| GP | W | L | OT | Pts |
|---|---|---|---|---|
| 0 | 0 | 0 | 0 | 0 |
GM: Neil Oliver Y3 WJT gold |
League Rank:23rd | Arena: Grande Prairie Arena |
| Conference: Western Conference | Conference Rank:12nd | Capacity:3,000 |
| Division: Northwest | Division Rank:4th | Total Player Salaries:4,863,256$ |
| Captain: Keaton Kanji | Last 10: 0-0-0 | |
| Coach: Mehdi Winberg | Home: 0-0-0 | |
| All-Time Record: 208 W - 144 L - 48 OTL | Away: 0-0-0 | |
| Player | # | POS | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Barnabas Vilezsal (A) | 58 | RW | 100.00 | 87 | 62 | 80 | 99 | 98 | 99 | 97 | 72 | 62 | 64 | 85 | 40 | 69 | 57 | 59 | 29 | 50 | 80 | 30 | 1,999,999$/2yrs | |||
Philippe-Olivier Jansen | 17 | LW | 100.00 | 78 | 42 | 73 | 85 | 89 | 86 | 84 | 80 | 71 | 80 | 55 | 93 | 77 | 32 | 80 | 52 | 50 | 80 | 25 | 1,800,000$/4yrs | |||
Willem Halward (A) | 86 | C | 100.00 | 74 | 30 | 59 | 92 | 99 | 99 | 75 | 98 | 99 | 80 | 59 | 32 | 93 | 56 | 83 | 53 | 50 | 79 | 25 | 1,700,000$/2yrs | |||
Roch Fingland | 55 | LW | 100.00 | 50 | 44 | 73 | 82 | 98 | 59 | 86 | 94 | 50 | 92 | 57 | 79 | 86 | 70 | 81 | 45 | 50 | 78 | 26 | 1,432,286$/1yrs | |||
Vaidas Indrisiunas | 71 | RW | 100.00 | 72 | 48 | 72 | 95 | 99 | 67 | 74 | 86 | 56 | 76 | 73 | 76 | 44 | 66 | 53 | 49 | 50 | 78 | 26 | 1,900,000$/3yrs | |||
Griffin Froats | 18 | RW | 100.00 | 83 | 63 | 54 | 85 | 86 | 96 | 97 | 82 | 72 | 72 | 47 | 77 | 79 | 43 | 53 | 57 | 50 | 78 | 24 | 1,787,131$/5yrs | |||
Jerry Malmkvist (R) | 87 | LW | 100.00 | 52 | 39 | 85 | 79 | 98 | 69 | 78 | 70 | 64 | 69 | 80 | 91 | 48 | 67 | 48 | 60 | 50 | 77 | 24 | 1,700,000$/4yrs | |||
Olaf Brieger | 19 | C | 100.00 | 30 | 44 | 64 | 72 | 66 | 67 | 69 | 94 | 91 | 94 | 75 | 96 | 68 | 92 | 72 | 57 | 50 | 77 | 23 | 800,000$/1yrs | |||
Keaton Kanji (C) | 24 | C | 100.00 | 67 | 56 | 73 | 60 | 49 | 99 | 69 | 83 | 85 | 99 | 49 | 87 | 96 | 81 | 38 | 12 | 50 | 76 | 33 | 1,400,000$/2yrs | |||
Leyman Shaeffer (R) | 11 | C | 100.00 | 31 | 46 | 74 | 99 | 68 | 89 | 93 | 84 | 71 | 73 | 63 | 63 | 45 | 80 | 63 | 60 | 50 | 76 | 24 | 1,666,000$/2yrs | |||
Dan Strom | 47 | LW | 100.00 | 45 | 57 | 85 | 97 | 82 | 83 | 65 | 95 | 80 | 40 | 86 | 82 | 38 | 50 | 56 | 36 | 50 | 76 | 29 | 1,500,000$/2yrs | |||
Dauren Abdykarimov | 16 | RW | 100.00 | 77 | 41 | 58 | 85 | 55 | 78 | 92 | 83 | 68 | 69 | 68 | 78 | 38 | 55 | 48 | 48 | 50 | 74 | 27 | 1,162,085$/5yrs | |||
Douwe Hoefnagels (R) | 67 | D | 100.00 | 61 | 41 | 89 | 89 | 98 | 95 | 73 | 92 | 25 | 55 | 58 | 82 | 49 | 45 | 91 | 48 | 50 | 78 | 25 | 1,999,999$/1yrs | |||
Culley Daggett (R) | 68 | D | 100.00 | 68 | 60 | 80 | 67 | 97 | 99 | 78 | 75 | 25 | 50 | 63 | 77 | 38 | 37 | 80 | 60 | 50 | 76 | 22 | 1,800,000$/5yrs | |||
