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San Jose Sharks 0-0-0, 0pts · 6th in Western |
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 | 65 | 33 | 92 | 81 | 76 | 86 | 90 | 77 | 60 | 85 | 77 | 52 | 77 | 69 | 68 | 0 | 70 | 86 | 26 | 9,350,000$/6yrs | |||
![]() | 0 | C/LW | 100.00 | 73 | 33 | 83 | 78 | 75 | 90 | 89 | 76 | 77 | 84 | 72 | 61 | 74 | 64 | 62 | 0 | 71 | 84 | 23 | 8,350,000$/6yrs | |||
![]() | 0 | C/LW | 100.00 | 63 | 32 | 90 | 71 | 73 | 88 | 90 | 70 | 88 | 76 | 69 | 74 | 70 | 89 | 99 | 0 | 55 | 83 | 37 | 6,250,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 79 | 34 | 65 | 72 | 75 | 86 | 90 | 72 | 59 | 68 | 78 | 77 | 75 | 78 | 74 | 0 | 70 | 83 | 31 | 4,500,000$/3yrs | |||
![]() | 0 | C/LW | 100.00 | 62 | 33 | 86 | 72 | 76 | 88 | 89 | 71 | 78 | 77 | 71 | 76 | 71 | 80 | 78 | 0 | 69 | 83 | 32 | 5,125,000$/4yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 85 | 45 | 76 | 64 | 81 | 84 | 89 | 66 | 79 | 67 | 69 | 77 | 67 | 89 | 92 | 0 | 47 | 81 | 37 | 4,500,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 68 | 33 | 80 | 65 | 77 | 86 | 87 | 66 | 59 | 66 | 72 | 68 | 69 | 85 | 83 | 0 | 73 | 79 | 35 | 5,350,000$/2yrs | |||
![]() | 0 | C/RW | 100.00 | 65 | 32 | 91 | 69 | 69 | 83 | 88 | 67 | 78 | 66 | 72 | 73 | 70 | 74 | 73 | 0 | 67 | 79 | 29 | 2,500,000$/1yrs | |||
![]() | 0 | RW | 100.00 | 58 | 33 | 94 | 69 | 81 | 81 | 88 | 65 | 58 | 65 | 70 | 73 | 68 | 65 | 64 | 0 | 28 | 77 | 24 | 850,000$/2yrs | |||
![]() | 0 | LW | 100.00 | 92 | 43 | 79 | 67 | 85 | 77 | 90 | 64 | 58 | 64 | 68 | 63 | 66 | 63 | 61 | 0 | 79 | 76 | 23 | ||||
![]() | 0 | C/LW/RW | 100.00 | 82 | 52 | 69 | 61 | 76 | 81 | 89 | 60 | 76 | 58 | 64 | 81 | 62 | 71 | 68 | 0 | 56 | 75 | 27 | 2,000,000$/1yrs | |||
![]() | 0 | C/LW | 100.00 | 81 | 37 | 81 | 58 | 84 | 77 | 87 | 59 | 80 | 60 | 61 | 72 | 60 | 79 | 77 | 0 | 68 | 74 | 32 | ||||
![]() | 0 | D | 100.00 | 63 | 35 | 77 | 79 | 99 | 96 | 89 | 73 | 30 | 85 | 68 | 74 | 70 | 84 | 87 | 0 | 71 | 89 | 34 | 8,000,000$/4yrs | |||
![]() | 8 | D | 100.00 | 57 | 35 | 87 | 82 | 84 | 99 | 88 | 73 | 30 | 84 | 71 | 75 | 72 | 72 | 71 | 0 | 61 | 88 | 27 | 7,500,000$/1yrs | |||
![]() | 0 | D | 100.00 | 61 | 31 | 86 | 83 | 60 | 94 | 78 | 69 | 30 | 86 | 59 | 66 | 64 | 60 | 59 | 0 | 68 | 85 | 21 | ||||
![]() | 0 | D | 100.00 | 60 | 32 | 84 | 74 | 70 | 87 | 88 | 66 | 30 | 79 | 63 | 62 | 64 | 79 | 77 | 0 | 65 | 83 | 32 | 4,350,000$/3yrs | |||
![]() | 0 | D | 100.00 | 92 | 43 | 51 | 56 | 80 | 89 | 88 | 61 | 30 | 63 | 57 | 83 | 59 | 84 | 85 | 0 | 69 | 78 | 35 | ||||
![]() | 0 | D | 100.00 | 70 | 40 | 71 | 55 | 87 | 88 | 90 | 59 | 30 | 61 | 53 | 81 | 56 | 86 | 83 | 0 | 47 | 76 | 36 | 2,000,000$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | C/LW | 100.00 | 62 | 33 | 93 | 68 | 76 | 78 | 60 | 67 | 56 | 62 | 58 | 70 | 66 | 67 | 66 | 0 | 20 | 74 | 27 | ||||
![]() | 0 | LW | 100.00 | 61 | 31 | 77 | 66 | 62 | 80 | 88 | 64 | 58 | 66 | 64 | 63 | 64 | 58 | 55 | 0 | 44 | 73 | 20 | 950,000$/1yrs | |||
