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Full Scoreboard »» |
Carolina Hurricanes 12-9-5, 29pts · 8th in Eastern |
Player | # | POS | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 10 | LW | 99.00 | 53 | 32 | 90 | 95 | 68 | 88 | 90 | 93 | 56 | 96 | 94 | 56 | 93 | 80 | 88 | 0 | 42 | 98 | 32 | 11,642,579$/3yrs | |||
![]() | 86 | RW | 100.00 | 62 | 32 | 87 | 99 | 70 | 91 | 90 | 89 | 56 | 91 | 95 | 65 | 92 | 77 | 76 | 0 | 42 | 98 | 30 | 9,500,000$/4yrs | |||
![]() | 0 | LW/RW | 100.00 | 67 | 33 | 87 | 79 | 68 | 84 | 89 | 79 | 60 | 79 | 82 | 62 | 80 | 80 | 79 | 0 | 42 | 87 | 32 | 5,000,000$/1yrs | |||
![]() | 0 | C | 100.00 | 68 | 38 | 78 | 75 | 79 | 86 | 90 | 77 | 88 | 77 | 77 | 81 | 77 | 77 | 82 | 0 | 34 | 87 | 30 | 5,000,000$/4yrs | |||
![]() | 25 | C/LW | 100.00 | 61 | 32 | 80 | 79 | 73 | 83 | 90 | 78 | 61 | 78 | 84 | 64 | 81 | 72 | 70 | 0 | 42 | 86 | 28 | 4,166,667$/2yrs | |||
![]() | 80 | C/LW/RW | 100.00 | 70 | 35 | 60 | 80 | 81 | 87 | 89 | 80 | 84 | 80 | 81 | 66 | 81 | 67 | 63 | 0 | 39 | 86 | 25 | 7,250,000$/4yrs | |||
![]() | 0 | C/LW | 100.00 | 65 | 32 | 89 | 67 | 72 | 80 | 90 | 71 | 61 | 77 | 69 | 79 | 70 | 74 | 73 | 0 | 42 | 82 | 29 | 3,500,000$/3yrs | |||
![]() | 91 | LW/RW | 100.00 | 81 | 33 | 95 | 74 | 76 | 73 | 90 | 70 | 60 | 61 | 82 | 65 | 76 | 69 | 68 | 0 | 42 | 81 | 26 | 1,300,000$/1yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 75 | 39 | 76 | 70 | 69 | 77 | 87 | 72 | 75 | 76 | 67 | 68 | 72 | 69 | 71 | 0 | 51 | 80 | 26 | 775,000$/1yrs | |||
![]() | 11 | RW | 100.00 | 69 | 33 | 88 | 68 | 80 | 82 | 90 | 63 | 59 | 61 | 71 | 84 | 67 | 68 | 67 | 0 | 42 | 80 | 25 | 1,000,000$/1yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 66 | 34 | 90 | 72 | 72 | 76 | 79 | 70 | 63 | 74 | 69 | 62 | 70 | 62 | 62 | 0 | 42 | 79 | 22 | 863,333$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 71 | 38 | 78 | 69 | 72 | 74 | 79 | 67 | 42 | 66 | 71 | 64 | 69 | 63 | 65 | 0 | 39 | 77 | 23 | 950,000$/1yrs | |||
![]() | 17 | D | 100.00 | 66 | 32 | 77 | 93 | 74 | 95 | 90 | 83 | 30 | 96 | 50 | 81 | 66 | 69 | 67 | 0 | 32 | 94 | 26 | 4,800,000$/1yrs | |||
![]() | 6 | D | 100.00 | 84 | 36 | 78 | 66 | 84 | 94 | 90 | 73 | 30 | 73 | 67 | 91 | 70 | 77 | 86 | 0 | 42 | 88 | 31 | 4,975,000$/4yrs | |||
![]() | 0 | D | 96.00 | 68 | 34 | 77 | 74 | 87 | 94 | 89 | 72 | 30 | 80 | 67 | 80 | 70 | 75 | 73 | 0 | 39 | 87 | 29 | 6,500,000$/7yrs | |||
![]() | 26 | D | 100.00 | 64 | 36 | 73 | 71 | 81 | 85 | 79 | 67 | 30 | 77 | 61 | 69 | 64 | 66 | 64 | 0 | 42 | 81 | 25 | 2,500,000$/1yrs | |||
![]() | 67 | D | 100.00 | 67 | 33 | 91 | 70 | 80 | 81 | 70 | 65 | 30 | 77 | 63 | 64 | 64 | 67 | 66 | 0 | 42 | 80 | 25 | 1,100,000$/2yrs | |||
![]() | 0 | D | 100.00 | 58 | 33 | 95 | 69 | 83 | 84 | 88 | 65 | 30 | 66 | 75 | 77 | 70 | 62 | 62 | 0 | 42 | 80 | 22 | 863,333$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
TEAM AVERAGE | 99.72 | 68 | 34 | 83 | 76 | 76 | 84 | 87 | 74 | 53 | 77 | 74 | 71 | 74 | 71 | 71 | 0 | 41 | 85 |
