Manitoba Moose | |
GP: 24 | W: 8 | L: 14 | OTL: 2 | P: 18 GF: 56 | GA: 97 | PP%: 12.90% | PK%: 84.85% GM : Alexandre Rivard | Morale : 50 | Team Overall : N/A Next Games #400 vs Coachella Valley Firebirds |
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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 | C | L | R | D | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | TA | SP | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Sam Gagner | X | X | 100.00 | 63 | 37 | 92 | 67 | 72 | 78 | 77 | 66 | 68 | 63 | 65 | 64 | 69 | 85 | 77 | 45 | 49 | 0 | 0 | 35 | 2 | 775,000$ | |||
2 | Mackenzie MacEachern | X | 100.00 | 72 | 38 | 90 | 62 | 79 | 78 | 74 | 59 | 63 | 64 | 58 | 61 | 62 | 70 | 72 | 53 | 50 | 0 | 0 | 30 | 1 | 775,000$ | ||||
3 | Matthew Peca | X | 100.00 | 58 | 37 | 92 | 64 | 67 | 85 | 75 | 62 | 74 | 66 | 60 | 62 | 63 | 71 | 73 | 38 | 50 | 0 | 0 | 31 | 1 | 700,000$ | ||||
4 | MacKenzie Entwistle | X | 100.00 | 78 | 56 | 86 | 63 | 84 | 79 | 85 | 62 | 75 | 59 | 60 | 64 | 58 | 65 | 66 | 63 | 50 | 0 | 0 | 25 | 2 | 850,000$ | ||||
5 | Boris Katchouk (R) | X | X | X | 100.00 | 73 | 59 | 90 | 65 | 82 | 79 | 83 | 64 | 62 | 63 | 67 | 68 | 65 | 67 | 69 | 70 | 50 | 0 | 0 | 26 | 1 | 750,000$ | ||
6 | Kyle MacLean (R) | X | X | 100.00 | 69 | 40 | 73 | 63 | 74 | 77 | 87 | 61 | 75 | 62 | 60 | 64 | 62 | 66 | 67 | 42 | 50 | 0 | 0 | 25 | 4 | 800,000$ | |||
7 | Ben Meyers (R) | X | 100.00 | 64 | 36 | 93 | 63 | 71 | 82 | 83 | 62 | 79 | 64 | 61 | 60 | 62 | 67 | 68 | 42 | 50 | 0 | 0 | 25 | 2 | 925,000$ | ||||
8 | Gustav Olofsson | X | 100.00 | 68 | 38 | 89 | 61 | 80 | 76 | 73 | 57 | 30 | 60 | 58 | 64 | 49 | 70 | 72 | 59 | 50 | 0 | 0 | 29 | 1 | 775,000$ | ||||
9 | Ashton Sautner | X | 100.00 | 67 | 40 | 77 | 56 | 76 | 68 | 85 | 55 | 30 | 54 | 53 | 57 | 45 | 70 | 72 | 35 | 50 | 0 | 0 | 30 | 1 | 750,000$ | ||||
10 | Dakota Mermis (R) | X | 100.00 | 65 | 45 | 71 | 63 | 73 | 84 | 82 | 62 | 30 | 64 | 60 | 67 | 50 | 70 | 72 | 35 | 50 | 0 | 0 | 30 | 1 | 775,000$ | ||||
11 | Brayden Pachal (R) | X | 100.00 | 75 | 44 | 66 | 64 | 81 | 82 | 81 | 62 | 30 | 63 | 59 | 68 | 53 | 65 | 67 | 42 | 50 | 0 | 0 | 25 | 4 | 775,000$ | ||||
12 | Jacob Moverare (R) | X | 100.00 | 72 | 39 | 86 | 63 | 85 | 75 | 83 | 58 | 30 | 61 | 59 | 64 | 50 | 66 | 68 | 58 | 50 | 0 | 0 | 26 | 4 | 775,000$ | ||||
13 | Vladislav Kolyachonok | X | 100.00 | 67 | 38 | 81 | 63 | 76 | 79 | 81 | 61 | 30 | 63 | 62 | 65 | 52 | 64 | 65 | 71 | 50 | 0 | 0 | 23 | 2 | 775,000$ | ||||
14 | Philip Broberg (R) | X | 100.00 | 75 | 39 | 95 | 65 | 89 | 79 | 81 | 63 | 30 | 67 | 58 | 64 | 50 | 63 | 65 | 86 | 50 | 0 | 0 | 23 | 1 | 925,000$ | ||||
Scratches | |||||||||||||||||||||||||||||
1 | Kurtis Gabriel | X | 100.00 | 40 | 35 | 40 | 40 | 35 | 80 | 90 | 40 | 20 | 40 | 40 | 40 | 30 | 25 | 25 | 11 | 50 | 0 | 0 | 31 | 2 | 750,000$ | ||||
2 | Brett Ritchie | X | 100.00 | 40 | 35 | 40 | 61 | 35 | 80 | 90 | 40 | 20 | 40 | 40 | 40 | 30 | 72 | 70 | 11 | 50 | 0 | 0 | 31 | 3 | 760,000$ | ||||
3 | Drake Caggiula | X | X | X | 100.00 | 70 | 38 | 78 | 64 | 66 | 82 | 81 | 62 | 65 | 63 | 59 | 60 | 61 | 71 | 72 | 35 | 50 | 0 | 0 | 30 | 3 | 760,000$ | ||
