Full Scoreboard ยป |
Dallas Stars 0-0-0, 0pts · 7th in Western Conference |
Priority | Type | Description |
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Player | # | POS | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | |||
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![]() | 0 | C | 100.00 | 66 | 15 | 93 | 91 | 85 | 98 | 94 | 93 | 90 | 95 | 94 | 68 | 83 | 78 | 79 | 76 | 50 | 83 | 29 | 12,500,000$/4yrs | |||
![]() | 0 | C/RW | 100.00 | 62 | 17 | 95 | 85 | 72 | 82 | 93 | 89 | 85 | 94 | 82 | 80 | 53 | 75 | 76 | 73 | 50 | 79 | 29 | 11,000,000$/3yrs | |||
![]() | 0 | LW | 100.00 | 31 | 1 | 99 | 96 | 58 | 96 | 98 | 96 | 31 | 99 | 98 | 43 | 43 | 73 | 74 | 78 | 50 | 79 | 29 | 8,250,000$/4yrs | |||
![]() | 0 | LW | 100.00 | 77 | 15 | 92 | 80 | 76 | 77 | 86 | 80 | 55 | 82 | 88 | 61 | 54 | 77 | 79 | 81 | 50 | 75 | 34 | 5,000,000$/1yrs | |||
![]() | 0 | C | 100.00 | 43 | 24 | 99 | 80 | 74 | 84 | 95 | 87 | 68 | 75 | 86 | 55 | 78 | 58 | 58 | 74 | 50 | 72 | 24 | 3,000,000$/4yrs | |||
![]() | 0 | LW/RW | 100.00 | 91 | 8 | 86 | 87 | 58 | 67 | 64 | 72 | 16 | 92 | 92 | 67 | 25 | 58 | 58 | 71 | 50 | 72 | 24 | 3,500,000$/3yrs | |||
![]() | 0 | LW/RW | 100.00 | 62 | 13 | 99 | 85 | 68 | 62 | 76 | 77 | 28 | 70 | 91 | 68 | 25 | 65 | 65 | 67 | 50 | 71 | 27 | 2,500,000$/2yrs | |||
![]() | 0 | C/LW | 100.00 | 31 | 1 | 99 | 82 | 69 | 78 | 80 | 82 | 85 | 83 | 89 | 56 | 25 | 58 | 58 | 61 | 50 | 71 | 25 | 3,500,000$/3yrs | |||
![]() | 0 | LW/RW | 100.00 | 47 | 23 | 99 | 84 | 70 | 78 | 77 | 75 | 47 | 70 | 75 | 61 | 67 | 70 | 70 | 59 | 50 | 69 | 29 | 685,000$/1yrs | |||
![]() | 0 | C/RW | 100.00 | 60 | 4 | 99 | 75 | 72 | 92 | 62 | 64 | 86 | 55 | 65 | 81 | 63 | 82 | 84 | 67 | 50 | 68 | 34 | 900,000$/3yrs | |||
![]() | 0 | C/LW | 100.00 | 54 | 14 | 99 | 80 | 79 | 79 | 99 | 58 | 85 | 60 | 59 | 78 | 75 | 75 | 77 | 62 | 50 | 68 | 31 | 775,000$/3yrs | |||
![]() | 0 | D | 100.00 | 87 | 36 | 67 | 80 | 86 | 90 | 90 | 76 | 25 | 80 | 62 | 84 | 63 | 83 | 83 | 53 | 50 | 78 | 28 | 8,000,000$/4yrs | |||
![]() | 0 | D | 100.00 | 35 | 1 | 99 | 95 | 81 | 99 | 97 | 90 | 25 | 82 | 66 | 82 | 25 | 76 | 77 | 54 | 50 | 77 | 25 | 7,000,000$/4yrs | |||
![]() | 0 | D | 100.00 | 75 | 17 | 89 | 84 | 85 | 90 | 99 | 63 | 25 | 61 | 47 | 84 | 25 | 72 | 74 | 65 | 50 | 75 | 32 | 4,000,000$/1yrs | |||
![]() | 0 | D | 100.00 | 56 | 12 | 94 | 86 | 66 | 98 | 87 | 91 | 25 | 86 | 50 | 77 | 42 | 68 | 70 | 68 | 50 | 74 | 31 | 3,250,000$/2yrs | |||
![]() | 0 | D | 100.00 | 60 | 4 | 97 | 84 | 72 | 98 | 89 | 76 | 25 | 72 | 48 | 76 | 25 | 72 | 73 | 65 | 50 | 73 | 32 | 1,000,000$/1yrs | |||
![]() | 0 | D | 100.00 | 44 | 17 | 90 | 80 | 63 | 80 | 95 | 87 | 27 | 88 | 74 | 72 | 61 | 60 | 60 | 74 | 50 | 72 | 25 | 2,000,000$/4yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | C | 100.00 | 79 | 38 | 67 | 76 | 85 | 64 | 78 | 75 | 76 | 73 | 64 | 62 | 63 | 59 | 59 | 73 | 50 | 67 | 24 | 685,000$/4yrs | |||
![]() | 0 | RW | 100.00 | 81 | 30 | 90 | 72 | 82 | 68 | 70 | 71 | 81 | 66 | 69 | 67 | 65 | 51 | 51 | 63 | 50 | 66 | 25 | 1,400,000$/1yrs | |||
![]() | 8 | D | 100.00 | 72 | 6 | 96 | 83 | 77 | 90 | 79 | 58 | 25 | 52 | 47 | 78 | 25 | 73 | 74 | 55 | 50 | 71 | 33 | 685,000$/1yrs | |||
TEAM AVERAGE | 100.00 | 61 | 15 | 92 | 83 | 74 | 84 | 85 | 78 | 51 | 77 | 72 | 70 | 49 | 69 | 70 | 67 | 50 | 73 |
