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Full Scoreboard ยป |
Toronto Maple Leafs 22-23-6, 50pts · 10th in Eastern Conference |
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 | # | POS | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | LW/RW | 100.00 | 58 | 5 | 99 | 91 | 64 | 68 | 84 | 80 | 20 | 91 | 93 | 60 | 25 | 71 | 73 | 72 | 57 | 75 | 26 | 6,000,000$/5yrs | |||
![]() | 0 | LW | 100.00 | 61 | 32 | 75 | 80 | 69 | 88 | 95 | 91 | 71 | 84 | 87 | 64 | 81 | 43 | 43 | 92 | 57 | 74 | 21 | 2,250,000$/4yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 67 | 31 | 69 | 81 | 73 | 72 | 67 | 95 | 73 | 88 | 88 | 64 | 81 | 47 | 47 | 88 | 57 | 74 | 22 | 4,500,000$/3yrs | |||
![]() | 0 | LW/RW | 100.00 | 46 | 28 | 99 | 77 | 81 | 89 | 94 | 87 | 76 | 79 | 81 | 61 | 78 | 49 | 49 | 90 | 52 | 72 | 23 | 3,750,000$/3yrs | |||
![]() | 0 | C | 100.00 | 67 | 41 | 76 | 75 | 77 | 83 | 85 | 88 | 77 | 80 | 80 | 63 | 81 | 44 | 44 | 91 | 57 | 72 | 19 | 925,000$/1yrs | |||
![]() | 0 | C | 100.00 | 62 | 14 | 93 | 83 | 70 | 88 | 94 | 81 | 91 | 79 | 73 | 47 | 45 | 71 | 72 | 74 | 73 | 71 | 31 | 3,500,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 56 | 21 | 76 | 81 | 58 | 93 | 95 | 86 | 65 | 79 | 79 | 56 | 77 | 47 | 47 | 88 | 77 | 71 | 20 | 2,900,000$/5yrs | |||
![]() | 0 | C | 100.00 | 61 | 3 | 99 | 84 | 70 | 85 | 96 | 63 | 88 | 69 | 79 | 62 | 25 | 73 | 75 | 76 | 54 | 70 | 30 | 1,750,000$/1yrs | |||
![]() | 0 | C/RW | 100.00 | 66 | 32 | 99 | 79 | 69 | 73 | 88 | 73 | 77 | 80 | 75 | 56 | 25 | 65 | 66 | 71 | 54 | 69 | 25 | 1,150,000$/4yrs | |||
![]() | 0 | C/LW | 100.00 | 93 | 26 | 73 | 84 | 75 | 78 | 85 | 56 | 89 | 53 | 68 | 70 | 53 | 75 | 79 | 64 | 51 | 68 | 28 | 1,250,000$/2yrs | |||
![]() | 0 | C/RW | 100.00 | 54 | 2 | 99 | 71 | 89 | 62 | 85 | 56 | 79 | 60 | 53 | 63 | 25 | 70 | 70 | 55 | 40 | 62 | 26 | 925,000$/1yrs | |||
![]() | 0 | C | 100.00 | 44 | 22 | 99 | 76 | 70 | 79 | 95 | 64 | 63 | 59 | 58 | 50 | 62 | 46 | 46 | 87 | 50 | 61 | 21 | 925,000$/3yrs | |||
![]() | 0 | D | 100.00 | 81 | 13 | 80 | 89 | 84 | 96 | 99 | 82 | 25 | 67 | 80 | 80 | 80 | 78 | 79 | 63 | 53 | 78 | 28 | 7,000,000$/2yrs | |||
![]() | 0 | D | 100.00 | 61 | 31 | 99 | 84 | 66 | 92 | 93 | 97 | 25 | 83 | 53 | 88 | 25 | 60 | 61 | 68 | 58 | 76 | 24 | 9,900,000$/3yrs | |||
![]() | 0 | D | 100.00 | 85 | 40 | 79 | 83 | 89 | 87 | 91 | 62 | 25 | 52 | 52 | 87 | 25 | 72 | 73 | 55 | 59 | 75 | 26 | 4,500,000$/1yrs | |||
![]() | 0 | D | 100.00 | 52 | 2 | 99 | 84 | 71 | 99 | 86 | 72 | 25 | 67 | 58 | 84 | 25 | 65 | 67 | 71 | 56 | 73 | 30 | 3,000,000$/3yrs | |||
![]() | 0 | D | 100.00 | 61 | 28 | 71 | 78 | 63 | 79 | 95 | 78 | 28 | 82 | 57 | 78 | 50 | 48 | 48 | 87 | 54 | 70 | 22 | 700,000$/3yrs | |||
![]() | 0 | D | 100.00 | 62 | 4 | 86 | 76 | 70 | 93 | 79 | 58 | 25 | 62 | 49 | 91 | 25 | 58 | 60 | 65 | 54 | 70 | 31 | 1,750,000$/2yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | LW/RW | 100.00 | 54 | 31 | 92 | 60 | 76 | 77 | 71 | 65 | 50 | 64 | 64 | 68 | 59 | 53 | 53 | 53 | 36 | 63 | 25 | 1,250,000$/4yrs | |||
![]() | 0 | D | 100.00 | 55 | 3 | 99 | 77 | 88 | 80 | 80 | 57 | 25 | 51 | 49 | 89 | 25 | 55 | 55 | 59 | 20 | 69 | 29 | 1,450,000$/1yrs | |||
