Full Scoreboard ยป |
Minnesota Wild 0-0-0, 0pts · 12th in Western Conference |
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 | # | 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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![]() | 87 | C | 100.00 | 58 | 4 | 96 | 88 | 71 | 99 | 98 | 87 | 97 | 96 | 87 | 50 | 75 | 82 | 89 | 86 | 50 | 79 | 35 | 9,700,000$/1yrs | |||
![]() | 13 | C/RW | 100.00 | 33 | 1 | 99 | 86 | 73 | 89 | 99 | 94 | 32 | 95 | 87 | 51 | 79 | 81 | 81 | 61 | 50 | 77 | 27 | 5,950,900$/2yrs | |||
![]() | 71 | C | 100.00 | 47 | 1 | 99 | 86 | 71 | 97 | 99 | 81 | 86 | 83 | 84 | 69 | 75 | 69 | 70 | 75 | 50 | 76 | 30 | 7,000,000$/1yrs | |||
![]() | 9 | LW/RW | 100.00 | 70 | 35 | 81 | 90 | 75 | 79 | 88 | 83 | 35 | 76 | 93 | 68 | 75 | 68 | 69 | 56 | 50 | 76 | 26 | 5,500,000$/3yrs | |||
![]() | 10 | LW | 100.00 | 44 | 10 | 99 | 92 | 62 | 99 | 97 | 83 | 31 | 97 | 85 | 42 | 80 | 66 | 67 | 81 | 50 | 75 | 31 | 6,500,000$/1yrs | |||
![]() | 27 | LW | 100.00 | 37 | 1 | 99 | 89 | 75 | 84 | 96 | 84 | 34 | 85 | 77 | 54 | 61 | 84 | 86 | 56 | 50 | 74 | 27 | 2,250,000$/1yrs | |||
![]() | 0 | C/LW | 100.00 | 83 | 14 | 82 | 86 | 78 | 88 | 93 | 75 | 98 | 76 | 74 | 61 | 75 | 79 | 80 | 68 | 50 | 74 | 29 | 7,000,000$/4yrs | |||
![]() | 6 | C/RW | 100.00 | 41 | 3 | 99 | 86 | 72 | 84 | 87 | 87 | 82 | 87 | 80 | 45 | 53 | 71 | 71 | 63 | 50 | 73 | 26 | 4,250,000$/4yrs | |||
![]() | 7 | RW | 100.00 | 50 | 12 | 99 | 82 | 67 | 89 | 97 | 83 | 39 | 68 | 75 | 51 | 68 | 75 | 75 | 73 | 50 | 70 | 32 | 1,250,000$/1yrs | |||
![]() | 12 | LW/RW | 100.00 | 44 | 11 | 99 | 80 | 73 | 90 | 96 | 78 | 62 | 84 | 72 | 38 | 63 | 78 | 80 | 73 | 50 | 70 | 33 | 3,250,000$/1yrs | |||
![]() | 17 | C | 100.00 | 70 | 28 | 99 | 80 | 85 | 79 | 79 | 62 | 99 | 61 | 67 | 77 | 25 | 81 | 83 | 58 | 50 | 70 | 29 | 2,000,000$/3yrs | |||
![]() | 19 | C/LW | 100.00 | 86 | 58 | 57 | 86 | 79 | 72 | 94 | 70 | 56 | 64 | 70 | 51 | 25 | 80 | 81 | 54 | 50 | 68 | 26 | 2,000,000$/1yrs | |||
![]() | 57 | D | 100.00 | 62 | 15 | 88 | 79 | 88 | 96 | 98 | 65 | 25 | 63 | 51 | 82 | 53 | 73 | 75 | 66 | 50 | 74 | 33 | 5,000,000$/3yrs | |||
![]() | 0 | D | 100.00 | 54 | 1 | 99 | 87 | 85 | 88 | 69 | 80 | 25 | 62 | 49 | 81 | 25 | 74 | 74 | 52 | 50 | 73 | 24 | 4,300,000$/1yrs | |||
![]() | 0 | D | 100.00 | 55 | 1 | 99 | 88 | 73 | 89 | 81 | 71 | 29 | 70 | 51 | 81 | 25 | 62 | 62 | 48 | 50 | 72 | 23 | 2,300,000$/3yrs | |||
![]() | 23 | D | 100.00 | 52 | 13 | 95 | 83 | 76 | 97 | 89 | 59 | 25 | 53 | 50 | 86 | 25 | 72 | 73 | 66 | 50 | 72 | 32 | 3,900,000$/2yrs | |||
![]() | 0 | D | 100.00 | 53 | 1 | 99 | 72 | 76 | 90 | 78 | 73 | 22 | 70 | 54 | 81 | 75 | 72 | 72 | 48 | 50 | 71 | 25 | 2,500,000$/4yrs | |||
![]() | 8 | D | 100.00 | 56 | 3 | 97 | 78 | 76 | 87 | 90 | 57 | 25 | 50 | 50 | 91 | 25 | 70 | 72 | 63 | 50 | 71 | 33 | 3,500,000$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
TEAM AVERAGE | 100.00 | 55 | 12 | 94 | 84 | 75 | 89 | 90 | 76 | 50 | 74 | 70 | 64 | 55 | 74 | 76 | 64 | 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 ) |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 35 | 100.00 | 82 | 80 | 91 | 80 | 84 | 89 | 91 | 92 | 90 | 76 | 78 | 58 | 58 | 40 | 50 | 80 | 26 | 6,250,000$/3yrs |
![]() | 40 | 100.00 | 76 | 72 | 99 | 61 | 85 | 80 | 86 | 80 | 91 | 78 | 78 | 46 | 46 | 61 | 50 | 74 | 32 | 950,000$/1yrs |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 100.00 | 79 | 76 | 95 | 71 | 85 | 85 | 89 | 86 | 91 | 77 | 78 | 52 | 52 | 51 | 50 | 77 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Peter DeBoer | 66 | 77 | 98 | 69 | 99 | 77 | 68 | CAN | 54 | 6 | 2,500,000$ |