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 | 97.00 | 95 | 95 | 82 | 80 | 95 | 88 | 95 | 95 | 94 | 94 | 95 | 72 | 77 | 0 | 38 | 94 | 28 | 5,500,000$/3yrs |
![]() | 30 | 97.00 | 73 | 72 | 70 | 79 | 72 | 73 | 76 | 80 | 79 | 79 | 76 | 71 | 75 | 0 | 49 | 80 | 28 | 950,000$/1yrs |
Scratches | ||||||||||||||||||||
![]() | 0 | 100.00 | 72 | 68 | 69 | 85 | 80 | 78 | 81 | 85 | 80 | 87 | 81 | 81 | 85 | 0 | 27 | 83 | 34 | 1,800,000$/3yrs |
TEAM AVERAGE | 98.00 | 80 | 78 | 74 | 81 | 82 | 80 | 84 | 87 | 84 | 87 | 84 | 75 | 79 | 0 | 38 | 86 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Jim Montgomery | 83 | 97 | 99 | 74 | 77 | 72 | 97 | CAN | 56 | 2 | 1,000,000$ |
General Manager | Mathieu Sergerie |
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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 | AMG | PPG | PPA | PPP | PPM | PKG | PKA | PKP | PKM | GW | GT | FO% | FOT | GA | TA | EG | HT | P/20 | PSG | PSS |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Nikita Kucherov | 86 | RW | 26 | 12 | 13 | 25 | 11 | 8 | 0 | 18 | 100 | 25 | 92 | 12.00% | 10 | 19.44 | 1 | 1 | 2 | 77 | 0 | 0 | 0 | 0 | 2 | 1 | 38.81% | 67 | 0 | 0 | 0 | 0 | 0.99 | 1 | 6 | |
2 | Pierre-Luc Dubois | 80 | C/LW/RW | 26 | 10 | 11 | 21 | 4 | 25 | 5 | 92 | 73 | 23 | 36 | 13.70% | 4 | 19.37 | 3 | 3 | 6 | 77 | 0 | 0 | 0 | 11 | 1 | 1 | 53.09% | 648 | 0 | 0 | 0 | 0 | 0.83 | 1 | 1 | |
3 | Artemi Panarin | 10 | LW | 26 | 5 | 15 | 20 | 6 | 0 | 0 | 9 | 96 | 28 | 63 | 5.21% | 4 | 20.18 | 1 | 6 | 7 | 77 | 0 | 0 | 0 | 4 | 1 | 0 | 39.58% | 48 | 0 | 0 | 0 | 0 | 0.76 | 0 | 6 | |
4 | Carter Verhaeghe | 25 | C/LW | 26 | 7 | 12 | 19 | 8 | 2 | 0 | 17 | 80 | 17 | 59 | 8.75% | 4 | 19.26 | 1 | 4 | 5 | 71 | 0 | 0 | 0 | 32 | 2 | 0 | 46.55% | 58 | 0 | 0 | 0 | 0 | 0.76 | 1 | 2 | |
5 | Phillip Danault | 0 | C | 22 | 8 | 10 | 18 | 10 | 10 | 0 | 38 | 65 | 20 | 51 | 12.31% | 16 | 20.27 | 0 | 2 | 2 | 55 | 0 | 0 | 0 | 63 | 0 | 0 | 53.16% | 602 | 0 | 0 | 0 | 0 | 0.81 | 0 | 0 | |
6 | Filip Hronek | 17 | D | 26 | 1 | 15 | 16 | 7 | 10 | 0 | 35 | 20 | 6 | 11 | 5.00% | 31 | 21.12 | 0 | 2 | 2 | 69 | 0 | 0 | 0 | 61 | 0 | 1 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.58 | 0 | 0 | |
7 | Jonathan Marchessault | 0 | LW/RW | 26 | 5 | 9 | 14 | 2 | 8 | 0 | 14 | 75 | 18 | 43 | 6.67% | 6 | 18.49 | 0 | 2 | 2 | 71 | 0 | 0 | 0 | 0 | 1 | 1 | 44.00% | 50 | 0 | 0 | 0 | 0 | 0.58 | 2 | 6 | |
8 | Adam Larsson | 6 | D | 26 | 4 | 9 | 13 | -2 | 44 | 0 | 66 | 29 | 8 | 20 | 13.79% | 36 | 21.59 | 1 | 1 | 2 | 33 | 0 | 0 | 0 | 23 | 1 | 1 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.46 | 0 | 0 | |
9 | Hampus Lindholm | 0 | D | 26 | 3 | 9 | 12 | 10 | 20 | 0 | 42 | 43 | 6 | 21 | 6.98% | 46 | 25.86 | 1 | 2 | 3 | 70 | 0 | 0 | 0 | 64 | 0 | 1 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.36 | 0 | 0 | |
10 | Alexander Kerfoot | 0 | C/LW | 26 | 5 | 3 | 8 | -2 | 2 | 0 | 8 | 33 | 2 | 16 | 15.15% | 7 | 12.40 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 70 | 0 | 0 | 44.53% | 274 | 0 | 0 | 0 | 0 | 0.50 | 0 | 0 | |
