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Full Scoreboard »» |
![]() | Toronto Marlies 3-1-0, 6pts · 5th in Conference 1 |
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 | 59 | 43 | 70 | 61 | 74 | 73 | 79 | 67 | 53 | 64 | 61 | 60 | 63 | 91 | 78 | 1 | 50 | 65 | 38 | 1,000,000$/1yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 63 | 43 | 72 | 66 | 67 | 72 | 72 | 65 | 65 | 64 | 59 | 65 | 63 | 83 | 63 | 1 | 50 | 64 | 33 | 1,000,000$/1yrs | |||
![]() | 0 | C | 100.00 | 55 | 43 | 70 | 68 | 63 | 74 | 70 | 65 | 61 | 63 | 61 | 58 | 65 | 62 | 53 | 1 | 50 | 62 | 30 | 1,000,000$/3yrs | |||
![]() | 0 | C | 100.00 | 57 | 41 | 73 | 69 | 61 | 65 | 64 | 66 | 46 | 66 | 61 | 60 | 65 | 52 | 50 | 1 | 50 | 62 | 24 | 975,000$/1yrs | |||
![]() | 0 | LW | 100.00 | 52 | 46 | 63 | 68 | 52 | 70 | 69 | 64 | 47 | 65 | 58 | 55 | 63 | 59 | 54 | 1 | 50 | 60 | 29 | 975,000$/1yrs | |||
![]() | 0 | C/RW | 99.00 | 54 | 48 | 62 | 62 | 62 | 70 | 69 | 63 | 61 | 60 | 58 | 52 | 61 | 65 | 59 | 1 | 50 | 60 | 31 | 1,275,000$/3yrs | |||
![]() | 0 | C | 100.00 | 64 | 45 | 67 | 60 | 71 | 69 | 67 | 60 | 60 | 58 | 54 | 59 | 58 | 80 | 55 | 1 | 50 | 60 | 30 | 1,250,000$/2yrs | |||
![]() | 0 | C | 100.00 | 62 | 42 | 62 | 65 | 62 | 61 | 60 | 62 | 55 | 62 | 58 | 62 | 62 | 50 | 50 | 1 | 50 | 60 | 21 | 853,333$/2yrs | |||
![]() | 0 | RW | 100.00 | 57 | 43 | 62 | 67 | 58 | 62 | 61 | 62 | 43 | 62 | 60 | 59 | 63 | 50 | 50 | 1 | 50 | 60 | 22 | 975,000$/2yrs | |||
![]() | 0 | RW | 100.00 | 64 | 42 | 65 | 62 | 67 | 58 | 57 | 62 | 42 | 59 | 62 | 59 | 62 | 50 | 50 | 1 | 50 | 59 | 20 | 975,000$/3yrs | |||
![]() | 0 | LW | 100.00 | 62 | 41 | 67 | 62 | 62 | 58 | 56 | 60 | 42 | 58 | 55 | 59 | 59 | 50 | 50 | 1 | 50 | 57 | 20 | 975,000$/3yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 54 | 41 | 65 | 60 | 56 | 62 | 60 | 57 | 42 | 56 | 52 | 57 | 56 | 60 | 53 | 1 | 50 | 56 | 30 | 975,000$/1yrs | |||
![]() | 0 | D | 100.00 | 63 | 41 | 73 | 65 | 66 | 63 | 62 | 62 | 40 | 60 | 54 | 63 | 60 | 50 | 50 | 1 | 50 | 61 | 22 | 975,000$/2yrs | |||
![]() | 0 | D | 99.00 | 64 | 44 | 67 | 60 | 71 | 71 | 70 | 60 | 40 | 53 | 53 | 64 | 58 | 63 | 57 | 1 | 50 | 61 | 30 | 1,000,000$/2yrs | |||
![]() | 0 | D | 99.00 | 62 | 49 | 61 | 65 | 68 | 67 | 65 | 63 | 40 | 58 | 58 | 63 | 62 | 54 | 50 | 1 | 50 | 61 | 26 | 1,000,000$/4yrs | |||
![]() | 0 | D | 100.00 | 60 | 41 | 72 | 66 | 63 | 65 | 62 | 57 | 40 | 51 | 51 | 64 | 58 | 54 | 50 | 1 | 50 | 59 | 26 | 975,000$/1yrs | |||
![]() | 0 | D | 100.00 | 64 | 41 | 62 | 62 | 68 | 61 | 58 | 53 | 40 | 51 | 51 | 63 | 55 | 52 | 50 | 1 | 50 | 58 | 24 | 975,000$/1yrs | |||
