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Full Scoreboard »» |
Florida Panthers 2-1-0, 4pts · 7th 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 | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | RW | 100.00 | 89 | 48 | 50 | 70 | 89 | 87 | 89 | 70 | 59 | 69 | 76 | 80 | 73 | 78 | 73 | 0 | 42 | 83 | 31 | 6,500,000$/6yrs | |||
![]() | 0 | LW/RW | 100.00 | 81 | 35 | 70 | 76 | 78 | 84 | 85 | 70 | 59 | 75 | 74 | 55 | 72 | 67 | 64 | 0 | 42 | 82 | 25 | 7,750,000$/4yrs | |||
![]() | 0 | C | 100.00 | 80 | 33 | 78 | 72 | 78 | 86 | 81 | 70 | 85 | 67 | 77 | 75 | 74 | 69 | 67 | 0 | 42 | 82 | 26 | 7,250,000$/3yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 72 | 39 | 74 | 70 | 85 | 81 | 87 | 70 | 60 | 72 | 75 | 57 | 73 | 75 | 73 | 0 | 42 | 81 | 30 | 3,700,000$/2yrs | |||
![]() | 0 | C/LW | 100.00 | 55 | 33 | 96 | 72 | 78 | 84 | 89 | 68 | 73 | 67 | 75 | 65 | 72 | 70 | 70 | 0 | 42 | 79 | 27 | 5,750,000$/5yrs | |||
![]() | 0 | C/LW | 100.00 | 63 | 32 | 92 | 70 | 71 | 80 | 89 | 68 | 59 | 70 | 71 | 56 | 69 | 64 | 63 | 0 | 42 | 78 | 23 | 4,000,000$/2yrs | |||
![]() | 0 | C | 100.00 | 53 | 32 | 96 | 65 | 72 | 79 | 84 | 66 | 75 | 68 | 71 | 56 | 68 | 72 | 71 | 0 | 42 | 76 | 28 | 3,500,000$/1yrs | |||
![]() | 0 | C/LW | 100.00 | 88 | 40 | 79 | 57 | 80 | 78 | 89 | 57 | 72 | 57 | 63 | 72 | 60 | 72 | 70 | 0 | 42 | 73 | 28 | 3,500,000$/3yrs | |||
![]() | 0 | C | 100.00 | 61 | 37 | 87 | 61 | 68 | 77 | 88 | 60 | 84 | 63 | 61 | 64 | 61 | 67 | 66 | 0 | 42 | 72 | 25 | 2,500,000$/1yrs | |||
![]() | 0 | C | 100.00 | 70 | 32 | 88 | 59 | 71 | 77 | 75 | 59 | 59 | 63 | 63 | 54 | 61 | 65 | 64 | 0 | 45 | 72 | 24 | 900,000$/2yrs | |||
![]() | 0 | C/LW | 100.00 | 74 | 40 | 73 | 59 | 73 | 78 | 90 | 60 | 79 | 63 | 60 | 57 | 60 | 65 | 62 | 0 | 42 | 71 | 24 | 2,500,000$/1yrs | |||
![]() | 0 | C/RW | 100.00 | 64 | 32 | 96 | 63 | 67 | 76 | 69 | 59 | 55 | 59 | 63 | 53 | 61 | 59 | 58 | 0 | 42 | 71 | 21 | 950,000$/1yrs | |||
![]() | 0 | D | 100.00 | 72 | 34 | 85 | 67 | 86 | 98 | 85 | 67 | 30 | 72 | 64 | 81 | 66 | 77 | 75 | 0 | 42 | 83 | 31 | 9,500,000$/5yrs | |||
![]() | 4 | D | 99.00 | 63 | 33 | 86 | 73 | 77 | 97 | 84 | 67 | 30 | 78 | 63 | 67 | 65 | 68 | 67 | 0 | 42 | 82 | 26 | 8,000,000$/4yrs | |||
![]() | 0 | D | 100.00 | 72 | 45 | 64 | 62 | 79 | 84 | 88 | 56 | 30 | 66 | 60 | 58 | 58 | 67 | 63 | 0 | 42 | 74 | 25 | 1,500,000$/1yrs | |||
![]() | 0 | D | 100.00 | 74 | 33 | 94 | 61 | 82 | 82 | 75 | 57 | 30 | 67 | 53 | 59 | 55 | 65 | 64 | 0 | 42 | 74 | 24 | 825,000$/5yrs | |||
![]() | 0 | D | 100.00 | 66 | 35 | 79 | 55 | 75 | 81 | 80 | 53 | 30 | 59 | 53 | 63 | 53 | 68 | 66 | 0 | 42 | 70 | 26 | 2,000,000$/2yrs | |||