4 | Austin Poganski | X | 100.00 | 68 | 40 | 81 | 56 | 77 | 78 | 85 | 57 | 62 | 58 | 59 | 60 | 55 | 68 | 70 | 50 | 50 | 0 | 0 | 28 | 2 | 750,000$ | ||||
TEAM AVERAGE | 100.00 | 66 | 41 | 79 | 61 | 72 | 79 | 82 | 59 | 49 | 60 | 58 | 61 | 54 | 66 | 67 | 47 | 50 | 0 |
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 | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | TA | SP | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Ivan Prosvetov (R) | 100.00 | 63 | 99 | 80 | 88 | 64 | 67 | 66 | 66 | 67 | 55 | 76 | 65 | 73 | 57 | 46 | 0 | 0 | 25 | 2 | 750,000$ | |
Scratches | |||||||||||||||||||||||
1 | Kevin Boyle | 100.00 | 40 | 90 | 80 | 50 | 40 | 40 | 40 | 40 | 40 | 40 | 40 | 25 | 25 | 11 | 50 | 0 | 0 | 32 | 1 | 702,020$ | |
TEAM AVERAGE | 100.00 | 52 | 95 | 80 | 69 | 52 | 54 | 53 | 53 | 54 | 48 | 58 | 45 | 49 | 34 | 48 | 0 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
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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 | HTT | SHT | OSB | OSM | SHT% | SB | MP | AMG | PPG | PPA | PPP | PPS | PPM | PKG | PKA | PKP | PKS | PKM | GW | GT | FO% | FOT | GA | TA | EG | HT | P/20 | PSG | PSS | FW | FL | FT | S1 | S2 | S3 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Philip Broberg | Manitoba Moose (WPG) | D | 23 | 1 | 13 | 14 | 9 | 14 | 0 | 39 | 22 | 30 | 10 | 25 | 3.33% | 14 | 424 | 18.45 | 1 | 2 | 3 | 15 | 30 | 0 | 0 | 0 | 1 | 33 | 1 | 0 | 0% | 0 | 0 | 0 | 0 | 0 | 0.66 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 |
Team Total or Average | 23 | 1 | 13 | 14 | 9 | 14 | 0 | 39 | 22 | 30 | 10 | 25 | 3.33% | 14 | 424 | 18.45 | 1 | 2 | 3 | 15 | 30 | 0 | 0 | 0 | 1 | 33 | 1 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.66 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 |
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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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 | Age | Birthday | Country | Rookie | Weight | Height | No Trade | Available For Trade | Acquired By | Last Trade Date | Force Waivers | Waiver Possible | Contract | Contract Signature Date | Force UFA | Emergency Recall | Type | Current Salary | Salary Remaining | Salary Cap | Salary Cap Remaining | Exclude from Salary Cap | Salary Year 2 | Salary Year 3 | Salary Year 4 | Salary Year 5 | Salary Year 6 | Salary Year 7 | Salary Year 8 | Salary Year 9 | Salary Year 10 | Salary Cap Year 2 | Salary Cap Year 3 | Salary Cap Year 4 | Salary Cap Year 5 | Salary Cap Year 6 | Salary Cap Year 7 | Salary Cap Year 8 | Salary Cap Year 9 | Salary Cap Year 10 | No Trade Year 2 | No Trade Year 3 | No Trade Year 4 | No Trade Year 5 | No Trade Year 6 | No Trade Year 7 | No Trade Year 8 | No Trade Year 9 | No Trade Year 10 | Link |
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Ashton Sautner | Manitoba Moose (WPG) | D | 30 | 1994-05-27 | CAN | No | 195 Lbs | 6 ft1 | No | No | N/A | No | No | 1 | False | False | Pro & Farm | 750,000$ | 525,773$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Link | ||