TEAM AVERAGE | 100.00 | 62 | 20 | 88 | 80 | 74 | 83 | 88 | 75 | 55 | 71 | 69 | 69 | 49 | 60 | 60 | 73 | 53 | 71 |
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 | 60 | 90 | 76 | 80 | 83 | 79 | 80 | 86 | 75 | 70 | 52 | 52 | 60 | 68 | 74 | 24 | 685,000$/3yrs |
![]() | 0 | 100.00 | 72 | 50 | 78 | 77 | 74 | 74 | 72 | 74 | 71 | 68 | 69 | 64 | 65 | 15 | 33 | 69 | 33 | 919,191$/1yrs |
Scratches | ||||||||||||||||||||
![]() | 0 | 100.00 | 76 | 47 | 74 | 70 | 73 | 78 | 78 | 78 | 78 | 72 | 72 | 51 | 51 | 43 | 39 | 69 | 24 | 1,250,000$/2yrs |
TEAM AVERAGE | 100.00 | 74 | 52 | 81 | 74 | 76 | 78 | 76 | 77 | 78 | 72 | 70 | 56 | 56 | 39 | 47 | 71 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Todd Reirden | 82 | 73 | 98 | 70 | 73 | 73 | 68 | USA | 50 | 7 | 2,500,000$ |
General Manager | Chris Walsh |
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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 | Jan Jenik | 0 | C/LW/RW | 51 | 23 | 17 | 40 | 0 | 20 | 0 | 75 | 159 | 49 | 82 | 14.47% | 16 | 18.66 | 4 | 4 | 8 | 106 | 2 | 1 | 3 | 52 | 5 | 2 | 46.88% | 96 | 42 | 14 | 0 | 0 | 0.84 | 0 | 7 | |
2 | Pavel Gogolev | 0 | LW | 51 | 19 | 19 | 38 | 1 | 12 | 0 | 59 | 178 | 58 | 107 | 10.67% | 12 | 17.50 | 3 | 6 | 9 | 102 | 0 | 0 | 0 | 0 | 3 | 3 | 44.00% | 50 | 37 | 16 | 0 | 0 | 0.85 | 1 | 7 | |
3 | Nikolaj Ehlers | 0 | LW/RW | 51 | 21 | 16 | 37 | -2 | 0 | 0 | 29 | 161 | 57 | 92 | 13.04% | 19 | 17.98 | 6 | 4 | 10 | 102 | 1 | 0 | 1 | 19 | 1 | 1 | 15.91% | 44 | 51 | 11 | 0 | 1 | 0.81 | 0 | 1 | |
4 | Owen Tippett | 0 | LW/RW | 51 | 11 | 21 | 32 | -8 | 4 | 0 | 14 | 176 | 56 | 110 | 6.25% | 17 | 15.78 | 1 | 1 | 2 | 52 | 0 | 0 | 0 | 4 | 2 | 0 | 54.55% | 44 | 36 | 10 | 0 | 0 | 0.80 | 0 | 1 | |
5 | Quinton Byfield | 0 | C | 51 | 8 | 23 | 31 | 0 | 4 | 0 | 62 | 81 | 37 | 70 | 9.88% | 14 | 17.28 | 2 | 7 | 9 | 107 | 0 | 0 | 0 | 0 | 3 | 0 | 47.69% | 931 | 12 | 12 | 0 | 0 | 0.70 | 1 | 4 | |
6 | Adam Fox | 0 | D | 51 | 5 | 23 | 28 | -3 | 0 | 0 | 42 | 144 | 47 | 57 | 3.47% | 84 | 26.14 | 1 | 2 | 3 | 109 | 1 | 1 | 2 | 61 | 0 | 1 | 0.00% | 0 | 24 | 64 | 0 | 0 | 0.42 | 0 | 0 | |
7 | Nazem Kadri | 0 | C | 51 | 8 | 17 | 25 | 11 | 8 | 0 | 59 | 104 | 33 | 52 | 7.69% | 8 | 13.60 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 54.66% | 644 | 22 | 8 | 0 | 0 | 0.72 | 0 | 0 | |
8 | Dougie Hamilton | 0 | D | 51 | 5 | 18 | 23 | -6 | 34 | 0 | 128 | 110 | 55 | 43 | 4.55% | 58 | 22.31 | 1 | 3 | 4 | 103 | 0 | 0 | 0 | 2 | 1 | 0 | 0.00% | 0 | 29 | 43 | 0 | 0 | 0.40 | 0 | 1 | |
9 | Nate Schmidt | 0 | D | 51 | 3 | 20 | 23 | -1 | 0 | 0 | 13 | 81 | 22 | 27 | 3.70% | 69 | 21.90 | 1 | 5 | 6 | 104 | 0 | 2 | 2 | 59 | 0 | 1 | 0.00% | 0 | 15 | 39 | 0 | 0 | 0.41 | 0 | 0 | |
10 | Jack Roslovic | 0 | C/RW | 51 | 11 | 12 | 23 | -7 | 0 | 0 | 57 | 133 | 32 | 62 | 8.27% | 16 | 15.89 | 1 | 0 | 1 | 52 | 0 | 0 | 0 | 27 | 0 | 2 | 45.87% | 545 | 29 | 9 | 0 | 0 | 0.57 | 1 | 1 | |
11 | Yauheni Aksiantsiuk | 0 | LW/RW | 30 | 5 | 10 | 15 | 6 | 8 | 0 | 31 | 62 | 20 | 57 | 8.06% | 4 | 15.32 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 33.33% | 30 | 14 | 6 | 0 | 0 | 0.65 | 0 | 1 | |
