![](images/LogoTeams/Pro/0.png)
![](images/LogoTeams/Pro/22.png)
![](images/LogoTeams/Pro/7.png)
![](images/LogoTeams/Pro/3.png)
![](images/LogoTeams/Pro/21.png)
![](images/LogoTeams/Pro/8.png)
![](images/LogoTeams/Pro/13.png)
![](images/LogoTeams/Pro/9.png)
![](images/LogoTeams/Pro/15.png)
![](images/LogoTeams/Pro/23.png)
![](images/LogoTeams/Pro/14.png)
![](images/LogoTeams/Pro/17.png)
![](images/LogoTeams/Pro/1.png)
![](images/LogoTeams/Pro/19.png)
![](images/LogoTeams/Pro/18.png)
![](images/LogoTeams/Pro/6.png)
![](images/LogoTeams/Pro/12.png)
![](images/LogoTeams/Pro/11.png)
![](images/LogoTeams/Pro/4.png)
![](images/LogoTeams/Pro/10.png)
![](images/LogoTeams/Pro/16.png)
![](images/LogoTeams/Pro/20.png)
![](images/LogoTeams/Pro/2.png)
![](images/LogoTeams/Pro/24.png)
![](images/LogoTeams/Pro/5.png)
![](images/NJHL.png)
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 | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | RW | 100.00 | 64 | 36 | 77 | 62 | 68 | 80 | 67 | 86 | 69 | 70 | 63 | 99 | 87 | 93 | 90 | 40 | 50 | 74 | 27 | 745,000$/1yrs | |||
![]() | 0 | LW | 100.00 | 62 | 62 | 61 | 91 | 90 | 74 | 71 | 73 | 80 | 53 | 70 | 67 | 47 | 50 | 56 | 42 | 50 | 72 | 26 | 1,444,444$/4yrs | |||
![]() | 0 | LW | 100.00 | 83 | 29 | 89 | 78 | 84 | 80 | 81 | 91 | 68 | 58 | 47 | 53 | 88 | 76 | 91 | 74 | 50 | 72 | 21 | 1,395,000$/1yrs | |||
![]() | 0 | LW | 100.00 | 82 | 63 | 76 | 92 | 75 | 59 | 65 | 79 | 48 | 54 | 58 | 93 | 37 | 40 | 51 | 61 | 50 | 70 | 23 | 1,993,444$/4yrs | |||
![]() | 0 | D | 100.00 | 31 | 63 | 95 | 97 | 81 | 70 | 74 | 79 | 25 | 52 | 79 | 87 | 51 | 53 | 52 | 53 | 50 | 73 | 24 | 1,944,444$/4yrs | |||
![]() | 0 | D | 100.00 | 60 | 48 | 91 | 92 | 40 | 71 | 71 | 82 | 25 | 52 | 76 | 90 | 95 | 77 | 94 | 14 | 50 | 69 | 31 | 1,144,444$/2yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | LW | 100.00 | 92 | 68 | 66 | 86 | 64 | 64 | 84 | 99 | 70 | 77 | 72 | 47 | 90 | 67 | 56 | 22 | 50 | 75 | 30 | 624,000$/2yrs | |||
![]() | 0 | C | 100.00 | 62 | 59 | 82 | 89 | 65 | 68 | 87 | 77 | 78 | 80 | 51 | 75 | 46 | 92 | 66 | 33 | 50 | 74 | 28 | 485,000$/2yrs | |||
![]() | 0 | C | 100.00 | 71 | 61 | 72 | 91 | 79 | 64 | 70 | 67 | 66 | 87 | 49 | 75 | 82 | 41 | 36 | 44 | 50 | 73 | 28 | 420,000$/2yrs | |||
![]() | 0 | RW | 100.00 | 87 | 54 | 65 | 87 | 51 | 88 | 48 | 96 | 58 | 76 | 59 | 85 | 81 | 53 | 67 | 60 | 50 | 73 | 22 | 545,000$/3yrs | |||
![]() | 0 | RW | 100.00 | 50 | 57 | 56 | 93 | 71 | 87 | 52 | 88 | 67 | 51 | 54 | 92 | 34 | 53 | 40 | 71 | 50 | 70 | 22 | 490,000$/3yrs | |||
![]() | 0 | RW | 100.00 | 56 | 68 | 67 | 78 | 71 | 71 | 50 | 86 | 64 | 61 | 42 | 97 | 71 | 87 | 91 | 43 | 50 | 68 | 26 | 711,444$/1yrs | |||
![]() | 0 | C | 100.00 | 50 | 54 | 71 | 77 | 66 | 73 | 66 | 96 | 64 | 60 | 63 | 59 | 48 | 94 | 98 | 33 | 50 | 68 | 28 | 581,000$/1yrs | |||
![]() | 0 | RW | 100.00 | 40 | 57 | 59 | 84 | 34 | 52 | 61 | 91 | 55 | 36 | 75 | 87 | 59 | 85 | 66 | 66 | 50 | 62 | 22 | 777,444$/1yrs | |||
![]() | 0 | D | 100.00 | 41 | 55 | 88 | 89 | 65 | 72 | 92 | 90 | 25 | 48 | 57 | 96 | 72 | 95 | 60 | 54 | 50 | 73 | 24 | 1,917,444$/4yrs | |||
![]() | 0 | D | 100.00 | 43 | 37 | 84 | 82 | 63 | 79 | 70 | 68 | 25 | 72 | 59 | 99 | 35 | 65 | 53 | 50 | 50 | 71 | 24 | 782,000$/3yrs | |||
![]() | 0 | D | 100.00 | 64 | 42 | 88 | 88 | 86 | 69 | 50 | 72 | 25 | 48 | 36 | 79 | 65 | 71 | 71 | 22 | 50 | 69 | 32 | 780,444$/1yrs | |||
![]() | 0 | D | 100.00 | 86 | 42 | 79 | 85 | 59 | 58 | 50 | 74 | 25 | 45 | 64 | 96 | 95 | 95 | 97 | 3 | 50 | 69 | 35 | 1,119,000$/1yrs | |||
![]() | 0 | D | 100.00 | 64 | 50 | 70 | 96 | 71 | 55 | 55 | 87 | 25 | 53 | 33 | 72 | 32 | 73 | 55 | 59 | 50 | 66 | 23 | 321,000$/2yrs | |||