Austin Poganski | Manitoba Moose (WPG) | RW | 28 | 1996-02-16 | USA | No | 198 Lbs | 6 ft1 | No | No | N/A | No | No | 2 | False | False | Pro & Farm | 750,000$ | 525,773$ | 0$ | 0$ | No | 750,000$ | - | - | - | - | - | - | - | - | 702,020$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | Link | ||
Ben Meyers | Manitoba Moose (WPG) | C | 25 | 1998-11-15 | USA | Yes | 194 Lbs | 5 ft11 | No | No | N/A | No | No | 2 | False | False | Pro & Farm | 925,000$ | 648,454$ | 0$ | 0$ | No | 925,000$ | - | - | - | - | - | - | - | - | 600,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | Link | ||
Boris Katchouk | Manitoba Moose (WPG) | C/LW/RW | 26 | 1998-06-18 | CAN | Yes | 206 Lbs | 6 ft2 | No | No | N/A | No | No | 1 | False | False | Pro & Farm | 750,000$ | 525,773$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Link | ||
Brayden Pachal | Manitoba Moose (WPG) | D | 25 | 1999-08-23 | CAN | Yes | 202 Lbs | 6 ft2 | No | No | Assign Manually | No | No | 4 | 2024-08-27 | False | False | Pro & Farm | 775,000$ | 543,299$ | 0$ | 0$ | No | 775,000$ | 775,000$ | 775,000$ | - | - | - | - | - | - | 600,000$ | 600,000$ | 600,000$ | - | - | - | - | - | - | No | No | No | - | - | - | - | - | - | Link | |
Brett Ritchie | Manitoba Moose (WPG) | RW | 31 | 1993-07-01 | CAN | No | 215 Lbs | 6 ft4 | No | No | N/A | No | No | 3 | False | False | Pro & Farm | 760,000$ | 532,784$ | 0$ | 0$ | No | 760,000$ | 760,000$ | - | - | - | - | - | - | - | 600,000$ | 600,000$ | - | - | - | - | - | - | - | No | No | - | - | - | - | - | - | - | Link | ||
Dakota Mermis | Manitoba Moose (WPG) | D | 30 | 1994-01-05 | USA | Yes | 195 Lbs | 6 ft0 | No | No | Assign Manually | No | No | 1 | 2024-08-20 | False | False | Pro & Farm | 775,000$ | 543,299$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Link | |
Drake Caggiula | Manitoba Moose (WPG) | C/LW/RW | 30 | 1994-06-20 | CAN | No | 176 Lbs | 5 ft10 | No | No | N/A | No | No | 3 | False | False | Pro & Farm | 760,000$ | 532,784$ | 0$ | 0$ | No | 760,000$ | 760,000$ | - | - | - | - | - | - | - | 600,000$ | 600,000$ | - | - | - | - | - | - | - | No | No | - | - | - | - | - | - | - | Link | ||
Gustav Olofsson | Manitoba Moose (WPG) | D | 29 | 1994-12-01 | SWE | No | 199 Lbs | 6 ft2 | No | No | N/A | No | No | 1 | 2024-05-19 | False | False | Pro & Farm | 775,000$ | 543,299$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Link | |
Ivan Prosvetov | Manitoba Moose (WPG) | G | 25 | 1999-03-04 | RUS | Yes | 195 Lbs | 6 ft5 | No | No | N/A | No | No | 2 | False | False | Pro & Farm | 750,000$ | 525,773$ | 0$ | 0$ | No | 750,000$ | - | - | - | - | - | - | - | - | 750,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | Link | ||
Jacob Moverare | Manitoba Moose (WPG) | D | 26 | 1998-08-31 | SWE | Yes | 210 Lbs | 6 ft3 | No | No | Assign Manually | No | No | 4 | 2024-08-20 | False | False | Pro & Farm | 775,000$ | 543,299$ | 0$ | 0$ | No | 775,000$ | 775,000$ | 775,000$ | - | - | - | - | - | - | 600,000$ | 600,000$ | 600,000$ | - | - | - | - | - | - | No | No | No | - | - | - | - | - | - | Link | |
Kevin Boyle | Manitoba Moose (WPG) | G | 32 | 1992-05-30 | USA | No | 201 Lbs | 6 ft0 | No | No | N/A | No | No | 1 | False | False | Pro & Farm | 702,020$ | 492,138$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Link | ||