11 | Thomas Harley | 0 | D | 26 | 2 | 6 | 8 | 3 | 8 | 0 | 29 | 22 | 7 | 8 | 9.09% | 23 | 15.96 | 1 | 0 | 1 | 19 | 0 | 0 | 0 | 39 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.39 | 0 | 0 | |
12 | Juuso Valimaki | 26 | D | 26 | 1 | 6 | 7 | -7 | 6 | 0 | 23 | 14 | 3 | 10 | 7.14% | 32 | 19.20 | 1 | 1 | 2 | 52 | 0 | 0 | 0 | 60 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.28 | 0 | 0 | |
13 | Taylor Raddysh | 11 | RW | 26 | 6 | 1 | 7 | -7 | 6 | 0 | 14 | 30 | 4 | 28 | 20.00% | 4 | 10.51 | 1 | 0 | 1 | 19 | 0 | 0 | 0 | 18 | 0 | 1 | 36.00% | 25 | 0 | 0 | 0 | 0 | 0.51 | 0 | 0 | |
14 | Carl Grundstrom | 91 | LW/RW | 26 | 3 | 4 | 7 | 0 | 8 | 0 | 28 | 27 | 3 | 21 | 11.11% | 3 | 11.07 | 2 | 0 | 2 | 16 | 0 | 0 | 0 | 41 | 1 | 0 | 50.00% | 16 | 0 | 0 | 0 | 0 | 0.49 | 0 | 0 | |
15 | Alex Barre-Boulet | 0 | C/LW/RW | 25 | 3 | 3 | 6 | -5 | 10 | 0 | 49 | 37 | 9 | 32 | 8.11% | 1 | 16.20 | 0 | 1 | 1 | 52 | 0 | 0 | 0 | 46 | 0 | 0 | 47.12% | 399 | 0 | 0 | 0 | 0 | 0.30 | 0 | 0 | |
16 | Conor Timmins | 67 | D | 26 | 1 | 5 | 6 | 0 | 20 | 0 | 28 | 8 | 4 | 7 | 12.50% | 30 | 15.58 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 59 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.30 | 0 | 0 | |
17 | Philip Tomasino | 0 | C/LW/RW | 26 | 1 | 5 | 6 | -7 | 0 | 0 | 9 | 18 | 5 | 16 | 5.56% | 1 | 8.44 | 0 | 0 | 0 | 10 | 0 | 0 | 0 | 0 | 0 | 0 | 44.71% | 208 | 0 | 0 | 0 | 0 | 0.55 | 0 | 0 | |
18 | Pavel Dorofeyev | 0 | LW/RW | 24 | 1 | 1 | 2 | -8 | 2 | 0 | 11 | 18 | 5 | 8 | 5.56% | 1 | 8.11 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 56.25% | 16 | 0 | 0 | 0 | 0 | 0.21 | 0 | 0 | |
Team Total or Average | 461 | 78 | 137 | 215 | 23 | 189 | 5 | 530 | 788 | 193 | 542 | 9.90% | 259 | 16.85 | 13 | 25 | 38 | 775 | 0 | 0 | 0 | 599 | 9 | 7 | 49.23% | 2411 | 0 | 0 | 0 | 0 | 0.55 | 5 | 21 |
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 | Ilya Sorokin | 19 | 11 | 5 | 3 | 0.909 | 2.82 | 1129 | 2 | 1 | 53 | 583 | 0 | 0 | 0 | 0.778 | 18 | 19 | 5 | 3 | 0 | 0 | |
2 | Spencer Martin | 9 | 1 | 4 | 2 | 0.908 | 2.97 | 465 | 0 | 0 | 23 | 249 | 0 | 1 | 0 | 0.500 | 2 | 7 | 19 | 0 | 0 | 1 | |
Team Total or Average | 28 | 12 | 9 | 5 | 0.909 | 2.86 | 1595 | 2 | 1 | 76 | 832 | 0 | 1 | 0 | 0.750 | 20 | 26 | 24 | 3 | 0 | 1 |
Projected Total Cap Hit | 77,883,061$ |
Projected Cap Space | 5,616,939$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 24,164,605$ |
Players In Salary Cap | 21 |
LTIR Players | 0 |
Hurricanes Roster | Pos | Age | Cap Hit | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 | 2030-31 |
---|---|---|---|---|---|---|---|---|---|---|---|
Adam Larsson | D | 31 | 4,975,000$ | 4,975,000$ | 4,975,000$ | 4,975,000$ | 4,975,000$ | UFA | |||
Alex Barre-Boulet ![]() | C/LW/RW | 26 | 775,000$ | 775,000$ | UFA | ||||||
Alexander Kerfoot | C/LW | 29 | 3,500,000$ | 3,500,000$ | 3,500,000$ | 3,500,000$ | UFA | ||||
Artemi Panarin | LW | 32 | 11,642,579$ | 11,642,578$ | 11,642,578$ | 11,642,578$ | UFA | ||||
Braden Holtby | G | 34 | 1,800,000$ | 1,800,000$ | 1,800,000$ | 1,800,000$ | UFA | ||||
Carl Grundstrom | LW/RW | 26 | 1,300,000$ | 1,300,000$ | |||||||