![]() | 0 | D | 100.00 | 53 | 49 | 54 | 93 | 52 | 90 | 50 | 88 | 25 | 61 | 33 | 75 | 61 | 90 | 49 | 68 | 50 | 65 | 21 | 544,444$/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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 100.00 | 81 | 76 | 98 | 67 | 62 | 97 | 75 | 55 | 75 | 59 | 97 | 67 | 41 | 44 | 50 | 74 | 26 | 1,365,000$/2yrs |
Scratches | ||||||||||||||||||||
![]() | 0 | 100.00 | 82 | 65 | 94 | 64 | 58 | 89 | 94 | 50 | 60 | 73 | 86 | 78 | 83 | 70 | 50 | 73 | 21 | 1,537,500$/1yrs |
![]() | 0 | 100.00 | 60 | 97 | 83 | 73 | 51 | 64 | 63 | 58 | 78 | 51 | 86 | 77 | 71 | 39 | 50 | 68 | 28 | 1,217,500$/1yrs |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary | ||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | Ralph Kay | 84 | 83 | 34 | 96 | 53 | 47 | 94 | CAN | 63 | 3 | 444,000$ |
General Manager | Tim Krautz |
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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 | MPG | PPG | PPA | PPP | PKG | PKA | PKP | PKM | GW | GT | FO% | EG | HT | P/GP | PSG | PSS | GSAVG |
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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 |
---|
Player Name | POS | Age | Cap Hit | 3-4 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
---|---|---|---|---|---|---|---|---|---|---|---|
Alex Kessell ![]() | RW | 22 | 490,000$ | 490,000$ | 490,000$ | 490,000$ | |||||
Anton Kurali ![]() | C | 28 | 420,000$ | 420,000$ | 420,000$ | ||||||
Ballard Winston ![]() | LW | 23 | 1,993,444$ | 1,993,444$ | 1,993,444$ | 1,993,444$ | 1,993,444$ | ||||
Bennet Gallahur ![]() | D | 24 | 1,944,444$ | 1,944,444$ | 1,944,444$ | 1,944,444$ | 1,944,444$ | ||||
Daine Finley ![]() | RW | 22 | 777,444$ | 777,444$ | |||||||
Darryl Feltrin ![]() | RW | 26 | 711,444$ | 711,444$ | |||||||
Derick Sordet ![]() | G | 28 | 1,217,500$ | 1,217,500$ | |||||||
Eli Pajaczkowski ![]() | D | 24 | 1,917,444$ | 1,917,444$ | 1,917,444$ | 1,917,444$ | 1,917,444$ | ||||
Huxley Vanderveen ![]() | D | 35 | 1,119,000$ | 1,119,000$ | |||||||
Iko Poysti ![]() | C | 28 | 581,000$ | 581,000$ | |||||||
Illija Ajbek ![]() | D | 31 | 1,144,444$ | 1,144,444$ | 1,144,444$ | ||||||
Keevin Fostvelt ![]() | G | 21 | 1,537,500$ | 1,537,500$ | |||||||
Melker Lennartsson ![]() | D | 24 | 782,000$ | 782,000$ | 782,000$ | 782,000$ | |||||
Nico Flache ![]() | D | 32 | 780,444$ | 780,444$ | |||||||
Paulo Keitaanranta ![]() | G | 26 | 1,365,000$ | 1,365,000$ | 1,365,000$ | ||||||
Pekka-Matti Laaperi ![]() | D | 23 | 321,000$ | 321,000$ | 321,000$ | ||||||
Pierre-Anthony Comrie ![]() | RW | 27 | 745,000$ | 745,000$ | |||||||
Quincy Dagenais ![]() | C | 28 | 485,000$ | 485,000$ | 485,000$ | ||||||
Rashit Musayev ![]() | D | 21 | 544,444$ | 544,444$ | 544,444$ | ||||||
Robert Friend ![]() | LW | 21 | 1,395,000$ | 1,395,000$ | |||||||
Sarno Huopio ![]() | LW | 30 | 624,000$ | 624,000$ | 624,000$ | ||||||
Valery Adlerov ![]() | RW | 22 | 545,000$ | 545,000$ | 545,000$ | 545,000$ | |||||
Wendell Sarrazin ![]() | LW | 26 | 1,444,444$ | 1,444,444$ | 1,444,444$ | 1,444,444$ | 1,444,444$ |
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 |
Date | Matchup | Result | Detail |
---|
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
2,288,496$ | 0$ | 0$ | 75,000,000$ |
Arena | About us | |
---|---|---|
![]() | Name | |
City | Syracuse | |
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 |
40 | 0 - 0.00% | 0$ | 0$ | 3000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
2,288,496$ | 2,288,496$ | 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 |
---|---|---|
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Defense #1 | Defense #2 | Goalie |
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