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Full Scoreboard »» |
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Full Scoreboard »» |
Toronto Marlies 1-0-0, 2pts · 2nd in Eastern |
Player | # | POS | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 22 | C/RW | 99.00 | 66 | 39 | 81 | 60 | 70 | 73 | 73 | 68 | 40 | 65 | 61 | 71 | 63 | 77 | 75 | 0 | 85 | 75 | 31 | 800,000$/1yrs | |||
![]() | 48 | C/LW | 100.00 | 67 | 32 | 88 | 65 | 72 | 82 | 68 | 66 | 60 | 70 | 62 | 62 | 64 | 67 | 65 | 0 | 49 | 75 | 25 | 1,250,000$/1yrs | |||
![]() | 0 | C | 100.00 | 66 | 32 | 95 | 69 | 73 | 78 | 75 | 64 | 60 | 66 | 68 | 56 | 66 | 63 | 63 | 0 | 37 | 75 | 23 | 925,000$/2yrs | |||
![]() | 72 | C/LW/RW | 100.00 | 62 | 32 | 96 | 57 | 74 | 71 | 68 | 62 | 62 | 69 | 61 | 58 | 62 | 78 | 78 | 0 | 83 | 73 | 31 | 900,000$/2yrs | |||
![]() | 73 | LW | 100.00 | 84 | 40 | 92 | 58 | 75 | 74 | 70 | 61 | 61 | 66 | 60 | 60 | 60 | 74 | 73 | 0 | 66 | 73 | 29 | 850,000$/2yrs | |||
![]() | 0 | C | 100.00 | 67 | 39 | 79 | 61 | 76 | 70 | 76 | 63 | 46 | 60 | 65 | 66 | 63 | 68 | 66 | 0 | 84 | 73 | 25 | 900,000$/2yrs | |||
![]() | 55 | C | 100.00 | 75 | 32 | 85 | 57 | 70 | 74 | 76 | 58 | 61 | 57 | 62 | 63 | 60 | 75 | 74 | 0 | 84 | 71 | 30 | 875,000$/2yrs | |||
![]() | 0 | C/LW | 100.00 | 74 | 46 | 64 | 55 | 71 | 74 | 90 | 60 | 59 | 60 | 63 | 55 | 61 | 73 | 69 | 0 | 81 | 70 | 28 | 800,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 68 | 32 | 94 | 55 | 72 | 76 | 73 | 53 | 59 | 58 | 55 | 71 | 54 | 79 | 79 | 0 | 81 | 70 | 32 | 1,200,000$/1yrs | |||
![]() | 0 | RW | 100.00 | 78 | 41 | 61 | 57 | 78 | 67 | 70 | 63 | 66 | 58 | 58 | 66 | 58 | 66 | 62 | 0 | 73 | 70 | 24 | 900,000$/2yrs | |||
![]() | 0 | C | 100.00 | 66 | 38 | 80 | 60 | 61 | 67 | 89 | 61 | 65 | 61 | 58 | 64 | 59 | 63 | 61 | 0 | 49 | 70 | 24 | 900,000$/2yrs | |||
![]() | 0 | RW | 100.00 | 61 | 37 | 89 | 58 | 64 | 64 | 68 | 59 | 42 | 57 | 57 | 62 | 57 | 59 | 58 | 0 | 56 | 68 | 21 | 891,667$/3yrs | |||
![]() | 0 | D | 100.00 | 76 | 32 | 84 | 61 | 73 | 88 | 82 | 58 | 30 | 66 | 57 | 64 | 58 | 64 | 62 | 0 | 89 | 74 | 23 | 897,500$/1yrs | |||
![]() | 0 | D | 100.00 | 63 | 32 | 75 | 63 | 71 | 82 | 70 | 57 | 30 | 67 | 50 | 59 | 53 | 63 | 61 | 0 | 49 | 72 | 24 | 900,000$/1yrs | |||
![]() | 0 | D | 100.00 | 82 | 43 | 63 | 55 | 81 | 80 | 85 | 54 | 30 | 59 | 56 | 67 | 55 | 67 | 64 | 0 | 79 | 71 | 25 | 900,000$/1yrs | |||
![]() | 2 | D | 100.00 | 89 | 43 | 50 | 50 | 78 | 66 | 66 | 49 | 30 | 56 | 52 | 71 | 54 | 73 | 68 | 0 | 81 | 69 | 28 | 775,000$/2yrs | |||
![]() | 0 | D | 100.00 | 70 | 32 | 83 | 55 | 67 | 83 | 74 | 51 | 30 | 58 | 57 | 62 | 54 | 65 | 63 | 0 | 27 | 69 | 24 | 925,000$/2yrs | |||
![]() | 23 | D | 100.00 | 65 | 36 | 94 | 55 | 75 | 77 | 77 | 50 | 30 | 59 | 52 | 58 | 51 | 67 | 66 | 0 | 83 | 68 | 25 | 850,000$/2yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | C | 100.00 | 67 | 39 | 80 | 62 | 71 | 70 | 86 | 63 | 66 | 59 | 66 | 65 | 63 | 66 | 64 | 0 | 23 | 72 | 26 | 1,000,000$/1yrs | |||