![]() | 0 | D | 100.00 | 61 | 42 | 57 | 57 | 63 | 57 | 55 | 55 | 40 | 54 | 52 | 61 | 55 | 51 | 50 | 1 | 50 | 57 | 24 | 1,400,000$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | RW | 100.00 | 52 | 44 | 57 | 59 | 58 | 65 | 65 | 60 | 43 | 60 | 59 | 53 | 60 | 60 | 53 | 1 | 50 | 58 | 31 | 975,000$/1yrs | |||
![]() | 0 | C | 100.00 | 55 | 42 | 65 | 61 | 62 | 68 | 67 | 58 | 55 | 54 | 54 | 56 | 58 | 73 | 69 | 1 | 50 | 58 | 35 | 1,000,000$/1yrs | |||
![]() | 0 | C | 100.00 | 62 | 40 | 71 | 62 | 64 | 64 | 62 | 57 | 54 | 54 | 52 | 58 | 57 | 52 | 50 | 1 | 50 | 57 | 25 | 1,000,000$/1yrs | |||
![]() | 0 | LW | 100.00 | 61 | 43 | 69 | 61 | 64 | 66 | 63 | 59 | 42 | 53 | 53 | 56 | 58 | 55 | 50 | 1 | 50 | 57 | 27 | 975,000$/1yrs | |||
![]() | 0 | C | 100.00 | 59 | 41 | 68 | 60 | 63 | 62 | 61 | 60 | 41 | 55 | 57 | 54 | 58 | 50 | 50 | 1 | 50 | 57 | 21 | 803,333$/2yrs | |||
![]() | 0 | C | 100.00 | 64 | 42 | 71 | 62 | 67 | 63 | 60 | 57 | 46 | 52 | 52 | 58 | 57 | 52 | 50 | 1 | 50 | 57 | 24 | 975,000$/1yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 59 | 42 | 63 | 58 | 62 | 62 | 61 | 56 | 40 | 54 | 54 | 56 | 56 | 52 | 50 | 1 | 50 | 56 | 26 | 1,000,000$/1yrs | |||
![]() | 0 | RW | 100.00 | 60 | 40 | 67 | 59 | 62 | 59 | 57 | 55 | 40 | 54 | 53 | 54 | 56 | 50 | 50 | 1 | 50 | 55 | 21 | 870,000$/2yrs | |||
![]() | 0 | LW | 100.00 | 55 | 40 | 64 | 60 | 56 | 57 | 55 | 53 | 40 | 51 | 51 | 53 | 54 | 51 | 50 | 1 | 50 | 53 | 24 | 975,000$/2yrs | |||
![]() | 0 | D | 100.00 | 65 | 41 | 68 | 61 | 70 | 64 | 61 | 56 | 40 | 52 | 51 | 66 | 56 | 53 | 50 | 1 | 50 | 60 | 26 | 1,000,000$/1yrs | |||
![]() | 0 | D | 100.00 | 63 | 40 | 70 | 61 | 67 | 62 | 59 | 55 | 40 | 52 | 52 | 62 | 56 | 52 | 50 | 1 | 50 | 58 | 25 | 1,000,000$/1yrs | |||
![]() | 0 | D | 100.00 | 59 | 40 | 67 | 62 | 62 | 62 | 60 | 57 | 40 | 54 | 53 | 60 | 57 | 52 | 50 | 1 | 50 | 58 | 25 | 1,000,000$/1yrs | |||
![]() | 0 | D | 100.00 | 55 | 40 | 64 | 59 | 58 | 60 | 58 | 53 | 40 | 51 | 50 | 60 | 54 | 56 | 50 | 1 | 50 | 56 | 29 | 1,000,000$/1yrs | |||
![]() | 0 | D | 100.00 | 51 | 41 | 67 | 57 | 56 | 65 | 65 | 56 | 40 | 51 | 52 | 52 | 55 | 60 | 53 | 1 | 50 | 55 | 32 | 1,000,000$/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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 100.00 | 74 | 69 | 70 | 79 | 73 | 71 | 70 | 68 | 72 | 72 | 67 | 56 | 52 | 1 | 50 | 65 | 24 | 1,100,000$/2yrs |
![]() | 0 | 100.00 | 73 | 67 | 68 | 76 | 71 | 71 | 70 | 70 | 73 | 71 | 68 | 52 | 50 | 1 | 50 | 65 | 23 | 1,400,000$/4yrs |
Scratches | ||||||||||||||||||||
