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Full Scoreboard »» |
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Full Scoreboard »» |
Iowa Wild 0-0-0, 0pts · 12th 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 | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 27 | RW | 100.00 | 65 | 37 | 81 | 59 | 63 | 71 | 87 | 65 | 50 | 59 | 65 | 67 | 62 | 72 | 70 | 0 | 50 | 73 | 29 | 800,000$/2yrs | |||
![]() | 0 | C | 100.00 | 59 | 38 | 92 | 56 | 73 | 70 | 69 | 67 | 49 | 61 | 57 | 71 | 59 | 75 | 74 | 0 | 37 | 72 | 29 | 800,000$/2yrs | |||
![]() | 65 | C | 100.00 | 67 | 39 | 79 | 59 | 72 | 70 | 85 | 64 | 77 | 63 | 59 | 68 | 61 | 70 | 68 | 0 | 53 | 72 | 28 | 775,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 74 | 41 | 67 | 59 | 76 | 68 | 71 | 63 | 37 | 60 | 59 | 66 | 59 | 66 | 63 | 0 | 34 | 71 | 24 | 775,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 63 | 33 | 93 | 62 | 76 | 75 | 86 | 59 | 58 | 61 | 64 | 51 | 62 | 63 | 62 | 0 | 41 | 71 | 23 | 894,167$/1yrs | |||
![]() | 0 | C | 100.00 | 59 | 38 | 92 | 61 | 73 | 68 | 74 | 61 | 60 | 59 | 63 | 64 | 61 | 63 | 62 | 0 | 54 | 71 | 23 | 846,667$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 62 | 38 | 87 | 58 | 72 | 67 | 88 | 63 | 42 | 59 | 59 | 66 | 59 | 66 | 65 | 0 | 52 | 70 | 26 | 1,250,000$/2yrs | |||
![]() | 0 | LW | 100.00 | 74 | 41 | 68 | 53 | 85 | 66 | 67 | 66 | 44 | 57 | 53 | 69 | 55 | 72 | 68 | 0 | 55 | 70 | 28 | 850,000$/1yrs | |||
![]() | 0 | RW | 100.00 | 77 | 33 | 96 | 55 | 83 | 69 | 75 | 54 | 56 | 58 | 58 | 58 | 56 | 70 | 70 | 0 | 30 | 69 | 27 | 825,000$/1yrs | |||
![]() | 0 | RW | 100.00 | 64 | 38 | 88 | 65 | 68 | 70 | 84 | 62 | 46 | 57 | 55 | 62 | 64 | 59 | 58 | 0 | 75 | 69 | 22 | 925,000$/1yrs | |||
![]() | 0 | C | 100.00 | 60 | 38 | 91 | 55 | 77 | 65 | 66 | 62 | 66 | 57 | 53 | 65 | 55 | 64 | 64 | 0 | 41 | 68 | 23 | 821,667$/1yrs | |||
![]() | 0 | C | 100.00 | 63 | 38 | 86 | 53 | 72 | 62 | 74 | 61 | 63 | 54 | 51 | 65 | 52 | 63 | 61 | 0 | 53 | 66 | 25 | 800,000$/2yrs | |||
![]() | 0 | RW | 100.00 | 62 | 38 | 87 | 52 | 69 | 61 | 83 | 61 | 70 | 52 | 50 | 64 | 51 | 61 | 59 | 0 | 27 | 65 | 23 | 859,167$/1yrs | |||
![]() | 0 | D | 100.00 | 70 | 40 | 76 | 61 | 75 | 66 | 60 | 56 | 30 | 55 | 48 | 62 | 59 | 56 | 53 | 0 | 34 | 68 | 22 | 886,667$/1yrs | |||
![]() | 0 | D | 100.00 | 70 | 40 | 74 | 48 | 78 | 65 | 67 | 48 | 30 | 54 | 52 | 70 | 53 | 71 | 69 | 0 | 54 | 67 | 27 | 850,000$/1yrs | |||
![]() | 0 | D | 100.00 | 61 | 38 | 89 | 51 | 70 | 63 | 77 | 49 | 30 | 57 | 49 | 65 | 53 | 63 | 61 | 0 | 53 | 67 | 24 | 836,667$/1yrs | |||
