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Cleveland Monsters 9-9-1, 19pts · 14th 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 | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Cole Koepke | 0 | LW/RW | 100.00 | 80 | 33 | 87 | 68 | 77 | 74 | 90 | 61 | 55 | 62 | 68 | 57 | 64 | 69 | 68 | 0 | 40 | 75 | 26 | 800,000$/2yrs | |||
Christian Fischer | 0 | C/LW/RW | 96.00 | 74 | 37 | 87 | 61 | 84 | 77 | 90 | 60 | 60 | 62 | 62 | 69 | 61 | 71 | 69 | 0 | 39 | 73 | 27 | 1,200,000$/2yrs | |||
Emil Bemstrom | 0 | C/RW | 100.00 | 60 | 33 | 94 | 63 | 75 | 75 | 82 | 62 | 59 | 64 | 63 | 58 | 63 | 67 | 66 | 0 | 43 | 73 | 25 | 775,000$/1yrs | |||
Jere Innala | 0 | LW | 100.00 | 64 | 37 | 88 | 61 | 65 | 71 | 85 | 63 | 36 | 59 | 67 | 67 | 63 | 68 | 67 | 0 | 43 | 73 | 26 | 870,000$/1yrs | |||
Sheldon Dries | 24 | C | 99.00 | 72 | 44 | 84 | 60 | 67 | 75 | 75 | 60 | 79 | 58 | 66 | 62 | 63 | 76 | 74 | 0 | 43 | 72 | 30 | 800,000$/2yrs | |||
Mathieu Olivier | 24 | RW | 99.00 | 87 | 69 | 57 | 57 | 84 | 74 | 84 | 60 | 57 | 60 | 59 | 70 | 60 | 71 | 67 | 0 | 44 | 72 | 27 | 875,000$/1yrs | |||
Sandis Vilmanis (R) | 0 | LW | 100.00 | 59 | 39 | 88 | 64 | 76 | 69 | 76 | 63 | 48 | 60 | 66 | 60 | 63 | 58 | 56 | 0 | 43 | 72 | 21 | 855,000$/3yrs | |||
Nathan Walker | 0 | LW | 100.00 | 77 | 44 | 85 | 55 | 70 | 73 | 81 | 60 | 75 | 60 | 60 | 65 | 60 | 76 | 75 | 0 | 46 | 71 | 30 | 900,000$/1yrs | |||
Liam Foudy | 19 | C | 100.00 | 66 | 33 | 95 | 60 | 76 | 75 | 77 | 60 | 58 | 60 | 60 | 64 | 60 | 65 | 65 | 0 | 31 | 71 | 24 | 950,000$/2yrs | |||
Noah Philp | 0 | C | 100.00 | 72 | 41 | 70 | 55 | 80 | 65 | 77 | 63 | 66 | 53 | 57 | 66 | 55 | 66 | 63 | 0 | 28 | 69 | 26 | 775,000$/1yrs | |||
Milo Roelens | 0 | C | 100.00 | 89 | 43 | 50 | 62 | 84 | 68 | 87 | 59 | 36 | 54 | 52 | 62 | 61 | 59 | 54 | 0 | 44 | 68 | 21 | 870,000$/2yrs | |||
Jaroslav Chmelar (R) | 0 | RW | 100.00 | 81 | 41 | 62 | 57 | 81 | 64 | 82 | 54 | 49 | 57 | 55 | 64 | 56 | 59 | 55 | 0 | 35 | 67 | 21 | 867,500$/3yrs | |||
Nick Blankenburg | 77 | D | 98.00 | 76 | 32 | 85 | 60 | 66 | 86 | 72 | 61 | 30 | 64 | 62 | 69 | 61 | 69 | 67 | 0 | 43 | 75 | 26 | 800,000$/2yrs | |||
Calle Rosen | 48 | D | 97.00 | 58 | 32 | 93 | 59 | 75 | 81 | 74 | 56 | 30 | 63 | 65 | 60 | 60 | 76 | 75 | 0 | 43 | 73 | 30 | 900,000$/1yrs | |||
Dennis Gilbert | 15 | D | 99.00 | 78 | 64 | 74 | 55 | 85 | 75 | 74 | 57 | 30 | 61 | 55 | 64 | 56 | 71 | 69 | 0 | 40 | 72 | 28 | 775,000$/1yrs | |||
Kevin Gravel | 0 | D | 100.00 | 68 | 33 | 93 | 55 | 84 | 79 | 69 | 51 | 30 | 54 | 50 | 63 | 50 | 79 | 78 | 0 | 40 | 69 | 32 | 800,000$/2yrs | |||
