Full Scoreboard »» |
Milwaukee Admirals 0-0-0, 0pts · 11th in Conference 2 |
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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Adam Ruzicka | 0 | LW | 100.00 | 68 | 43 | 85 | 72 | 89 | 81 | 73 | 73 | 72 | 71 | 66 | 67 | 70 | 59 | 52 | 1 | 50 | 69 | 24 | 1,500,000$/4yrs | |||
Connor Brown | 0 | LW/RW | 100.00 | 58 | 43 | 80 | 75 | 74 | 87 | 77 | 70 | 46 | 66 | 63 | 68 | 69 | 79 | 71 | 1 | 50 | 68 | 29 | 3,800,000$/2yrs | |||
Josh Leivo | 0 | LW/RW | 100.00 | 70 | 56 | 70 | 72 | 74 | 79 | 80 | 72 | 41 | 69 | 63 | 66 | 70 | 78 | 68 | 1 | 50 | 68 | 30 | 2,000,000$/4yrs | |||
Vasily Podkolzin | 0 | LW/RW | 100.00 | 71 | 54 | 79 | 77 | 81 | 82 | 70 | 72 | 50 | 66 | 67 | 66 | 72 | 57 | 50 | 1 | 50 | 68 | 22 | 975,000$/2yrs | |||
Axel Jonsson-Fjallby | 0 | LW | 100.00 | 69 | 43 | 86 | 75 | 79 | 81 | 71 | 71 | 40 | 66 | 65 | 69 | 70 | 56 | 50 | 1 | 50 | 67 | 25 | 1,000,000$/1yrs | |||
Kole Lind | 0 | RW | 100.00 | 62 | 48 | 63 | 73 | 67 | 70 | 67 | 67 | 46 | 65 | 64 | 66 | 68 | 54 | 50 | 1 | 50 | 64 | 24 | 1,500,000$/4yrs | |||
Tye Kartye (R) | 0 | LW | 100.00 | 66 | 48 | 61 | 69 | 64 | 62 | 63 | 66 | 43 | 63 | 63 | 66 | 66 | 50 | 50 | 1 | 50 | 62 | 22 | 975,000$/3yrs | |||
Raphael Lavoie | 0 | C/RW | 100.00 | 66 | 49 | 67 | 69 | 66 | 62 | 62 | 65 | 42 | 61 | 61 | 62 | 65 | 50 | 50 | 1 | 50 | 61 | 22 | 975,000$/1yrs | |||
Sam Houde (R) | 0 | C | 100.00 | 97 | 40 | 65 | 66 | 59 | 62 | 62 | 60 | 51 | 56 | 57 | 53 | 61 | 51 | 50 | 1 | 50 | 59 | 23 | 975,000$/3yrs | |||
Jack Badini | 0 | C | 100.00 | 61 | 45 | 69 | 60 | 65 | 63 | 60 | 54 | 50 | 50 | 50 | 54 | 55 | 53 | 50 | 1 | 50 | 55 | 25 | 1,000,000$/3yrs | |||
Andreas Englund | 0 | D | 100.00 | 75 | 75 | 63 | 71 | 75 | 78 | 77 | 66 | 40 | 61 | 58 | 70 | 65 | 71 | 63 | 1 | 50 | 68 | 27 | 1,100,000$/1yrs | |||
Justin Barron | 0 | D | 100.00 | 64 | 49 | 71 | 74 | 79 | 77 | 64 | 69 | 40 | 68 | 62 | 68 | 68 | 56 | 50 | 1 | 50 | 67 | 21 | 975,000$/2yrs | |||
Alex Petrovic (R) | 0 | D | 100.00 | 66 | 48 | 62 | 66 | 67 | 73 | 73 | 64 | 40 | 60 | 57 | 69 | 62 | 65 | 58 | 1 | 50 | 64 | 31 | 975,000$/3yrs | |||
Adam Ginning (R) | 0 | D | 100.00 | 67 | 44 | 62 | 68 | 65 | 62 | 62 | 62 | 40 | 60 | 56 | 67 | 62 | 51 | 50 | 1 | 50 | 62 | 23 | 975,000$/3yrs | |||
Colton Poolman | 0 | D | 100.00 | 64 | 45 | 73 | 67 | 63 | 67 | 67 | 61 | 40 | 57 | 51 | 68 | 60 | 55 | 50 | 1 | 50 | 62 | 27 | 1,000,000$/3yrs | |||
Declan Chisholm | 0 | D | 100.00 | 58 | 48 | 70 | 71 | 64 | 63 | 62 | 65 | 40 | 65 | 56 | 67 | 64 | 51 | 50 | 1 | 50 | 62 | 23 | 975,000$/1yrs | |||
Parker Wotherspoon | 0 | D | 100.00 | 61 | 54 | 63 | 70 | 63 | 64 | 62 | 61 | 40 | 58 | 52 | 68 | 61 | 53 | 50 | 1 | 50 | 61 | 25 | 1,000,000$/2yrs | |||