![]() | 0 | D | 100.00 | 69 | 32 | 88 | 55 | 70 | 84 | 72 | 51 | 30 | 60 | 54 | 61 | 52 | 63 | 62 | 0 | 42 | 70 | 23 | 903,333$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 9 | D | 100.00 | 72 | 40 | 72 | 53 | 78 | 67 | 84 | 52 | 30 | 58 | 58 | 66 | 58 | 65 | 62 | 0 | 37 | 70 | 26 | 775,000$/1yrs | |||
![]() | 0 | D | 100.00 | 85 | 42 | 50 | 45 | 77 | 60 | 69 | 45 | 30 | 50 | 48 | 65 | 49 | 62 | 57 | 0 | 37 | 64 | 24 | 800,000$/2yrs | |||
TEAM AVERAGE | 99.95 | 71 | 36 | 80 | 63 | 77 | 81 | 83 | 61 | 53 | 65 | 64 | 63 | 63 | 68 | 66 | 0 | 42 | 75 |
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 | 99.00 | 85 | 84 | 76 | 83 | 85 | 74 | 86 | 88 | 85 | 88 | 86 | 70 | 75 | 0 | 43 | 87 | 27 | 3,750,000$/4yrs |
![]() | 0 | 100.00 | 60 | 62 | 66 | 87 | 57 | 60 | 60 | 60 | 60 | 61 | 60 | 61 | 64 | 0 | 43 | 68 | 22 | 2,200,000$/2yrs |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 99.50 | 73 | 73 | 71 | 85 | 71 | 67 | 73 | 74 | 73 | 75 | 73 | 66 | 70 | 0 | 43 | 78 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Scott Arniel | 76 | 95 | 94 | 73 | 68 | 82 | 57 | CAN | 63 | 4 | 1,000,000$ |
General Manager | Jean Francois Barette |
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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 | Tom Wilson | 0 | RW | 3 | 1 | 3 | 4 | 2 | 6 | 0 | 13 | 18 | 3 | 10 | 5.56% | 0 | 17.64 | 0 | 0 | 0 | 12 | 0 | 0 | 0 | 0 | 0 | 0 | 25.00% | 4 | 0 | 0 | 0 | 0 | 1.51 | 0 | 0 | |
2 | Yegor Sharangovich | 0 | C/LW | 3 | 2 | 1 | 3 | 2 | 0 | 0 | 0 | 13 | 1 | 2 | 15.38% | 0 | 13.44 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 25.00% | 4 | 0 | 0 | 0 | 0 | 1.49 | 0 | 0 | |
3 | Andrei Svechnikov | 0 | LW/RW | 3 | 1 | 1 | 2 | 1 | 2 | 0 | 8 | 13 | 1 | 6 | 7.69% | 0 | 21.05 | 0 | 0 | 0 | 15 | 0 | 0 | 0 | 1 | 0 | 0 | 20.00% | 5 | 0 | 0 | 0 | 0 | 0.63 | 0 | 0 | |
4 | Mason Marchment | 0 | C/LW/RW | 3 | 2 | 0 | 2 | 1 | 2 | 0 | 5 | 8 | 3 | 5 | 25.00% | 0 | 12.02 | 0 | 0 | 0 | 12 | 0 | 0 | 0 | 0 | 1 | 0 | 33.33% | 3 | 0 | 0 | 0 | 0 | 1.11 | 0 | 0 | |
5 | Pierre-Olivier Joseph | 0 | D | 3 | 0 | 2 | 2 | 6 | 4 | 0 | 5 | 0 | 2 | 1 | 0.00% | 2 | 13.84 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.96 | 0 | 0 | |
6 | Thomas Novak | 0 | C | 3 | 1 | 1 | 2 | 2 | 0 | 0 | 0 | 4 | 2 | 3 | 25.00% | 1 | 17.21 | 0 | 0 | 0 | 12 | 0 | 0 | 0 | 0 | 0 | 0 | 46.84% | 79 | 0 | 0 | 0 | 0 | 0.77 | 0 | 0 | |
7 | Michael Kesselring | 0 | D | 3 | 1 | 1 | 2 | 0 | 2 | 0 | 11 | 7 | 2 | 5 | 14.29% | 3 | 19.91 | 0 | 0 | 0 | 11 | 0 | 0 | 0 | 1 | 1 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.67 | 0 | 0 | |
8 | Emil Andrae | 0 | D | 3 | 0 | 2 | 2 | 6 | 0 | 0 | 0 | 3 | 1 | 3 | 0.00% | 1 | 13.96 | 0 | 0 | 0 | 11 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.96 | 0 | 0 | |