Kurtis Gabriel | Manitoba Moose (WPG) | RW | 31 | 1993-04-20 | CAN | No | 212 Lbs | 6 ft6 | No | No | N/A | No | No | 2 | False | False | Pro & Farm | 750,000$ | 525,773$ | 0$ | 0$ | No | 750,000$ | - | - | - | - | - | - | - | - | 750,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | Link | ||
Kyle MacLean | Manitoba Moose (WPG) | C/LW | 25 | 1999-04-29 | USA | Yes | 190 Lbs | 6 ft1 | No | No | Assign Manually | No | No | 4 | 2024-08-27 | False | False | Pro & Farm | 800,000$ | 560,825$ | 0$ | 0$ | No | 800,000$ | 800,000$ | 800,000$ | - | - | - | - | - | - | 600,000$ | 600,000$ | 600,000$ | - | - | - | - | - | - | No | No | No | - | - | - | - | - | - | Link | |
MacKenzie Entwistle | Manitoba Moose (WPG) | RW | 25 | 1999-07-14 | CAN | No | 205 Lbs | 6 ft3 | No | No | N/A | No | No | 2 | 2024-08-21 | False | False | Pro & Farm | 850,000$ | 595,876$ | 0$ | 0$ | No | 850,000$ | - | - | - | - | - | - | - | - | 600,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | Link | |
Mackenzie MacEachern | Manitoba Moose (WPG) | LW | 30 | 1994-03-09 | USA | No | 193 Lbs | 6 ft2 | No | No | N/A | No | No | 1 | 2024-05-19 | False | False | Pro & Farm | 775,000$ | 543,299$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Link | |
Matthew Peca | Manitoba Moose (WPG) | C | 31 | 1993-04-27 | CAN | No | 181 Lbs | 5 ft10 | No | No | N/A | No | No | 1 | False | False | Pro & Farm | 700,000$ | 490,722$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Link | ||
Philip Broberg | Manitoba Moose (WPG) | D | 23 | 2001-06-25 | SWE | Yes | 212 Lbs | 6 ft4 | No | No | Trade | 2024-11-20 | No | No | 1 | False | False | Pro & Farm | 925,000$ | 648,454$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Link | |
Sam Gagner | Manitoba Moose (WPG) | C/LW | 35 | 1989-07-28 | CAN | No | 200 Lbs | 5 ft11 | No | No | Trade | 2024-02-19 | No | No | 2 | 2024-05-19 | False | False | Pro & Farm | 775,000$ | 543,299$ | 0$ | 0$ | No | 775,000$ | - | - | - | - | - | - | - | - | 775,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | Link |
Vladislav Kolyachonok | Manitoba Moose (WPG) | D | 23 | 2001-05-26 | BLR | No | 193 Lbs | 6 ft1 | No | No | N/A | No | No | 2 | 2024-05-19 | False | False | Pro & Farm | 775,000$ | 543,299$ | 0$ | 0$ | No | 775,000$ | - | - | - | - | - | - | - | - | 775,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | Link |
Total Players | Average Age | Average Weight | Average Height | Average Contract | Average Year 1 Salary |
---|---|---|---|---|---|
20 | 28.00 | 199 Lbs | 6 ft2 | 2.00 | 779,851$ |
5 vs 5 Forward | |||||||
---|---|---|---|---|---|---|---|
Line # | Left Wing | Center | Right Wing | Time % | PHY | DF | OF |
1 | 38 | 1 | 2 | 2 | |||
2 | 30 | 1 | 2 | 2 | |||
3 | 22 | 1 | 2 | 2 | |||
4 | 10 | 1 | 2 | 2 |
5 vs 5 Defense | |||||||
---|---|---|---|---|---|---|---|
Line # | Defense | Defense | Time % | PHY | DF | OF | |
1 | 38 | 1 | 2 | 2 | |||
2 | 30 | 1 | 2 | 2 | |||
3 | 22 | 1 | 2 | 2 | |||
4 | 10 | 1 | 2 | 2 |
Power Play Forward | |||||||
---|---|---|---|---|---|---|---|