Carter Verhaeghe | C/LW | 28 | 4,166,667$ | 4,166,667$ | 4,166,667$ | UFA | |||||
Conor Timmins ![]() | D | 25 | 1,100,000$ | 1,100,000$ | 1,100,000$ | ||||||
Filip Hronek | D | 26 | 4,800,000$ | 4,800,000$ | |||||||
Hampus Lindholm | D | 29 | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | UFA |
Ilya Sorokin | G | 28 | 5,500,000$ | 5,500,000$ | 5,500,000$ | 5,500,000$ | UFA | ||||
Jonathan Marchessault | LW/RW | 32 | 5,000,000$ | 5,000,000$ | UFA | ||||||
Juuso Valimaki | D | 25 | 2,500,000$ | 2,500,000$ | |||||||
Nikita Kucherov | RW | 30 | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | UFA | |||
Pavel Dorofeyev ![]() | LW/RW | 23 | 950,000$ | 950,000$ | RFA | ||||||
Philip Tomasino ![]() | C/LW/RW | 22 | 863,333$ | 863,333$ | RFA | ||||||
Phillip Danault | C | 30 | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | UFA | |||
Pierre-Luc Dubois | C/LW/RW | 25 | 7,250,000$ | 7,250,000$ | 7,250,000$ | 7,250,000$ | 7,250,000$ | UFA | |||
Spencer Martin ![]() | G | 28 | 950,000$ | 950,000$ | UFA | ||||||
Taylor Raddysh ![]() | RW | 25 | 1,000,000$ | 1,000,000$ | |||||||
Thomas Harley ![]() | D | 22 | 863,333$ | 863,333$ | RFA |
Non-Roster | Pos | Age | Cap Hit | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 | 2030-31 |
---|---|---|---|---|---|---|---|---|---|---|---|
Adam Ginning ![]() | D | 23 | 775,000$ | 775,000$ | ![]() | ||||||
Adam Raska ![]() | RW | 22 | 848,333$ | 848,333$ | RFA | ||||||
Artemi Knyazev ![]() | D | 22 | 789,167$ | 789,167$ | RFA | ||||||
Brandon Duhaime ![]() | RW | 26 | 850,000$ | 850,000$ | 850,000$ | UFA | |||||
Brett Berard ![]() | LW | 21 | 836,667$ | 867,500$ | 867,500$ | 775,000$ | RFA | ||||
Cale Fleury ![]() | D | 25 | 900,000$ | 900,000$ | ![]() | ||||||
Cross Hanas ![]() | LW/RW | 21 | 775,000$ | 775,000$ | RFA | ||||||
Damien Giroux ![]() | C | 23 | 800,000$ | 800,000$ | 800,000$ | ![]() | |||||
David Farrance ![]() | D | 24 | 1,000,000$ | 1,000,000$ | ![]() | ||||||
Dylan Gambrell ![]() | C | 27 | 1,200,000$ | 1,200,000$ | UFA | ||||||
Filip Kral ![]() | D | 24 | 800,000$ | 800,000$ | 800,000$ | ![]() | |||||
Jan Drozg ![]() | RW | 24 | 850,000$ | 850,000$ | ![]() | ||||||
Jett Woo ![]() | D | 23 | 775,000$ | 775,000$ | RFA | ||||||
Jon Gillies ![]() | G | 29 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Jordan Bellerive ![]() | C | 24 | 800,000$ | 800,000$ | ![]() | ||||||
Karson Kuhlman ![]() | C/RW | 28 | 850,000$ | 850,000$ | UFA | ||||||
Keaton Middleton ![]() | D | 25 | 850,000$ | 850,000$ | ![]() | ||||||
Mark Kastelic ![]() | C | 24 | 835,000$ | 835,000$ | 835,000$ | ![]() | |||||
Matt Kessel ![]() | D | 23 | 883,750$ | 883,750$ | ![]() | ||||||
Matthew Highmore ![]() | C | 27 | 900,000$ | 900,000$ | UFA | ||||||
Noah Juulsen ![]() | D | 26 | 775,000$ | 775,000$ | UFA | ||||||
Sampo Ranta ![]() | LW | 23 | 850,000$ | 850,000$ | 850,000$ | ![]() | |||||
Shane Gersich ![]() | LW | 27 | 900,000$ | 900,000$ | UFA | ||||||
Steven Lorentz ![]() | C/LW | 27 | 1,250,000$ | 1,250,000$ | UFA | ||||||
