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---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | LW | 100.00 | 59 | 37 | 90 | 81 | 83 | 88 | 94 | 82 | 58 | 83 | 85 | 62 | 84 | 65 | 70 | 0 | 80 | 23 | 6,378,834$/5yrs | |||||
![]() | C | 100.00 | 62 | 50 | 89 | 84 | 67 | 89 | 94 | 82 | 79 | 80 | 83 | 65 | 84 | 69 | 71 | 0 | 79 | 27 | 8,915,444$/9yrs | |||||
![]() | C | 100.00 | 58 | 35 | 92 | 82 | 76 | 89 | 87 | 81 | 76 | 80 | 82 | 66 | 83 | 65 | 66 | 0 | 78 | 24 | 7,452,000$/3yrs | |||||
![]() | LW | 100.00 | 82 | 77 | 66 | 68 | 99 | 86 | 81 | 66 | 52 | 74 | 67 | 73 | 69 | 67 | 68 | 0 | 76 | 26 | 3,369,750$/4yrs | |||||
![]() | C | 100.00 | 56 | 35 | 88 | 82 | 78 | 86 | 79 | 76 | 73 | 71 | 74 | 65 | 77 | 70 | 72 | 0 | 75 | 28 | 2,158,000$/2yrs | |||||
![]() | RW | 100.00 | 67 | 39 | 91 | 75 | 82 | 83 | 86 | 74 | 58 | 73 | 71 | 62 | 76 | 66 | 67 | 0 | 75 | 25 | 1,827,500$/2yrs | |||||
![]() | C | 100.00 | 69 | 35 | 86 | 70 | 75 | 84 | 87 | 70 | 65 | 73 | 71 | 63 | 69 | 82 | 76 | 0 | 74 | 33 | 2,961,000$/2yrs | |||||
![]() | LW | 100.00 | 58 | 36 | 84 | 73 | 81 | 88 | 79 | 75 | 62 | 74 | 71 | 64 | 76 | 61 | 62 | 0 | 74 | 22 | 5,955,444$/9yrs | |||||
![]() | C | 100.00 | 62 | 35 | 83 | 75 | 77 | 87 | 72 | 76 | 80 | 74 | 71 | 65 | 77 | 61 | 64 | 0 | 74 | 20 | 1,850,000$/3yrs | |||||
![]() | C | 100.00 | 57 | 45 | 82 | 71 | 83 | 86 | 89 | 72 | 81 | 73 | 66 | 61 | 74 | 61 | 62 | 0 | 72 | 22 | 6,186,444$/9yrs | |||||
![]() | LW | 100.00 | 72 | 36 | 83 | 69 | 81 | 84 | 82 | 66 | 56 | 67 | 71 | 60 | 66 | 67 | 69 | 0 | 72 | 27 | 2,351,000$/3yrs | |||||
![]() | D | 100.00 | 79 | 38 | 81 | 79 | 75 | 94 | 87 | 76 | 30 | 89 | 70 | 77 | 58 | 86 | 78 | 0 | 81 | 36 | 5,896,714$/7yrs | |||||
![]() | D | 100.00 | 56 | 37 | 93 | 71 | 83 | 94 | 93 | 70 | 30 | 78 | 68 | 81 | 56 | 81 | 72 | 0 | 77 | 31 | 6,009,000$/5yrs | |||||
![]() | D | 100.00 | 62 | 33 | 88 | 77 | 64 | 93 | 88 | 69 | 30 | 81 | 65 | 71 | 56 | 66 | 69 | 0 | 75 | 25 | 4,538,166$/6yrs | |||||
![]() | D | 100.00 | 77 | 75 | 73 | 65 | 92 | 87 | 88 | 63 | 30 | 74 | 66 | 77 | 55 | 68 | 69 | 0 | 75 | 28 | 2,847,000$/2yrs | |||||
![]() | D | 100.00 | 71 | 38 | 76 | 63 | 81 | 88 | 80 | 62 | 30 | 70 | 64 | 77 | 52 | 78 | 74 | 0 | 73 | 32 | 3,009,000$/2yrs | |||||
![]() | D | 100.00 | 73 | 39 | 78 | 65 | 77 | 88 | 90 | 64 | 30 | 63 | 58 | 73 | 53 | 66 | 68 | 0 | 71 | 26 | 1,162,500$/4yrs | |||||
![]() | D | 100.00 | 71 | 36 | 85 | 63 | 80 | 85 | 76 | 58 | 30 | 60 | 55 | 76 | 50 | 69 | 71 | 0 | 70 | 29 | 2,679,750$/4yrs | |||||
Scratches | ||||||||||||||||||||||||||
![]() | D | 100.00 | 59 | 36 | 93 | 72 | 68 | 86 | 81 | 71 | 30 | 70 | 64 | 66 | 54 | 61 | 63 | 0 | 71 | 22 | 1,308,166$/2yrs | |||||