Kirill Kudryavtsev (R) | 0 | D | 100.00 | 56 | 38 | 92 | 62 | 77 | 66 | 60 | 57 | 30 | 55 | 48 | 62 | 60 | 56 | 55 | 0 | 33 | 68 | 20 | 850,000$/2yrs | |||
Cade Webber (R) | 0 | D | 100.00 | 72 | 41 | 73 | 51 | 89 | 62 | 90 | 52 | 30 | 53 | 50 | 67 | 52 | 63 | 60 | 0 | 43 | 67 | 23 | 875,000$/2yrs | |||
Alex Petrovic | 0 | D | 100.00 | 79 | 34 | 99 | 55 | 89 | 77 | 65 | 50 | 30 | 50 | 50 | 49 | 50 | 78 | 78 | 0 | 43 | 66 | 32 | 800,000$/2yrs | |||
Scratches | ||||||||||||||||||||||||||
Logan Brown | 22 | C | 100.00 | 64 | 34 | 90 | 57 | 90 | 73 | 70 | 58 | 71 | 60 | 58 | 55 | 58 | 69 | 68 | 0 | 21 | 69 | 26 | 950,000$/1yrs | |||
Chase Pearson | 12 | C | 100.00 | 70 | 40 | 74 | 49 | 82 | 61 | 73 | 65 | 77 | 51 | 49 | 68 | 50 | 68 | 65 | 0 | 21 | 66 | 27 | ||||
Shane Bowers | 15 | RW | 100.00 | 60 | 38 | 92 | 52 | 75 | 63 | 81 | 61 | 68 | 50 | 53 | 65 | 52 | 64 | 64 | 0 | 39 | 66 | 25 | 775,000$/2yrs | |||
Tyler Tullio (R) | 0 | RW | 100.00 | 64 | 38 | 84 | 54 | 70 | 62 | 85 | 59 | 66 | 52 | 54 | 63 | 53 | 59 | 57 | 0 | 34 | 66 | 22 | 823,333$/1yrs | |||
Matej Pekar (R) | 12 | LW | 100.00 | 77 | 41 | 63 | 50 | 74 | 60 | 71 | 62 | 66 | 54 | 45 | 65 | 49 | 62 | 59 | 0 | 21 | 65 | 24 | 850,000$/1yrs | |||
Daniel Torgersson (R) | 0 | LW/RW | 100.00 | 59 | 39 | 93 | 51 | 83 | 60 | 86 | 60 | 37 | 50 | 50 | 63 | 50 | 59 | 58 | 0 | 34 | 65 | 22 | 867,500$/1yrs | |||
Reece Newkirk | 0 | C | 100.00 | 68 | 39 | 77 | 50 | 70 | 59 | 71 | 61 | 67 | 50 | 48 | 64 | 49 | 61 | 58 | 0 | 21 | 64 | 23 | 775,000$/1yrs | |||
Ryan Francis (R) | 0 | C | 100.00 | 60 | 38 | 90 | 48 | 68 | 58 | 69 | 61 | 67 | 47 | 47 | 64 | 47 | 61 | 60 | 0 | 21 | 63 | 22 | ||||
Fabian Wagner (R) | 0 | C | 100.00 | 55 | 37 | 99 | 52 | 70 | 58 | 60 | 48 | 60 | 42 | 42 | 58 | 50 | 55 | 55 | 0 | 21 | 59 | 20 | 858,333$/2yrs | |||
Scott Morrow (R) | 0 | D | 100.00 | 61 | 33 | 99 | 55 | 78 | 86 | 65 | 50 | 30 | 50 | 50 | 58 | 50 | 60 | 60 | 0 | 21 | 65 | 22 | 916,667$/2yrs | |||
Dmitri Samorukov | 58 | D | 100.00 | 63 | 39 | 85 | 46 | 77 | 61 | 88 | 45 | 30 | 51 | 48 | 66 | 50 | 64 | 63 | 0 | 21 | 64 | 25 | 900,000$/1yrs |
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 ) |
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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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Colten Ellis | 45 | 100.00 | 76 | 69 | 72 | 74 | 79 | 75 | 77 | 76 | 75 | 75 | 76 | 64 | 64 | 0 | 44 | 78 | 24 | 800,000$/2yrs |
Isaac Poulter | 0 | 100.00 | 74 | 76 | 71 | 71 | 78 | 75 | 74 | 74 | 75 | 75 | 75 | 62 | 63 | 0 | 40 | 77 | 23 | 950,000$/1yrs |