![]() | 0 | D | 100.00 | 64 | 40 | 84 | 49 | 83 | 63 | 66 | 48 | 30 | 54 | 51 | 65 | 53 | 63 | 61 | 0 | 39 | 66 | 23 | 870,000$/1yrs | |||
![]() | 0 | D | 100.00 | 69 | 41 | 76 | 50 | 84 | 63 | 67 | 49 | 30 | 56 | 52 | 64 | 54 | 61 | 58 | 0 | 56 | 66 | 21 | 867,500$/2yrs | |||
![]() | 0 | D | 100.00 | 87 | 44 | 50 | 47 | 89 | 61 | 66 | 46 | 30 | 51 | 52 | 64 | 52 | 61 | 56 | 0 | 34 | 64 | 22 | 828,333$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | LW/RW | 100.00 | 63 | 33 | 92 | 55 | 76 | 74 | 72 | 57 | 55 | 57 | 60 | 55 | 59 | 65 | 65 | 0 | 20 | 68 | 25 | ||||
![]() | 0 | C | 100.00 | 60 | 40 | 92 | 53 | 88 | 63 | 66 | 62 | 67 | 53 | 53 | 66 | 53 | 64 | 64 | 0 | 39 | 67 | 24 | 859,167$/1yrs | |||
![]() | 0 | C | 100.00 | 58 | 39 | 94 | 58 | 81 | 64 | 67 | 58 | 55 | 57 | 55 | 61 | 56 | 57 | 57 | 0 | 19 | 67 | 19 | 896,667$/2yrs | |||
![]() | 0 | LW | 100.00 | 58 | 38 | 95 | 52 | 74 | 61 | 65 | 61 | 38 | 53 | 50 | 64 | 51 | 61 | 60 | 0 | 20 | 66 | 21 | 859,167$/1yrs | |||
![]() | 0 | C | 100.00 | 58 | 38 | 95 | 51 | 76 | 61 | 65 | 63 | 60 | 52 | 50 | 66 | 51 | 64 | 64 | 0 | 40 | 66 | 23 | ||||
![]() | 0 | D | 100.00 | 90 | 43 | 50 | 51 | 78 | 63 | 66 | 49 | 30 | 54 | 56 | 63 | 55 | 59 | 54 | 0 | 40 | 66 | 21 | ||||
![]() | 0 | D | 100.00 | 73 | 41 | 69 | 49 | 84 | 62 | 66 | 48 | 30 | 54 | 51 | 64 | 53 | 61 | 58 | 0 | 40 | 66 | 21 | ||||
![]() | 0 | D | 100.00 | 71 | 40 | 72 | 48 | 76 | 62 | 66 | 47 | 30 | 53 | 51 | 65 | 52 | 63 | 60 | 0 | 19 | 65 | 22 | 855,833$/1yrs | |||
![]() | 0 | D | 100.00 | 64 | 40 | 85 | 47 | 82 | 62 | 65 | 47 | 30 | 52 | 50 | 65 | 51 | 63 | 61 | 0 | 19 | 65 | 22 | 825,000$/2yrs |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 50 | 100.00 | 75 | 64 | 67 | 82 | 73 | 64 | 75 | 84 | 69 | 82 | 75 | 69 | 72 | 0 | 37 | 77 | 26 | 950,000$/1yrs |
![]() | 0 | 100.00 | 60 | 63 | 66 | 81 | 54 | 61 | 61 | 70 | 61 | 70 | 61 | 65 | 68 | 0 | 52 | 69 | 24 | 867,500$/1yrs |
Scratches | ||||||||||||||||||||
![]() | 0 | 100.00 | 67 | 65 | 66 | 72 | 66 | 65 | 67 | 66 | 65 | 67 | 66 | 63 | 69 | 0 | 25 | 71 | 25 | 800,000$/1yrs |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Jean-Jacques Daigneault | 58 | 59 | 53 | 65 | 57 | 64 | 81 | CAN | 59 | 5 | 500,000$ |
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 | 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 |
---|---|---|
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 | 2020-21 | 2021-22 | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 |
---|---|---|---|---|---|---|---|---|---|---|---|
Alexander Holtz | LW/RW | 23 | 894,167$ | 894,167$ | RFA | ||||||