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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8 | ? | Wildcard for a single, non-space character. |
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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 |
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![]() | 0 | 100.00 | 95 | 85 | 86 | 68 | 83 | 99 | 99 | 99 | 99 | 86 | 95 | 62 | 62 | 59 | 50 | 84 | 24 | 9,000,000$/3yrs |
![]() | 0 | 100.00 | 80 | 81 | 81 | 73 | 78 | 83 | 85 | 84 | 85 | 80 | 80 | 88 | 94 | 81 | 50 | 79 | 38 | 700,000$/1yrs |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 100.00 | 88 | 83 | 84 | 71 | 81 | 91 | 92 | 92 | 92 | 83 | 88 | 75 | 78 | 70 | 50 | 82 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Jared Bednar | 65 | 83 | 87 | 64 | 77 | 58 | 63 | CAN | 50 | 5 | 2,500,000$ |
General Manager | Jeff Shirley |
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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 |
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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 |
# | 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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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 | 0.0% | 0.0% | 0.0% | 0.0 | Unlucky |
Puck Time | |
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Offensive Zone | 0 |
Neutral Zone | 0 |
Defensive Zone | 0 |
Puck Time | |
---|---|
Offensive Zone Start | 0 |
Neutral Zone Start | 0 |
Defensive Zone Start | 0 |
Puck Time | |
---|---|
With Puck | 0 |
Without Puck | 0 |
Faceoffs | |
---|---|
Faceoffs Won | 0 |
Faceoffs Lost | 0 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 0.0 | 9.57 |
2nd Period | 0.0 | 20.31 |
3rd Period | 0.0 | 30.68 |
Overtime | 0.0 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.0 | 0.64 |
2nd Period | 0.0 | 1.65 |
3rd Period | 0.0 | 2.67 |
Overtime | 0.0 | 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 |
---|---|
PP Goal | 0 |
PK Attempt | 0 |
PK Goal Against | 0 |
Home | |
---|---|
Shots For | 0.0 |
Shots Against | 0.0 |
Goals For | 0.0 |
Goals Against | 0.0 |
Hits | 0.0 |
Shots Blocked | 0.0 |
Pim | 0.0 |
Projected Total Cap Hit | 0$ |
Projected Cap Space | 90,000,000$ |
Retains And Buyout Cap Hit | 6,000,000$ |
Salary Cap To Date | 0$ |
Players In Salary Cap | 23 |
LTIR Players | 0 |
Player Name | Pos | Age | Cap Hit | 2018-2019 | 2019-2020 | 2020-2021 | 2021-2022 | 2022-2023 | 2023-2024 | 2024-2025 | 2025-2026 |
---|---|---|---|---|---|---|---|---|---|---|---|
Brandon Sutter ![]() | C/RW | 34 | 900,000$ | 900,000$ | 900,000$ | 900,000$ | |||||
Brenden Dillon ![]() | D | 32 | 4,000,000$ | 4,000,000$ | |||||||
Carter Hart ![]() | C | 24 | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ | |||||
Darnell Nurse | D | 28 | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | ||||
Dominik Kubalik ![]() | LW/RW | 27 | 2,500,000$ | 2,500,000$ | 2,500,000$ | ||||||
Jake Gardiner | D | 32 | 1,000,000$ | 1,000,000$ | |||||||
Jake Leschyshyn ![]() | C | 24 | 3,000,000$ | 3,000,000$ | 3,000,000$ | 3,000,000$ | 3,000,000$ | ||||
Johnny Gaudreau | LW | 29 | 8,250,000$ | 8,250,000$ | 8,250,000$ | 8,250,000$ | 8,250,000$ | ||||