Vasilica Ciubotariu (R) | 0 | D | 100.00 | 70 | 53 | 80 | 75 | 87 | 89 | 93 | 94 | 25 | 43 | 47 | 73 | 91 | 86 | 91 | 61 | 50 | 75 | 24 | 1,375,000$/1yrs | |||
Eli Pajaczkowski | 4 | D | 100.00 | 40 | 55 | 90 | 90 | 69 | 79 | 96 | 90 | 25 | 50 | 59 | 99 | 72 | 95 | 60 | 37 | 50 | 75 | 27 | 1,917,444$/1yrs | |||
Conny Ericsson | 88 | D | 100.00 | 54 | 46 | 74 | 91 | 86 | 93 | 85 | 88 | 25 | 48 | 48 | 72 | 93 | 94 | 91 | 6 | 50 | 74 | 35 | 1,955,000$/1yrs | |||
Borge Bakke (R) | 3 | D | 100.00 | 81 | 67 | 67 | 73 | 81 | 80 | 77 | 55 | 64 | 41 | 59 | 77 | 60 | 69 | 76 | 82 | 50 | 71 | 22 | 1,450,900$/4yrs | |||
| Scratches | ||||||||||||||||||||||||||
Johannes Wilhelmsson | 9 | RW | 100.00 | 75 | 42 | 81 | 92 | 78 | 65 | 83 | 69 | 70 | 84 | 60 | 83 | 83 | 50 | 63 | 7 | 50 | 77 | 34 | 1,999,999$/2yrs | |||
Wade OCuirneen | 61 | RW | 100.00 | 86 | 41 | 89 | 96 | 76 | 66 | 91 | 59 | 49 | 81 | 57 | 82 | 89 | 99 | 89 | 27 | 50 | 76 | 29 | 1,700,000$/2yrs | |||
Dempsey Roos | 88 | LW | 100.00 | 46 | 59 | 72 | 68 | 51 | 96 | 63 | 68 | 48 | 91 | 82 | 96 | 63 | 90 | 47 | 47 | 50 | 74 | 28 | 1,700,000$/5yrs | |||
Burke Hensel (R) | 89 | LW | 100.00 | 61 | 57 | 64 | 76 | 68 | 78 | 55 | 65 | 44 | 81 | 89 | 98 | 57 | 90 | 61 | 54 | 50 | 74 | 24 | 1,765,820$/4yrs | |||
Vyacheslav Burdelyov | 13 | C | 100.00 | 70 | 33 | 66 | 92 | 73 | 70 | 85 | 71 | 97 | 57 | 84 | 52 | 36 | 64 | 40 | 46 | 50 | 73 | 26 | 1,170,000$/3yrs | |||
Raphael Dupuis | 12 | RW | 100.00 | 89 | 63 | 63 | 71 | 55 | 83 | 68 | 70 | 90 | 74 | 50 | 75 | 73 | 84 | 48 | 52 | 50 | 70 | 25 | 999,999$/1yrs | |||
Krister Sandell (R) | 14 | LW | 100.00 | 42 | 49 | 65 | 65 | 77 | 76 | 65 | 57 | 74 | 84 | 81 | 67 | 56 | 78 | 37 | 72 | 50 | 70 | 21 | 800,000$/3yrs | |||
Marcos Pendlebury (R) | 52 | D | 100.00 | 45 | 55 | 60 | 95 | 73 | 95 | 50 | 91 | 25 | 54 | 57 | 85 | 60 | 61 | 55 | 50 | 50 | 71 | 25 | 1,800,900$/4yrs | |||
Branislav Pecnik | 34 | D | 100.00 | 78 | 63 | 56 | 64 | 59 | 79 | 58 | 65 | 62 | 69 | 73 | 68 | 71 | 71 | 64 | 84 | 50 | 67 | 21 | 1,700,000$/4yrs | |||
| Priority | Type | Description |
|---|---|---|
| 1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
| 2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
| 3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig) |
| 4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
| 5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter. |
| 6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
| 7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
| 8 | ? | Wildcard for a single, non-space character. |
| 8 | * | Wildcard for zero or more non-space characters. |
| 9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