![]() | 0 | 100.00 | 71 | 66 | 67 | 66 | 68 | 68 | 70 | 66 | 68 | 69 | 63 | 56 | 51 | 1 | 50 | 62 | 28 | 975,000$/2yrs |
![]() | 0 | 100.00 | 69 | 63 | 65 | 69 | 68 | 67 | 69 | 66 | 67 | 67 | 55 | 52 | 50 | 1 | 50 | 61 | 24 | 975,000$/2yrs |
![]() | 0 | 100.00 | 68 | 61 | 63 | 64 | 66 | 68 | 70 | 68 | 69 | 66 | 56 | 50 | 50 | 1 | 50 | 61 | 21 | 975,000$/3yrs |
![]() | 0 | 100.00 | 67 | 61 | 62 | 65 | 65 | 66 | 68 | 66 | 66 | 64 | 56 | 50 | 50 | 1 | 50 | 60 | 21 | 975,000$/2yrs |
![]() | 0 | 100.00 | 66 | 60 | 59 | 67 | 64 | 62 | 64 | 60 | 63 | 63 | 53 | 54 | 50 | 1 | 50 | 58 | 26 | 1,000,000$/2yrs |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Don Granato | 71 | 69 | 71 | 70 | 83 | 67 | 1 | USA | 57 | 1 | 1,500,000$ |
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 | MP | PPG | PPA | PPP | PKG | PKA | PKP | PKM | GW | GT | FO% | EG | HT | P/GP | PSG | PSS | GSAVG | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Patrick Brown | ![]() | C/LW/RW | 4 | 1 | 5 | 6 | 4 | 19 | 5 | 7 | 14 | 1 | 3 | 7.14% | 0 | 19.05 | 0 | 2 | 2 | 0 | 0 | 0 | 10 | 0 | 0 | 60.49% | 0 | 0 | 1.50 | 0 | 1 | 0.85 | |||
2 | Brett Seney | ![]() | LW | 4 | 2 | 3 | 5 | 4 | 5 | 5 | 1 | 17 | 6 | 8 | 11.76% | 0 | 16.73 | 1 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 1 | 33.33% | 0 | 0 | 1.25 | 0 | 0 | 1.36 | |||
3 | Blake Wheeler | ![]() | RW | 4 | 2 | 1 | 3 | 4 | 4 | 0 | 8 | 6 | 2 | 3 | 33.33% | 1 | 17.40 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 75.00% | 0 | 0 | 0.75 | 1 | 1 | 0.90 | |||
4 | Georgii Merkulov | ![]() | C | 4 | 3 | 0 | 3 | -1 | 0 | 0 | 7 | 15 | 3 | 14 | 20.00% | 0 | 13.53 | 1 | 0 | 1 | 0 | 0 | 0 | 5 | 1 | 0 | 32.14% | 0 | 0 | 0.75 | 0 | 1 | 0.84 | |||
5 | C.J. Smith | ![]() | C/LW/RW | 4 | 1 | 1 | 2 | 0 | 5 | 5 | 4 | 7 | 1 | 3 | 14.29% | 0 | 12.59 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 0 | 100.00% | 0 | 0 | 0.50 | 0 | 0 | 0.30 | |||
6 | Jake Lucchini | ![]() | C | 4 | 0 | 2 | 2 | 0 | 5 | 5 | 3 | 12 | 1 | 3 | 0.00% | 1 | 13.76 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 58.97% | 0 | 0 | 0.50 | 0 | 0 | 0.38 | |||
7 | Dominic Toninato | ![]() | C/RW | 4 | 1 | 1 | 2 | 0 | 0 | 0 | 2 | 12 | 2 | 7 | 8.33% | 2 | 17.19 | 0 | 1 | 1 | 0 | 0 | 0 | 12 | 0 | 0 | 70.37% | 0 | 0 | 0.50 | 0 | 0 | 0.66 | |||
8 | William Wallinder | ![]() | D | 4 | 0 | 1 | 1 | -2 | 0 | 0 | 3 | 5 | 0 | 0 | 0.00% | 2 | 20.21 | 0 | 0 | 0 | 0 | 0 | 0 | 11 | 0 | 0 | 0.00% | 0 | 0 | 0.25 | 0 | 0 | 0.09 | |||
9 | Jujhar Khaira | ![]() | C | 4 | 0 | 1 | 1 | -1 | 0 | 0 | 7 | 5 | 2 | 2 | 0.00% | 2 | 13.89 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 60.00% | 0 | 0 | 0.25 | 0 | 0 | 0.26 | |||