Line # | Left Wing | Center | Right Wing | Time % | PHY | DF | OF |
1 | 60 | 1 | 2 | 2 | |||
2 | 40 | 1 | 2 | 2 |
Power Play Defense | |||||||
---|---|---|---|---|---|---|---|
Line # | Defense | Defense | Time % | PHY | DF | OF | |
1 | 60 | 1 | 2 | 2 | |||
2 | 40 | 1 | 2 | 2 |
Penalty Kill 4 Players Forward | ||||||
---|---|---|---|---|---|---|
Line # | Center | Wing | Time % | PHY | DF | OF |
1 | 60 | 1 | 2 | 2 | ||
2 | 40 | 1 | 2 | 2 |
Penalty Kill 4 Players Defense | ||||||
---|---|---|---|---|---|---|
Line # | Defense | Defense | Time % | PHY | DF | OF |
1 | 60 | 1 | 2 | 2 | ||
2 | 40 | 1 | 2 | 2 |
Penalty Kill 3 Players | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Line # | Wing | Time % | PHY | DF | OF | Defense | Defense | Time % | PHY | DF | OF |
1 | 60 | 1 | 2 | 2 | 60 | 1 | 2 | 2 | |||
2 | 40 | 1 | 2 | 2 | 40 | 1 | 2 | 2 |
4 vs 4 Forward | ||||||
---|---|---|---|---|---|---|
Line # | Center | Wing | Time % | PHY | DF | OF |
1 | 60 | 1 | 2 | 2 | ||
2 | 40 | 1 | 2 | 2 |
4 vs 4 Defense | ||||||
---|---|---|---|---|---|---|
Line # | Defense | Defense | Time % | PHY | DF | OF |
1 | 60 | 1 | 2 | 2 | ||
2 | 40 | 1 | 2 | 2 |
Last Minutes Offensive | ||||
---|---|---|---|---|
Left Wing | Center | Right Wing | Defense | Defense |
Last Minutes Defensive | ||||
---|---|---|---|---|
Left Wing | Center | Right Wing | Defense | Defense |
Extra Forwards | ||
---|---|---|
Normal | PowerPlay | Penalty Kill |
, , | , |
Extra Defensemen | ||
---|---|---|
Normal | PowerPlay | Penalty Kill |
, , | , |
Penalty Shots |
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, , , , |
Goalie |
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#1 : , #2 : |
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 |
Overall | Home | Visitor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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# | VS Team | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | 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 |
1 | Bakersfield Condors | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 7 | 8 | -1 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 7 | 8 | -1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0.500 | 7 | 14 | 21 | 0 | 0 | 23 | 20 | 11 | 4 | 73 | 221 | 245 | 220 | 21 | 86 | 20 | 10 | 64 | 1 | 0 | 0.00% | 5 | 0 | 100.00% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
2 | Bridgeport Islanders | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 4 | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 4 | 3 | 1 | 2 | 1.000 | 4 | 8 | 12 | 0 | 0 | 23 | 20 | 11 | 4 | 38 | 221 | 245 | 220 | 21 | 51 | 12 | 0 | 32 | 1 | 1 | 100.00% | 0 | 0 | 0% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
3 | Charlotte Checkers | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | -3 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | -3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.000 | 0 | 0 | 0 | 0 | 0 | 23 | 20 | 11 | 4 | 42 | 221 | 245 | 220 | 21 | 30 | 8 | 2 | 26 | 1 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
