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Toronto Maple Leafs Team Overall:71 0-0-0, 0pts |
# | Player | Position | Height | Weight | Age | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | Overall | Condition | Contract | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Scratches | ||||||||||||||||||||||||||
0 | ![]() | RW | 6' 4" | 219 | 27 | 72 | 40 | 86 | 82 | 85 | 81 | 84 | 80 | 72 | 86 | 84 | 72 | 67 | 66 | 59 | 0 | 40 | 82 | 100.00 | 4,750,000$/1yrs | |
0 | ![]() | RW | 5' 10" | 178 | 24 | 65 | 40 | 82 | 83 | 72 | 85 | 89 | 79 | 59 | 87 | 83 | 68 | 69 | 69 | 66 | 0 | 40 | 81 | 100.00 | 1,673,333$/1yrs | |
0 | ![]() | C | 6' 0" | 181 | 27 | 67 | 40 | 84 | 89 | 70 | 83 | 82 | 76 | 60 | 85 | 77 | 71 | 68 | 68 | 59 | 0 | 40 | 80 | 100.00 | 5,850,000$/1yrs | |
0 | ![]() | C | 6' 4" | 210 | 31 | 70 | 40 | 85 | 77 | 80 | 80 | 91 | 76 | 74 | 82 | 81 | 67 | 58 | 79 | 67 | 0 | 40 | 79 | 100.00 | 6,000,000$/1yrs | |
0 | ![]() | C | 6' 3" | 207 | 26 | 81 | 40 | 77 | 76 | 80 | 81 | 92 | 73 | 79 | 82 | 71 | 78 | 74 | 68 | 66 | 0 | 40 | 79 | 100.00 | 1,487,500$/1yrs | |
0 | ![]() | LW | 6' 1" | 194 | 33 | 72 | 64 | 79 | 74 | 76 | 77 | 93 | 73 | 53 | 80 | 77 | 74 | 91 | 81 | 68 | 0 | 40 | 78 | 100.00 | 4,450,000$/1yrs | |
0 | ![]() | RW | 5' 8" | 181 | 35 | 68 | 40 | 84 | 78 | 76 | 84 | 88 | 75 | 62 | 84 | 74 | 64 | 72 | 79 | 66 | 0 | 40 | 78 | 100.00 | 6,000,000$/2yrs | |
0 | ![]() | C | 5' 11" | 195 | 32 | 65 | 40 | 85 | 82 | 79 | 79 | 86 | 73 | 77 | 82 | 78 | 65 | 82 | 86 | 69 | 0 | 40 | 78 | 100.00 | 8,000,000$/1yrs | |
0 | ![]() | LW | 6' 3" | 209 | 28 | 68 | 40 | 85 | 76 | 81 | 75 | 80 | 72 | 52 | 82 | 70 | 63 | 54 | 73 | 59 | 0 | 40 | 75 | 100.00 | 4,350,000$/2yrs | |
0 | ![]() | C | 6' 6" | 208 | 30 | 81 | 73 | 87 | 66 | 76 | 73 | 94 | 65 | 79 | 76 | 66 | 80 | 54 | 74 | 67 | 0 | 40 | 74 | 100.00 | 2,916,666$/1yrs | |
0 | ![]() | C | 6' 6" | 211 | 24 | 76 | 65 | 74 | 74 | 78 | 71 | 84 | 66 | 77 | 79 | 67 | 75 | 54 | 62 | 58 | 0 | 40 | 74 | 100.00 | 1,710,833$/1yrs | |
0 | ![]() | LW | 6' 0" | 190 | 33 | 64 | 40 | 81 | 71 | 75 | 73 | 84 | 66 | 61 | 76 | 69 | 70 | 57 | 76 | 60 | 0 | 40 | 73 | 100.00 | 5,187,500$/1yrs | |
0 | ![]() | C | 6' 0" | 213 | 20 | 69 | 40 | 78 | 70 | 88 | 72 | 77 | 67 | 67 | 77 | 69 | 69 | 84 | 57 | 58 | 0 | 40 | 73 | 100.00 | 3,425,000$/1yrs | |
0 | ![]() | LW | 6' 1" | 165 | 24 | 74 | 40 | 89 | 66 | 61 | 78 | 79 | 65 | 64 | 77 | 65 | 82 | 54 | 57 | 58 | 0 | 40 | 73 | 100.00 | 1,137,500$/3yrs | |