Scratches | ||||||||||||||||||||
Eric Comrie | 0 | 98.00 | 67 | 70 | 70 | 74 | 66 | 66 | 70 | 76 | 72 | 74 | 70 | 73 | 77 | 0 | 38 | 75 | 29 | 825,000$/2yrs |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Lane Lambert | 93 | 84 | 82 | 95 | 78 | 74 | 86 | CAN | 60 | 5 | 1,000,000$ |
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 | Nathan Walker | Monsters (CBJ) | LW | 19 | 6 | 10 | 16 | 5 | 19 | 5 | 37 | 46 | 20 | 35 | 13.04% | 3 | 18.37 | 0 | 4 | 4 | 44 | 0 | 0 | 0 | 21 | 0 | 0 | 46.67% | 30 | 0 | 0 | 0 | 0 | 0.92 | 0 | 0 | |
2 | Jere Innala | Monsters (CBJ) | LW | 19 | 6 | 10 | 16 | 2 | 2 | 0 | 11 | 73 | 24 | 49 | 8.22% | 5 | 17.01 | 2 | 1 | 3 | 32 | 0 | 0 | 0 | 19 | 2 | 1 | 44.44% | 54 | 0 | 0 | 0 | 0 | 0.99 | 0 | 0 | |
3 | Sheldon Dries | Monsters (CBJ) | C | 19 | 6 | 8 | 14 | 4 | 8 | 0 | 31 | 67 | 22 | 30 | 8.96% | 3 | 16.95 | 1 | 3 | 4 | 45 | 0 | 0 | 0 | 27 | 0 | 0 | 59.08% | 435 | 0 | 0 | 0 | 0 | 0.87 | 1 | 1 | |
4 | Mathieu Olivier | Monsters (CBJ) | RW | 19 | 6 | 8 | 14 | -7 | 21 | 5 | 81 | 68 | 17 | 36 | 8.82% | 8 | 19.12 | 4 | 2 | 6 | 43 | 0 | 0 | 0 | 29 | 1 | 0 | 51.28% | 39 | 0 | 0 | 0 | 0 | 0.77 | 0 | 0 | |
5 | Nick Blankenburg | Monsters (CBJ) | D | 19 | 3 | 11 | 14 | -2 | 20 | 0 | 59 | 40 | 11 | 36 | 7.50% | 43 | 24.03 | 1 | 2 | 3 | 57 | 0 | 0 | 0 | 44 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.61 | 0 | 0 | |
6 | Christian Fischer | Monsters (CBJ) | C/LW/RW | 11 | 2 | 10 | 12 | -1 | 6 | 0 | 12 | 35 | 10 | 28 | 5.71% | 5 | 22.16 | 0 | 4 | 4 | 27 | 0 | 0 | 0 | 36 | 0 | 0 | 46.26% | 214 | 0 | 0 | 0 | 0 | 0.98 | 0 | 1 | |
7 | Dennis Gilbert | Monsters (CBJ) | D | 19 | 1 | 9 | 10 | -1 | 19 | 5 | 43 | 24 | 6 | 18 | 4.17% | 14 | 20.60 | 0 | 4 | 4 | 40 | 0 | 0 | 0 | 39 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.51 | 0 | 0 | |
8 | Emil Bemstrom | Monsters (CBJ) | C/RW | 19 | 3 | 6 | 9 | -5 | 0 | 0 | 4 | 42 | 12 | 48 | 7.14% | 2 | 19.22 | 2 | 2 | 4 | 53 | 0 | 0 | 0 | 39 | 0 | 0 | 49.31% | 290 | 0 | 0 | 0 | 0 | 0.49 | 0 | 0 | |
9 | Liam Foudy | Monsters (CBJ) | C | 16 | 5 | 3 | 8 | 4 | 2 | 0 | 6 | 29 | 7 | 20 | 17.24% | 1 | 13.35 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 46.69% | 257 | 0 | 0 | 0 | 0 | 0.75 | 0 | 0 | |
10 | Calle Rosen | Monsters (CBJ) | D | 19 | 3 | 4 | 7 | -4 | 8 | 0 | 10 | 32 | 7 | 16 | 9.38% | 21 | 24.34 | 2 | 1 | 3 | 56 | 0 | 0 | 0 | 51 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.30 | 0 | 0 | |
11 | Cole Koepke | Monsters (CBJ) | LW/RW | 20 | 2 | 5 | 7 | 4 | 4 | 0 | 24 | 26 | 8 | 24 | 7.69% | 1 | 14.25 | 1 | 0 | 1 | 18 | 0 | 0 | 0 | 22 | 1 | 0 | 51.35% | 37 | 0 | 0 | 0 | 0 | 0.49 | 0 | 1 | |
