Forward Lines | |||||||
---|---|---|---|---|---|---|---|
Defensive Pairings | |||||||
---|---|---|---|---|---|---|---|
1st Power Play Unit | |||||||
---|---|---|---|---|---|---|---|
2nd Power Play Unit | |||||||
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Goalies | |||||||
---|---|---|---|---|---|---|---|
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Total | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.000 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0 | nan% | nan% | nan% | nan | Unlucky |
Puck Time | |
---|---|
Offensive Zone | NAN |
Neutral Zone | NAN |
Defensive Zone | NAN |
Puck Time | |
---|---|
Offensive Zone Start | 0 |
Neutral Zone Start | 0 |
Defensive Zone Start | 0 |
Puck Time | |
---|---|
With Puck | NAN |
Without Puck | NAN |
Faceoffs | |
---|---|
Faceoffs Won | 0 |
Faceoffs Lost | 0 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | nan | 9.57 |
2nd Period | nan | 20.31 |
3rd Period | nan | 30.68 |
Overtime | nan | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | nan | 0.64 |
2nd Period | nan | 1.65 |
3rd Period | nan | 2.67 |
Overtime | nan | 2.83 |
Even Strenght Goal | 0 |
---|---|
PP Goal | 0 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 0 | 0 |
Lost | 0 | 0 |
Overtime Lost | 0 | 0 |
PP Attempt | 0 |
---|---|
PP Goal | 0 |
PK Attempt | 0 |
PK Goal Against | 0 |
Home | |
---|---|
Shots For | nan |
Shots Against | nan |
Goals For | nan |
Goals Against | nan |
Hits | nan |
Shots Blocked | nan |
Pim | nan |
Date | Matchup | Result | Detail | ||
---|---|---|---|---|---|
2023-10-14 | @ | ||||
2023-10-15 | @ | ||||
2023-10-16 | @ | ||||
2023-10-17 | @ | ||||
2023-10-18 | @ | ||||
2023-10-20 | @ | ||||
2023-10-21 | @ | ||||
2023-10-22 | @ | ||||
2023-10-23 | @ | ||||
2023-10-26 | @ |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
107,516,082$ | 0$ | 0$ | 91,500,000$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | PNC Arena | |
City | Caroline | ||
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 | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
Attendance PCT | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
Income | |||||
---|---|---|---|---|---|
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
5 | 0 - 0.00% | 0$ | 0$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
107,516,082$ | 109,050,582$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
0$ | 0$ | 0$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 15 | 0$ | 0$ |
Team Total Estimate | |||
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Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
0$ | 0$ | 8,750,000$ | 8,750,000$ |
FOWARD | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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DEFENSE | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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GOALIE | ||||||||||||||||||||||||||||||
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Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
---|---|---|---|---|---|---|---|
2024 | |||||||
2025 | |||||||
2026 | |||||||
2027 |
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 |
---|---|---|---|---|---|
Aapeli Rasanen | |||||
Alex Jefferies | |||||
Alexei Kolosov | |||||
Carter Gylander | |||||
Dmitry Kuzmin | |||||
Eamon Powell | |||||
Francisco Pinelli | |||||
Ian Moore | |||||
Jesper Sellgren | |||||
Maxim Groshev | |||||
Patrick Hamrla | |||||
Sasha Mutala | |||||
Trevor Kuntar |
Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
---|---|---|---|---|---|---|---|
2024 | |||||||
2025 | |||||||
2026 | |||||||
2027 |
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 |
---|---|---|---|---|---|
Aapeli Rasanen | |||||
Alex Jefferies | |||||
Alexei Kolosov | |||||
Carter Gylander | |||||
Dmitry Kuzmin | |||||
Eamon Powell | |||||
Francisco Pinelli | |||||
Ian Moore | |||||
Jesper Sellgren | |||||
Maxim Groshev | |||||
Patrick Hamrla | |||||
Sasha Mutala | |||||
Trevor Kuntar |