0 | ![]() | LW | 6' 3" | 202 | 29 | 73 | 66 | 90 | 66 | 77 | 68 | 90 | 61 | 53 | 73 | 65 | 75 | 58 | 71 | 59 | 0 | 40 | 71 | 100.00 | 1,537,500$/1yrs | |
0 | ![]() | LW | 5' 11" | 187 | 30 | 69 | 40 | 88 | 70 | 75 | 68 | 88 | 61 | 57 | 72 | 66 | 76 | 54 | 75 | 60 | 0 | 40 | 71 | 100.00 | 1,412,500$/1yrs | |
0 | ![]() | LW | 6' 3" | 236 | 27 | 85 | 64 | 75 | 63 | 95 | 68 | 89 | 62 | 52 | 72 | 67 | 65 | 74 | 70 | 59 | 0 | 40 | 71 | 100.00 | 1,999,462$/1yrs | |
0 | ![]() | C | 6' 0" | 190 | 23 | 69 | 40 | 88 | 73 | 75 | 77 | 86 | 63 | 67 | 74 | 65 | 65 | 92 | 60 | 58 | 0 | 40 | 71 | 100.00 | 925,000$/1yrs | |
0 | ![]() | LW | 6' 2" | 195 | 27 | 75 | 66 | 77 | 68 | 75 | 64 | 80 | 63 | 52 | 73 | 66 | 66 | 54 | 67 | 65 | 0 | 40 | 70 | 100.00 | 2,750,000$/1yrs | |
0 | ![]() | C | 6' 4" | 212 | 28 | 67 | 42 | 82 | 63 | 79 | 63 | 68 | 59 | 80 | 68 | 64 | 76 | 54 | 65 | 59 | 0 | 40 | 69 | 100.00 | 1,675,000$/1yrs | |
0 | ![]() | LW | 6' 0" | 170 | 21 | 58 | 51 | 73 | 62 | 60 | 68 | 61 | 64 | 55 | 65 | 65 | 61 | 60 | 54 | 54 | 0 | 40 | 65 | 100.00 | 1,337,500$/3yrs | |
0 | ![]() | C | 5' 9" | 175 | 28 | 56 | 55 | 67 | 62 | 59 | 65 | 62 | 63 | 67 | 63 | 62 | 65 | 63 | 65 | 59 | 0 | 40 | 64 | 100.00 | 762,500$/1yrs | |
0 | ![]() | C | 5' 10" | 176 | 28 | 56 | 65 | 66 | 62 | 58 | 66 | 64 | 62 | 55 | 60 | 62 | 59 | 54 | 67 | 60 | 0 | 40 | 63 | 100.00 | 1,500,000$/1yrs | |
0 | ![]() | C/LW | 6' 1" | 207 | 23 | 56 | 55 | 61 | 61 | 67 | 67 | 66 | 60 | 55 | 58 | 58 | 60 | 54 | 57 | 54 | 0 | 40 | 62 | 100.00 | 700,000$/2yrs | |
0 | ![]() | C | 5' 11" | 190 | 25 | 56 | 54 | 65 | 59 | 62 | 66 | 64 | 60 | 69 | 60 | 58 | 61 | 54 | 60 | 56 | 0 | 40 | 62 | 100.00 | 1,425,000$/1yrs | |
0 | ![]() | C | 6' 2" | 192 | 24 | 55 | 58 | 67 | 59 | 62 | 66 | 64 | 58 | 55 | 57 | 57 | 59 | 54 | 60 | 56 | 0 | 40 | 61 | 100.00 | 700,000$/1yrs | |
0 | ![]() | C/LW | 6' 2" | 194 | 29 | 55 | 57 | 67 | 57 | 64 | 61 | 60 | 59 | 55 | 58 | 58 | 62 | 54 | 68 | 60 | 0 | 40 | 61 | 100.00 | 750,000$/1yrs | |
0 | ![]() | C/LW | 6' 2" | 214 | 20 | 56 | 57 | 65 | 59 | 69 | 62 | 61 | 59 | 55 | 57 | 60 | 58 | 54 | 54 | 52 | 0 | 40 | 61 | 100.00 | 925,000$/2yrs | |
0 | ![]() | C | 6' 4" | 207 | 23 | 55 | 55 | 64 | 58 | 69 | 67 | 66 | 56 | 70 | 55 | 56 | 59 | 54 | 59 | 55 | 0 | 40 | 60 | 100.00 | 894,167$/1yrs | |
0 | ![]() | C | 6' 2" | 186 | 23 | 55 | 55 | 67 | 59 | 62 | 65 | 63 | 57 | 55 | 57 | 57 | 60 | 54 | 59 | 55 | 0 | 40 | 60 | 100.00 | 1,075,000$/1yrs | |
0 | ![]() | C | 5' 10" | 170 | 23 | 55 | 57 | 66 | 58 | 56 | 65 | 64 | 59 | 70 | 57 | 59 | 57 | 54 | 57 | 54 | 0 | 40 | 60 | 100.00 | 891,667$/1yrs | |
