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---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 19 | C | 100.00 | 77 | 42 | 76 | 62 | 91 | 79 | 80 | 63 | 78 | 65 | 62 | 61 | 63 | 64 | 66 | 0 | 50 | 70 | 25 | 925,000$/2yrs | |||
![]() | 26 | LW | 100.00 | 75 | 42 | 86 | 64 | 86 | 71 | 70 | 64 | 53 | 62 | 68 | 55 | 64 | 66 | 68 | 0 | 50 | 69 | 27 | 1,028,000$/1yrs | |||
![]() | 36 | LW/RW | 100.00 | 60 | 37 | 94 | 66 | 76 | 87 | 95 | 65 | 62 | 61 | 63 | 58 | 67 | 64 | 66 | 0 | 50 | 69 | 25 | 831,500$/2yrs | |||
![]() | 37 | C | 100.00 | 83 | 46 | 80 | 62 | 81 | 69 | 72 | 63 | 64 | 62 | 60 | 57 | 62 | 65 | 63 | 0 | 50 | 67 | 24 | 900,000$/1yrs | |||
![]() | 29 | RW | 100.00 | 63 | 38 | 87 | 59 | 80 | 77 | 68 | 63 | 56 | 61 | 58 | 64 | 62 | 66 | 68 | 0 | 50 | 67 | 27 | 750,000$/1yrs | |||
![]() | 33 | C | 100.00 | 71 | 38 | 92 | 58 | 73 | 85 | 86 | 59 | 68 | 58 | 59 | 60 | 59 | 70 | 72 | 0 | 50 | 67 | 30 | 758,333$/3yrs | |||
![]() | 24 | C | 100.00 | 63 | 39 | 86 | 56 | 72 | 83 | 88 | 57 | 70 | 59 | 60 | 58 | 61 | 85 | 74 | 0 | 50 | 66 | 37 | 750,000$/1yrs | |||
![]() | 34 | C | 100.00 | 63 | 39 | 86 | 63 | 72 | 80 | 73 | 62 | 54 | 58 | 61 | 56 | 63 | 65 | 67 | 0 | 50 | 66 | 25 | 863,333$/1yrs | |||
![]() | 57 | C | 100.00 | 71 | 39 | 75 | 62 | 70 | 79 | 81 | 60 | 64 | 58 | 61 | 57 | 62 | 61 | 63 | 0 | 50 | 66 | 21 | 1,005,000$/4yrs | |||
![]() | 20 | C | 100.00 | 60 | 38 | 86 | 62 | 69 | 81 | 94 | 61 | 72 | 60 | 56 | 57 | 62 | 65 | 67 | 0 | 50 | 66 | 25 | 775,000$/2yrs | |||
![]() | 3 | C | 100.00 | 67 | 38 | 93 | 56 | 80 | 79 | 74 | 57 | 76 | 58 | 59 | 62 | 56 | 63 | 64 | 0 | 50 | 65 | 23 | 1,117,667$/3yrs | |||
![]() | 15 | D | 100.00 | 63 | 38 | 87 | 71 | 76 | 84 | 88 | 67 | 30 | 66 | 57 | 63 | 50 | 67 | 69 | 0 | 50 | 70 | 26 | 1,207,000$/2yrs | |||
![]() | 53 | D | 100.00 | 67 | 38 | 91 | 68 | 79 | 83 | 75 | 67 | 30 | 66 | 64 | 61 | 53 | 61 | 63 | 0 | 50 | 70 | 21 | 1,158,333$/3yrs | |||
![]() | 58 | D | 100.00 | 70 | 39 | 81 | 69 | 83 | 81 | 79 | 68 | 30 | 67 | 59 | 63 | 52 | 61 | 63 | 0 | 50 | 70 | 21 | 1,713,333$/3yrs | |||
![]() | 40 | D | 100.00 | 77 | 34 | 79 | 60 | 86 | 70 | 91 | 58 | 30 | 60 | 54 | 58 | 49 | 66 | 68 | 0 | 50 | 67 | 26 | 1,847,000$/1yrs | |||
![]() | 4 | D | 100.00 | 76 | 72 | 87 | 59 | 88 | 78 | 71 | 58 | 30 | 60 | 56 | 61 | 48 | 65 | 66 | 0 | 50 | 67 | 27 | 1,000,000$/1yrs | |||
![]() | 9 | D | 100.00 | 64 | 35 | 79 | 66 | 68 | 87 | 69 | 64 | 30 | 60 | 62 | 57 | 52 | 61 | 62 | 0 | 50 | 66 | 22 | 1,268,750$/4yrs | |||
![]() | 18 | D | 100.00 | 66 | 38 | 84 | 59 | 75 | 77 | 89 | 54 | 30 | 61 | 56 | 57 | 52 | 63 | 65 | 0 | 50 | 65 | 24 | 780,000$/2yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 27 | C | 100.00 | 67 | 38 | 83 | 65 | 66 | 85 | 82 | 63 | 72 | 64 | 65 | 68 | 62 | 70 | 69 | 0 | 50 | 70 | 30 | 750,000$/1yrs | |||