![]() | 0 | C/RW | 100.00 | 58 | 36 | 93 | 58 | 60 | 66 | 75 | 62 | 71 | 60 | 55 | 63 | 57 | 65 | 64 | 0 | 24 | 69 | 26 | ||||
![]() | 0 | RW | 100.00 | 69 | 41 | 76 | 62 | 88 | 63 | 60 | 60 | 65 | 54 | 55 | 64 | 62 | 65 | 62 | 0 | 24 | 69 | 27 | ||||
![]() | 0 | C | 100.00 | 57 | 34 | 90 | 59 | 87 | 72 | 72 | 57 | 75 | 60 | 58 | 55 | 58 | 68 | 67 | 0 | 24 | 69 | 25 | ||||
![]() | 0 | RW | 100.00 | 66 | 39 | 82 | 57 | 75 | 66 | 69 | 62 | 48 | 59 | 55 | 65 | 57 | 65 | 63 | 0 | 73 | 69 | 23 | 896,250$/1yrs | |||
![]() | 0 | C | 100.00 | 61 | 39 | 86 | 62 | 75 | 67 | 83 | 58 | 65 | 61 | 59 | 63 | 60 | 56 | 54 | 0 | 77 | 69 | 20 | 950,000$/3yrs | |||
![]() | 0 | RW | 100.00 | 64 | 39 | 83 | 55 | 76 | 65 | 77 | 62 | 45 | 53 | 58 | 65 | 56 | 64 | 63 | 0 | 26 | 68 | 25 | 875,000$/2yrs | |||
![]() | 0 | RW | 100.00 | 69 | 40 | 77 | 54 | 79 | 64 | 68 | 62 | 41 | 53 | 55 | 66 | 54 | 64 | 62 | 0 | 24 | 68 | 23 | 900,000$/3yrs | |||
![]() | 0 | C | 100.00 | 60 | 38 | 90 | 55 | 69 | 65 | 69 | 63 | 62 | 54 | 57 | 66 | 55 | 66 | 65 | 0 | 24 | 68 | 25 | 900,000$/1yrs | |||
![]() | 0 | LW | 100.00 | 60 | 38 | 91 | 58 | 78 | 65 | 69 | 60 | 49 | 59 | 55 | 63 | 57 | 61 | 60 | 0 | 23 | 68 | 21 | 990,833$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 66 | 32 | 83 | 55 | 73 | 73 | 68 | 52 | 80 | 50 | 56 | 60 | 54 | 74 | 72 | 0 | 23 | 66 | 30 | 780,000$/2yrs | |||
![]() | 91 | RW | 100.00 | 58 | 38 | 94 | 60 | 77 | 61 | 60 | 57 | 65 | 51 | 52 | 64 | 59 | 63 | 62 | 0 | 23 | 66 | 25 | 800,000$/2yrs | |||
![]() | 0 | C | 100.00 | 79 | 45 | 75 | 55 | 83 | 71 | 75 | 51 | 75 | 55 | 53 | 61 | 52 | 61 | 58 | 0 | 28 | 66 | 21 | 825,000$/2yrs | |||
![]() | 0 | RW | 100.00 | 62 | 38 | 87 | 53 | 73 | 62 | 66 | 61 | 40 | 53 | 51 | 64 | 52 | 61 | 60 | 0 | 24 | 66 | 21 | 850,000$/2yrs | |||
![]() | 0 | LW | 100.00 | 62 | 39 | 87 | 50 | 79 | 64 | 68 | 49 | 30 | 55 | 54 | 66 | 55 | 64 | 63 | 0 | 24 | 65 | 23 | 867,500$/2yrs | |||
![]() | 0 | C | 100.00 | 52 | 33 | 95 | 55 | 78 | 74 | 68 | 51 | 73 | 59 | 50 | 55 | 51 | 60 | 60 | 0 | 48 | 65 | 21 | 925,000$/3yrs | |||
![]() | 0 | D | 100.00 | 70 | 48 | 51 | 55 | 91 | 81 | 73 | 55 | 30 | 59 | 55 | 63 | 55 | 67 | 62 | 0 | 27 | 70 | 26 | 950,000$/1yrs | |||
![]() | 0 | D | 100.00 | 68 | 39 | 77 | 52 | 66 | 65 | 68 | 51 | 30 | 57 | 54 | 65 | 56 | 63 | 60 | 0 | 24 | 68 | 23 | 916,667$/1yrs | |||
![]() | 0 | D | 100.00 | 65 | 39 | 83 | 48 | 79 | 63 | 65 | 48 | 30 | 54 | 51 | 67 | 52 | 66 | 64 | 0 | 76 | 66 | 24 | 867,500$/2yrs | |||
![]() | 0 | D | 100.00 | 70 | 40 | 74 | 47 | 82 | 61 | 88 | 46 | 30 | 52 | 48 | 66 | 50 | 64 | 62 | 0 | 24 | 65 | 26 | ||||