Dylan Blujus | 0 | D | 100.00 | 62 | 45 | 68 | 64 | 67 | 67 | 66 | 57 | 40 | 52 | 52 | 67 | 57 | 59 | 50 | 1 | 50 | 61 | 29 | 1,000,000$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
Antoine Roussel | 0 | LW | 100.00 | 62 | 44 | 53 | 64 | 66 | 71 | 73 | 61 | 43 | 55 | 55 | 62 | 60 | 85 | 72 | 1 | 50 | 61 | 33 | 2,500,000$/1yrs | |||
Aidan Dudas | 0 | LW | 100.00 | 53 | 43 | 68 | 71 | 53 | 65 | 64 | 63 | 42 | 60 | 56 | 53 | 63 | 51 | 50 | 1 | 50 | 59 | 23 | 1,000,000$/3yrs | |||
Bobby McMann | 0 | LW/RW | 100.00 | 60 | 45 | 71 | 66 | 64 | 66 | 64 | 63 | 42 | 55 | 61 | 57 | 63 | 55 | 50 | 1 | 50 | 59 | 27 | 1,000,000$/3yrs | |||
Danila Klimovich | 0 | RW | 100.00 | 67 | 46 | 64 | 68 | 67 | 57 | 56 | 62 | 41 | 56 | 58 | 62 | 63 | 50 | 50 | 1 | 50 | 59 | 20 | 975,000$/2yrs | |||
Patrick Khodorenko | 0 | C | 100.00 | 53 | 51 | 54 | 56 | 56 | 58 | 54 | 53 | 48 | 53 | 52 | 51 | 53 | 51 | 50 | 1 | 50 | 53 | 24 | 1,000,000$/3yrs | |||
Lucas Johansen | 0 | D | 100.00 | 59 | 45 | 71 | 69 | 62 | 63 | 62 | 59 | 40 | 55 | 54 | 63 | 61 | 53 | 50 | 1 | 50 | 60 | 25 | 1,200,000$/3yrs | |||
Max Gildon | 0 | D | 100.00 | 61 | 45 | 63 | 66 | 65 | 63 | 62 | 60 | 40 | 55 | 52 | 63 | 59 | 52 | 50 | 1 | 50 | 60 | 24 | 1,000,000$/3yrs | |||
Alex Kannok-Leipert | 0 | D | 100.00 | 65 | 58 | 59 | 69 | 64 | 61 | 60 | 56 | 40 | 51 | 51 | 67 | 59 | 50 | 50 | 1 | 50 | 60 | 22 | 975,000$/2yrs | |||
Josh Maniscalco (R) | 0 | D | 100.00 | 63 | 44 | 69 | 64 | 65 | 61 | 60 | 58 | 40 | 54 | 54 | 65 | 59 | 51 | 50 | 1 | 50 | 60 | 24 | 975,000$/3yrs | |||
Billy Sweezey | 0 | D | 100.00 | 58 | 63 | 58 | 61 | 65 | 68 | 67 | 60 | 40 | 55 | 51 | 60 | 58 | 55 | 50 | 1 | 50 | 59 | 27 | 1,000,000$/2yrs | |||
Adam Brubacher | 0 | D | 100.00 | 62 | 45 | 65 | 62 | 67 | 64 | 61 | 54 | 40 | 51 | 51 | 63 | 56 | 55 | 50 | 1 | 50 | 59 | 27 | 975,000$/2yrs | |||
Connor Corcoran | 0 | D | 100.00 | 62 | 45 | 65 | 70 | 64 | 59 | 56 | 56 | 40 | 51 | 53 | 64 | 59 | 50 | 50 | 1 | 50 | 59 | 22 | 975,000$/2yrs | |||
Simon Johansson (R) | 0 | D | 100.00 | 56 | 40 | 69 | 67 | 59 | 62 | 63 | 62 | 40 | 58 | 54 | 60 | 61 | 51 | 50 | 1 | 50 | 59 | 24 | 975,000$/3yrs | |||
Zach Uens (R) | 0 | D | 100.00 | 59 | 44 | 65 | 68 | 63 | 58 | 56 | 54 | 40 | 51 | 51 | 60 | 57 | 50 | 50 | 1 | 50 | 57 | 22 | 975,000$/3yrs |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Jaroslav Halak | 0 | 100.00 | 70 | 81 | 81 | 73 | 77 | 79 | 78 | 79 | 79 | 76 | 79 | 92 | 85 | 1 | 50 | 72 | 38 | 5,250,000$/1yrs |
Arvid Soderblom | 0 | 100.00 | 77 | 70 | 70 | 75 | 73 | 73 | 71 | 71 | 74 | 73 | 71 | 56 | 51 | 1 | 50 | 66 | 23 | 975,000$/2yrs |
Scratches | ||||||||||||||||||||
Dustin Wolf | 0 | 100.00 | 74 | 63 | 70 | 54 | 68 | 73 | 75 | 75 | 75 | 71 | 59 | 50 | 50 | 1 | 50 | 64 | 22 | 975,000$/1yrs |