TEAM AVERAGE | 100.00 | 70 | 36 | 81 | 70 | 77 | 86 | 87 | 67 | 57 | 71 | 67 | 71 | 67 | 75 | 74 | 0 | 60 | 80 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
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5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
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7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 100.00 | 89 | 95 | 83 | 75 | 92 | 83 | 91 | 93 | 89 | 96 | 91 | 87 | 92 | 0 | 52 | 92 | 36 | 10,000,000$/1yrs |
![]() | 0 | 100.00 | 85 | 93 | 80 | 77 | 86 | 78 | 88 | 93 | 87 | 92 | 88 | 81 | 86 | 0 | 57 | 90 | 33 | 1,250,000$/1yrs |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 100.00 | 87 | 94 | 82 | 76 | 89 | 81 | 90 | 93 | 88 | 94 | 90 | 84 | 89 | 0 | 55 | 91 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Paul Maurice | 93 | 91 | 84 | 94 | 97 | 81 | 72 | CAN | 50 | 4 | 1,000,000$ |
General Manager | Charles-Antoine Sirois |
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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 |
# | 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 |
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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 |
# | 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 | 88,000,000$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 0$ |
Players In Salary Cap | 17 |
LTIR Players | 0 |
Sharks Roster | Pos | Age | Cap Hit | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 | 2030-31 | 2031-32 | 2032-33 |
---|---|---|---|---|---|---|---|---|---|---|---|
Alex Killorn ![]() | LW/RW | 35 | 5,350,000$ | 5,350,000$ | 5,350,000$ | UFA | |||||
Claude Giroux ![]() | C/LW | 37 | 6,250,000$ | 6,250,000$ | UFA | ||||||
Frank Vatrano ![]() | LW/RW | 31 | 4,500,000$ | 4,500,000$ | 4,500,000$ | 4,500,000$ | UFA | ||||
Ian Cole ![]() | D | 36 | 2,000,000$ | 2,000,000$ | UFA | ||||||
Janne Kuokkanen ![]() | C/LW | 27 | 0$ | ||||||||
Lane Hutson ![]() | D | 21 | 0$ | RFA | |||||||
Luke Kunin ![]() | C/LW/RW | 27 | 2,000,000$ | 2,000,000$ | |||||||
Martin Necas ![]() | RW | 26 | 9,350,000$ | 9,350,000$ | 9,350,000$ | 9,350,000$ | 9,350,000$ | 9,350,000$ | 9,350,000$ | UFA | |
Nick Foligno ![]() | C/LW/RW | 37 | 4,500,000$ | 4,500,000$ | UFA | ||||||
Petr Mrazek ![]() | G | 33 | 1,250,000$ | 1,250,000$ | UFA | ||||||
Pius Suter ![]() | C/RW | 29 | 2,500,000$ | 2,500,000$ | UFA | ||||||
Radko Gudas ![]() | D | 35 | 0$ | UFA | |||||||
Ryan Nugent-Hopkins ![]() | C/LW | 32 | 5,125,000$ | 5,125,000$ | 5,125,000$ | 5,125,000$ | 5,125,000$ | UFA | |||
Sean Kuraly ![]() | C/LW | 32 | 0$ | UFA | |||||||
Sergei Bobrovsky | G | 36 | 10,000,000$ | 10,000,000$ | UFA | ||||||
Shayne Gostisbehere ![]() | D | 32 | 4,350,000$ | 4,350,000$ | 4,350,000$ | 4,350,000$ | UFA | ||||
Simon Holmstrom ![]() | RW | 24 | 850,000$ | 850,000$ | 850,000$ | ||||||