12 | Ryan Merkley | 0 | D | 51 | 3 | 10 | 13 | -2 | 22 | 0 | 83 | 72 | 30 | 34 | 4.17% | 80 | 23.43 | 0 | 2 | 2 | 109 | 0 | 0 | 0 | 7 | 1 | 0 | 0.00% | 0 | 17 | 40 | 1 | 0 | 0.22 | 0 | 0 | |
13 | Cody Eakin | 0 | C | 51 | 8 | 2 | 10 | -9 | 0 | 0 | 24 | 73 | 16 | 49 | 10.96% | 5 | 8.88 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 8 | 1 | 1 | 55.98% | 184 | 26 | 7 | 0 | 0 | 0.44 | 0 | 0 | |
14 | Pierre Engvall | 0 | LW/RW | 45 | 2 | 7 | 9 | -9 | 6 | 0 | 17 | 38 | 11 | 22 | 5.26% | 23 | 12.89 | 0 | 0 | 0 | 0 | 0 | 2 | 2 | 47 | 0 | 0 | 45.16% | 31 | 5 | 12 | 0 | 0 | 0.31 | 0 | 0 | |
15 | Cedric Paquette | 0 | C/LW | 51 | 1 | 6 | 7 | -7 | 14 | 0 | 98 | 45 | 24 | 42 | 2.22% | 8 | 9.73 | 0 | 0 | 0 | 0 | 0 | 2 | 2 | 54 | 0 | 0 | 58.23% | 79 | 14 | 12 | 0 | 0 | 0.28 | 0 | 0 | |
16 | Michal Kempny | 0 | D | 51 | 0 | 4 | 4 | -10 | 6 | 0 | 29 | 45 | 23 | 14 | 0.00% | 46 | 13.55 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 57 | 0 | 0 | 0.00% | 0 | 2 | 22 | 0 | 0 | 0.12 | 0 | 0 | |
17 | Nikita Zadorov | 0 | D | 51 | 0 | 4 | 4 | -9 | 10 | 0 | 75 | 31 | 16 | 10 | 0.00% | 47 | 13.45 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 58 | 0 | 0 | 0.00% | 0 | 5 | 37 | 0 | 0 | 0.12 | 0 | 0 | |
18 | Frederik Gauthier | 0 | C/RW | 25 | 3 | 0 | 3 | -3 | 0 | 0 | 4 | 10 | 5 | 7 | 30.00% | 2 | 8.38 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 37.50% | 8 | 0 | 3 | 0 | 0 | 0.29 | 0 | 0 | |
19 | Alex Newhook | 0 | C | 6 | 1 | 1 | 2 | 3 | 0 | 0 | 2 | 3 | 3 | 3 | 33.33% | 1 | 14.97 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 66.67% | 3 | 0 | 1 | 1 | 0 | 0.45 | 1 | 1 | |
Team Total or Average | 871 | 137 | 230 | 367 | -55 | 148 | 0 | 901 | 1706 | 594 | 940 | 8.03% | 529 | 16.53 | 20 | 34 | 54 | 958 | 4 | 9 | 13 | 462 | 20 | 13 | 49.16% | 2689 | 380 | 366 | 2 | 1 | 0.51 | 4 | 24 |
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 | Connor Ingram | Maple Leafs | 23 | 13 | 8 | 2 | 0.915 | 2.92 | 1397 | 2 | 0 | 68 | 803 | 368 | 1 | 1 | 0.933 | 15 | 23 | 1 | 3 | 1 | 2 |
2 | Tyler Parsons | Maple Leafs | 4 | 2 | 1 | 1 | 0.913 | 2.54 | 213 | 0 | 0 | 9 | 104 | 51 | 0 | 0 | 0.667 | 3 | 4 | 38 | 0 | 0 | 0 |
Team Total or Average | 27 | 15 | 9 | 3 | 0.915 | 2.87 | 1611 | 2 | 0 | 77 | 907 | 419 | 1 | 1 | 0.889 | 18 | 27 | 39 | 3 | 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 |
# | 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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 7 | 7 | 0 | 2 | 0.500 | 7 | 12 | 19 | 0 | 0 | 2 | 5 | 0 | 0 | 68 | 28 | 23 | 17 | 0 | 66 | 20 | 8 | 32 | 6 | 1 | 16.67% | 4 | 1 | 75.00% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 42 | 25 | 44 | 17 | 32 | 17 | 50.0% | 10.3% | 89.4% | 99.7 | FUN | |
2 | 2 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 8 | 8 | 0 | 2 | 0.500 | 8 | 11 | 19 | 0 | 0 | 1 | 2 | 4 | 1 | 60 | 18 | 23 | 18 | 1 | 65 | 29 | 10 | 36 | 8 | 2 | 25.00% | 5 | 2 | 60.00% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 40 | 23 | 46 | 19 | 33 | 15 | 50.0% | 13.3% | 87.7% | 101.0 | FUN | |