10 | Sam Honzek | ![]() | LW | 4 | 1 | 0 | 1 | 0 | 2 | 0 | 6 | 6 | 1 | 2 | 16.67% | 1 | 14.04 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 100.00% | 0 | 0 | 0.25 | 0 | 0 | 0.26 | |||
11 | Dillon Heatherington | ![]() | D | 4 | 0 | 1 | 1 | 2 | 0 | 0 | 4 | 5 | 2 | 2 | 0.00% | 8 | 25.85 | 0 | 0 | 0 | 0 | 0 | 0 | 11 | 0 | 0 | 0.00% | 0 | 0 | 0.25 | 0 | 0 | 0.50 | |||
12 | Tommy Miller | ![]() | D | 4 | 0 | 1 | 1 | -2 | 2 | 0 | 1 | 2 | 3 | 1 | 0.00% | 5 | 19.79 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 0 | 0 | 0.00% | 0 | 0 | 0.25 | 0 | 0 | -0.00 | |||
13 | Tyson Feist | ![]() | D | 4 | 1 | 0 | 1 | 2 | 0 | 0 | 4 | 5 | 2 | 0 | 20.00% | 3 | 15.28 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0.25 | 0 | 0 | 0.53 | |||
14 | Jani Nyman | ![]() | RW | 4 | 0 | 0 | 0 | -1 | 2 | 0 | 6 | 8 | 5 | 2 | 0.00% | 0 | 10.93 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 50.00% | 0 | 0 | 0.00 | 0 | 0 | 0.03 | |||
15 | Alec Regula | ![]() | D | 4 | 0 | 0 | 0 | 2 | 4 | 0 | 3 | 4 | 2 | 0 | 0.00% | 2 | 16.72 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 0 | 0.00% | 0 | 0 | 0.00 | 0 | 0 | 0.09 | |||
16 | Owen Beck | ![]() | C | 4 | 0 | 0 | 0 | -2 | 0 | 0 | 5 | 4 | 1 | 3 | 0.00% | 1 | 12.63 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 60.00% | 0 | 0 | 0.00 | 0 | 0 | -0.04 | |||
17 | Ronnie Attard | ![]() | D | 4 | 0 | 0 | 0 | 2 | 13 | 5 | 5 | 5 | 4 | 1 | 0.00% | 8 | 24.52 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 0 | 0 | 0.00% | 0 | 0 | 0.00 | 0 | 0 | -0.18 | |||
18 | Ville Koivunen | ![]() | RW | 4 | 0 | 0 | 0 | -2 | 2 | 0 | 6 | 11 | 2 | 5 | 0.00% | 1 | 13.73 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 60.00% | 0 | 0 | 0.00 | 0 | 0 | 0.02 | |||
Team Total or Average | 72 | 12 | 17 | 29 | 9 | 63 | 25 | 82 | 143 | 40 | 59 | 8.39% | 37 | 16.55 | 3 | 4 | 7 | 63 | 0 | 0 | 0 | 91 | 2 | 1 | 58.19% | 232 | 21 | 23 | 0 | 0 | 0.49 | 1 | 3 |
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 | Joel Blomqvist | ![]() | 3 | 2 | 0 | 0 | 0.947 | 1.57 | 153 | 0 | 0 | 4 | 76 | 40 | 0 | 0 | 0.000 | 0 | 2 | 2 | 1 | 0 | 0 |
2 | Arturs Silovs | ![]() | 2 | 1 | 1 | 0 | 0.857 | 3.30 | 91 | 2 | 0 | 5 | 35 | 18 | 0 | 0 | 1.000 | 3 | 2 | 2 | 0 | 0 | 0 |
Team Total or Average | 5 | 3 | 1 | 0 | 0.919 | 2.20 | 245 | 2 | 0 | 9 | 111 | 58 | 0 | 0 | 1.000 | 3 | 4 | 4 | 1 | 0 | 0 |
Player Name | POS | Age | Cap Hit | 2017-18 | 2018-19 | 2019-20 | 2020-21 | 2021-22 | 2022-23 | 2023-24 | 2024-25 |
---|---|---|---|---|---|---|---|---|---|---|---|