12 | Sandis Vilmanis | Monsters (CBJ) | LW | 19 | 3 | 4 | 7 | -1 | 0 | 0 | 1 | 49 | 10 | 43 | 6.12% | 4 | 12.24 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 43.75% | 96 | 0 | 0 | 0 | 0 | 0.60 | 0 | 0 | |
13 | Shane Bowers | Monsters (CBJ) | RW | 10 | 1 | 5 | 6 | 6 | 0 | 0 | 1 | 14 | 4 | 12 | 7.14% | 0 | 11.32 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 75.00% | 8 | 0 | 0 | 0 | 0 | 1.06 | 0 | 0 | |
14 | Tyler Tullio | Monsters (CBJ) | RW | 7 | 2 | 4 | 6 | 5 | 2 | 0 | 6 | 18 | 3 | 8 | 11.11% | 0 | 15.80 | 0 | 0 | 0 | 21 | 0 | 0 | 0 | 0 | 0 | 0 | 66.67% | 6 | 0 | 0 | 0 | 0 | 1.08 | 0 | 0 | |
15 | Kevin Gravel | Monsters (CBJ) | D | 19 | 0 | 4 | 4 | 4 | 0 | 0 | 21 | 16 | 3 | 9 | 0.00% | 27 | 17.14 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 45 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.25 | 0 | 0 | |
16 | Cade Webber | Monsters (CBJ) | D | 19 | 1 | 3 | 4 | 1 | 8 | 0 | 29 | 19 | 5 | 7 | 5.26% | 26 | 19.24 | 1 | 2 | 3 | 40 | 0 | 0 | 0 | 14 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.22 | 0 | 0 | |
17 | Milo Roelens | Monsters (CBJ) | C | 19 | 0 | 3 | 3 | -2 | 13 | 5 | 39 | 15 | 6 | 18 | 0.00% | 5 | 8.43 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 35.52% | 183 | 0 | 0 | 0 | 0 | 0.37 | 0 | 0 | |
18 | Daniel Torgersson | Monsters (CBJ) | LW/RW | 7 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 8 | 2 | 2 | 25.00% | 0 | 8.63 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2 | 0 | 0.00% | 4 | 0 | 0 | 0 | 0 | 0.66 | 0 | 0 | |
19 | Jaroslav Chmelar | Monsters (CBJ) | RW | 15 | 1 | 1 | 2 | -2 | 0 | 0 | 11 | 16 | 5 | 11 | 6.25% | 0 | 6.50 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 40.00% | 5 | 0 | 0 | 0 | 0 | 0.41 | 0 | 0 | |
20 | Alex Petrovic | Monsters (CBJ) | D | 19 | 1 | 1 | 2 | 3 | 16 | 0 | 37 | 5 | 2 | 8 | 20.00% | 6 | 14.95 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.14 | 0 | 0 | |
21 | Noah Philp | Monsters (CBJ) | C | 9 | 0 | 0 | 0 | -2 | 0 | 0 | 7 | 14 | 4 | 10 | 0.00% | 0 | 8.18 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 63.11% | 103 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
22 | Kirill Kudryavtsev | Monsters (CBJ) | D | 13 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0.19 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
Team Total or Average | 355 | 54 | 109 | 163 | 11 | 148 | 20 | 470 | 656 | 188 | 468 | 8.23% | 174 | 15.78 | 14 | 25 | 39 | 491 | 0 | 0 | 0 | 400 | 6 | 2 | 49.97% | 1761 | 0 | 0 | 0 | 0 | 0.58 | 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 | Colten Ellis | Monsters (CBJ) | 7 | 4 | 2 | 0 | 0.904 | 2.84 | 381 | 0 | 0 | 18 | 187 | 0 | 0 | 1 | 0.000 | 0 | 6 | 4 | 0 | 0 | 1 |