9 | Josh Norris | 0 | C | 3 | 1 | 0 | 1 | 1 | 0 | 0 | 4 | 13 | 5 | 6 | 7.69% | 0 | 20.62 | 0 | 0 | 0 | 15 | 0 | 0 | 0 | 0 | 0 | 0 | 44.74% | 76 | 0 | 0 | 0 | 0 | 0.32 | 0 | 0 | |
10 | Yakov Trenin | 0 | C/LW | 3 | 0 | 1 | 1 | 1 | 0 | 0 | 3 | 2 | 2 | 4 | 0.00% | 0 | 10.68 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 0 | 0 | 50.00% | 4 | 0 | 0 | 0 | 0 | 0.62 | 0 | 0 | |
11 | Cole Perfetti | 0 | C/LW | 3 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 4 | 4 | 3 | 0.00% | 1 | 20.51 | 0 | 0 | 0 | 15 | 0 | 0 | 0 | 0 | 0 | 0 | 40.00% | 5 | 0 | 0 | 0 | 0 | 0.33 | 0 | 0 | |
12 | Jack Drury | 0 | C | 3 | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 1 | 0.00% | 0 | 13.04 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 14 | 0 | 0 | 50.88% | 57 | 0 | 0 | 0 | 0 | 0.51 | 0 | 0 | |
13 | Miro Heiskanen | 4 | D | 3 | 0 | 0 | 0 | -2 | 2 | 0 | 8 | 7 | 3 | 7 | 0.00% | 4 | 27.65 | 0 | 0 | 0 | 17 | 0 | 0 | 0 | 13 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
14 | Seth Jones | 0 | D | 3 | 0 | 0 | 0 | -2 | 6 | 0 | 12 | 9 | 1 | 3 | 0.00% | 10 | 27.01 | 0 | 0 | 0 | 17 | 0 | 0 | 0 | 11 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
15 | Peyton Krebs | 0 | C/LW | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0.00% | 0 | 11.31 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 14 | 0 | 0 | 100.00% | 1 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
16 | Kaedan Korczak | 0 | D | 3 | 0 | 0 | 0 | 0 | 2 | 0 | 4 | 1 | 0 | 0 | 0.00% | 4 | 17.59 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
17 | Gage Goncalves | 0 | C | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | 0 | 1 | 0.00% | 0 | 8.50 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 51.72% | 29 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
18 | Jonathan Lekkerimaki | 0 | C/RW | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 1 | 0 | 0.00% | 0 | 6.63 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 50.00% | 2 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
Team Total or Average | 54 | 9 | 14 | 23 | 20 | 26 | 0 | 76 | 110 | 32 | 61 | 8.18% | 26 | 16.26 | 0 | 0 | 0 | 140 | 0 | 0 | 0 | 87 | 2 | 0 | 46.47% | 269 | 0 | 0 | 0 | 0 | 0.52 | 0 | 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 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 | Joseph Woll | 3 | 2 | 1 | 0 | 0.918 | 2.68 | 179 | 0 | 0 | 8 | 98 | 0 | 0 | 0 | 0.000 | 0 | 3 | 0 | 0 | 0 | 0 | |
Team Total or Average | 3 | 2 | 1 | 0 | 0.918 | 2.68 | 179 | 0 | 0 | 8 | 98 | 0 | 0 | 0 | 0.000 | 0 | 3 | 0 | 0 | 0 | 0 |
Projected Total Cap Hit | 77,478,336$ |