![]() | 22 | C | 100.00 | 81 | 42 | 77 | 55 | 90 | 61 | 76 | 57 | 64 | 56 | 52 | 59 | 53 | 61 | 63 | 0 | 50 | 65 | 21 | 825,000$/3yrs | |||
![]() | 13 | C | 100.00 | 69 | 37 | 64 | 55 | 78 | 80 | 79 | 56 | 63 | 58 | 57 | 59 | 55 | 67 | 69 | 0 | 50 | 65 | 27 | 786,000$/1yrs | |||
![]() | 61 | C | 100.00 | 69 | 37 | 62 | 58 | 78 | 72 | 80 | 57 | 62 | 56 | 53 | 55 | 54 | 63 | 65 | 0 | 50 | 64 | 24 | 786,667$/1yrs | |||
![]() | 2 | RW | 100.00 | 59 | 38 | 78 | 54 | 69 | 81 | 83 | 55 | 59 | 56 | 58 | 53 | 58 | 63 | 65 | 0 | 50 | 63 | 24 | 855,000$/1yrs | |||
![]() | 32 | D | 100.00 | 58 | 38 | 79 | 59 | 67 | 71 | 74 | 53 | 30 | 58 | 56 | 54 | 45 | 63 | 65 | 0 | 50 | 62 | 23 | 850,833$/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 | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 1 | 100.00 | 77 | 76 | 77 | 97 | 76 | 75 | 77 | 76 | 75 | 77 | 76 | 68 | 81 | 0 | 50 | 79 | 29 | 800,000$/2yrs |
![]() | 14 | 100.00 | 75 | 67 | 65 | 70 | 74 | 73 | 75 | 74 | 73 | 75 | 74 | 70 | 84 | 0 | 50 | 75 | 30 | 750,000$/1yrs |
Scratches | ||||||||||||||||||||
![]() | 46 | 100.00 | 72 | 79 | 78 | 90 | 71 | 70 | 72 | 71 | 70 | 72 | 71 | 62 | 67 | 0 | 50 | 74 | 23 | 925,000$/3yrs |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Jacques Lemaire | 75 | 75 | 75 | 75 | 75 | 75 | 75 | CAN | 73 | 4 | 0$ |
General Manager |
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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 | PPG | PPA | PPP | PKG | PKA | PKP | PKM | GW | GT | FO% | EG | HT | P/GP | PSG | PSS | GSAVG |
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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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Player Name | POS | Age | Cap Hit | 2017-18 | 2018-19 | 2019-20 | 2020-21 | 2021-22 | 2022-23 | 2023-24 | 2024-25 |
---|---|---|---|---|---|---|---|---|---|---|---|
Akira Schmid ![]() | G | 23 | 925,000$ | 925,000$ | 925,000$ | 925,000$ | ![]() | ||||
Alex Nylander ![]() | LW/RW | 25 | 831,500$ | 913,000$ | 750,000$ | ![]() | |||||
Brendan Perlini ![]() | LW | 27 | 1,028,000$ | 1,028,000$ | UFA | ||||||
Chris Mueller ![]() | C | 37 | 750,000$ | 750,000$ | UFA | ||||||
Christian Jaros ![]() | D | 27 | 1,000,000$ | 1,000,000$ | UFA | ||||||
Connor Zary ![]() | C | 21 | 1,005,000$ | 1,005,000$ | 1,005,000$ | 1,005,000$ | 1,005,000$ | ![]() | |||
David Gustafsson ![]() | C | 23 | 1,117,667$ | 1,803,000$ | 775,000$ | 775,000$ | ![]() | ||||
Jake McGrew ![]() | RW | 24 | 855,000$ | 855,000$ | ![]() | ||||||
Jasper Weatherby ![]() | C | 25 | 925,000$ | 925,000$ | 925,000$ | ![]() | |||||
Jon Gillies ![]() | G | 29 | 800,000$ | 850,000$ | 750,000$ | UFA | |||||
Jordan Harris ![]() | D | 22 | 1,268,750$ | 1,137,500$ | 1,137,500$ | 1,400,000$ | 1,400,000$ | ![]() | |||