Ivan Prosvetov | 0 | 100.00 | 72 | 64 | 68 | 63 | 68 | 69 | 70 | 68 | 69 | 69 | 58 | 52 | 50 | 1 | 50 | 62 | 24 | 1,500,000$/3yrs |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Troy Mann | 64 | 63 | 69 | 63 | 62 | 57 | 1 | CAN | 53 | 3 | 500,000$ |
General Manager |
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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 |
# | 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 |
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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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Player Name | POS | Age | Cap Hit | 2017-18 | 2018-19 | 2019-20 | 2020-21 | 2021-22 | 2022-23 | 2023-24 | 2024-25 |
---|---|---|---|---|---|---|---|---|---|---|---|
Adam Brubacher | D | 27 | 975,000$ | 975,000$ | 975,000$ | UFA | |||||
Adam Ginning | D | 23 | 975,000$ | 975,000$ | 975,000$ | 975,000$ | RFA | ||||
Adam Ruzicka | LW | 24 | 1,500,000$ | 1,500,000$ | 1,500,000$ | 1,500,000$ | 1,500,000$ | UFA | |||
Aidan Dudas | LW | 23 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | RFA | ||||
Alex Kannok-Leipert | D | 22 | 975,000$ | 975,000$ | 975,000$ | RFA | |||||
Alex Petrovic | D | 31 | 975,000$ | 975,000$ | 975,000$ | 975,000$ | UFA | ||||
Andreas Englund | D | 27 | 1,100,000$ | 1,100,000$ | UFA | ||||||
Antoine Roussel | LW | 33 | 2,500,000$ | 2,500,000$ | UFA | ||||||
Arvid Soderblom | G | 23 | 975,000$ | 975,000$ | 975,000$ | RFA | |||||
Axel Jonsson-Fjallby | LW | 25 | 1,000,000$ | 1,000,000$ | RFA | ||||||
Billy Sweezey | D | 27 | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | |||||
Bobby McMann | LW/RW | 27 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | ||||
Colton Poolman | D | 27 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | ||||
Connor Brown | LW/RW | 29 | 3,800,000$ | 3,800,000$ | 3,800,000$ | UFA | |||||
Connor Corcoran | D | 22 | 975,000$ | 975,000$ | 975,000$ | RFA | |||||
Danila Klimovich | RW | 20 | 975,000$ | 975,000$ | 975,000$ | RFA | |||||
Declan Chisholm | D | 23 | 975,000$ | 975,000$ | RFA | ||||||
Dustin Wolf | G | 22 | 975,000$ | 975,000$ | RFA | ||||||
Dylan Blujus | D | 29 | 1,000,000$ | 1,000,000$ | UFA | ||||||
Ivan Prosvetov | G | 24 | 1,500,000$ | 1,500,000$ | 1,500,000$ | 1,500,000$ | UFA | ||||
Jack Badini | C | 25 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | ||||
Jaroslav Halak | G | 38 | 5,250,000$ | 5,250,000$ | UFA | ||||||
Josh Leivo | LW/RW | 30 | 2,000,000$ | 2,000,000$ | 2,000,000$ | 2,000,000$ | 2,000,000$ | UFA | |||
Josh Maniscalco | D | 24 | 975,000$ | 975,000$ | 975,000$ | 975,000$ | UFA | ||||
Justin Barron | D | 21 | 975,000$ | 975,000$ | 975,000$ | RFA | |||||