0 | ![]() | C | 6' 0" | 190 | 31 | 55 | 54 | 67 | 55 | 62 | 58 | 57 | 56 | 70 | 56 | 55 | 61 | 54 | 71 | 62 | 0 | 40 | 59 | 100.00 | 3,375,000$/1yrs | |
0 | ![]() | D | 6' 3" | 209 | 30 | 83 | 64 | 78 | 73 | 81 | 92 | 95 | 64 | 40 | 77 | 63 | 85 | 54 | 79 | 70 | 0 | 40 | 78 | 100.00 | 4,166,666$/1yrs | |
0 | ![]() | D | 6' 1" | 235 | 32 | 68 | 40 | 84 | 82 | 98 | 89 | 83 | 62 | 40 | 76 | 60 | 88 | 54 | 78 | 60 | 0 | 40 | 78 | 100.00 | 4,250,000$/2yrs | |
0 | ![]() | D | 6' 7" | 257 | 30 | 77 | 72 | 81 | 76 | 99 | 82 | 90 | 62 | 40 | 74 | 64 | 90 | 54 | 71 | 59 | 0 | 40 | 78 | 100.00 | 2,137,500$/1yrs | |
0 | ![]() | D | 6' 0" | 206 | 29 | 83 | 64 | 80 | 83 | 84 | 86 | 94 | 63 | 40 | 78 | 60 | 89 | 54 | 67 | 59 | 0 | 40 | 78 | 100.00 | 2,837,500$/3yrs | |
0 | ![]() | D | 6' 3" | 210 | 28 | 70 | 40 | 76 | 78 | 81 | 87 | 86 | 62 | 40 | 75 | 63 | 92 | 54 | 69 | 59 | 0 | 40 | 77 | 100.00 | 1,600,000$/1yrs | |
0 | ![]() | D | 6' 1" | 197 | 29 | 74 | 64 | 81 | 79 | 78 | 77 | 92 | 60 | 40 | 74 | 59 | 82 | 54 | 68 | 59 | 0 | 40 | 74 | 100.00 | 1,850,000$/3yrs | |
0 | ![]() | D | 6' 4" | 225 | 35 | 72 | 40 | 88 | 69 | 88 | 77 | 83 | 57 | 40 | 71 | 57 | 86 | 54 | 84 | 72 | 0 | 40 | 73 | 100.00 | 6,000,000$/1yrs | |
0 | ![]() | D | 6' 4" | 208 | 25 | 71 | 64 | 84 | 79 | 79 | 77 | 77 | 59 | 40 | 72 | 59 | 87 | 54 | 57 | 58 | 0 | 40 | 73 | 100.00 | 925,000$/1yrs | |
0 | ![]() | D | 6' 1" | 194 | 25 | 74 | 40 | 77 | 71 | 76 | 81 | 84 | 59 | 40 | 72 | 60 | 82 | 54 | 61 | 58 | 0 | 40 | 72 | 100.00 | 815,000$/1yrs | |
0 | ![]() | D | 6' 1" | 188 | 29 | 63 | 40 | 89 | 69 | 73 | 73 | 67 | 62 | 40 | 74 | 66 | 79 | 54 | 57 | 58 | 0 | 40 | 72 | 100.00 | 750,000$/3yrs | |
0 | ![]() | D | 6' 3" | 201 | 30 | 64 | 40 | 88 | 73 | 77 | 74 | 71 | 58 | 40 | 72 | 61 | 78 | 54 | 69 | 59 | 0 | 40 | 71 | 100.00 | 937,500$/3yrs | |
0 | ![]() | D | 6' 2" | 190 | 28 | 56 | 52 | 71 | 63 | 66 | 66 | 60 | 61 | 40 | 65 | 56 | 65 | 54 | 64 | 59 | 0 | 40 | 64 | 100.00 | 900,000$/1yrs | |
0 | ![]() | D | 6' 3" | 212 | 24 | 55 | 54 | 66 | 58 | 69 | 66 | 64 | 56 | 40 | 56 | 54 | 59 | 54 | 59 | 55 | 0 | 40 | 60 | 100.00 | 925,000$/1yrs |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | Goalie | Height | Weight | Age | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | Overall | Condition | Contract |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Scratches | ||||||||||||||||||||||||