3 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 7 | 7 | 0 | 2 | 0.500 | 7 | 14 | 21 | 0 | 0 | 3 | 2 | 2 | 0 | 65 | 26 | 16 | 23 | 0 | 76 | 21 | 6 | 38 | 8 | 3 | 37.50% | 3 | 1 | 66.67% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 40 | 22 | 45 | 17 | 33 | 17 | 40.0% | 10.8% | 90.8% | 101.6 | FUN | |
4 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 2 | 5 | 4 | 1.000 | 7 | 12 | 19 | 0 | 1 | 4 | 2 | 1 | 0 | 69 | 27 | 29 | 13 | 0 | 60 | 19 | 6 | 46 | 11 | 2 | 18.18% | 3 | 1 | 66.67% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 49 | 30 | 36 | 17 | 34 | 19 | 83.3% | 10.1% | 96.7% | 106.8 | LUCKY | |
5 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 3 | 2 | 2 | 1.000 | 5 | 9 | 14 | 0 | 0 | 2 | 2 | 1 | 0 | 32 | 14 | 9 | 9 | 0 | 44 | 6 | 8 | 23 | 3 | 1 | 33.33% | 4 | 1 | 75.00% | 1 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 19 | 10 | 23 | 8 | 16 | 8 | 66.7% | 15.6% | 93.2% | 108.8 | LUCKY | |
6 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 0 | 1 | 0 | 29 | 11 | 10 | 8 | 0 | 47 | 15 | 0 | 17 | 1 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 21 | 13 | 23 | 7 | 15 | 8 | 20.0% | 3.4% | 91.5% | 94.9 | DULL | |
7 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 4 | 4 | 0 | 2 | 0.500 | 4 | 8 | 12 | 0 | 0 | 0 | 2 | 2 | 0 | 85 | 21 | 23 | 41 | 0 | 52 | 24 | 8 | 34 | 2 | 0 | 0.00% | 4 | 1 | 75.00% | 1 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 44 | 28 | 43 | 17 | 32 | 15 | 57.1% | 4.7% | 92.3% | 97.0 | DULL | |
8 | 5 | 2 | 1 | 0 | 0 | 0 | 2 | 0 | 19 | 14 | 5 | 8 | 0.800 | 19 | 28 | 47 | 0 | 0 | 5 | 7 | 5 | 3 | 182 | 61 | 62 | 51 | 20 | 179 | 46 | 12 | 75 | 18 | 3 | 16.67% | 6 | 1 | 83.33% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 115 | 71 | 110 | 41 | 84 | 44 | 55.2% | 10.4% | 92.2% | 102.6 | LUCKY | |
9 | 3 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 16 | 8 | 8 | 4 | 0.667 | 16 | 26 | 42 | 0 | 0 | 5 | 4 | 7 | 0 | 120 | 36 | 42 | 42 | 0 | 108 | 29 | 8 | 57 | 7 | 3 | 42.86% | 4 | 2 | 50.00% | 2 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 65 | 41 | 62 | 25 | 51 | 26 | 68.4% | 13.3% | 92.6% | 105.9 | LUCKY | |
10 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 7 | 6 | 1 | 3 | 0.750 | 7 | 11 | 18 | 0 | 0 | 2 | 4 | 1 | 0 | 78 | 26 | 30 | 20 | 5 | 79 | 26 | 4 | 41 | 6 | 4 | 66.67% | 2 | 1 | 50.00% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 50 | 31 | 40 | 15 | 34 | 19 | 37.5% | 9.0% | 92.4% | 101.4 | LUCKY | |
11 | 3 | 0 | 2 | 0 | 0 | 0 | 0 | 1 | 4 | 11 | -7 | 1 | 0.167 | 4 | 6 | 10 | 1 | 0 | 1 | 1 | 2 | 0 | 107 | 49 | 31 | 25 | 4 | 113 | 31 | 18 | 51 | 6 | 0 | 0.00% | 9 | 0 | 100.00% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 66 | 40 | 67 | 26 | 51 | 24 | 26.7% | 3.7% | 90.3% | 94.0 | Unlucky | |
12 | 2 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 8 | 7 | 1 | 3 | 0.750 | 8 | 15 | 23 | 0 | 0 | 0 | 1 | 7 | 0 | 77 | 19 | 20 | 32 | 6 | 74 | 31 | 2 | 34 | 1 | 1 | 100.00% | 1 | 0 | 100.00% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 43 | 27 | 46 | 15 | 32 | 15 | 50.0% | 10.4% | 90.5% | 100.9 | FUN | |