4 | Chicago Wolves | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | 5 | -1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | 5 | -1 | 1 | 0.500 | 4 | 8 | 12 | 0 | 0 | 23 | 20 | 11 | 4 | 14 | 221 | 245 | 220 | 21 | 47 | 9 | 9 | 14 | 2 | 1 | 50.00% | 2 | 2 | 0.00% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
5 | Cleveland Monsters | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | -4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | -4 | 0 | 0.000 | 0 | 0 | 0 | 0 | 0 | 23 | 20 | 11 | 4 | 11 | 221 | 245 | 220 | 21 | 57 | 14 | 4 | 28 | 0 | 0 | 0% | 2 | 0 | 100.00% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
6 | Colorado Eagles | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 6 | -5 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 6 | -5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 23 | 20 | 11 | 4 | 14 | 221 | 245 | 220 | 21 | 42 | 15 | 2 | 26 | 1 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
7 | Hartford Wolf Pack | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 6 | 3 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 6 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 1.000 | 9 | 18 | 27 | 0 | 0 | 23 | 20 | 11 | 4 | 118 | 221 | 245 | 220 | 21 | 79 | 20 | 2 | 83 | 1 | 1 | 100.00% | 1 | 0 | 100.00% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
8 | Hershey Bears | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 8 | 6 | 2 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 8 | 6 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0.500 | 8 | 16 | 24 | 0 | 0 | 23 | 20 | 11 | 4 | 87 | 221 | 245 | 220 | 21 | 86 | 16 | 4 | 37 | 3 | 0 | 0.00% | 2 | 1 | 50.00% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
9 | Iowa Wild | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 23 | 20 | 11 | 4 | 14 | 221 | 245 | 220 | 21 | 38 | 4 | 4 | 9 | 3 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
10 | Laval Rocket | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 1.000 | 3 | 4 | 7 | 0 | 0 | 23 | 20 | 11 | 4 | 31 | 221 | 245 | 220 | 21 | 31 | 9 | 0 | 16 | 1 | 0 | 0.00% | 0 | 0 | 0% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
11 | Milwaukee Admirals | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 4 | -1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 4 | -1 | 0 | 0.000 | 3 | 6 | 9 | 0 | 0 | 23 | 20 | 11 | 4 | 34 | 221 | 245 | 220 | 21 | 58 | 19 | 2 | 27 | 1 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
12 | Rochester Americans | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 1 | 2 | 0 | 0 | 23 | 20 | 11 | 4 | 7 | 221 | 245 | 220 | 21 | 34 | 10 | 17 | 7 | 1 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
13 | Rockford IceHogs | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 3 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 3 | 2 | 2 | 1.000 | 5 | 10 | 15 | 0 | 0 | 23 | 20 | 11 | 4 | 42 | 221 | 245 | 220 | 21 | 47 | 16 | 2 | 30 | 0 | 0 | 0% | 1 | 0 | 100.00% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
14 | San Diego Gulls | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 4 | 1 | 2 | 1.000 | 5 | 10 | 15 | 0 | 0 | 23 | 20 | 11 | 4 | 35 | 221 | 245 | 220 | 21 | 33 | 13 | 8 | 23 | 1 | 0 | 0.00% | 4 | 0 | 100.00% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