2 | Isaac Poulter | Monsters (CBJ) | 6 | 4 | 2 | 0 | 0.936 | 2.11 | 342 | 2 | 1 | 12 | 187 | 0 | 0 | 0 | 1.000 | 3 | 6 | 11 | 1 | 0 | 1 |
3 | Eric Comrie | Monsters (CBJ) | 7 | 1 | 5 | 1 | 0.899 | 3.27 | 422 | 0 | 0 | 23 | 227 | 0 | 0 | 0 | 0.000 | 0 | 7 | 4 | 0 | 0 | 1 |
Team Total or Average | 20 | 9 | 9 | 1 | 0.912 | 2.78 | 1146 | 2 | 1 | 53 | 601 | 0 | 0 | 1 | 1.000 | 3 | 19 | 19 | 1 | 0 | 3 |
Player Name | POS | Age | Cap Hit | 2020-21 | 2021-22 | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 |
---|---|---|---|---|---|---|---|---|---|---|---|
Alex Petrovic | D | 32 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Cade Webber | D | 23 | 875,000$ | 875,000$ | 875,000$ | RFA | |||||
Calle Rosen | D | 30 | 900,000$ | 900,000$ | UFA | ||||||
Chase Pearson | C | 27 | 0$ | UFA | |||||||
Christian Fischer | C/LW/RW | 27 | 1,200,000$ | 1,200,000$ | 1,200,000$ | UFA | |||||
Cole Koepke | LW/RW | 26 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Colten Ellis | G | 24 | 800,000$ | 800,000$ | 800,000$ | RFA | |||||
Daniel Torgersson | LW/RW | 22 | 867,500$ | 867,500$ | RFA | ||||||
Dennis Gilbert | D | 28 | 775,000$ | 775,000$ | UFA | ||||||
Dmitri Samorukov | D | 25 | 900,000$ | 900,000$ | RFA | ||||||
Emil Bemstrom | C/RW | 25 | 775,000$ | 775,000$ | RFA | ||||||
Eric Comrie | G | 29 | 825,000$ | 825,000$ | 825,000$ | UFA | |||||
Fabian Wagner | C | 20 | 858,333$ | 858,333$ | 858,333$ | RFA | |||||
Isaac Poulter | G | 23 | 950,000$ | 950,000$ | RFA | ||||||
Jaroslav Chmelar | RW | 21 | 867,500$ | 867,500$ | 867,500$ | 867,500$ | RFA | ||||
Jere Innala | LW | 26 | 870,000$ | 870,000$ | RFA | ||||||
Kevin Gravel | D | 32 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Kirill Kudryavtsev | D | 20 | 850,000$ | 850,000$ | 850,000$ | RFA | |||||
Liam Foudy | C | 24 | 950,000$ | 950,000$ | 950,000$ | RFA | |||||
Logan Brown | C | 26 | 950,000$ | 950,000$ | RFA | ||||||
Matej Pekar | LW | 24 | 850,000$ | 850,000$ | RFA | ||||||
Mathieu Olivier | RW | 27 | 875,000$ | 875,000$ | UFA | ||||||
Milo Roelens | C | 21 | 870,000$ | 870,000$ | 870,000$ | RFA | |||||
Nathan Walker | LW | 30 | 900,000$ | 900,000$ | UFA | ||||||
Nick Blankenburg | D | 26 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Noah Philp | C | 26 | 775,000$ | 775,000$ | RFA | ||||||
Reece Newkirk | C | 23 | 775,000$ | 775,000$ | RFA | ||||||
Ryan Francis | C | 22 | 0$ | RFA | |||||||