TEAM AVERAGE | 100.00 | 66 | 42 | 84 | 73 | 79 | 88 | 85 | 71 | 52 | 74 | 70 | 69 | 67 | 69 | 69 | 0 | 75 |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | OV | AGE | CONTRACT | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 100.00 | 88 | 72 | 80 | 97 | 87 | 86 | 88 | 87 | 86 | 88 | 87 | 85 | 89 | 0 | 88 | 36 | 5,742,334$/2yrs | |
![]() | 0 | 100.00 | 87 | 89 | 92 | 93 | 86 | 85 | 87 | 86 | 85 | 87 | 86 | 64 | 71 | 0 | 86 | 24 | 3,866,500$/4yrs | |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 100.00 | 88 | 81 | 86 | 95 | 87 | 86 | 88 | 87 | 86 | 88 | 87 | 75 | 80 | 0 | 87 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Reggie Dunlop | 75 | 75 | 75 | 75 | 75 | 75 | 75 | USA | 83 | 4 | 0$ |
General Manager | Alexis Vincent |
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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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Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | VS Team | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | P | PCT | G | A | TP | SO | EG | GP1 | GP2 | GP3 | GP4 | SHF | SH1 | SP2 | SP3 | SP4 | SHA | SHB | Pim | Hit | PPA | PPG | PP% | PKA | PK GA | PK% | PK GF | W OF FO | T OF FO | OF FO% | W DF FO | T DF FO | DF FO% | W NT FO | T NT FO | NT FO% | PZ DF | PZ OF | PZ NT | PC DF | PC OF | PC NT | GF% | SH% | SV% | PDO | PDOBRK |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Total | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.000 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0 | nan% | nan% | nan% | nan | Unlucky |
Puck Time | |
---|---|
Offensive Zone | NAN |
Neutral Zone | NAN |
Defensive Zone | NAN |
Puck Time | |
---|---|
Offensive Zone Start | 0 |
Neutral Zone Start | 0 |
Defensive Zone Start | 0 |
Puck Time | |
---|---|
With Puck | NAN |
Without Puck | NAN |
Faceoffs | |
---|---|
Faceoffs Won | 0 |
Faceoffs Lost | 0 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | nan | 9.57 |
2nd Period | nan | 20.31 |
3rd Period | nan | 30.68 |
Overtime | nan | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | nan | 0.64 |
2nd Period | nan | 1.65 |
3rd Period | nan | 2.67 |
Overtime | nan | 2.83 |
Even Strenght Goal | 0 |
---|---|
PP Goal | 0 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 0 | 0 |
Lost | 0 | 0 |
Overtime Lost | 0 | 0 |
PP Attempt | 0 |
---|---|
PP Goal | 0 |
PK Attempt | 0 |
PK Goal Against | 0 |
Home | |
---|---|
Shots For | nan |
Shots Against | nan |
Goals For | nan |
Goals Against | nan |
Hits | nan |
Shots Blocked | nan |
Pim | nan |
![]() | |
Projected Total Cap Hit | 0$ |
Projected Cap Space | 82,500,000$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 0$ |
Players In Salary Cap | 21 |
Contracts | 48/50 |
LTIR Players | 0 |
Stars Roster | Pos | Age | Cap Hit | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 |
---|---|---|---|---|---|---|---|---|---|---|---|
Andreas Athanasiou ![]() | C | 28 | 2,158,000$ | 1,316,000$ | 3,000,000$ | UFA | |||||
Ben Bishop ![]() | G | 36 | 5,742,334$ | 6,568,000$ | 4,916,667$ | UFA | |||||