15 | Syracuse Crunch | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 6 | -4 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 6 | -4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.000 | 2 | 4 | 6 | 0 | 0 | 23 | 20 | 11 | 4 | 39 | 221 | 245 | 220 | 21 | 49 | 11 | 2 | 20 | 2 | 1 | 50.00% | 1 | 0 | 100.00% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
16 | Toronto Marlies | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | 4 | -1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | 4 | -1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.500 | 3 | 6 | 9 | 0 | 0 | 23 | 20 | 11 | 4 | 62 | 221 | 245 | 220 | 21 | 58 | 13 | 0 | 26 | 1 | 0 | 0.00% | 0 | 0 | 0% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
17 | Utica Comets | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | -6 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | -6 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.000 | 0 | 0 | 0 | 0 | 0 | 23 | 20 | 11 | 4 | 6 | 221 | 245 | 220 | 21 | 40 | 12 | 2 | 8 | 3 | 0 | 0.00% | 1 | 1 | 0.00% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
18 | Wilkes-Barre/Scranton Penguins | 4 | 0 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 19 | -19 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | -3 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 16 | -16 | 0 | 0.000 | 0 | 0 | 0 | 0 | 0 | 23 | 20 | 11 | 4 | 31 | 221 | 245 | 220 | 21 | 151 | 50 | 14 | 38 | 8 | 0 | 0.00% | 7 | 1 | 85.71% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
Total | 24 | 6 | 14 | 0 | 1 | 0 | 1 | 2 | 56 | 97 | -41 | 13 | 4 | 7 | 0 | 0 | 0 | 1 | 1 | 33 | 50 | -17 | 11 | 2 | 7 | 0 | 1 | 0 | 0 | 1 | 23 | 47 | -24 | 18 | 0.375 | 56 | 109 | 165 | 0 | 0 | 23 | 20 | 11 | 4 | 698 | 221 | 245 | 220 | 21 | 1017 | 271 | 84 | 514 | 31 | 4 | 12.90% | 33 | 5 | 84.85% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 | |
_Since Last GM Reset | 24 | 6 | 14 | 0 | 1 | 0 | 1 | 2 | 56 | 97 | -41 | 13 | 4 | 7 | 0 | 0 | 0 | 1 | 1 | 33 | 50 | -17 | 11 | 2 | 7 | 0 | 1 | 0 | 0 | 1 | 23 | 47 | -24 | 18 | 0.375 | 56 | 109 | 165 | 0 | 0 | 23 | 20 | 11 | 4 | 698 | 221 | 245 | 220 | 21 | 1017 | 271 | 84 | 514 | 31 | 4 | 12.90% | 33 | 5 | 84.85% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 | |
_Vs Conference | 16 | 3 | 9 | 0 | 1 | 0 | 1 | 2 | 34 | 64 | -30 | 10 | 3 | 5 | 0 | 0 | 0 | 1 | 1 | 25 | 36 | -11 | 6 | 0 | 4 | 0 | 1 | 0 | 0 | 1 | 9 | 28 | -19 | 12 | 0.375 | 34 | 65 | 99 | 0 | 0 | 23 | 20 | 11 | 4 | 475 | 221 | 245 | 220 | 21 | 656 | 170 | 52 | 307 | 24 | 4 | 16.67% | 17 | 5 | 70.59% | 0 | 222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% | 417 | 293 | 780 | 159 | 259 | 111 |
Total For Players | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Games Played | Points | Streak | Goals | Assists | Points | Shots For | Shots Against | Shots Blocked | Penalty Minutes | Hits | Empty Net Goals | Shutouts |
24 | 18 | SOL1 | 56 | 109 | 165 | 698 | 1017 | 271 | 84 | 514 | 0 | 0 |
All Games | ||||||||
---|---|---|---|---|---|---|---|---|
GP | W | L | OTW | OTL | SOW | SOL | GF | GA |
24 | 6 | 14 | 1 | 0 | 1 | 2 | 56 | 97 |