0 | ![]() | 5' 11" | 180 | 28 | 85 | 99 | 99 | 78 | 92 | 93 | 69 | 59 | 0 | 40 | 86 | 100.00 | 1,500,000$/1yrs | |||||||
0 | ![]() | 6' 0" | 181 | 31 | 74 | 79 | 80 | 86 | 84 | 73 | 62 | 55 | 0 | 40 | 78 | 100.00 | 1,250,000$/3yrs | |||||||
0 | ![]() | 6' 2" | 191 | 26 | 60 | 65 | 63 | 74 | 73 | 58 | 58 | 55 | 0 | 40 | 68 | 100.00 | 925,000$/2yrs | |||||||
0 | ![]() | 6' 2" | 201 | 26 | 65 | 64 | 64 | 60 | 69 | 60 | 63 | 57 | 0 | 40 | 64 | 100.00 | 925,000$/1yrs |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Todd McLellan | 80 | 87 | 80 | 86 | 81 | 75 | 68 | CAN | 55 | 1 | 5,000,000$ |
General Manager | Jonathan Prevost |
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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 | AMG | PPG | PPA | PPP | PPM | PKG | PKA | PKP | PKM | GW | GT | FO% | FOT | GA | TA | EG | HT | P/20 | PSG | PSS |
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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 |
---|
Projected Total Cap Hit | 0$ |
Projected Cap Space | 91,500,000$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 0$ |
Players In Salary Cap | 49 |
LTIR Players | 0 |
Player Name | Pos | Age | Cap Hit | 2022-2023 | 2023-2024 | 2024-2025 | 2025-2026 | 2026-2027 | 2027-2028 | 2028-2029 | 2029-2030 |
---|---|---|---|---|---|---|---|---|---|---|---|
Adam Larsson ![]() | D | 30 | 4,166,666$ | 4,166,666$ | |||||||
Adam Lowry ![]() | C | 30 | 2,916,666$ | 2,916,666$ | |||||||
Adam Pelech ![]() | D | 28 | 1,600,000$ | 1,600,000$ | |||||||
Alex Killorn ![]() | LW | 33 | 4,450,000$ | 4,450,000$ | |||||||
Alex Tuch ![]() | RW | 27 | 4,750,000$ | 4,750,000$ | |||||||
Andre Burakovsky ![]() | LW | 28 | 4,900,000$ | 4,900,000$ | 4,900,000$ | ||||||
Ben Hutton ![]() | D | 30 | 750,000$ | 750,000$ | 750,000$ | 750,000$ | |||||
Brett Kulak ![]() | D | 29 | 1,850,000$ | 1,850,000$ | 1,850,000$ | 1,850,000$ | |||||
Brock Nelson ![]() | C | 31 | 6,000,000$ | 6,000,000$ | |||||||
Caleb Jones ![]() | D | 25 | 815,000$ | 815,000$ | |||||||
Calle Rosen ![]() | D | 29 | 750,000$ | 750,000$ | 750,000$ | 750,000$ | |||||
Cameron Crotty ![]() | D | 24 | 925,000$ | 925,000$ | |||||||
Casey Desmith ![]() | C/LW | 31 | 1,250,000$ | 1,250,000$ | 1,250,000$ | 1,250,000$ | |||||
Christian Wolanin ![]() | D | 28 | 900,000$ | 900,000$ | |||||||
Clayton Keller ![]() | RW | 24 | 1,673,333$ | 1,673,333$ | |||||||
Cole Reinhardt ![]() | C/LW | 23 | 700,000$ | 700,000$ | 700,000$ | ||||||
David Savard ![]() | D | 32 | 4,250,000$ | 4,250,000$ | 4,250,000$ | ||||||