Projected Cap Space | 18,021,664$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 2,421,198$ |
Players In Salary Cap | 22 |
LTIR Players | 0 |
Panthers Roster | Pos | Age | Cap Hit | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 | 2030-31 | 2031-32 | 2032-33 |
---|---|---|---|---|---|---|---|---|---|---|---|
Andrei Svechnikov ![]() | LW/RW | 25 | 7,750,000$ | 7,750,000$ | 7,750,000$ | 7,750,000$ | 7,750,000$ | UFA | |||
Cole Perfetti ![]() | C/LW | 23 | 4,000,000$ | 4,000,000$ | 4,000,000$ | RFA | |||||
Emil Andrae ![]() | D | 23 | 903,333$ | 903,333$ | RFA | ||||||
Gage Goncalves ![]() | C | 24 | 900,000$ | 900,000$ | 900,000$ | ||||||
Jack Drury ![]() | C | 25 | 2,500,000$ | 2,500,000$ | |||||||
Jesper Wallstedt ![]() | G | 22 | 2,200,000$ | 2,200,000$ | 2,200,000$ | RFA | |||||
Jonathan Lekkerimaki ![]() | C/RW | 21 | 950,000$ | 950,000$ | RFA | ||||||
Joseph Woll ![]() | G | 27 | 3,750,000$ | 3,750,000$ | 3,750,000$ | 3,750,000$ | 3,750,000$ | UFA | |||
Josh Norris ![]() | C | 26 | 7,250,000$ | 7,250,000$ | 7,250,000$ | 7,250,000$ | UFA | ||||
Kaedan Korczak ![]() | D | 24 | 825,000$ | 825,000$ | 3,250,000$ | 3,250,000$ | 3,250,000$ | 3,250,000$ | UFA | ||
Leon Gawanke ![]() | D | 26 | 775,000$ | 775,000$ | |||||||
Mason Marchment ![]() | C/LW/RW | 30 | 3,700,000$ | 3,700,000$ | 3,700,000$ | UFA | |||||
Michael Kesselring ![]() | D | 25 | 1,500,000$ | 1,500,000$ | |||||||
Miro Heiskanen ![]() | D | 26 | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | UFA | |||
Nikita Okhotyuk ![]() | D | 24 | 800,000$ | 800,000$ | 800,000$ | ||||||
Peyton Krebs ![]() | C/LW | 24 | 2,500,000$ | 2,500,000$ | RFA | ||||||
Pierre-Olivier Joseph ![]() | D | 26 | 2,000,000$ | 2,000,000$ | 2,000,000$ | ||||||
Seth Jones ![]() | D | 31 | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | UFA | ||
Thomas Novak ![]() | C | 28 | 3,500,000$ | 3,500,000$ | UFA | ||||||
Tom Wilson ![]() | RW | 31 | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | UFA | |
Yakov Trenin ![]() | C/LW | 28 | 3,500,000$ | 3,500,000$ | 3,500,000$ | 3,500,000$ | UFA | ||||
Yegor Sharangovich ![]() | C/LW | 27 | 5,750,000$ | 5,750,000$ | 5,750,000$ | 5,750,000$ | 5,750,000$ | 5,750,000$ | UFA |
Non-Roster | Pos | Age | Cap Hit | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 | 2030-31 | 2031-32 | 2032-33 |
---|---|---|---|---|---|---|---|---|---|---|---|
Adam Brooks ![]() | C | 29 | 800,000$ | 800,000$ | UFA | ||||||
Adam Jiricek ![]() | D | 19 | 975,000$ | 975,000$ | 975,000$ | RFA | |||||
Adam Sykora ![]() | LW/RW | 21 | 800,000$ | 800,000$ | 800,000$ | RFA | |||||
Albin Grewe ![]() | LW | 24 | 800,000$ | 800,000$ | 800,000$ | 800,000$ | ![]() | ||||