Home Games | ||||||||
---|---|---|---|---|---|---|---|---|
GP | W | L | OTW | OTL | SOW | SOL | GF | GA |
13 | 4 | 7 | 0 | 0 | 1 | 1 | 33 | 50 |
Visitor Games | ||||||||
---|---|---|---|---|---|---|---|---|
GP | W | L | OTW | OTL | SOW | SOL | GF | GA |
11 | 2 | 7 | 1 | 0 | 0 | 1 | 23 | 47 |
Last 10 Games | |||||
---|---|---|---|---|---|
W | L | OTW | OTL | SOW | SOL |
3 | 4 | 1 | 0 | 1 | 1 |
Power Play Attemps | Power Play Goals | Power Play % | Penalty Kill Attemps | Penalty Kill Goals Against | Penalty Kill % | Penalty Kill Goals For |
---|---|---|---|---|---|---|
31 | 4 | 12.90% | 33 | 5 | 84.85% | 0 |
Shots 1 Period | Shots 2 Period | Shots 3 Period | Shots 4+ Period | Goals 1 Period | Goals 2 Period | Goals 3 Period | Goals 4+ Period |
---|---|---|---|---|---|---|---|
221 | 245 | 220 | 21 | 23 | 20 | 11 | 4 |
Face Offs | ||||||||
---|---|---|---|---|---|---|---|---|
Won Offensive Zone | Total Offensive | Won Offensive % | Won Defensif Zone | Total Defensive | Won Defensive % | Won Neutral Zone | Total Neutral | Won Neutral % |
222 | 510 | 43.53% | 220 | 614 | 35.83% | 143 | 361 | 39.61% |
Puck Time | |||||
---|---|---|---|---|---|
In Offensive Zone | Control In Offensive Zone | In Defensive Zone | Control In Defensive Zone | In Neutral Zone | Control In Neutral Zone |
417 | 293 | 780 | 159 | 259 | 111 |
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 |
Arena Capacity - Ticket Price Attendance - % | ||
---|---|---|
Level 1 | Level 2 | |
Capacity | 2000 | 1000 |
Ticket Price | 35 | 15 |
Attendance | 24,001 | 12,483 |
Attendance PCT | 92.31% | 96.02% |
Income | |||||
---|---|---|---|---|---|
Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Capacity | Team Popularity |
23 | 2806 - 93.55% | 93,245$ | 1,212,189$ | 3000 | 100 |
Expenses | |||
---|---|---|---|
Year To Date Expenses | Players Total Salaries | Players Total Salaries Cap | Coaches Salaries |
449,467$ | 1,559,702$ | 1,355,606$ | 0$ |
Salary Cap Per Days | Salary Cap To Date | Players In Salary Cap | Players Out of Salary Cap |
---|---|---|---|
8,040$ | 449,467$ | 0 | 0 |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
2,144,642$ | 136 | 8,040$ | 1,093,440$ |
# | Player Name | GP | G | A | P | +/- | PIM | HIT | HTT | SHT | SHT% | SB | MP | AMG | PPG | PPA | PPP | PPS | PKG | PKA | PKP | PKS | GW | GT | FO% | HT | P/20 | PSG | PSS |
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# | Goalie Name | GP | W | L | OTL | PCT | GAA | MP | PIM | SO | GA | SA | SAR | A | EG | PS % | PSA |
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Overall | Home | Visitor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Year | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | P | 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 |
# | Player Name | GP | G | A | P | +/- | PIM | HIT | HTT | SHT | SHT% | SB | MP | AMG | PPG | PPA | PPP | PPS | PKG | PKA | PKP | PKS | GW | GT | FO% | HT | P/20 | PSG | PSS |
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# | Goalie Name | GP | W | L | OTL | PCT | GAA | MP | PIM | SO | GA | SA | SAR | A | EG | PS % | PSA |
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