Tim Gettinger ![]() | LW | 25 | 900,000$ | 900,000$ | ![]() | ||||||
Tobias Geisser ![]() | D | 24 | 800,000$ | 800,000$ | ![]() | ||||||
Troy Grosenick ![]() | G | 34 | 775,000$ | 775,000$ | 775,000$ | UFA | |||||
Tyson Foerster ![]() | C | 21 | 894,167$ | 894,167$ | RFA | ||||||
Tyson Kozak ![]() | C | 20 | 775,000$ | 775,000$ | RFA | ||||||
Zack Ostapchuk ![]() | C | 20 | 825,000$ | 825,000$ | 825,000$ | 825,000$ | RFA | ||||
Zane McIntyre ![]() | G | 31 | 775,000$ | 775,000$ | UFA |
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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 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 | 3 | -1 | 1 | 0.500 | 2 | 4 | 6 | 0 | 0 | 1 | 1 | 0 | 0 | 25 | 8 | 7 | 9 | 1 | 37 | 10 | 6 | 25 | 1 | 0 | 0.00% | 3 | 0 | 100.00% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 21 | 14 | 28 | 7 | 13 | 6 | 40.0% | 8.0% | 91.9% | 99.9 | DULL | |
2 | 3 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 5 | 7 | 6 | 1.000 | 12 | 24 | 36 | 0 | 1 | 1 | 6 | 5 | 0 | 94 | 19 | 27 | 48 | 0 | 83 | 39 | 16 | 58 | 11 | 1 | 9.09% | 8 | 2 | 75.00% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 66 | 46 | 75 | 22 | 38 | 19 | 78.6% | 12.8% | 94.0% | 106.7 | LUCKY | |
3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | 5 | -1 | 1 | 0.500 | 4 | 8 | 12 | 0 | 0 | 3 | 0 | 1 | 0 | 34 | 9 | 7 | 16 | 5 | 38 | 13 | 16 | 13 | 0 | 0 | 0.00% | 8 | 2 | 75.00% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 25 | 17 | 26 | 8 | 12 | 6 | 57.1% | 11.8% | 86.8% | 98.6 | FUN | |
4 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 5 | 8 | -3 | 0 | 0.000 | 5 | 7 | 12 | 0 | 0 | 3 | 0 | 2 | 0 | 58 | 22 | 18 | 18 | 0 | 57 | 17 | 18 | 41 | 10 | 2 | 20.00% | 8 | 3 | 62.50% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 45 | 30 | 51 | 14 | 23 | 11 | 37.5% | 8.6% | 86.0% | 94.6 | Unlucky | |
5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 2 | 3 | -1 | 1 | 0.500 | 2 | 3 | 5 | 0 | 0 | 0 | 2 | 0 | 0 | 27 | 13 | 6 | 6 | 5 | 35 | 11 | 10 | 21 | 4 | 0 | 0.00% | 4 | 1 | 75.00% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 25 | 16 | 24 | 8 | 15 | 7 | 50.0% | 7.4% | 91.4% | 98.8 | DULL | |
6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 3 | 2 | 1.000 | 4 | 7 | 11 | 0 | 0 | 2 | 0 | 2 | 0 | 39 | 8 | 13 | 18 | 0 | 30 | 5 | 6 | 20 | 3 | 0 | 0.00% | 3 | 1 | 66.67% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 24 | 17 | 24 | 7 | 11 | 5 | 100.0% | 10.3% | 96.7% | 106.9 | LUCKY | |
7 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 | 1 | 1 | 2 | 1.000 | 2 | 2 | 4 | 0 | 0 | 0 | 1 | 0 | 1 | 33 | 12 | 11 | 9 | 5 | 34 | 12 | 6 | 20 | 2 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 24 | 17 | 28 | 7 | 12 | 6 | 66.7% | 6.1% | 97.1% | 103.1 | DULL | |
8 | 3 | 2 | 0 | 0 | 0 | 0 | 0 | 1 | 14 | 10 | 4 | 5 | 0.833 | 14 | 23 | 37 | 0 | 0 | 6 | 4 | 4 | 1 | 94 | 34 | 33 | 25 | 5 | 104 | 25 | 23 | 51 | 10 | 1 | 10.00% | 9 | 1 | 88.89% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 71 | 50 | 75 | 21 | 37 | 18 | 59.1% | 14.9% | 90.4% | 105.3 | FUN | |