| 10 | text | Any text entered in the filter will match text found within the column |
| Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Rylee Hak | 1 | 100.00 | 92 | 76 | 93 | 83 | 86 | 89 | 83 | 66 | 62 | 65 | 57 | 69 | 51 | 67 | 50 | 80 | 23 | 1,950,000$/1yrs |
Tord Tourula | 45 | 100.00 | 82 | 66 | 96 | 69 | 99 | 81 | 81 | 66 | 72 | 52 | 90 | 84 | 29 | 60 | 50 | 76 | 24 | 1,400,000$/2yrs |
| Scratches | ||||||||||||||||||||
Visa-Antti Reimavuo | 33 | 100.00 | 82 | 55 | 99 | 89 | 78 | 78 | 81 | 82 | 58 | 61 | 95 | 90 | 99 | 29 | 50 | 76 | 30 | 1,500,000$/2yrs |
Fredrik Becken | 40 | 100.00 | 68 | 76 | 73 | 69 | 81 | 77 | 75 | 69 | 73 | 82 | 63 | 79 | 80 | 56 | 50 | 74 | 19 | 800,000$/2yrs |
| Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary | ||||||||||||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | Mehdi Winberg | 62 | 62 | 90 | 35 | 97 | 89 | 55 | SWE | 68 | 1 | 600,000$ | |||||||||||||||||||||||||||||||||||||||||||||||
| General Manager | Neil Oliver |
|---|
| 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 | MPG | PPG | PPA | PPP | PKG | PKA | PKP | PKM | GW | GT | FO% | EG | HT | P/GP | PSG | PSS | GSAVG |
|---|
| 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 |
|---|
| Player Name | POS | Age | Cap Hit | 6-7 | 7 | 8 | 9 | 10 | 11 | 12 | 13 |
|---|---|---|---|---|---|---|---|---|---|---|---|
Barnabas Vilezsal ![]() | RW | 30 | 1,999,999$ | 1,999,999$ | 1,999,999$ | ||||||
Borge Bakke | D | 22 | 1,450,900$ | 1,450,900$ | 1,450,900$ | 1,450,900$ | 1,450,900$ | ||||
Branislav Pecnik | D | 21 | 1,700,000$ | 1,700,000$ | 1,700,000$ | 1,700,000$ | 1,700,000$ | ||||
Burke Hensel | LW | 24 | 1,765,820$ | 1,765,820$ | 1,765,820$ | 1,765,820$ | 1,765,820$ | ||||
Conny Ericsson ![]() | D | 35 | 1,955,000$ | 1,955,000$ | |||||||
Culley Daggett | D | 22 | 1,800,000$ | 1,800,000$ | 1,800,000$ | 1,800,000$ | 1,800,000$ | 1,800,000$ | |||
Dan Strom ![]() | LW | 29 | 1,500,000$ | 1,500,000$ | 1,500,000$ | ||||||
Dauren Abdykarimov ![]() | RW | 27 | 1,162,085$ | 1,162,085$ | 1,162,085$ | 1,162,085$ | 1,162,085$ | 1,162,085$ | |||
Dempsey Roos ![]() | LW | 28 | 1,700,000$ | 1,700,000$ | 1,700,000$ | 1,700,000$ | 1,700,000$ | 1,700,000$ | |||
Douwe Hoefnagels ![]() | D | 25 | 1,999,999$ | 1,999,999$ | |||||||
Eli Pajaczkowski ![]() | D | 27 | 1,917,444$ | 1,917,444$ | |||||||
Fredrik Becken | G | 19 | 800,000$ | 800,000$ | 800,000$ | ||||||
Griffin Froats | RW | 24 | 1,787,131$ | 1,787,131$ | 1,787,131$ | 1,787,131$ | 1,787,131$ | 1,787,131$ | |||
Jerry Malmkvist | LW | 24 | 1,700,000$ | 1,700,000$ | 1,700,000$ | 1,700,000$ | 1,700,000$ | ||||
Johannes Wilhelmsson ![]() | RW | 34 | 1,999,999$ | 1,999,999$ | 1,999,999$ | ||||||