Axel Andersson ![]() | D | 25 | 800,000$ | 800,000$ | 800,000$ | ![]() | |||||
Ben Harpur ![]() | D | 30 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Blade Jenkins ![]() | LW | 25 | 800,000$ | 800,000$ | 800,000$ | ![]() | |||||
Brooklyn Kalmikov ![]() | LW | 24 | 800,000$ | 800,000$ | 800,000$ | ![]() | |||||
Caedan Bankier ![]() | C | 22 | 850,000$ | 850,000$ | 850,000$ | 850,000$ | RFA | ||||
Case McCarthy ![]() | D | 24 | 800,000$ | 800,000$ | 800,000$ | ![]() | |||||
Colton Dach ![]() | C/LW | 22 | 825,000$ | 825,000$ | RFA | ||||||
Connor Mayer ![]() | D | 26 | 800,000$ | 800,000$ | 800,000$ | ![]() | |||||
Daniil Gushchin ![]() | LW | 23 | 900,000$ | 900,000$ | 900,000$ | 900,000$ | ![]() | ||||
Dawson Barteaux ![]() | D | 25 | 800,000$ | 800,000$ | 800,000$ | ![]() | |||||
Dylan Peterson ![]() | C/LW/RW | 23 | 850,000$ | 850,000$ | 850,000$ | RFA | |||||
Dylan Wells ![]() | G | 27 | 775,000$ | 775,000$ | ![]() | ||||||
Francesco Pinelli ![]() | C | 22 | 845,000$ | 845,000$ | RFA | ||||||
Helge Grans ![]() | D | 23 | 787,500$ | 787,500$ | 787,500$ | RFA | |||||
Isak Rosen ![]() | RW | 22 | 894,167$ | 894,167$ | RFA | ||||||
Jakub Brabenec ![]() | C | 22 | 828,333$ | 828,333$ | RFA | ||||||
Jeremy Davies ![]() | D | 28 | 828,000$ | 828,000$ | 828,000$ | UFA | |||||
Keith Petruzzelli ![]() | G | 26 | 850,000$ | 850,000$ | ![]() | ||||||
Landon Slaggert ![]() | LW | 23 | 800,000$ | 800,000$ | 800,000$ | RFA | |||||
Niklas Kokko ![]() | G | 21 | 891,666$ | 891,666$ | 891,666$ | RFA | |||||
Ozzy Wiesblatt ![]() | RW | 23 | 800,000$ | 800,000$ | 800,000$ | RFA | |||||
Reid Schaefer ![]() | LW | 22 | 886,666$ | 886,666$ | 886,666$ | RFA | |||||
Sergei Murashov ![]() | G | 21 | 861,110$ | 861,110$ | 861,110$ | RFA | |||||
Tye Felhaber ![]() | LW | 27 | 800,000$ | 800,000$ | 800,000$ | ![]() | |||||
Vasily Podkolzin ![]() | LW/RW | 24 | 1,000,000$ | 1,000,000$ | RFA | ||||||
Victor Mete ![]() | D | 27 | 850,000$ | 850,000$ | 850,000$ | UFA | |||||
Yan Kuznetsov ![]() | D | 23 | 850,000$ | 850,000$ | 850,000$ | RFA |
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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 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 3 | 6 | 0 | 0 | 1 | 1 | 1 | 0 | 32 | 17 | 4 | 11 | 0 | 27 | 5 | 6 | 29 | 7 | 0 | 0.00% | 3 | 0 | 100.00% | 0 | 55 | 115 | 47.83% | 45 | 108 | 41.67% | 25 | 46 | 54.35% | 22 | 14 | 24 | 8 | 12 | 6 | 60.0% | 9.4% | 92.6% | 102.0 | LUCKY | |