9 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 4 | 4 | 4 | 1.000 | 8 | 16 | 24 | 0 | 0 | 4 | 2 | 2 | 0 | 58 | 10 | 28 | 20 | 0 | 66 | 24 | 10 | 57 | 5 | 1 | 20.00% | 5 | 0 | 100.00% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 45 | 32 | 48 | 14 | 25 | 12 | 63.6% | 13.8% | 93.9% | 107.7 | LUCKY | |
10 | 2 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 8 | 9 | -1 | 2 | 0.500 | 8 | 12 | 20 | 0 | 0 | 4 | 2 | 1 | 1 | 69 | 22 | 19 | 26 | 5 | 59 | 15 | 16 | 38 | 8 | 1 | 12.50% | 8 | 2 | 75.00% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 50 | 34 | 49 | 15 | 25 | 11 | 50.0% | 11.6% | 84.7% | 96.3 | FUN | |
11 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 5 | -2 | 0 | 0.000 | 3 | 6 | 9 | 0 | 0 | 1 | 0 | 2 | 0 | 22 | 6 | 4 | 12 | 0 | 33 | 17 | 12 | 25 | 3 | 1 | 33.33% | 6 | 1 | 83.33% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 18 | 11 | 28 | 7 | 12 | 5 | 33.3% | 13.6% | 84.8% | 98.5 | FUN | |
12 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 18 | 11 | 3 | 4 | 0 | 22 | 9 | 2 | 19 | 4 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 22 | 15 | 25 | 7 | 12 | 6 | 20.0% | 5.6% | 81.8% | 87.4 | Unlucky | |
13 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | -2 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 0 | 1 | 0 | 22 | 3 | 9 | 10 | 0 | 35 | 13 | 14 | 20 | 3 | 0 | 0.00% | 6 | 1 | 83.33% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 21 | 14 | 26 | 7 | 11 | 5 | 33.3% | 4.5% | 91.4% | 96.0 | DULL | |
14 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 2 | -1 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 1 | 0 | 0 | 40 | 11 | 18 | 11 | 0 | 23 | 1 | 8 | 20 | 5 | 0 | 0.00% | 4 | 1 | 75.00% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 27 | 19 | 20 | 6 | 11 | 6 | 50.0% | 2.5% | 91.3% | 93.8 | DULL | |
15 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | -2 | 0 | 0.000 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 37 | 15 | 9 | 13 | 0 | 30 | 2 | 8 | 13 | 1 | 0 | 0.00% | 3 | 0 | 100.00% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 25 | 18 | 22 | 7 | 12 | 6 | 0.0% | 0.0% | 93.3% | 93.3 | DULL | |
16 | 2 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 8 | 10 | -2 | 2 | 0.500 | 8 | 10 | 18 | 0 | 0 | 1 | 2 | 4 | 2 | 62 | 20 | 24 | 15 | 8 | 81 | 27 | 6 | 36 | 8 | 3 | 37.50% | 3 | 1 | 66.67% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 49 | 35 | 51 | 14 | 23 | 12 | 35.7% | 12.9% | 87.7% | 100.6 | FUN | |
17 | 2 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 5 | 4 | 1 | 3 | 0.750 | 5 | 10 | 15 | 0 | 0 | 2 | 2 | 1 | 0 | 54 | 18 | 17 | 18 | 1 | 65 | 23 | 18 | 49 | 6 | 3 | 50.00% | 9 | 0 | 100.00% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 41 | 27 | 55 | 15 | 25 | 12 | 33.3% | 9.3% | 93.8% | 103.1 | LUCKY | |
_Vs Division | 8 | 4 | 4 | 0 | 0 | 0 | 0 | 0 | 22 | 20 | 2 | 8 | 0.500 | 22 | 40 | 62 | 0 | 1 | 7 | 6 | 9 | 0 | 246 | 75 | 70 | 101 | 0 | 222 | 72 | 50 | 151 | 29 | 3 | 10.34% | 23 | 6 | 73.91% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 183 | 128 | 198 | 59 | 97 | 50 | 57.6% | 8.9% | 91.0% | 99.9 | Unlucky | |