![]() | 0 | D | 100.00 | 66 | 40 | 80 | 43 | 86 | 59 | 80 | 43 | 30 | 48 | 48 | 64 | 48 | 61 | 59 | 0 | 24 | 62 | 23 | 875,000$/2yrs |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 99.00 | 72 | 60 | 70 | 94 | 56 | 78 | 73 | 72 | 78 | 77 | 74 | 65 | 64 | 0 | 77 | 76 | 23 | 950,000$/2yrs |
![]() | 0 | 100.00 | 60 | 61 | 65 | 75 | 60 | 60 | 60 | 60 | 60 | 72 | 60 | 64 | 67 | 0 | 84 | 68 | 24 | 900,000$/2yrs |
Scratches | ||||||||||||||||||||
![]() | 0 | 100.00 | 65 | 60 | 65 | 78 | 58 | 62 | 65 | 66 | 62 | 66 | 65 | 66 | 69 | 0 | 24 | 69 | 25 | 850,000$/1yrs |
![]() | 0 | 100.00 | 60 | 62 | 66 | 76 | 56 | 60 | 60 | 60 | 60 | 65 | 60 | 75 | 78 | 0 | 29 | 68 | 30 | 850,000$/2yrs |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Jacques Martin | 57 | 61 | 60 | 58 | 99 | 97 | 37 | CAN | 72 | 4 | 500,000$ |
General Manager |
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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 | AMG | PPG | PPA | PPP | PPM | PKG | PKA | PKP | PKM | GW | GT | FO% | FOT | GA | TA | EG | HT | P/20 | PSG | PSS |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Ryker Evans | D | 1 | 0 | 3 | 3 | 0 | 0 | 0 | 3 | 0 | 2 | 2 | 0.00% | 2 | 24.05 | 0 | 3 | 3 | 2 | 0 | 0 | 0 | 2 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 2.49 | 0 | 0 | ||
2 | Jacob Peterson | C/LW | 1 | 0 | 2 | 2 | 0 | 0 | 0 | 0 | 3 | 2 | 3 | 0.00% | 0 | 17.23 | 0 | 2 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 1 | 0 | 0 | 0 | 0 | 2.32 | 0 | 0 | ||
3 | Andrew Poturalski | C/RW | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 2 | 1 | 1 | 50.00% | 0 | 22.55 | 1 | 0 | 1 | 2 | 0 | 0 | 0 | 4 | 0 | 0 | 16.67% | 12 | 0 | 0 | 0 | 0 | 0.89 | 0 | 0 | ||
4 | Dryden Hunt | LW | 1 | 1 | 0 | 1 | -1 | 0 | 0 | 1 | 1 | 0 | 0 | 100.00% | 0 | 17.40 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 100.00% | 1 | 0 | 0 | 0 | 0 | 1.15 | 0 | 0 | ||
5 | Alex Steeves | C | 1 | 1 | 0 | 1 | 0 | 2 | 0 | 3 | 5 | 2 | 2 | 20.00% | 0 | 18.18 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 2 | 0 | 0 | 38.46% | 26 | 0 | 0 | 0 | 0 | 1.10 | 0 | 0 | ||
6 | Ruslan Iskhakov | C | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0.00% | 0 | 5.65 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 18.18% | 11 | 0 | 0 | 0 | 0 | 3.54 | 0 | 0 | ||
7 | Jagger Firkus | RW | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 2 | 0 | 1 | 50.00% | 0 | 5.65 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 3.54 | 0 | 0 | ||
8 | Travis Boyd | C/LW/RW | 1 | 0 | 0 | 0 | -1 | 0 | 0 | 0 | 1 | 1 | 0 | 0.00% | 0 | 18.45 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 66.67% | 6 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | ||
9 | Brayden Pachal | D | 1 | 0 | 0 | 0 | 0 | 2 | 0 | 2 | 0 | 0 | 0 | 0.00% | 0 | 16.93 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | ||
10 | Michael Eyssimont | C/LW | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 1 | 0.00% | 0 | 14.70 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 100.00% | 1 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | ||