Justin Barron ![]() | D | 21 | 1,158,333$ | 1,158,333$ | 1,158,333$ | 1,158,333$ | RFA | ||||
Justin Scott ![]() | C | 27 | 786,000$ | 786,000$ | UFA | ||||||
Kyle Rau ![]() | C | 30 | 750,000$ | 750,000$ | UFA | ||||||
Lean Bergmann ![]() | C | 24 | 900,000$ | 900,000$ | ![]() | ||||||
Leon Gawanke ![]() | D | 24 | 780,000$ | 810,000$ | 750,000$ | ![]() | |||||
Linus Sandin ![]() | RW | 27 | 750,000$ | 750,000$ | UFA | ||||||
Mason Primeau ![]() | C | 21 | 825,000$ | 825,000$ | 825,000$ | 825,000$ | RFA | ||||
Mitchell Gillam ![]() | G | 30 | 750,000$ | 750,000$ | UFA | ||||||
Pascal Laberge ![]() | C | 25 | 863,333$ | 863,333$ | ![]() | ||||||
Philip Broberg ![]() | D | 21 | 1,713,333$ | 1,713,333$ | 1,713,333$ | 1,713,333$ | RFA | ||||
Simon Ryfors ![]() | C | 25 | 775,000$ | 800,000$ | 750,000$ | ![]() | |||||
Thomas Schemitsch ![]() | D | 26 | 1,847,000$ | 1,847,000$ | ![]() | ||||||
Travis Dermott ![]() | D | 26 | 1,207,000$ | 914,000$ | 1,500,000$ | UFA | |||||
Turner Elson ![]() | C | 30 | 758,333$ | 750,000$ | 762,500$ | 762,500$ | UFA | ||||
Victor Berglund ![]() | D | 23 | 850,833$ | 850,833$ | RFA | ||||||
Zachary Gallant ![]() | C | 24 | 786,667$ | 786,667$ | ![]() |
Forward Lines | |||||||
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Goalies | |||||||
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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 | |
---|---|---|
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 | |||
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Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
2,644,599$ | 0$ | 0$ | 75,000,000$ |
Arena | About us | |
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![]() | Name | |
City | San Jose | |
Capacity | 3000 | |
Season Ticket Holders | 10% |
Arena Capacity - Ticket Price Attendance - % | |||||
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Arena Capacity | 2000 | 1000 | |||
Ticket Price | 40$ | 20$ | $ | $ | $ |
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$ | 3000 | 100 |
Expenses | |||
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Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
2,644,599$ | 2,600,674$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
0$ | 0$ | 0$ | 0$ |
Estimate | |||
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Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 7 | 0$ | 0$ |
Team Total Estimate | |||
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Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
0$ | 0$ | 0$ | 0$ |
Sponsors | |||
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TV Rights | Primary Sponsor | Secondary Sponsor | Secondary Sponsor |
Left Wing | Center | Right Wing |
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Defense #1 | Defense #2 | Goalie |
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