13 | 4 | 0 | 3 | 0 | 0 | 0 | 0 | 1 | 9 | 15 | -6 | 1 | 0.125 | 9 | 14 | 23 | 1 | 0 | 3 | 5 | 1 | 0 | 152 | 45 | 62 | 45 | 3 | 140 | 42 | 14 | 83 | 6 | 0 | 0.00% | 7 | 0 | 100.00% | 1 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 89 | 54 | 86 | 32 | 69 | 34 | 37.5% | 5.9% | 89.3% | 95.2 | Unlucky | |
14 | 6 | 1 | 4 | 0 | 0 | 0 | 1 | 0 | 13 | 21 | -8 | 4 | 0.333 | 13 | 21 | 34 | 1 | 0 | 3 | 6 | 3 | 1 | 195 | 71 | 70 | 54 | 2 | 203 | 52 | 20 | 99 | 14 | 1 | 7.14% | 10 | 1 | 90.00% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 126 | 76 | 138 | 52 | 100 | 50 | 37.5% | 6.7% | 89.7% | 96.3 | Unlucky | |
15 | 4 | 1 | 3 | 0 | 0 | 0 | 0 | 0 | 10 | 16 | -6 | 2 | 0.250 | 10 | 15 | 25 | 0 | 0 | 8 | 1 | 1 | 0 | 138 | 54 | 40 | 44 | 0 | 130 | 41 | 10 | 66 | 15 | 1 | 6.67% | 5 | 2 | 60.00% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 88 | 51 | 83 | 33 | 67 | 35 | 39.1% | 7.2% | 87.7% | 94.9 | Unlucky | |
16 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 1 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 26 | 10 | 11 | 5 | 0 | 30 | 12 | 2 | 20 | 4 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 20 | 12 | 24 | 8 | 14 | 8 | 20.0% | 3.8% | 86.7% | 90.5 | Unlucky | |
17 | 4 | 0 | 3 | 0 | 0 | 0 | 0 | 1 | 9 | 14 | -5 | 1 | 0.125 | 9 | 14 | 23 | 0 | 0 | 3 | 5 | 1 | 0 | 133 | 47 | 49 | 37 | 2 | 136 | 58 | 12 | 83 | 5 | 0 | 0.00% | 6 | 2 | 66.67% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 89 | 54 | 84 | 33 | 70 | 35 | 42.9% | 6.8% | 89.7% | 96.5 | Unlucky | |
18 | 3 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 8 | 6 | 2 | 5 | 0.833 | 8 | 13 | 21 | 0 | 0 | 2 | 3 | 2 | 1 | 108 | 34 | 33 | 37 | 4 | 97 | 38 | 4 | 55 | 2 | 0 | 0.00% | 2 | 1 | 50.00% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 62 | 37 | 70 | 26 | 52 | 25 | 61.5% | 7.4% | 93.8% | 101.2 | DULL | |
19 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 2 | 3 | 4 | 1.000 | 5 | 10 | 15 | 0 | 0 | 0 | 3 | 2 | 0 | 71 | 30 | 26 | 15 | 0 | 67 | 17 | 2 | 24 | 5 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 44 | 28 | 39 | 17 | 36 | 18 | 71.4% | 7.0% | 97.0% | 104.1 | DULL | |
_Vs Division | 20 | 5 | 10 | 0 | 0 | 0 | 3 | 2 | 53 | 68 | -15 | 18 | 0.450 | 53 | 81 | 134 | 2 | 0 | 19 | 19 | 12 | 4 | 700 | 261 | 233 | 194 | 31 | 704 | 196 | 64 | 332 | 59 | 9 | 15.25% | 32 | 5 | 84.38% | 0 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 446 | 270 | 439 | 169 | 339 | 173 | 41.1% | 7.6% | 90.3% | 97.9 | Unlucky | |
_Vs Conference | 34 | 8 | 17 | 0 | 1 | 1 | 3 | 4 | 85 | 109 | -24 | 29 | 0.426 | 85 | 133 | 218 | 3 | 0 | 27 | 36 | 18 | 5 | 1190 | 427 | 414 | 333 | 40 | 1174 | 363 | 98 | 597 | 81 | 9 | 11.11% | 49 | 8 | 83.67% | 1 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 753 | 458 | 744 | 287 | 582 | 296 | 42.9% | 7.1% | 90.7% | 97.9 | Unlucky | |
_Since Last GM Reset | 51 | 17 | 23 | 0 | 2 | 2 | 3 | 4 | 148 | 159 | -11 | 50 | 0.490 | 148 | 242 | 390 | 3 | 1 | 44 | 56 | 43 | 6 | 1795 | 627 | 609 | 536 | 47 | 1766 | 557 | 154 | 914 | 128 | 22 | 17.19% | 77 | 17 | 77.92% | 5 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 1119 | 681 | 1117 | 432 | 866 | 441 | 47.0% | 8.2% | 91.0% | 99.2 | Unlucky | |