11 | Matt Nieto | LW/RW | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0.00% | 1 | 11.02 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 4 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | ||
12 | Vinni Lettieri | C | 1 | 0 | 0 | 0 | -1 | 0 | 0 | 0 | 3 | 2 | 1 | 0.00% | 0 | 18.30 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 43.75% | 16 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | ||
13 | Jake Christiansen | D | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 2 | 16.40 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | ||
14 | Connor Mackey | D | 1 | 0 | 0 | 0 | 0 | 2 | 0 | 5 | 2 | 0 | 0 | 0.00% | 2 | 18.82 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | ||
15 | Jan Jenik | RW | 1 | 0 | 0 | 0 | 0 | 4 | 0 | 0 | 1 | 2 | 0 | 0.00% | 0 | 12.38 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 100.00% | 1 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | ||
16 | Victor Soderstrom | D | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0.00% | 2 | 20.95 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 3 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | ||
17 | Albert Johansson | D | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0.00% | 0 | 18.13 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | ||
18 | Josh Doan | C | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 1 | 2 | 0.00% | 0 | 13.95 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 50.00% | 16 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | ||
Team Total or Average | 18 | 4 | 6 | 10 | 0 | 10 | 0 | 20 | 24 | 15 | 16 | 16.67% | 9 | 16.15 | 3 | 5 | 8 | 23 | 0 | 0 | 0 | 28 | 1 | 0 | 39.56% | 91 | 0 | 0 | 0 | 0 | 0.69 | 0 | 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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Cooper Black | 1 | 1 | 0 | 0 | 0.926 | 2.00 | 60 | 0 | 0 | 2 | 27 | 0 | 0 | 0 | 0.000 | 0 | 1 | 0 | 0 | 0 | 0 | |
Team Total or Average | 1 | 1 | 0 | 0 | 0.926 | 2.00 | 60 | 0 | 0 | 2 | 27 | 0 | 0 | 0 | 0.000 | 0 | 1 | 0 | 0 | 0 | 0 |
Player Name | POS | Age | Cap Hit | 2020-21 | 2021-22 | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 |
---|---|---|---|---|---|---|---|---|---|---|---|
Adam Ruzicka | C | 25 | 0$ | ||||||||
Aku Raty | RW | 23 | 896,250$ | 896,250$ | RFA | ||||||
Albert Johansson | D | 24 | 925,000$ | 925,000$ | 925,000$ | ||||||
Aleksi Heponiemi | C/RW | 26 | 0$ | ||||||||
Alex Steeves | C | 25 | 900,000$ | 900,000$ | 900,000$ | ||||||
Andrew Poturalski | C/RW | 31 | 800,000$ | 800,000$ | UFA | ||||||
Brandon Coe | RW | 23 | 900,000$ | 900,000$ | 900,000$ | 900,000$ | |||||
Brayden Pachal | D | 25 | 900,000$ | 900,000$ | |||||||
Cal Foote | D | 26 | 950,000$ | 950,000$ | |||||||
Cal Petersen | G | 30 | 850,000$ | 850,000$ | 850,000$ | UFA | |||||