_Vs Conference | 15 | 6 | 6 | 0 | 0 | 0 | 1 | 2 | 51 | 49 | 2 | 16 | 0.533 | 51 | 89 | 140 | 0 | 1 | 21 | 12 | 17 | 2 | 465 | 146 | 133 | 180 | 15 | 456 | 142 | 117 | 278 | 50 | 6 | 12.00% | 54 | 12 | 77.78% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 349 | 243 | 379 | 111 | 185 | 92 | 54.9% | 11.0% | 89.3% | 100.2 | FUN | |
_Since Last GM Reset | 26 | 9 | 9 | 0 | 0 | 2 | 3 | 3 | 80 | 79 | 1 | 29 | 0.558 | 80 | 138 | 218 | 0 | 1 | 29 | 23 | 25 | 5 | 786 | 241 | 253 | 278 | 35 | 832 | 263 | 195 | 526 | 84 | 13 | 15.48% | 90 | 16 | 82.22% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 606 | 422 | 664 | 193 | 324 | 161 | 51.5% | 10.2% | 90.5% | 100.7 | FUN | |
Total | 26 | 9 | 9 | 0 | 0 | 2 | 3 | 3 | 80 | 79 | 1 | 29 | 0.558 | 80 | 138 | 218 | 0 | 1 | 29 | 23 | 25 | 5 | 786 | 241 | 253 | 278 | 35 | 832 | 263 | 195 | 526 | 84 | 13 | 15.48% | 90 | 16 | 82.22% | 0 | 447 | 889 | 50.28% | 460 | 944 | 48.73% | 216 | 401 | 53.87% | 606 | 422 | 664 | 193 | 324 | 161 | 51.5% | 10.2% | 90.5% | 100.7 | FUN |
Puck Time | |
---|---|
Offensive Zone | 23 |
Neutral Zone | 12 |
Defensive Zone | 25 |
Puck Time | |
---|---|
Offensive Zone Start | 889 |
Neutral Zone Start | 401 |
Defensive Zone Start | 944 |
Puck Time | |
---|---|
With Puck | 29 |
Without Puck | 31 |
Faceoffs | |
---|---|
Faceoffs Won | 1123 |
Faceoffs Lost | 1111 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 9.3 | 9.57 |
2nd Period | 19.0 | 20.31 |
3rd Period | 29.7 | 30.68 |
Overtime | 31.0 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 1.1 | 0.64 |
2nd Period | 2.0 | 1.65 |
3rd Period | 3.0 | 2.67 |
Overtime | 3.2 | 2.83 |
Even Strenght Goal | 67 |
---|---|
PP Goal | 13 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 3 | 9 |
Lost | 5 | 4 |
Overtime Lost | 3 | 2 |
PP Attempt | 84 |
---|---|
PP Goal | 13 |
PK Attempt | 90 |
PK Goal Against | 16 |
Home | |
---|---|
Shots For | 30.2 |
Shots Against | 32.0 |
Goals For | 3.1 |
Goals Against | 3.0 |
Hits | 20.2 |
Shots Blocked | 10.1 |
Pim | 7.5 |
Date | Matchup | Result | Detail | |||||||||||
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2023-10-11 | @ | Senators5,Hurricanes4 (SO) | RECAP | |||||||||||
2023-10-14 | @ | Hurricanes2,Kings1 (SO) | RECAP | |||||||||||
2023-10-15 | @ | Hurricanes1,Ducks2 | RECAP | |||||||||||
2023-10-17 | @ | Hurricanes6,Sharks5 (SO) | RECAP | |||||||||||
2023-10-19 | @ | Hurricanes3,Kraken1 | RECAP | |||||||||||
2023-10-21 | @ | Hurricanes2,Avalanche3 (SO) | RECAP | |||||||||||
2023-10-24 | @ | Hurricanes6,Lightning3 | RECAP | |||||||||||
2023-10-26 | @ | Kraken3,Hurricanes2 (OT) | RECAP | |||||||||||
2023-10-27 | @ | Sharks5,Hurricanes2 | RECAP | |||||||||||
2023-10-30 | @ | Hurricanes3,Flyers0 | RECAP | |||||||||||
2023-11-02 | @ | Hurricanes4,Rangers1 | RECAP | |||||||||||
2023-11-04 | @ | Hurricanes3,Islanders5 | RECAP | |||||||||||
2023-11-07 | @ | Sabres5,Hurricanes3 | RECAP | |||||||||||