Total | 51 | 17 | 23 | 0 | 2 | 2 | 3 | 4 | 148 | 159 | -11 | 50 | 0.490 | 148 | 242 | 390 | 3 | 1 | 44 | 56 | 43 | 6 | 1795 | 627 | 609 | 536 | 47 | 1766 | 557 | 154 | 914 | 128 | 22 | 17.19% | 77 | 17 | 77.92% | 5 | 629 | 1296 | 48.53% | 594 | 1204 | 49.34% | 367 | 752 | 48.80% | 1119 | 681 | 1117 | 432 | 866 | 441 | 47.0% | 8.2% | 91.0% | 99.2 | Unlucky |
Puck Time | |
---|---|
Offensive Zone | 21 |
Neutral Zone | 16 |
Defensive Zone | 21 |
Puck Time | |
---|---|
Offensive Zone Start | 1296 |
Neutral Zone Start | 752 |
Defensive Zone Start | 1204 |
Puck Time | |
---|---|
With Puck | 30 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 1590 |
Faceoffs Lost | 1662 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 12.3 | 9.57 |
2nd Period | 24.2 | 20.31 |
3rd Period | 34.7 | 30.68 |
Overtime | 35.7 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.9 | 0.64 |
2nd Period | 2.0 | 1.65 |
3rd Period | 2.8 | 2.67 |
Overtime | 2.9 | 2.83 |
Even Strenght Goal | 118 |
---|---|
PP Goal | 22 |
PK Goal | 5 |
Empty Net Goal | 3 |
Home | Away | |
---|---|---|
Win | 11 | 11 |
Lost | 13 | 10 |
Overtime Lost | 2 | 4 |
PP Attempt | 128 |
---|---|
PP Goal | 22 |
PK Attempt | 77 |
PK Goal Against | 17 |
Home | |
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Shots For | 35.2 |
Shots Against | 34.6 |
Goals For | 2.9 |
Goals Against | 3.1 |
Hits | 17.9 |
Shots Blocked | 10.9 |
Pim | 3.0 |
Projected Total Cap Hit | 70,425,437$ |
Projected Cap Space | 16,074,563$ |
Retains And Buyout Cap Hit | 6,125,000$ |
Salary Cap To Date | 40,696,252$ |
Players In Salary Cap | 23 |
LTIR Players | 0 |
Player Name | Pos | Age | Cap Hit | 2015-2016 | 2016-2017 | 2017-2018 | 2018-2019 | 2019-2020 | 2020-2021 | 2021-2022 | 2022-2023 |
---|---|---|---|---|---|---|---|---|---|---|---|
Adam Fox | D | 24 | 9,900,000$ | 9,900,000$ | 9,900,000$ | 9,900,000$ | |||||
Alex Newhook ![]() | C | 21 | 925,000$ | 925,000$ | 925,000$ | 925,000$ | |||||
Cedric Paquette ![]() | C/LW | 28 | 1,250,000$ | 1,250,000$ | 1,250,000$ | ||||||
Cody Eakin ![]() | C | 30 | 1,750,000$ | 1,750,000$ | |||||||
Connor Ingram ![]() | RW | 24 | 685,000$ | 685,000$ | 685,000$ | 685,000$ | |||||
Dougie Hamilton | D | 28 | 7,000,000$ | 7,000,000$ | 7,000,000$ | ||||||
Frederik Gauthier ![]() | C/RW | 26 | 925,000$ | 925,000$ | |||||||
Jack Roslovic ![]() | C/RW | 25 | 1,150,000$ | 1,150,000$ | 1,150,000$ | 1,150,000$ | 1,150,000$ | ||||
Jan Jenik | C/LW/RW | 22 | 4,500,000$ | 4,500,000$ | 4,500,000$ | 4,500,000$ | |||||
Jaycob Megna ![]() | D | 29 | 1,450,000$ | 1,450,000$ | |||||||
Michal Kempny ![]() | D | 31 | 1,750,000$ | 1,750,000$ | 1,750,000$ | ||||||
Michal Neuvirth ![]() | C/LW | 33 | 919,191$ | 919,191$ | |||||||
Nate Schmidt | D | 30 | 3,000,000$ | 3,000,000$ | 3,000,000$ | 3,000,000$ | |||||
Nazem Kadri | C | 31 | 3,500,000$ | 3,500,000$ | 3,500,000$ | ||||||
Nikita Zadorov | D | 26 | 4,500,000$ | 4,500,000$ | |||||||
Nikolaj Ehlers | LW/RW | 26 | 6,000,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | |||
Owen Tippett ![]() | LW/RW | 23 | 3,750,000$ | 3,750,000$ | 3,750,000$ | 3,750,000$ | |||||
Pavel Gogolev ![]() | LW | 21 | 2,250,000$ | 2,250,000$ | 2,250,000$ | 2,250,000$ | 2,250,000$ | ||||