Anton Wahlberg | C | 19 | 896,667$ | 896,667$ | 896,667$ | RFA | |||||
Anttoni Honka | D | 24 | 836,667$ | 836,667$ | |||||||
Charles-Alexis Legault | D | 21 | 0$ | RFA | |||||||
Chase de Leo | C | 29 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Christoffer Sedoff | D | 23 | 870,000$ | 870,000$ | RFA | ||||||
Cooper Marody | C | 28 | 775,000$ | 775,000$ | UFA | ||||||
Daniil Chayka | D | 22 | 825,000$ | 825,000$ | 825,000$ | RFA | |||||
David Tendeck | G | 25 | 800,000$ | 800,000$ | |||||||
Evan Nause | D | 22 | 886,667$ | 886,667$ | RFA | ||||||
Grigori Denisenko | LW/RW | 24 | 775,000$ | 775,000$ | |||||||
Henri Nikkanen | C | 24 | 859,167$ | 859,167$ | |||||||
Henry Rybinski | RW | 23 | 859,167$ | 859,167$ | RFA | ||||||
Ivan Prosvetov | G | 26 | 950,000$ | 950,000$ | |||||||
Jake Wise | C | 25 | 800,000$ | 800,000$ | 800,000$ | ||||||
Josh Bloom | LW | 21 | 859,167$ | 859,167$ | RFA | ||||||
Lucas Condotta | LW | 28 | 850,000$ | 850,000$ | UFA | ||||||
Magnus Chrona | G | 24 | 867,500$ | 867,500$ | |||||||
Marian Studenic | LW/RW | 26 | 1,250,000$ | 1,250,000$ | 1,250,000$ | UFA | |||||
Nikita Novikov | D | 21 | 867,500$ | 867,500$ | 867,500$ | RFA | |||||
Owen Lindmark | C | 23 | 0$ | RFA | |||||||
Philippe Daoust | C | 23 | 821,667$ | 821,667$ | RFA | ||||||
Rodwin Dionicio | D | 21 | 0$ | RFA | |||||||
Roman Schmidt | D | 22 | 828,333$ | 828,333$ | RFA | ||||||
Rory Kerins | C | 23 | 846,667$ | 846,667$ | RFA | ||||||
Ryan O'Rourke | D | 22 | 855,833$ | 855,833$ | RFA | ||||||
Sheldon Rempal | RW | 29 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Vitali Kravtsov | LW/RW | 25 | 0$ | ||||||||
Walker Duehr | RW | 27 | 825,000$ | 825,000$ | UFA | ||||||
Wyatt Aamodt | D | 27 | 850,000$ | 850,000$ | UFA | ||||||
Xavier Bourgeault | RW | 22 | 925,000$ | 925,000$ | RFA |
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 |
2,327,419$ | 0$ | 0$ | 75,000,000$ |
Arena | About us | |
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![]() | Name | |
City | Iowa | |
Capacity | 3000 | |
Season Ticket Holders | 0% |
Arena Capacity - Ticket Price Attendance - % | |||||
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Arena Capacity | 2000 | 1000 | |||
Ticket Price | 35$ | 0$ | $ | $ | $ |
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 |
36 | 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 |
2,327,419$ | 2,327,419$ | 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$ | 12 | 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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