Kole Lind | RW | 24 | 1,500,000$ | 1,500,000$ | 1,500,000$ | 1,500,000$ | 1,500,000$ | UFA | |||
Lucas Johansen | D | 25 | 1,200,000$ | 1,200,000$ | 1,200,000$ | 1,200,000$ | UFA | ||||
Max Gildon | D | 24 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | RFA | ||||
Parker Wotherspoon | D | 25 | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | |||||
Patrick Khodorenko | C | 24 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | ||||
Raphael Lavoie | C/RW | 22 | 975,000$ | 975,000$ | RFA | ||||||
Sam Houde | C | 23 | 975,000$ | 975,000$ | 975,000$ | 975,000$ | RFA | ||||
Simon Johansson | D | 24 | 975,000$ | 975,000$ | 975,000$ | 975,000$ | RFA | ||||
Tye Kartye | LW | 22 | 975,000$ | 975,000$ | 975,000$ | 975,000$ | RFA | ||||
Vasily Podkolzin | LW/RW | 22 | 975,000$ | 975,000$ | 975,000$ | RFA | |||||
Zach Uens | D | 22 | 975,000$ | 975,000$ | 975,000$ | 975,000$ | RFA |
Forward Lines | |||||||
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Defensive Pairings | |||||||
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1st Power Play Unit | |||||||
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2nd Power Play Unit | |||||||
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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 | 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 | |
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Offensive Zone Start | 0 |
Neutral Zone Start | 0 |
Defensive Zone Start | 0 |
Puck Time | |
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With Puck | 0 |
Without Puck | 0 |
Faceoffs | |
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Faceoffs Won | 0 |
Faceoffs Lost | 0 |
Team Average Shots after | League Average Shots after | |
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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 |
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PP Goal | 0 |
PK Attempt | 0 |
PK Goal Against | 0 |
Home | |
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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 |
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 |
4,692,500$ | 0$ | 0$ | 75,000,000$ |
Arena | About us | |
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Name | ||
City | Milwaukee | |
Capacity | 3000 | |
Season Ticket Holders | 10% |
Arena Capacity - Ticket Price Attendance - % | |||||
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Arena Capacity | 2000 | 1000 | |||
Ticket Price | 35$ | 15$ | $ | $ | $ |
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 |
4,692,500$ | 4,692,500$ | 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$ | 2 | 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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