Sandis Vilmanis | LW | 21 | 855,000$ | 855,000$ | 855,000$ | 855,000$ | RFA | ||||
Scott Morrow | D | 22 | 916,667$ | 916,667$ | 916,667$ | RFA | |||||
Shane Bowers | RW | 25 | 775,000$ | 775,000$ | 775,000$ | RFA | |||||
Sheldon Dries | C | 30 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Tyler Tullio | RW | 22 | 823,333$ | 823,333$ | 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 | Comets | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 7 | 2 | 4 | 1.000 | 9 | 18 | 27 | 0 | 0 | 20 | 21 | 15 | 1 | 62 | 224 | 232 | 219 | 8 | 80 | 28 | 14 | 48 | 6 | 2 | 33.33% | 7 | 4 | 42.86% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 70.0% | 14.5% | 91.3% | 105.8 | LUCKY |
2 | Senators | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 3 | 2 | 1.000 | 4 | 8 | 12 | 0 | 0 | 20 | 21 | 15 | 1 | 25 | 224 | 232 | 219 | 8 | 27 | 7 | 8 | 21 | 4 | 2 | 50.00% | 3 | 0 | 100.00% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 66.7% | 16.0% | 96.3% | 112.3 | LUCKY |
3 | Wolves | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 20 | 21 | 15 | 1 | 40 | 224 | 232 | 219 | 8 | 22 | 10 | 9 | 20 | 2 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 20.0% | 2.5% | 81.8% | 84.3 | Unlucky |
4 | Griffins | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 7 | 8 | -1 | 2 | 0.500 | 7 | 13 | 20 | 1 | 0 | 20 | 21 | 15 | 1 | 76 | 224 | 232 | 219 | 8 | 66 | 12 | 14 | 53 | 4 | 2 | 50.00% | 7 | 1 | 85.71% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 41.7% | 9.2% | 87.9% | 97.1 | FUN |
5 | Rocket | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 4 | -1 | 0 | 0.000 | 3 | 5 | 8 | 0 | 0 | 20 | 21 | 15 | 1 | 27 | 224 | 232 | 219 | 8 | 29 | 7 | 8 | 31 | 2 | 1 | 50.00% | 4 | 1 | 75.00% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 40.0% | 11.1% | 86.2% | 97.3 | FUN |
6 | Bears | 4 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 13 | 10 | 3 | 4 | 0.500 | 13 | 25 | 38 | 0 | 1 | 20 | 21 | 15 | 1 | 148 | 224 | 232 | 219 | 8 | 132 | 43 | 43 | 98 | 10 | 2 | 20.00% | 17 | 3 | 82.35% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 61.1% | 8.8% | 92.4% | 101.2 | DULL |
7 | Crunch | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | -2 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 20 | 21 | 15 | 1 | 27 | 224 | 232 | 219 | 8 | 25 | 9 | 4 | 25 | 1 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 25.0% | 3.7% | 88.0% | 91.7 | Unlucky |