Drake Caggiula ![]() | C | 28 | 1,500,000$ | 1,500,000$ | |||||||
Erik Johnson ![]() | D | 35 | 6,000,000$ | 6,000,000$ | |||||||
Felix Sandstrom ![]() | RW | 26 | 925,000$ | 925,000$ | 925,000$ | ||||||
Jamie Oleksiak ![]() | D | 30 | 2,137,500$ | 2,137,500$ | |||||||
Jimmy Vesey ![]() | LW | 29 | 800,000$ | 800,000$ | |||||||
Joel Eriksson Ek ![]() | C | 26 | 1,487,500$ | 1,487,500$ | |||||||
Joey Daccord ![]() | LW | 26 | 925,000$ | 925,000$ | |||||||
Johnathan Kovacevic ![]() | D | 25 | 925,000$ | 925,000$ | |||||||
Justin Richards ![]() | C | 25 | 1,425,000$ | 1,425,000$ | |||||||
Juuse Saros ![]() | C | 28 | 1,500,000$ | 1,500,000$ | |||||||
Kristian Reichel ![]() | C | 24 | 700,000$ | 700,000$ | |||||||
Lukas Reichel ![]() | LW | 21 | 1,337,500$ | 1,337,500$ | 1,337,500$ | 1,337,500$ | |||||
Mackenzie MacEachern ![]() | C/LW | 29 | 750,000$ | 750,000$ | |||||||
Mackenzie Weegar ![]() | D | 29 | 3,250,000$ | 3,250,000$ | 3,250,000$ | 3,250,000$ | |||||
Mark Jankowski ![]() | C | 28 | 1,675,000$ | 1,675,000$ | |||||||
Mason McTavish ![]() | C | 20 | 3,425,000$ | 3,425,000$ | |||||||
Mats Zuccarello ![]() | RW | 35 | 6,000,000$ | 6,000,000$ | 6,000,000$ | ||||||
Matt Duchene ![]() | C | 32 | 8,000,000$ | 8,000,000$ | |||||||
Matt Nieto ![]() | LW | 30 | 850,000$ | 850,000$ | |||||||
Michael Rasmussen ![]() | C | 24 | 1,710,833$ | 1,710,833$ | |||||||
Mike Hoffman ![]() | LW | 33 | 5,187,500$ | 5,187,500$ | |||||||
Miles Wood ![]() | LW | 27 | 2,750,000$ | 2,750,000$ | |||||||
Nic Petan ![]() | C | 28 | 750,000$ | 750,000$ | |||||||
Nick Ritchie ![]() | LW | 27 | 2,500,000$ | 2,500,000$ | |||||||
Nick Schmaltz ![]() | C | 27 | 5,850,000$ | 5,850,000$ | |||||||
Noah Cates ![]() | LW | 24 | 1,137,500$ | 1,137,500$ | 1,137,500$ | 1,137,500$ | |||||
Philipp Kurashev ![]() | C | 23 | 925,000$ | 925,000$ | |||||||
Riley Damiani ![]() | C | 23 | 891,667$ | 891,667$ | |||||||
Riley Sutter ![]() | C | 23 | 894,167$ | 894,167$ | |||||||
Roby Jarventie ![]() | C/LW | 20 | 925,000$ | 925,000$ | 925,000$ | ||||||
Ryan Dzingel ![]() | C | 31 | 3,375,000$ | 3,375,000$ | |||||||
Shane Bowers ![]() | C | 23 | 1,075,000$ | 1,075,000$ |
Forward Lines | |||||||
---|---|---|---|---|---|---|---|
Defensive Pairings | |||||||
---|---|---|---|---|---|---|---|
1st Power Play Unit | |||||||
---|---|---|---|---|---|---|---|
2nd Power Play Unit | |||||||
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Goalies | |||||||