Pierre Engvall ![]() | LW/RW | 25 | 1,250,000$ | 1,250,000$ | 1,250,000$ | 1,250,000$ | 1,250,000$ | ||||
Quinton Byfield ![]() | C | 19 | 925,000$ | 925,000$ | |||||||
Ryan Merkley ![]() | D | 22 | 700,000$ | 700,000$ | 700,000$ | 700,000$ | |||||
Tyler Parsons ![]() | LW/RW | 24 | 1,250,000$ | 1,250,000$ | 1,250,000$ | ||||||
Yauheni Aksiantsiuk ![]() | LW/RW | 20 | 2,900,000$ | 2,900,000$ | 1,750,000$ | 1,750,000$ | 1,750,000$ | 1,750,000$ |
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Priority | Type | Description |
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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 |
---|---|---|---|---|---|
Alexander Holtz | 2 | 4 | |||
Alexander Pashin | 3 | 45 | |||
Brennan Othmann | 5 | 2 | |||
Carson Lambos | 5 | 16 | |||
Charles Beaudoin | 2 | 64 | |||
Colby Ambrosio | 3 | 77 | |||
Danila Klimovich | 4 | 16 | |||
Devon Levi | 3 | 67 | |||
Dylan Peterson | 3 | 55 | |||
Francesco Arcuri | 4 | 92 | |||
Ilya Solovyov | 3 | 79 | |||
Joshua Roy | 5 | 21 | |||
Kirill Gerasimyuk | 5 | 63 | |||
Logan Stankoven | 4 | 21 | |||
Nikita Novikov | 5 | 69 | |||
Niko Huuhtanen | 5 | 35 | |||
Sasha Pastujov | 5 | 13 | |||
Viktor Hurtig | 5 | 93 | |||
Viljami Marjala | 4 | 64 | |||
Xavier Simoneau | 4 | 35 | |||
Zachary Uens | 2 | 81 |
Date | Matchup | Result | Detail | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2022-02-18 | @ | Maple Leafs1,Senators3 | RECAP | |||||||||||
2022-02-20 | @ | Sabres1,Maple Leafs3 | RECAP | |||||||||||
2022-02-21 | @ | Senators3,Maple Leafs2 (SO) | RECAP | |||||||||||
2022-02-23 | @ | Maple Leafs1,Flyers4 | RECAP | |||||||||||
2022-02-25 | @ | Maple Leafs3,Bruins1 | RECAP | |||||||||||
2022-02-26 | @ | Canadiens3,Maple Leafs2 (SO) | RECAP | |||||||||||
2022-02-28 | @ | Sabres5,Maple Leafs2 | RECAP | |||||||||||
2022-03-01 | @ | Maple Leafs1,Red Wings4 | RECAP | |||||||||||
2022-03-04 | @ | Rangers3,Maple Leafs1 | RECAP | |||||||||||
2022-03-05 | @ | Maple Leafs1,Sabres5 | RECAP | |||||||||||
2022-03-08 | @ | Red Wings4,Maple Leafs2 | RECAP | |||||||||||
2022-03-09 | @ | Maple Leafs5,Canadiens3 | RECAP | |||||||||||
2022-03-11 | @ | Lightning4,Maple Leafs2 | RECAP | |||||||||||
2022-03-13 | @ | Maple Leafs8,Ducks2 | RECAP | |||||||||||
2022-03-14 | @ | Sabres3,Maple Leafs2 | RECAP | |||||||||||
2022-03-16 | @ | Maple Leafs1,Lightning2 (SO) | RECAP | |||||||||||
2022-03-18 | @ | Maple Leafs4,Golden Knights2 | RECAP | |||||||||||
2022-03-20 | @ | Bruins3,Maple Leafs5 | RECAP | |||||||||||
2022-03-22 | @ | Maple Leafs1,Stars4 | RECAP | |||||||||||
2022-03-23 | @ | Maple Leafs2,Blue Jackets1 | RECAP | |||||||||||
2022-03-25 | @ | Oilers6,Maple Leafs4 | RECAP | |||||||||||
2022-03-27 | @ | Maple Leafs3,Rangers4 (SO) | RECAP | |||||||||||
2022-03-28 | @ | Jets3,Maple Leafs2 | RECAP | |||||||||||
2022-03-31 | @ | Golden Knights0,Maple Leafs3 | RECAP | |||||||||||
2022-04-02 | @ | Red Wings5,Maple Leafs3 | RECAP | |||||||||||
2022-04-03 | @ | Maple Leafs4,Rangers5 | RECAP | |||||||||||
2022-04-05 | @ | Maple Leafs4,Kings3 (OT) | RECAP | |||||||||||
2022-04-06 | @ | Ducks4,Maple Leafs1 | RECAP | |||||||||||