Alec Regula | D | 24 | 1,400,000$ | 1,400,000$ | |||||||
Ales Stezka | G | 28 | 975,000$ | 975,000$ | 975,000$ | UFA | |||||
Anton Malmström | D | 25 | 1,000,000$ | 1,000,000$ | |||||||
Arturs Silovs | G | 24 | 1,100,000$ | 1,100,000$ | 1,100,000$ | ||||||
Blake Wheeler | RW | 38 | 1,000,000$ | 1,000,000$ | UFA | ||||||
Brett Seney | LW | 29 | 975,000$ | 975,000$ | UFA | ||||||
C.J. Smith | C/LW/RW | 30 | 975,000$ | 975,000$ | UFA | ||||||
Carl Berglund | C | 25 | 1,000,000$ | 1,000,000$ | |||||||
Carsen Twarynski | LW | 27 | 975,000$ | 975,000$ | UFA | ||||||
Chad Hillebrand | C/LW/RW | 26 | 1,000,000$ | 1,000,000$ | |||||||
Darren Brady | D | 29 | 1,000,000$ | 1,000,000$ | UFA | ||||||
Dillon Heatherington | D | 30 | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | |||||
Domenic DiVincentiis | G | 21 | 975,000$ | 975,000$ | 975,000$ | RFA | |||||
Dominic Toninato | C/RW | 31 | 1,275,000$ | 1,275,000$ | 1,275,000$ | 1,275,000$ | UFA | ||||
Garrett Pyke | D | 25 | 1,000,000$ | 1,000,000$ | |||||||
Georgii Merkulov | C | 24 | 975,000$ | 975,000$ | |||||||
Jake Lucchini | C | 30 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | ||||
Jani Nyman | RW | 20 | 975,000$ | 975,000$ | 975,000$ | 975,000$ | RFA | ||||
Jaydon Dureau | LW | 24 | 975,000$ | 975,000$ | 975,000$ | ||||||
Jiri Patera | G | 26 | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | |||||
Joakim Ryan | D | 32 | 1,000,000$ | 1,000,000$ | UFA | ||||||
Joel Blomqvist | G | 23 | 1,400,000$ | 1,400,000$ | 1,400,000$ | 1,400,000$ | 1,400,000$ | ||||
Jujhar Khaira | C | 30 | 1,250,000$ | 1,250,000$ | 1,250,000$ | UFA | |||||
Magnus Chrona | G | 24 | 975,000$ | 975,000$ | 975,000$ | ||||||
Martin Frk | RW | 31 | 975,000$ | 975,000$ | UFA | ||||||
Matyas Sapovaliv | C | 21 | 803,333$ | 975,000$ | 975,000$ | RFA | |||||
Miko Matikka | RW | 21 | 870,000$ | 975,000$ | 975,000$ | RFA | |||||
Nikke Kokko | G | 21 | 975,000$ | 975,000$ | 975,000$ | 975,000$ | RFA | ||||
Owen Beck | C | 21 | 853,333$ | 975,000$ | 975,000$ | RFA | |||||
Patrick Brown | C/LW/RW | 33 | 1,000,000$ | 1,000,000$ | UFA | ||||||
Ronnie Attard | D | 26 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | |||
Sam Honzek | LW | 20 | 975,000$ | 975,000$ | 975,000$ | 975,000$ | RFA | ||||
Scooter Brickey | D | 26 | 1,000,000$ | 1,000,000$ | |||||||
Tommy Miller | D | 26 | 975,000$ | 975,000$ | |||||||
Ty Glover | C | 24 | 975,000$ | 975,000$ | |||||||
Tyson Feist | D | 24 | 975,000$ | 975,000$ | |||||||
Ville Koivunen | RW | 22 | 975,000$ | 975,000$ | 975,000$ | RFA | |||||