2023-11-10 | @ | Hurricanes3,Panthers5 | RECAP | |||||||||||
2023-11-11 | @ | Hurricanes4,Lightning2 | RECAP | |||||||||||
2023-11-15 | @ | Flyers3,Hurricanes5 | RECAP | |||||||||||
2023-11-18 | @ | Penguins2,Hurricanes0 | RECAP | |||||||||||
2023-11-22 | @ | Oilers2,Hurricanes4 | RECAP | |||||||||||
2023-11-24 | @ | Lightning5,Hurricanes4 (SO) | RECAP | |||||||||||
2023-11-26 | @ | Blue Jackets4,Hurricanes1 | RECAP | |||||||||||
2023-11-28 | @ | Hurricanes4,Flyers2 | RECAP | |||||||||||
2023-11-30 | @ | Islanders3,Hurricanes2 | RECAP | |||||||||||
2023-12-02 | @ | Sabres4,Hurricanes5 (SO) | RECAP | |||||||||||
2023-12-04 | @ | Hurricanes1,Jets3 | RECAP | |||||||||||
2023-12-06 | @ | Hurricanes4,Oilers2 | RECAP | |||||||||||
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Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
78,135,911$ | 0$ | 77,883,061$ | 5,364,089$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | PNC Center | |
City | Carolina | ||
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 | 63836 | 53265 | 21150 | 43366 | 10260 |
Attendance PCT | 96.72% | 96.85% | 96.14% | 98.56% | 93.27% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
30 | 17443 - 96.91% | 1,529,080$ | 16,819,876$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
78,135,911$ | 78,135,912$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
24,477,113$ | 406,958$ | 24,164,605$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
45,872,389$ | 132 | 412,166$ | 54,405,912$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
56,598,312$ | 78,135,911$ | 24,929,790$ | 14,203,867$ |
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 | Ronde 8 |
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2024 | ||||||||
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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 |
---|---|---|---|---|---|
Alec Bélanger | 2020 | 211 | |||
Alex Gagne | 2021 | 203 | |||
Alex Hurtig | 2023 | 206 | |||
Alexander Suzdalev | 2022 | 75 | |||
Angus Booth | 2022 | 144 | |||
Anton Johansson | 2022 | 114 | |||
Arno Tiefensee | 2023 | 142 | |||
Brody Lamb | 2021 | 117 | |||
Carson Musser | 2023 | 152 | |||
Carter Berger | 2019 | 115 | 5.5 - 4.5 | ||
Cole Brown | 2023 | 174 | |||
Dylan James | 2022 | 77 | |||
Filip Westerlund | 4.0 - 5.5 | ||||
Frederic Brunet | 2022 | 150 | |||
Jackson Dorrington | 2022 | 214 | |||
Jacob Julien | 2023 | 151 | |||
Jacob Melanson | 2021 | 139 | |||
Jake Ratzlaff | 2020 | 111 | |||
Jan Bednar | 2020 | 82 | |||
Jiri Felcman | 2023 | 110 | |||
Jonathan Tychonick | |||||
Justin Bergeron | 2019 | 187 | |||
Karel Plasek | 2019 | 177 | 6.0 - 3.0 | ||
Kasper Halttunen | 2023 | 46 | |||
Linus Arnesson | 6B | ||||
Luca Munzenberger | 2021 | 94 | |||
Matthew Gleason | 2020 | 185 | |||
Michael Callow | 2022 | 182 | |||
Nikola Pasic | 2019 | 208 | 5.0 - 5.0 | ||
Owen Pederson | 2020 | 149 | |||
Shai Buium | 2021 | 67 | |||
Simon Robertsson | 2021 | 25 | |||
Tyler Bauer | |||||
Vadim Moroz | 2023 | 106 |
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