2 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 4 | -1 | 0 | 0.000 | 3 | 5 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 37 | 13 | 15 | 9 | 0 | 43 | 9 | 10 | 25 | 1 | 0 | 0.00% | 5 | 2 | 60.00% | 0 | 55 | 115 | 47.83% | 45 | 108 | 41.67% | 25 | 46 | 54.35% | 22 | 15 | 24 | 6 | 13 | 6 | 60.0% | 8.1% | 90.7% | 98.8 | Unlucky | |
3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 6 | 9 | 0 | 0 | 1 | 2 | 0 | 0 | 41 | 11 | 17 | 13 | 0 | 28 | 12 | 10 | 22 | 7 | 0 | 0.00% | 5 | 1 | 80.00% | 0 | 55 | 115 | 47.83% | 45 | 108 | 41.67% | 25 | 46 | 54.35% | 23 | 15 | 24 | 8 | 12 | 6 | 75.0% | 7.3% | 92.9% | 100.2 | DULL | |
_Vs Division | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 4 | -1 | 0 | 0.000 | 3 | 5 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 37 | 13 | 15 | 9 | 0 | 43 | 9 | 10 | 25 | 1 | 0 | 0.00% | 5 | 2 | 60.00% | 0 | 55 | 115 | 47.83% | 45 | 108 | 41.67% | 25 | 46 | 54.35% | 22 | 15 | 24 | 6 | 13 | 6 | 60.0% | 8.1% | 90.7% | 98.8 | Unlucky | |
_Vs Conference | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 6 | 6 | 0 | 2 | 0.500 | 6 | 8 | 14 | 0 | 0 | 2 | 2 | 2 | 0 | 69 | 30 | 19 | 20 | 0 | 70 | 14 | 16 | 54 | 8 | 0 | 0.00% | 8 | 2 | 75.00% | 0 | 55 | 115 | 47.83% | 45 | 108 | 41.67% | 25 | 46 | 54.35% | 45 | 30 | 48 | 15 | 26 | 13 | 60.0% | 8.7% | 91.4% | 100.1 | DULL | |
_Since Last GM Reset | 3 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 9 | 8 | 1 | 4 | 0.667 | 9 | 14 | 23 | 0 | 0 | 3 | 4 | 2 | 0 | 110 | 41 | 36 | 33 | 0 | 98 | 26 | 26 | 76 | 15 | 0 | 0.00% | 13 | 3 | 76.92% | 0 | 55 | 115 | 47.83% | 45 | 108 | 41.67% | 25 | 46 | 54.35% | 68 | 46 | 72 | 23 | 38 | 19 | 64.3% | 8.2% | 91.8% | 100.0 | DULL | |
Total | 3 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 9 | 8 | 1 | 4 | 0.667 | 9 | 14 | 23 | 0 | 0 | 3 | 4 | 2 | 0 | 110 | 41 | 36 | 33 | 0 | 98 | 26 | 26 | 76 | 15 | 0 | 0.00% | 13 | 3 | 76.92% | 0 | 55 | 115 | 47.83% | 45 | 108 | 41.67% | 25 | 46 | 54.35% | 68 | 46 | 72 | 23 | 38 | 19 | 64.3% | 8.2% | 91.8% | 100.0 | DULL |
Puck Time | |
---|---|
Offensive Zone | 22 |
Neutral Zone | 12 |
Defensive Zone | 24 |
Puck Time | |
---|---|
Offensive Zone Start | 115 |
Neutral Zone Start | 46 |
Defensive Zone Start | 108 |
Puck Time | |
---|---|
With Puck | 29 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 125 |
Faceoffs Lost | 144 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 13.7 | 9.57 |
2nd Period | 25.7 | 20.31 |
3rd Period | 36.7 | 30.68 |
Overtime | 36.7 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 1.0 | 0.64 |
2nd Period | 2.3 | 1.65 |
3rd Period | 3.0 | 2.67 |
Overtime | 3.0 | 2.83 |
Even Strenght Goal | 9 |
---|---|
PP Goal | 0 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 2 | 0 |
Lost | 1 | 0 |
Overtime Lost | 0 | 0 |
PP Attempt | 15 |
---|---|
PP Goal | 0 |