Brayden Point ![]() | C | 27 | 8,915,444$ | 4,239,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ |
Cam Fowler ![]() | D | 31 | 6,009,000$ | 4,045,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | UFA | ||
Cam York ![]() | D | 22 | 1,308,166$ | 1,308,333$ | 1,308,000$ | RFA | |||||
Carson Soucy ![]() | D | 28 | 2,847,000$ | 2,944,000$ | 2,750,000$ | UFA | |||||
Craig Smith ![]() | C | 33 | 2,961,000$ | 2,822,000$ | 3,100,000$ | UFA | |||||
Denis Gurianov ![]() | RW | 25 | 1,827,500$ | 755,000$ | 2,900,000$ | UFA | |||||
Dylan Cozens ![]() | C | 22 | 6,186,444$ | 4,234,000$ | 1,744,000$ | 7,100,000$ | 7,100,000$ | 7,100,000$ | 7,100,000$ | 7,100,000$ | 7,100,000$ |
Dysin Mayo ![]() | D | 26 | 1,162,500$ | 1,800,000$ | 950,000$ | 950,000$ | 950,000$ | UFA | |||
Elias Pettersson ![]() | C | 24 | 7,452,000$ | 7,656,000$ | 7,350,000$ | 7,350,000$ | ![]() | ||||
Jake Oettinger ![]() | G | 24 | 3,866,500$ | 3,466,000$ | 4,000,000$ | 4,000,000$ | 4,000,000$ | UFA | |||
Jason Robertson ![]() | LW | 23 | 6,378,834$ | 894,167$ | 7,750,000$ | 7,750,000$ | 7,750,000$ | 7,750,000$ | UFA | ||
Jordan Greenway ![]() | LW | 26 | 3,369,750$ | 4,479,000$ | 3,000,000$ | 3,000,000$ | 3,000,000$ | UFA | |||
Kris Letang ![]() | D | 36 | 5,896,714$ | 4,677,000$ | 6,100,000$ | 6,100,000$ | 6,100,000$ | 6,100,000$ | 6,100,000$ | 6,100,000$ | UFA |
Matt Boldy ![]() | LW | 22 | 5,955,444$ | 3,274,000$ | 1,325,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ |
Matty Beniers ![]() | C | 20 | 1,850,000$ | 1,850,000$ | 1,850,000$ | 1,850,000$ | RFA | ||||
Samuel Girard ![]() | D | 25 | 4,538,166$ | 2,229,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | UFA | |
Travis Hamonic ![]() | D | 32 | 3,009,000$ | 3,018,000$ | 3,000,000$ | UFA | |||||
Tucker Poolman ![]() | D | 29 | 2,679,750$ | 3,219,000$ | 2,500,000$ | 2,500,000$ | 2,500,000$ | UFA | |||
Warren Foegele ![]() | LW | 27 | 2,351,000$ | 1,553,000$ | 2,750,000$ | 2,750,000$ | UFA |
Non-Roster | Pos | Age | Cap Hit | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 |
---|---|---|---|---|---|---|---|---|---|---|---|
Aleksi Heponiemi ![]() | C | 24 | 1,262,500$ | 1,775,000$ | 750,000$ | ![]() | |||||
Andreas Englund ![]() | D | 27 | 750,000$ | 700,000$ | 750,000$ | UFA | |||||
Arvid Holm ![]() | G | 24 | 873,333$ | 873,333$ | 873,333$ | ![]() | |||||
Bobby Brink ![]() | RW | 21 | 1,137,500$ | 1,137,500$ | 1,137,500$ | 1,137,500$ | RFA | ||||
Brogan Rafferty ![]() | D | 28 | 1,625,000$ | 2,500,000$ | 750,000$ | UFA | |||||
Calen Addison ![]() | D | 23 | 910,833$ | 910,833$ | 910,833$ | ![]() | |||||
Cameron Hillis ![]() | C | 22 | 910,000$ | 910,000$ | 910,000$ | ![]() | |||||
Dominik Simon ![]() | C | 28 | 917,000$ | 917,000$ | UFA | ||||||
Dustin Wolf ![]() | G | 22 | 825,000$ | 825,000$ | 825,000$ | 825,000$ | ![]() | ||||