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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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 | nan% | nan% | nan% | nan | Unlucky |
Puck Time | |
---|---|
Offensive Zone | NAN |
Neutral Zone | NAN |
Defensive Zone | NAN |
Puck Time | |
---|---|
Offensive Zone Start | 0 |
Neutral Zone Start | 0 |
Defensive Zone Start | 0 |
Puck Time | |
---|---|
With Puck | NAN |
Without Puck | NAN |
Faceoffs | |
---|---|
Faceoffs Won | 0 |
Faceoffs Lost | 0 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | nan | 9.57 |
2nd Period | nan | 20.31 |
3rd Period | nan | 30.68 |
Overtime | nan | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | nan | 0.64 |
2nd Period | nan | 1.65 |
3rd Period | nan | 2.67 |
Overtime | nan | 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 | nan |
Shots Against | nan |
Goals For | nan |
Goals Against | nan |
Hits | nan |
Shots Blocked | nan |
Pim | nan |
Date | Matchup | Result | Detail |
---|
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
114,230,832$ | 0$ | 0$ | 91,500,000$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | Scotiabank Arena | |
City | Toronto | ||
Capacity | 18000 | ||
Season Ticket Holders | 40% |
Arena Capacity - Ticket Price Attendance - % | |||||
---|---|---|---|---|---|
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Arena Capacity | 6000 | 5000 | 2000 | 4000 | 1000 |
Ticket Price | 100$ | 60$ | 35$ | 25$ | 200$ |
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 |
41 | 0 - 0.00% | 0$ | 0$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
114,230,832$ | 114,267,794$ | 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$ | 10,000,000$ | 10,000,000$ |
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GOALIE | ||||||||||||||||||||||||||||||||||||
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Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
---|---|---|---|---|---|---|---|
2023 | |||||||
2024 | |||||||
2025 | |||||||
2026 |
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 |
Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
---|---|---|---|---|---|
Jack Thompson | |||||
Jake Sanderson | |||||
Oskar Olausson | |||||
Sam Colangelo |
Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
---|---|---|---|---|---|---|---|
2023 | |||||||
2024 | |||||||
2025 | |||||||
2026 |
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 |
Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
---|---|---|---|---|---|
Jack Thompson | |||||
Jake Sanderson | |||||
Oskar Olausson | |||||
Sam Colangelo |