Tim Stutzle ![]() | C/LW | 23 | 8,350,000$ | 8,350,000$ | 8,350,000$ | 8,350,000$ | 8,350,000$ | 8,350,000$ | 8,350,000$ | UFA | |
Victor Hedman ![]() | D | 34 | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | UFA | |||
Will Cuylle ![]() | LW | 23 | 0$ | RFA | |||||||
Zach Benson ![]() | LW | 20 | 950,000$ | 950,000$ | RFA | ||||||
Zach Werenski ![]() | D | 27 | 7,500,000$ | 7,500,000$ |
Non-Roster | Pos | Age | Cap Hit | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 | 2030-31 | 2031-32 | 2032-33 |
---|---|---|---|---|---|---|---|---|---|---|---|
Aatu Raty ![]() | C | 22 | 0$ | RFA | |||||||
Aidan McDonough ![]() | C/LW | 25 | 800,000$ | 800,000$ | ![]() | ||||||
Amadeus Lombardi ![]() | C | 22 | 838,333$ | 838,333$ | RFA | ||||||
Bobby Brink ![]() | RW | 23 | 1,500,000$ | 1,500,000$ | RFA | ||||||
Brendan Brisson ![]() | C/LW/RW | 23 | 0$ | RFA | |||||||
Brett Murray ![]() | LW | 26 | 0$ | ![]() | |||||||
Christian Kyrou ![]() | D | 21 | 870,000$ | 870,000$ | RFA | ||||||
Clay Hanus ![]() | D | 24 | 0$ | RFA | |||||||
Daniil Chechelev ![]() | G | 24 | 0$ | RFA | |||||||
Ethan Del Mastro ![]() | D | 22 | 855,833$ | 855,833$ | RFA | ||||||
Evan Cormier ![]() | G | 27 | 0$ | ![]() | |||||||
Filip Bystedt ![]() | C | 21 | 950,000$ | 950,000$ | RFA | ||||||
Filip Hallander ![]() | C | 24 | 0$ | ![]() | |||||||
Gavin White ![]() | D | 22 | 857,500$ | 857,500$ | RFA | ||||||
Hunter Brzustewicz ![]() | D | 20 | 0$ | RFA | |||||||
Ilya Usov ![]() | C | 23 | 0$ | RFA | |||||||
Jack Malone ![]() | C/LW/RW | 24 | 0$ | RFA | |||||||
Jacob Ingham ![]() | G | 25 | 900,000$ | 900,000$ | ![]() | ||||||
Joel Blomqvist ![]() | G | 23 | 886,667$ | 886,667$ | RFA | ||||||
Justin Richards ![]() | C/RW | 27 | 800,000$ | 800,000$ | ![]() | ||||||
Marc-Andre Gaudet ![]() | D | 22 | 0$ | RFA | |||||||
Matthew Poitras ![]() | C | 21 | 870,000$ | 870,000$ | RFA | ||||||
Nathan Clurman ![]() | D | 27 | 0$ | ![]() | |||||||
Nick Cicek ![]() | D | 25 | 0$ | ![]() | |||||||
Nick Wolff ![]() | D | 28 | 0$ | UFA | |||||||
Noah ostlund ![]() | C | 21 | 918,333$ | 918,333$ | RFA | ||||||
Oskar Pettersson ![]() | RW | 21 | 865,000$ | 865,000$ | RFA | ||||||
Otto Stenberg ![]() | C/LW/RW | 20 | 0$ | RFA | |||||||
Owen Beck ![]() | C | 21 | 885,000$ | 885,000$ | RFA | ||||||
Paul Ludwinski ![]() | C | 21 | 931,667$ | 931,667$ | RFA | ||||||
Pheonix Copley ![]() | G | 33 | 0$ | UFA | |||||||
Robert Calisti ![]() | D | 24 | 0$ | RFA | |||||||
Talyn Boyko ![]() | G | 22 | 0$ | RFA | |||||||
Tim Berni ![]() | D | 25 | 0$ | ![]() | |||||||
Ty Mueller ![]() | C | 22 | 0$ | RFA | |||||||
Ville Ottavainen ![]() | D | 22 | 867,500$ | 867,500$ | 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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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 | |
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Offensive Zone | NAN |