Dylan Blujus ![]() | D | 29 | 1,099,000$ | 1,099,000$ | UFA | ||||||
Grigori Denisenko ![]() | LW | 22 | 1,775,000$ | 1,775,000$ | 1,775,000$ | ![]() | |||||
Harri Sateri ![]() | G | 33 | 1,000,000$ | 1,000,000$ | UFA | ||||||
Jack Drury ![]() | C | 23 | 925,000$ | 925,000$ | 925,000$ | 925,000$ | ![]() | ||||
Joel Teasdale ![]() | LW | 24 | 1,325,000$ | 1,900,000$ | 750,000$ | ![]() | |||||
Joshua Ho-Sang ![]() | RW | 27 | 1,000,000$ | 1,000,000$ | UFA | ||||||
Justin Kapelmaster ![]() | G | 27 | 1,200,000$ | 1,200,000$ | UFA | ||||||
Kole Lind ![]() | RW | 24 | 987,500$ | 1,125,000$ | 850,000$ | ![]() | |||||
Kyle Capobianco ![]() | D | 25 | 958,000$ | 1,349,000$ | 762,500$ | 762,500$ | UFA | ||||
Nicholas Robertson ![]() | LW | 21 | 796,667$ | 796,667$ | 796,667$ | 796,667$ | RFA | ||||
Nikita Alexandrov ![]() | C | 22 | 880,000$ | 880,000$ | 880,000$ | 880,000$ | ![]() | ||||
Pavel Dorofeyev ![]() | LW | 22 | 925,000$ | 925,000$ | 925,000$ | RFA | |||||
Rob Hamilton ![]() | D | 29 | 1,213,000$ | 1,213,000$ | UFA | ||||||
Ryan Lohin ![]() | C | 26 | 1,100,000$ | 1,100,000$ | UFA | ||||||
Scott Wilson ![]() | LW | 31 | 975,000$ | 975,000$ | UFA | ||||||
Sheldon Rempal ![]() | RW | 27 | 844,667$ | 1,009,000$ | 762,500$ | 762,500$ | UFA | ||||
Vinni Lettieri ![]() | C | 28 | 982,500$ | 1,215,000$ | 750,000$ | UFA | |||||
Vitali Kravtsov ![]() | LW | 23 | 1,325,000$ | 1,775,000$ | 875,000$ | ![]() |
Forward Lines | |||||||
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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 | |
---|---|
Offensive Zone | NAN |
Neutral Zone | NAN |
Defensive Zone | NAN |
Puck Time | |
---|---|
Offensive Zone Start | 0 |
Neutral Zone Start | 0 |
Defensive Zone Start | 0 |
Puck Time | |
---|---|
With Puck | NAN |
Without Puck | NAN |
Faceoffs | |
---|---|
Faceoffs Won | 0 |
Faceoffs Lost | 0 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | nan | 9.57 |
2nd Period | nan | 20.31 |
3rd Period | nan | 30.68 |
Overtime | nan | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | nan | 0.64 |
2nd Period | nan | 1.65 |
3rd Period | nan | 2.67 |
Overtime | nan | 2.83 |
Even Strenght Goal | 0 |
---|---|
PP Goal | 0 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 0 | 0 |
Lost | 0 | 0 |
Overtime Lost | 0 | 0 |
PP Attempt | 0 |
---|---|
PP Goal | 0 |
PK Attempt | 0 |
PK Goal Against | 0 |
Home | |
---|---|
Shots For | nan |
Shots Against | nan |
Goals For | nan |
Goals Against | nan |
Hits | nan |
Shots Blocked | nan |
Pim | nan |
Date | Matchup | Result | Detail |
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Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
66,346,500$ | 0$ | 0$ | 82,500,000$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | American Airlines Center | |
City | Dallas | ||
Capacity | 17000 | ||
Season Ticket Holders | 40% |
Arena Capacity - Ticket Price Attendance - % | |||||
