

























GP | W | L | OT | Pts |
---|---|---|---|---|
0 | 0 | 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 | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 52 | C | 100.00 | 81 | 45 | 61 | 94 | 75 | 73 | 62 | 78 | 79 | 71 | 92 | 69 | 50 | 43 | 98 | 38 | 50 | 76 | 29 | 1,600,000$/2yrs | |||
![]() | 95 | RW | 100.00 | 64 | 49 | 74 | 74 | 95 | 67 | 78 | 78 | 82 | 45 | 91 | 85 | 70 | 40 | 35 | 81 | 50 | 75 | 21 | 900,000$/2yrs | |||
![]() | 56 | LW | 100.00 | 53 | 55 | 75 | 83 | 71 | 91 | 89 | 89 | 67 | 54 | 44 | 98 | 63 | 97 | 84 | 9 | 50 | 74 | 34 | 1,100,000$/1yrs | |||
![]() | 93 | RW | 100.00 | 67 | 34 | 73 | 64 | 58 | 89 | 78 | 93 | 77 | 66 | 60 | 82 | 87 | 30 | 27 | 71 | 50 | 73 | 21 | 800,000$/1yrs | |||
![]() | 58 | C | 100.00 | 37 | 37 | 75 | 93 | 85 | 60 | 66 | 63 | 99 | 51 | 71 | 65 | 81 | 74 | 41 | 4 | 50 | 68 | 34 | 700,000$/1yrs | |||
![]() | 63 | C | 100.00 | 89 | 32 | 74 | 76 | 47 | 95 | 83 | 72 | 82 | 37 | 87 | 41 | 86 | 50 | 62 | 76 | 50 | 68 | 21 | 800,000$/1yrs | |||
![]() | 89 | LW | 100.00 | 36 | 45 | 87 | 61 | 48 | 81 | 65 | 71 | 97 | 37 | 71 | 93 | 70 | 73 | 67 | 16 | 50 | 66 | 31 | 700,000$/2yrs | |||
![]() | 16 | D | 100.00 | 69 | 62 | 61 | 95 | 78 | 89 | 87 | 83 | 25 | 76 | 51 | 75 | 51 | 78 | 80 | 68 | 50 | 77 | 22 | 1,700,000$/3yrs | |||
![]() | 14 | D | 100.00 | 95 | 41 | 68 | 64 | 85 | 65 | 51 | 68 | 25 | 82 | 70 | 93 | 52 | 35 | 36 | 42 | 50 | 75 | 26 | 1,212,000$/1yrs | |||
![]() | 22 | D | 100.00 | 55 | 38 | 64 | 75 | 85 | 99 | 60 | 71 | 25 | 85 | 43 | 90 | 74 | 97 | 76 | 34 | 50 | 74 | 28 | 728,000$/1yrs | |||
![]() | 2 | D | 100.00 | 99 | 37 | 65 | 55 | 64 | 62 | 87 | 94 | 25 | 88 | 53 | 79 | 76 | 74 | 82 | 39 | 50 | 73 | 27 | 1,350,000$/3yrs | |||
![]() | 40 | D | 100.00 | 58 | 57 | 92 | 89 | 71 | 59 | 85 | 68 | 25 | 55 | 67 | 81 | 99 | 57 | 96 | 29 | 50 | 72 | 29 | 1,100,000$/1yrs | |||
![]() | 0 | D | 100.00 | 40 | 39 | 59 | 90 | 57 | 86 | 51 | 63 | 25 | 87 | 45 | 99 | 52 | 59 | 49 | 54 | 50 | 69 | 25 | 700,000$/2yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 80 | C | 100.00 | 45 | 42 | 85 | 95 | 76 | 79 | 50 | 91 | 96 | 58 | 43 | 99 | 80 | 41 | 44 | 1 | 50 | 73 | 35 | 1,400,000$/1yrs | |||
![]() | 0 | LW | 100.00 | 25 | 62 | 83 | 69 | 80 | 98 | 90 | 83 | 58 | 53 | 63 | 77 | 35 | 30 | 68 | 73 | 50 | 72 | 21 | 1,000,000$/3yrs | |||
![]() | 0 | LW | 100.00 | 33 | 50 | 73 | 72 | 79 | 67 | 93 | 79 | 83 | 49 | 71 | 82 | 95 | 30 | 56 | 68 | 50 | 71 | 21 | 900,000$/3yrs | |||
![]() | 0 | C | 100.00 | 69 | 59 | 87 | 62 | 65 | 79 | 97 | 64 | 91 | 42 | 66 | 94 | 35 | 26 | 81 | 74 | 50 | 71 | 21 | 800,000$/3yrs | |||
![]() | 59 | RW | 100.00 | 79 | 45 | 66 | 78 | 93 | 62 | 74 | 60 | 82 | 50 | 85 | 35 | 77 | 44 | 75 | 48 | 50 | 68 | 25 | 818,750$/5yrs | |||
![]() | 44 | D | 100.00 | 55 | 40 | 68 | 74 | 99 | 99 | 81 | 83 | 25 | 42 | 77 | 78 | 58 | 43 | 32 | 63 | 50 | 75 | 22 | 800,000$/1yrs | |||
![]() | 0 | D | 100.00 | 68 | 48 | 91 | 68 | 83 | 77 | 85 | 66 | 72 | 67 | 59 | 85 | 89 | 64 | 80 | 79 | 50 | 75 | 18 | 900,000$/3yrs | |||
![]() | 6 | D | 100.00 | 90 | 39 | 94 | 89 | 66 | 88 | 67 | 81 | 25 | 56 | 48 | 57 | 76 | 46 | 61 | 20 | 50 | 71 | 32 | 904,000$/1yrs | |||
![]() | 0 | D | 100.00 | 48 | 64 | 73 | 88 | 92 | 61 | 49 | 56 | 25 | 67 | 61 | 81 | 77 | 42 | 41 | 4 | 50 | 70 | 35 | 1,000,000$/1yrs | |||