General Manager | Jeff |
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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 |
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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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 | |
---|---|
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 |
---|---|
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 | 0$ |
Salary Cap To Date | 0$ |
Players In Salary Cap | 20 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|
Adam Lowry ![]() | C | 29 | 2,000,000$ | 2,000,000$ | 2,000,000$ | 2,000,000$ | |||||
Adrian Kempe | LW/RW | 26 | 5,500,000$ | 5,500,000$ | 5,500,000$ | 5,500,000$ | |||||
Artemi Panarin | LW | 31 | 6,500,000$ | 6,500,000$ | |||||||
Boone Jenner | C/LW | 29 | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ | ||||
Caleb Jones ![]() | D | 25 | 2,500,000$ | 2,500,000$ | 2,500,000$ | 2,500,000$ | 2,500,000$ | ||||
Colin White | C/RW | 26 | 4,250,000$ | 4,250,000$ | 4,250,000$ | 4,250,000$ | 4,250,000$ | ||||
Henri Jokiharju ![]() | D | 23 | 2,300,000$ | 2,300,000$ | 2,300,000$ | 2,300,000$ | |||||
Ilya Samsonov ![]() | LW/RW | 26 | 6,250,000$ | 6,250,000$ | 6,250,000$ | 6,250,000$ | |||||
Jakob Chychrun | D | 24 | 4,300,000$ | 4,300,000$ | |||||||
Jonathan Drouin | LW | 27 | 2,250,000$ | 2,250,000$ | |||||||
Jordan Eberle | RW | 32 | 1,250,000$ | 1,250,000$ | |||||||
Josh Bailey | LW/RW | 33 | 3,250,000$ | 3,250,000$ | |||||||
Marco Scandella | D | 33 | 3,500,000$ | 3,500,000$ | |||||||
Pavel Francouz ![]() | C/RW | 32 | 950,000$ | 950,000$ | |||||||
Sam Bennett ![]() | C/LW | 26 | 2,000,000$ | 2,000,000$ | |||||||
Sam Reinhart | C/RW | 27 | 5,950,900$ | 5,950,900$ | 5,950,900$ | ||||||
Sidney Crosby | C | 35 | 9,700,000$ | 9,700,000$ | |||||||
Travis Hamonic | D | 32 | 3,900,000$ | 3,900,000$ | 3,900,000$ | ||||||
Tyler Myers ![]() | D | 33 | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | |||||
William Karlsson | C | 30 | 7,000,000$ | 7,000,000$ |
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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 |
---|---|---|---|---|---|
Aram Minnetian | 8 | 72 | |||
Felix Nilsson | 8 | 48 | |||
Jaroslav Chmelar | 5 | 84 | |||
Kaleb Lawrence | 7 | 88 | |||
Kasper Kulonummi | 6 | 54 | |||
Ludwig Persson | 7 | 62 | |||
Matthew Morden | 7 | 86 | |||
Ryan Healey | 7 | 64 | |||
Samu Salminen | 5 | 34 | |||
Zakhar Bardakov | 4 | 88 |
Date | Matchup | Result | Detail | |||||||||||
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2023-09-24 | @ | |||||||||||||
2023-09-25 | @ | |||||||||||||
2023-09-26 | @ | |||||||||||||
2023-09-27 | @ | |||||||||||||
2023-09-28 | @ | |||||||||||||
2023-09-30 | @ | |||||||||||||
2023-10-01 | @ | |||||||||||||
2023-10-03 | @ | |||||||||||||
2023-10-05 | @ | |||||||||||||
Trade Deadline --- Trades cant be done after this day is simulated! | ||||||||||||||
2023-10-07 | @ |
Salary Cap | |||
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Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
85,350,900$ | 0$ | 0$ | 90,000,000$ |
Arena | Goal Horn | About us | |
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![]() | Name | Xcel Energy Center | |
City | Minnesota | ||
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 |
85,350,900$ | 85,350,900$ | 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$ | 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$ | 834,115,817$ | 834,115,817$ |
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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