William Wallinder | D | 22 | 975,000$ | 975,000$ | 975,000$ | ||||||
Zac Dalpe | C | 35 | 1,000,000$ | 1,000,000$ | UFA |
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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 | 1 | 3 | 2 | 1.000 | 4 | 5 | 9 | 0 | 0 | 4 | 5 | 3 | 1 | 39 | 40 | 46 | 55 | 5 | 33 | 16 | 4 | 14 | 0 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 48 | 90 | 53.33% | 49 | 80 | 61.25% | 38 | 61 | 62.30% | 82 | 44 | 81 | 41 | 80 | 37 | 80.0% | 10.3% | 97.0% | 107.2 | LUCKY |
2 | ![]() | 2 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 4 | 6 | -2 | 2 | 0.500 | 4 | 6 | 10 | 0 | 0 | 4 | 5 | 3 | 1 | 68 | 40 | 46 | 55 | 5 | 51 | 17 | 51 | 51 | 5 | 1 | 20.00% | 8 | 1 | 87.50% | 0 | 48 | 90 | 53.33% | 49 | 80 | 61.25% | 38 | 61 | 62.30% | 82 | 44 | 81 | 41 | 80 | 37 | 37.5% | 5.9% | 88.2% | 94.1 | Unlucky |
3 | ![]() | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 2 | 3 | 2 | 1.000 | 5 | 6 | 11 | 0 | 0 | 4 | 5 | 3 | 1 | 36 | 40 | 46 | 55 | 5 | 27 | 4 | 10 | 17 | 7 | 2 | 28.57% | 5 | 1 | 80.00% | 0 | 48 | 90 | 53.33% | 49 | 80 | 61.25% | 38 | 61 | 62.30% | 82 | 44 | 81 | 41 | 80 | 37 | 75.0% | 13.9% | 92.6% | 106.5 | LUCKY |
_Vs Conference | 3 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 8 | 7 | 1 | 4 | 0.667 | 8 | 11 | 19 | 0 | 0 | 4 | 5 | 3 | 1 | 107 | 40 | 46 | 55 | 5 | 84 | 33 | 55 | 65 | 5 | 1 | 20.00% | 10 | 1 | 90.00% | 0 | 48 | 90 | 53.33% | 49 | 80 | 61.25% | 38 | 61 | 62.30% | 82 | 44 | 81 | 41 | 80 | 37 | 53.8% | 7.5% | 91.7% | 99.1 | DULL | |
_Since Last GM Reset | 4 | 2 | 1 | 0 | 0 | 0 | 1 | 0 | 13 | 9 | 4 | 6 | 0.750 | 13 | 17 | 30 | 0 | 0 | 4 | 5 | 3 | 1 | 143 | 40 | 46 | 55 | 5 | 111 | 37 | 65 | 82 | 12 | 3 | 25.00% | 15 | 2 | 86.67% | 0 | 48 | 90 | 53.33% | 49 | 80 | 61.25% | 38 | 61 | 62.30% | 82 | 44 | 81 | 41 | 80 | 37 | 58.8% | 9.1% | 91.9% | 101.0 | LUCKY | |
Total | 4 | 2 | 1 | 0 | 0 | 0 | 1 | 0 | 13 | 9 | 4 | 6 | 0.750 | 13 | 17 | 30 | 0 | 0 | 4 | 5 | 3 | 1 | 143 | 40 | 46 | 55 | 5 | 111 | 37 | 65 | 82 | 12 | 3 | 25.00% | 15 | 2 | 86.67% | 0 | 48 | 90 | 53.33% | 49 | 80 | 61.25% | 38 | 61 | 62.30% | 82 | 44 | 81 | 41 | 80 | 37 | 58.8% | 9.1% | 91.9% | 101.0 | LUCKY |
Puck Time | |
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Offensive Zone | 20 |
Neutral Zone | 20 |
Defensive Zone | 20 |
Puck Time | |
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Offensive Zone Start | 90 |
Neutral Zone Start | 61 |
Defensive Zone Start | 80 |
Puck Time | |
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With Puck | 30 |
Without Puck | 30 |