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Arena Capacity | 5000 | 4000 | 3000 | 4000 | 1000 |
Ticket Price | 100$ | 55$ | 15$ | 10$ | 125$ |
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$ | 17000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
66,346,500$ | 86,464,546$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
0$ | 0$ | 0$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 7 | 0$ | 0$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
0$ | 0$ | 38,267,777$ | 38,267,777$ |
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 |
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2023 | ![]() | ![]() ![]() | ![]() ![]() | ![]() ![]() | ![]() | ![]() | |
2024 | ![]() ![]() | ![]() ![]() | ![]() | ![]() | ![]() ![]() | ![]() | ![]() |
2025 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2026 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2027 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() ![]() | ![]() ![]() |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
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Aleksi Heimosalmi | ![]() | 2022 | 70 | ||
Brock Faber | ![]() | 2021 | 48 | ||
Erik Portillo | ![]() | 2020 | 91 | ||
Ilya Fedotov | ![]() | 2022 | 66 | ||
Isaak Rosen | ![]() | 2022 | 29 | ||
Justin Ertel | ![]() | 2022 | 134 | ||
Karl Henriksson | ![]() | 2020 | 85 | ||
Kent Johnson | ![]() | 2022 | 9 | ||
Kieran Ruscheinski | ![]() | 2020 | 215 | ||
Kyle Masters | ![]() | 2022 | 166 | ||
Lane Zablocki | ![]() | 2018 | 145 | ||
Olof Lindbom | ![]() | 2019 | 53 | ||
Petr Kvaca | ![]() | 2018 | 176 | ||
Ruslan Iskhakov | ![]() | 2019 | 57 | ||
Scott Walford | ![]() | 2018 | 124 | ||
Theo Jacobsson | ![]() | 2022 | 198 |
Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
---|---|---|---|---|---|---|---|
2023 | ![]() | ![]() ![]() | ![]() ![]() | ![]() ![]() | ![]() | ![]() | |
2024 | ![]() ![]() | ![]() ![]() | ![]() | ![]() | ![]() ![]() | ![]() | ![]() |
2025 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2026 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2027 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() ![]() | ![]() ![]() |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
---|---|---|---|---|---|
Aleksi Heimosalmi | ![]() | 2022 | 70 | ||
Brock Faber | ![]() | 2021 | 48 | ||
Erik Portillo | ![]() | 2020 | 91 | ||
Ilya Fedotov | ![]() | 2022 | 66 | ||
Isaak Rosen | ![]() | 2022 | 29 | ||
Justin Ertel | ![]() | 2022 | 134 | ||
Karl Henriksson | ![]() | 2020 | 85 | ||
Kent Johnson | ![]() | 2022 | 9 | ||
Kieran Ruscheinski | ![]() | 2020 | 215 | ||
Kyle Masters | ![]() | 2022 | 166 | ||
Lane Zablocki | ![]() | 2018 | 145 | ||
Olof Lindbom | ![]() | 2019 | 53 | ||
Petr Kvaca | ![]() | 2018 | 176 | ||
Ruslan Iskhakov | ![]() | 2019 | 57 | ||
Scott Walford | ![]() | 2018 | 124 | ||
Theo Jacobsson | ![]() | 2022 | 198 |