PK Attempt | 13 |
PK Goal Against | 3 |
Home | |
---|---|
Shots For | 36.7 |
Shots Against | 32.7 |
Goals For | 3.0 |
Goals Against | 2.7 |
Hits | 25.3 |
Shots Blocked | 8.7 |
Pim | 8.7 |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
77,478,333$ | 0$ | 77,478,336$ | 18,021,667$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | BBT Center | |
City | Florida | ||
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 | 16475 | 14509 | 5415 | 11038 | 2937 |
Attendance PCT | 91.53% | 96.73% | 90.25% | 91.98% | 97.90% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
38 | 16791 - 93.29% | 1,547,397$ | 4,642,190$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
77,478,333$ | 77,478,333$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
2,452,446$ | 403,533$ | 2,421,198$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
58,801,073$ | 186 | 408,741$ | 76,025,826$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
78,703,164$ | 77,478,333$ | 98,113,004$ | 78,210,913$ |
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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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2026 | ||||||||
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2029 | ||||||||
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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 |
Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
---|---|---|---|---|---|
Adam Ingram | 2022 | 56 | |||
Benjamin Roger | 2021 | 80 | |||
Blake Biondi | 2020 | 110 | |||
Caleb Desnoyers | 2025 | 3 | |||
Cameron Berg | 2020 | 216 | |||
Cameron Whynot | 2021 | 84 | |||
Cayden Lindstrom | 2024 | 8 | |||
Chase Yoder | |||||
Daniil But | 2023 | 30 | |||
David Edstrom | 2023 | 32 | |||
David Rozsival | 2025 | 179 | |||
Dean Letourneau | 2024 | 40 | |||
Dmitri Gamzin | 2024 | 128 | |||
Ethan Procyszyn | 2024 | 86 | |||
Gabriel D'Aigle | 2025 | 76 | |||
Haakon Hanelt | 2021 | 152 | |||
Harry Nansi | 2025 | 163 | |||
Hayden Paupanekis | 2025 | 86 | |||
Isak Walther | 2019 | 192 | 5.5 - 5.0 | ||
James Hardie | 2020 | 134 | |||
Jaromir Pytlik | 2020 | 60 | |||
Leon Muggli | 2024 | 75 | |||
Luca Marrelli | 2024 | 89 | |||
Marek Vanacker | 2024 | 41 | |||
Mason West | 2025 | 35 | |||
Michael Hrabal | 2023 | 34 | |||
Nicholas Moldenhauer | 2022 | 64 | |||
Noel Nordh | 2023 | 96 | |||
Pano Fimis | 2022 | 54 | |||
Peyton Kettles | 2025 | 70 | |||
Ryder Ritchie | 2024 | 30 | |||
Ryker Lee | 2025 | 46 | |||
Semyon Frolov | 2025 | 67 | |||
Taige Harding | 2021 | 100 | |||
Tinus-Luc Koblar | 2025 | 80 | |||
Wyatt Schingoethe | 2020 | 163 |
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