Keaton Kanji ![]() | C | 33 | 1,400,000$ | 1,400,000$ | 1,400,000$ | ||||||
Krister Sandell | LW | 21 | 800,000$ | 800,000$ | 800,000$ | 800,000$ | |||||
Leyman Shaeffer | C | 24 | 1,666,000$ | 1,666,000$ | 1,666,000$ | ||||||
Marcos Pendlebury ![]() | D | 25 | 1,800,900$ | 1,800,900$ | 1,800,900$ | 1,800,900$ | 1,800,900$ | ||||
Olaf Brieger | C | 23 | 800,000$ | 800,000$ | |||||||
Philippe-Olivier Jansen ![]() | LW | 25 | 1,800,000$ | 1,800,000$ | 1,800,000$ | 1,800,000$ | 1,800,000$ | ||||
Raphael Dupuis ![]() | RW | 25 | 999,999$ | 999,999$ | |||||||
Roch Fingland ![]() | LW | 26 | 1,432,286$ | 1,432,286$ | |||||||
Rylee Hak | G | 23 | 1,950,000$ | 1,950,000$ | |||||||
Tord Tourula | G | 24 | 1,400,000$ | 1,400,000$ | 1,400,000$ | ||||||
Vaidas Indrisiunas ![]() | RW | 26 | 1,900,000$ | 1,900,000$ | 1,900,000$ | 1,900,000$ | |||||
Vasilica Ciubotariu | D | 24 | 1,375,000$ | 1,375,000$ | |||||||
Visa-Antti Reimavuo ![]() | G | 30 | 1,500,000$ | 1,500,000$ | 1,500,000$ | ||||||
Vyacheslav Burdelyov ![]() | C | 26 | 1,170,000$ | 1,170,000$ | 1,170,000$ | 1,170,000$ | |||||
Wade OCuirneen ![]() | RW | 29 | 1,700,000$ | 1,700,000$ | 1,700,000$ | ||||||
Willem Halward ![]() | C | 25 | 1,700,000$ | 1,700,000$ | 1,700,000$ |
| 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 |
| Salary Cap | |||
|---|---|---|---|
| Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
| 4,863,256$ | 0$ | 0$ | 75,000,000$ |
| Arena | About us | |
|---|---|---|
| Name | |
| City | Grande Prairie | |
| Capacity | 3000 | |
| Season Ticket Holders | 10% | |
| Arena Capacity - Ticket Price Attendance - % | |||||
|---|---|---|---|---|---|
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| Arena Capacity | 2000 | 1000 | |||
| Ticket Price | 40$ | 20$ | $ | $ | $ |
| 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 |
| 40 | 0 - 0.00% | 0$ | 0$ | 3000 | 100 |
| Expenses | |||
|---|---|---|---|
| Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
| 4,863,256$ | 4,863,256$ | 0$ | 0$ |
| Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
|---|---|---|---|
| 0$ | 4,863,256$ | 0$ | 0$ |
| Estimate | |||
|---|---|---|---|
| Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
| 0$ | 147 | 37,165$ | 5,463,255$ |
| Team Total Estimate | |||
|---|---|---|---|
| Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
| 5,463,255$ | 0$ | 0$ | 0$ |
| Sponsors | |||
|---|---|---|---|
| TV Rights | Primary Sponsor | Secondary Sponsor | Secondary Sponsor |
Rookie
Injured
Cold Streak
Hot Streak | Left Wing | Center | Right Wing |
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| Defense #1 | Defense #2 | Goalie |
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