Calum Ritchie | C | 20 | 950,000$ | 950,000$ | 950,000$ | 950,000$ | RFA | ||||
Connor Mackey | D | 28 | 775,000$ | 775,000$ | 775,000$ | UFA | |||||
Cooper Black | G | 23 | 950,000$ | 950,000$ | 950,000$ | ||||||
Drew Bavaro | D | 24 | 867,500$ | 867,500$ | 867,500$ | ||||||
Dryden Hunt | LW | 29 | 850,000$ | 850,000$ | 850,000$ | UFA | |||||
Eetu Tuulola | RW | 27 | 0$ | UFA | |||||||
Gabriel Fortier | C | 25 | 900,000$ | 900,000$ | |||||||
Ivan Lodnia | RW | 25 | 800,000$ | 800,000$ | 800,000$ | ||||||
Jacob Peterson | C/LW | 25 | 1,250,000$ | 1,250,000$ | |||||||
Jagger Firkus | RW | 21 | 891,667$ | 891,667$ | 891,667$ | 891,667$ | RFA | ||||
Jake Christiansen | D | 25 | 850,000$ | 850,000$ | 850,000$ | ||||||
Jan Jenik | RW | 24 | 900,000$ | 900,000$ | 900,000$ | ||||||
Josh Doan | C | 23 | 925,000$ | 925,000$ | 925,000$ | ||||||
Laurent Dauphin | LW/RW | 30 | 780,000$ | 780,000$ | 780,000$ | UFA | |||||
Lauri Pajuniemi | RW | 25 | 875,000$ | 875,000$ | 875,000$ | ||||||
Lias Andersson | C | 26 | 1,000,000$ | 1,000,000$ | |||||||
Matt Nieto | LW/RW | 32 | 1,200,000$ | 1,200,000$ | UFA | ||||||
Matthew Seminoff | RW | 21 | 850,000$ | 850,000$ | 850,000$ | RFA | |||||
Maxim Groshev | LW | 23 | 867,500$ | 867,500$ | 867,500$ | ||||||
Michael Benning | D | 23 | 916,667$ | 916,667$ | RFA | ||||||
Michael Eyssimont | C/LW | 28 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Michael Vukojevic | D | 23 | 875,000$ | 875,000$ | 875,000$ | ||||||
Oliver Kapanen | C | 21 | 925,000$ | 925,000$ | 925,000$ | 925,000$ | RFA | ||||
Olle Eriksson Ek | G | 25 | 850,000$ | 850,000$ | |||||||
Philip Kemp | D | 26 | 0$ | ||||||||
Ruslan Iskhakov | C | 24 | 900,000$ | 900,000$ | 900,000$ | ||||||
Ryker Evans | D | 23 | 897,500$ | 897,500$ | RFA | ||||||
Travis Boyd | C/LW/RW | 31 | 900,000$ | 900,000$ | 900,000$ | UFA | |||||
Trent Miner | G | 24 | 900,000$ | 900,000$ | 900,000$ | ||||||
Victor Soderstrom | D | 24 | 900,000$ | 900,000$ | |||||||
Vinni Lettieri | C | 30 | 875,000$ | 875,000$ | 875,000$ | UFA | |||||
William Stromgren | LW | 21 | 990,833$ | 990,833$ | 990,833$ | RFA | |||||
Zack Ostapchuk | C | 21 | 825,000$ | 825,000$ | 825,000$ | RFA |
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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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1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 2 | 2 | 2 | 1.000 | 4 | 6 | 10 | 0 | 0 | 2 | 2 | 0 | 0 | 24 | 4 | 9 | 11 | 0 | 27 | 9 | 10 | 20 | 5 | 3 | 60.00% | 5 | 1 | 80.00% | 0 | 14 | 35 | 40.00% | 12 | 39 | 30.77% | 10 | 17 | 58.82% | 22 | 15 | 25 | 7 | 12 | 6 | 50.0% | 16.7% | 92.6% | 109.3 | LUCKY | |
_Vs Conference | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 2 | 2 | 2 | 1.000 | 4 | 6 | 10 | 0 | 0 | 2 | 2 | 0 | 0 | 24 | 4 | 9 | 11 | 0 | 27 | 9 | 10 | 20 | 5 | 3 | 60.00% | 5 | 1 | 80.00% | 0 | 14 | 35 | 40.00% | 12 | 39 | 30.77% | 10 | 17 | 58.82% | 22 | 15 | 25 | 7 | 12 | 6 | 50.0% | 16.7% | 92.6% | 109.3 | LUCKY | |