Kailer Yamamoto ![]() | LW/RW | 24 | 3,500,000$ | 3,500,000$ | 3,500,000$ | 3,500,000$ | |||||
Kevin Connauton ![]() | D | 33 | 685,000$ | 685,000$ | |||||||
Mac Hollowell ![]() | D | 25 | 2,000,000$ | 2,000,000$ | 2,000,000$ | 2,000,000$ | 2,000,000$ | ||||
Marc-Andre Fleury | C/LW | 38 | 700,000$ | 700,000$ | |||||||
Max Pacioretty | LW | 34 | 5,000,000$ | 5,000,000$ | |||||||
Mika Zibanejad | C | 29 | 12,500,000$ | 12,500,000$ | 12,500,000$ | 12,500,000$ | 12,500,000$ | ||||
Reid Boucher ![]() | LW/RW | 29 | 685,000$ | 685,000$ | |||||||
Riley Sheahan ![]() | C/LW | 31 | 775,000$ | 775,000$ | 775,000$ | 775,000$ | |||||
Riley Sutter ![]() | C | 24 | 685,000$ | 685,000$ | 685,000$ | 685,000$ | 685,000$ | ||||
Ryan Strome | C/RW | 29 | 11,000,000$ | 11,000,000$ | 11,000,000$ | 11,000,000$ | |||||
Sam Steel ![]() | C/LW | 25 | 3,500,000$ | 3,500,000$ | 3,500,000$ | 3,500,000$ | |||||
Taylor Raddysh ![]() | RW | 25 | 1,400,000$ | 1,400,000$ | |||||||
Torey Krug ![]() | D | 31 | 3,250,000$ | 3,250,000$ | 3,250,000$ | ||||||
Zach Werenski | D | 25 | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ |
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 |
Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
---|---|---|---|---|---|
Albert Wikman | 8 | 89 | |||
Brandon Svoboda | 8 | 65 | |||
Daniil Orlov | 6 | 65 | |||
Filip Bystedt | 7 | 18 | |||
Garrett Brown | 7 | 66 | |||
Kyle Kukkonen | 5 | 92 | |||
Vladmir Grudinin | 6 | 89 |
Date | Matchup | Result | Detail | |||||||||||
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2023-09-24 | @ | |||||||||||||
2023-09-25 | @ | |||||||||||||
2023-09-26 | @ | |||||||||||||
2023-09-28 | @ | |||||||||||||
2023-09-29 | @ | |||||||||||||
2023-09-30 | @ | |||||||||||||
2023-10-01 | @ | |||||||||||||
2023-10-02 | @ | |||||||||||||
2023-10-05 | @ | |||||||||||||
Trade Deadline --- Trades cant be done after this day is simulated! | ||||||||||||||
2023-10-08 | @ |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
90,130,009$ | 6,000,000$ | 0$ | 90,000,000$ |
Arena | Goal Horn | About us | |
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![]() | Name | American Airlines Center | |
City | Dallas | ||
Capacity | 18000 | ||
Season Ticket Holders | 50% |
Arena Capacity - Ticket Price Attendance - % | |||||
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Arena Capacity | 6000 | 5000 | 2000 | 4000 | 1000 |
Ticket Price | 300$ | 150$ | 100$ | 75$ | 400$ |
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 |
5 | 0 - 0.00% | 0$ | 0$ | 18000 | 100 |
Expenses | |||
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Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
90,130,009$ | 90,130,009$ | 0$ | 6,000,000$ |
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$ | 16 | 0$ | 0$ |
Team Total Estimate | |||
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Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
0$ | 0$ | 929,266,872$ | 929,266,872$ |
Left Wing | Center | Right Wing | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Defense #1 | Defense #2 | Goalie | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Year | Round 1 | Round 2 | Round 3 | Round 4 |
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9 | ||||
10 | ||||
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13 |