Faceoffs | |
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Faceoffs Won | 135 |
Faceoffs Lost | 96 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 10.0 | 9.57 |
2nd Period | 21.5 | 20.31 |
3rd Period | 35.3 | 30.68 |
Overtime | 36.5 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 1.0 | 0.64 |
2nd Period | 2.3 | 1.65 |
3rd Period | 3.0 | 2.67 |
Overtime | 3.3 | 2.83 |
Even Strenght Goal | 10 |
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PP Goal | 3 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
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Win | 1 | 2 |
Lost | 1 | 0 |
Overtime Lost | 0 | 0 |
PP Attempt | 12 |
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PP Goal | 3 |
PK Attempt | 15 |
PK Goal Against | 2 |
Home | |
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Shots For | 35.8 |
Shots Against | 27.8 |
Goals For | 3.3 |
Goals Against | 2.3 |
Hits | 20.5 |
Shots Blocked | 9.3 |
Pim | 16.3 |
Date | Matchup | Result | Detail | |||||||||||
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Thu, Oct 9 | ![]() | @ | ![]() | TOR4,BOS1 | RECAP | |||||||||
Sat, Oct 11 | ![]() | @ | ![]() | TOR2,BUF1 (SO) | RECAP | |||||||||
Sun, Oct 12 | ![]() | @ | ![]() | LOS2,TOR5 | RECAP | |||||||||
Wed, Oct 15 | ![]() | @ | ![]() | BUF5,TOR2 | RECAP | |||||||||
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Trade Deadline --- Trades can’t be done after this day is simulated! | ||||||||||||||
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Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
3,992,500$ | 0$ | 0$ | 75,000,000$ |
Arena | About us | |
---|---|---|
![]() | Name | |
City | Toronto | |
Capacity | 3000 | |
Season Ticket Holders | 10% |
Arena Capacity - Ticket Price Attendance - % | |||||
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Arena Capacity | 2000 | 1000 | |||
Ticket Price | 28$ | 12$ | $ | $ | $ |
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 |
39 | 0 - 0.00% | 0$ | 0$ | 3000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
3,992,500$ | 3,992,500$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
260,000$ | 0$ | 188,992$ | 0$ |
Estimate | |||
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Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 184 | 32,500$ | 5,232,500$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
5,232,500$ | 0$ | 0$ | 0$ |
Sponsors | |||
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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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