_Since Last GM Reset | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 2 | 2 | 2 | 1.000 | 4 | 6 | 10 | 0 | 0 | 2 | 2 | 0 | 0 | 24 | 4 | 9 | 11 | 0 | 27 | 9 | 10 | 20 | 5 | 3 | 60.00% | 5 | 1 | 80.00% | 0 | 14 | 35 | 40.00% | 12 | 39 | 30.77% | 10 | 17 | 58.82% | 22 | 15 | 25 | 7 | 12 | 6 | 50.0% | 16.7% | 92.6% | 109.3 | LUCKY | |
Total | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 2 | 2 | 2 | 1.000 | 4 | 6 | 10 | 0 | 0 | 2 | 2 | 0 | 0 | 24 | 4 | 9 | 11 | 0 | 27 | 9 | 10 | 20 | 5 | 3 | 60.00% | 5 | 1 | 80.00% | 0 | 14 | 35 | 40.00% | 12 | 39 | 30.77% | 10 | 17 | 58.82% | 22 | 15 | 25 | 7 | 12 | 6 | 50.0% | 16.7% | 92.6% | 109.3 | LUCKY |
Puck Time | |
---|---|
Offensive Zone | 22 |
Neutral Zone | 12 |
Defensive Zone | 25 |
Puck Time | |
---|---|
Offensive Zone Start | 35 |
Neutral Zone Start | 17 |
Defensive Zone Start | 39 |
Puck Time | |
---|---|
With Puck | 29 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 36 |
Faceoffs Lost | 55 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 4.0 | 9.57 |
2nd Period | 13.0 | 20.31 |
3rd Period | 24.0 | 30.68 |
Overtime | 24.0 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 2.0 | 0.64 |
2nd Period | 4.0 | 1.65 |
3rd Period | 4.0 | 2.67 |
Overtime | 4.0 | 2.83 |
Even Strenght Goal | 1 |
---|---|
PP Goal | 3 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 1 | 0 |
Lost | 0 | 0 |
Overtime Lost | 0 | 0 |
PP Attempt | 5 |
---|---|
PP Goal | 3 |
PK Attempt | 5 |
PK Goal Against | 1 |
Home | |
---|---|
Shots For | 24.0 |
Shots Against | 27.0 |
Goals For | 4.0 |
Goals Against | 2.0 |
Hits | 20.0 |
Shots Blocked | 9.0 |
Pim | 10.0 |
Date | Matchup | Result | Detail | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2025-05-01 | @ | Americans2,Marlies4 | RECAP | |||||||||||
2025-05-03 | @ | |||||||||||||
2025-05-05 | @ | |||||||||||||
2025-05-07 | @ | |||||||||||||
2025-05-09 | @ | |||||||||||||
2025-05-11 | @ | |||||||||||||
Trade Deadline --- Trades can’t be done after this day is simulated! | ||||||||||||||
2025-05-13 | @ |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
3,330,792$ | 0$ | 0$ | 75,000,000$ |
Arena | About us | |
---|---|---|
![]() | Name | |
City | Toronto | |
Capacity | 3000 | |
Season Ticket Holders | 0% |
Arena Capacity - Ticket Price Attendance - % | |||||
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Arena Capacity | 2000 | 1000 | |||
Ticket Price | 35$ | 0$ | $ | $ | $ |
Attendance | 0 | 0 | |||
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 |
35 | 0 - 0.00% | 0$ | 0$ | 3000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
3,330,792$ | 3,330,792$ | 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$ | 12 | 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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