2022-04-08 | @ | Rangers3,Maple Leafs1 | RECAP | |||||||||||
2022-04-10 | @ | Maple Leafs5,Avalanche3 | RECAP | |||||||||||
2022-04-12 | @ | Maple Leafs1,Flames4 | RECAP | |||||||||||
2022-04-13 | @ | Wild3,Maple Leafs5 | RECAP | |||||||||||
2022-04-16 | @ | Red Wings3,Maple Leafs4 | RECAP | |||||||||||
2022-04-18 | @ | Maple Leafs3,Blue Jackets1 | RECAP | |||||||||||
2022-04-19 | @ | Maple Leafs3,Wild4 (OT) | RECAP | |||||||||||
2022-04-21 | @ | Kings5,Maple Leafs4 | RECAP | |||||||||||
2022-04-22 | @ | Maple Leafs4,Bruins5 | RECAP | |||||||||||
2022-04-24 | @ | Sabres2,Maple Leafs3 (SO) | RECAP | |||||||||||
2022-04-26 | @ | Lightning4,Maple Leafs3 | RECAP | |||||||||||
2022-04-27 | @ | Maple Leafs7,Ducks2 | RECAP | |||||||||||
2022-04-29 | @ | Flames3,Maple Leafs6 | RECAP | |||||||||||
2022-05-02 | @ | Maple Leafs3,Lightning4 | RECAP | |||||||||||
2022-05-03 | @ | Maple Leafs1,Panthers2 (OT) | RECAP | |||||||||||
2022-05-04 | @ | Panthers3,Maple Leafs4 (OT) | RECAP | |||||||||||
2022-05-06 | @ | Bruins2,Maple Leafs3 (SO) | RECAP | |||||||||||
2022-05-08 | @ | Maple Leafs3,Oilers1 | RECAP | |||||||||||
2022-05-09 | @ | Maple Leafs2,Jets1 | RECAP | |||||||||||
2022-05-11 | @ | Bruins3,Maple Leafs4 (SO) | RECAP | |||||||||||
2022-05-13 | @ | Maple Leafs2,Sabres5 | RECAP | |||||||||||
2022-05-15 | @ | Panthers1,Maple Leafs3 | RECAP | |||||||||||
2022-05-16 | @ | Senators5,Maple Leafs1 | RECAP | |||||||||||
2022-05-18 | @ | |||||||||||||
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Trade Deadline --- Trades cant be done after this day is simulated! | ||||||||||||||
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2022-06-16 | @ | |||||||||||||
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Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
62,229,191$ | 6,125,000$ | 70,425,437$ | 16,074,563$ |
Arena | Goal Horn | About us | |
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![]() | Name | Scotiabank Arena | |
City | Toronto | ||
Capacity | 18000 | ||
Season Ticket Holders | 50% |
Arena Capacity - Ticket Price Attendance - % | |||||
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Arena Capacity | 6000 | 5000 | 2000 | 4000 | 1000 |
Ticket Price | 250$ | 125$ | 90$ | 75$ | 400$ |
Attendance | 150390 | 122832 | 49348 | 80799 | 24765 |
Attendance PCT | 96.40% | 94.49% | 94.90% | 77.69% | 95.25% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
15 | 16467 - 91.48% | 4,204,020$ | 109,304,531$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
62,229,191$ | 62,229,191$ | 0$ | 6,125,000$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
42,256,597$ | 429,167$ | 40,696,252$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
63,060,306$ | 55 | 446,408$ | 24,552,440$ |
Team Total Estimate | |||
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Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
26,110,478$ | 70,425,437$ | 532,794,291$ | 573,772,339$ |
Left Wing | Center | Right Wing | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Year | Round 1 | Round 2 | Round 3 | Round 4 |
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