Neutral Zone | NAN |
Defensive Zone | NAN |
Puck Time | |
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Offensive Zone Start | 0 |
Neutral Zone Start | 0 |
Defensive Zone Start | 0 |
Puck Time | |
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With Puck | NAN |
Without Puck | NAN |
Faceoffs | |
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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 |
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PP Goal | 0 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
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Win | 0 | 0 |
Lost | 0 | 0 |
Overtime Lost | 0 | 0 |
PP Attempt | 0 |
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PP Goal | 0 |
PK Attempt | 0 |
PK Goal Against | 0 |
Home | |
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Shots For | nan |
Shots Against | nan |
Goals For | nan |
Goals Against | nan |
Hits | nan |
Shots Blocked | nan |
Pim | nan |
Date | Matchup | Result | Detail |
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Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
82,825,000$ | 0$ | 0$ | 5,175,000$ |
Arena | Goal Horn | About us | |
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![]() | Name | HP Pavilion at San Jose | |
City | San Jose | ||
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 |
41 | 0 - 0.00% | 0$ | 0$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
82,825,000$ | 82,825,000$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
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0$ | 0$ | 0$ | 0$ |
Estimate | |||
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Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 0 | 0$ | 0$ |
Team Total Estimate | |||
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Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
0$ | 82,825,000$ | 45,273,619$ | 45,273,619$ |
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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2025 | ||||||||
2026 | ||||||||
2027 | ||||||||
2028 | ||||||||
2029 |
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 |
---|---|---|---|---|---|
Alex Ciernik | 2023 | 62 | |||
Ben Boyd | 2021 | 194 | |||
Cameron Whitehead | 2022 | 126 | |||
Carey Terrance | 2023 | 80 | |||
Carson Wetsch | 2024 | 109 | |||
Chandler Romeo | 2021 | 217 | |||
Charlie Stramel | 2023 | 49 | |||
Chris Pelosi | 2023 | 109 | |||
Cole Huckins | 2021 | 85 | |||
Dalyn Wakely | 2024 | 205 | |||
Egor Zavragin | 2023 | 81 | |||
Ethan Bowen | 2020 | 175 | |||
Evan Vierling | 2020 | 105 | |||
Filip Barklund | |||||
Jonathan Castagna | 2023 | 85 | |||
Jordan Gustafson | 2022 | 92 | |||
Ludvig Jansson | 2022 | 139 | |||
Nick Malik | 2020 | 85 | |||
Quinn Finley | 2022 | 98 | |||
Quinn Olson | 2019 | 98 | |||
Samu Salminen | 2021 | 53 | |||
Tanner Ludtke | 2023 | 101 | |||
Victor Johansson | 2024 | 143 | |||
Viktor Hurtig | 2021 | 185 |