![]() | 18 | D | 100.00 | 90 | 63 | 65 | 71 | 55 | 89 | 48 | 85 | 25 | 60 | 73 | 59 | 43 | 68 | 51 | 9 | 50 | 68 | 34 | 700,000$/1yrs |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 33 | 100.00 | 64 | 92 | 71 | 82 | 92 | 80 | 68 | 61 | 79 | 65 | 63 | 36 | 74 | 71 | 50 | 75 | 21 | 800,000$/2yrs |
![]() | 32 | 100.00 | 83 | 67 | 74 | 66 | 65 | 53 | 78 | 84 | 68 | 82 | 61 | 93 | 49 | 51 | 50 | 72 | 26 | 1,497,500$/1yrs |
Scratches |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary | ||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | Julian Weiss | 94 | 30 | 94 | 92 | 40 | 97 | 57 | USA | 47 | 1 | 1,000,000$ |
General Manager | Alexander Phillips |
---|
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 | 5-6 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
---|---|---|---|---|---|---|---|---|---|---|---|
Alek Isotalus ![]() | D | 29 | 1,100,000$ | 1,100,000$ | |||||||
Atley Hebert ![]() | G | 26 | 1,497,500$ | 1,497,500$ | |||||||
Butch Fitzstephens ![]() | LW | 31 | 700,000$ | 700,000$ | 700,000$ | ||||||
Callen Dreeshen ![]() | D | 26 | 1,212,000$ | 1,212,000$ | |||||||
Daxton Wentworth ![]() | D | 35 | 1,000,000$ | 1,000,000$ | |||||||
Dru Pearkes ![]() | C | 29 | 1,600,000$ | 1,600,000$ | 1,600,000$ | ||||||
Erling Olsson ![]() | D | 25 | 700,000$ | 700,000$ | 700,000$ | ||||||
Henrick Polley ![]() | G | 21 | 800,000$ | 800,000$ | 800,000$ | ||||||
Hugues Glenn ![]() | C | 34 | 700,000$ | 700,000$ | |||||||
Ignaty Syromolotov ![]() | LW | 21 | 900,000$ | 900,000$ | 900,000$ | 900,000$ | |||||
Igor Karsenev ![]() | LW | 34 | 1,100,000$ | 1,100,000$ | |||||||
Igor Zheldakov ![]() | D | 22 | 1,700,000$ | 1,700,000$ | 1,700,000$ | 1,700,000$ | |||||
Jaki Krabbe ![]() | RW | 25 | 818,750$ | 818,750$ | 818,750$ | 818,750$ | 818,750$ | 818,750$ | |||
Johnny Leclair ![]() | D | 27 | 1,350,000$ | 1,350,000$ | 1,350,000$ | 1,350,000$ | |||||
Keeley Lamp ![]() | D | 34 | 700,000$ | 700,000$ | |||||||
Leonid Pafov ![]() | D | 22 | 800,000$ | 800,000$ | |||||||
Mark Stefanski ![]() | C | 21 | 800,000$ | 800,000$ | |||||||
Ole Hansen ![]() | D | 18 | 900,000$ | 900,000$ | 900,000$ | 900,000$ | |||||
Oskar Dudrov ![]() | D | 32 | 904,000$ | 904,000$ | |||||||
Ruslan Sarvarov ![]() | C | 35 | 1,400,000$ | 1,400,000$ | |||||||
Shiro Kaima ![]() | C | 21 | 800,000$ | 800,000$ | 800,000$ | 800,000$ | |||||
Takeji Takata ![]() | RW | 21 | 800,000$ | 800,000$ | |||||||
Tani Pahkamaa ![]() | RW | 21 | 900,000$ | 900,000$ | 900,000$ | ||||||
Yann Hammond ![]() | LW | 21 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | |||||
Zane Haddix ![]() | D | 28 | 728,000$ | 728,000$ |
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 |
2,491,025$ | 0$ | 0$ | 75,000,000$ |
Arena | About us | |
---|---|---|
![]() | Name | |
City | Berkeley | |
Capacity | 3000 | |
Season Ticket Holders | 10% |
Arena Capacity - Ticket Price Attendance - % | |||||
---|---|---|---|---|---|
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
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 | |||||
---|---|---|---|---|---|
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
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 |
2,491,025$ | 2,491,025$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
0$ | 0$ | 0$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 0 | 0$ | 0$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
0$ | 0$ | 0$ | 0$ |
Sponsors | |||
---|---|---|---|
TV Rights | Primary Sponsor | Secondary Sponsor | Secondary Sponsor |
Left Wing | Center | Right Wing |
---|---|---|
|
|
|
Defense #1 | Defense #2 | Goalie |
---|---|---|
|
|
|