8 | Thunderbirds | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 3 | 4 | -1 | 1 | 0.500 | 3 | 6 | 9 | 0 | 0 | 20 | 21 | 15 | 1 | 50 | 224 | 232 | 219 | 8 | 37 | 7 | 6 | 24 | 5 | 2 | 40.00% | 3 | 0 | 100.00% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 20.0% | 6.0% | 89.2% | 95.2 | Unlucky |
9 | Americans | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 4 | 2 | 1.000 | 5 | 10 | 15 | 0 | 0 | 20 | 21 | 15 | 1 | 32 | 224 | 232 | 219 | 8 | 37 | 9 | 10 | 22 | 5 | 1 | 20.00% | 5 | 0 | 100.00% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 80.0% | 15.6% | 97.3% | 112.9 | LUCKY |
10 | IceHogs | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 2 | -1 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 20 | 21 | 15 | 1 | 27 | 224 | 232 | 219 | 8 | 36 | 7 | 10 | 27 | 2 | 0 | 0.00% | 4 | 1 | 75.00% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 50.0% | 3.7% | 94.4% | 98.1 | DULL |
11 | Moose | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 2 | -1 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 20 | 21 | 15 | 1 | 34 | 224 | 232 | 219 | 8 | 29 | 7 | 13 | 27 | 4 | 1 | 25.00% | 4 | 1 | 75.00% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 0.0% | 2.9% | 93.1% | 96.0 | DULL |
12 | Stars | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 5 | -2 | 0 | 0.000 | 3 | 6 | 9 | 0 | 0 | 20 | 21 | 15 | 1 | 46 | 224 | 232 | 219 | 8 | 36 | 11 | 4 | 24 | 3 | 0 | 0.00% | 2 | 1 | 50.00% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 42.9% | 6.5% | 86.1% | 92.6 | Unlucky |
13 | Marlies | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 4 | 7 | 0 | 0 | 20 | 21 | 15 | 1 | 44 | 224 | 232 | 219 | 8 | 31 | 12 | 2 | 25 | 5 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 60.0% | 6.8% | 93.5% | 100.4 | DULL |
14 | Silver Knights | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 2 | 1.000 | 3 | 6 | 9 | 0 | 0 | 20 | 21 | 15 | 1 | 43 | 224 | 232 | 219 | 8 | 15 | 7 | 7 | 24 | 4 | 1 | 25.00% | 1 | 0 | 100.00% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 66.7% | 7.0% | 93.3% | 100.3 | DULL |
_Vs Division | 7 | 5 | 3 | 0 | 0 | 0 | 1 | 0 | 23 | 21 | 2 | 12 | 0.857 | 23 | 45 | 68 | 0 | 1 | 20 | 21 | 15 | 1 | 250 | 224 | 232 | 219 | 8 | 234 | 81 | 66 | 166 | 18 | 4 | 22.22% | 25 | 7 | 72.00% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 57.6% | 9.2% | 91.0% | 100.2 | FUN | |
_Vs Conference | 14 | 7 | 5 | 0 | 0 | 1 | 1 | 0 | 48 | 40 | 8 | 17 | 0.607 | 48 | 91 | 139 | 1 | 1 | 20 | 21 | 15 | 1 | 491 | 224 | 232 | 219 | 8 | 464 | 134 | 109 | 347 | 42 | 12 | 28.57% | 49 | 9 | 81.63% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 53.7% | 9.8% | 91.4% | 101.2 | LUCKY | |
_Since Last GM Reset | 19 | 8 | 9 | 0 | 0 | 1 | 1 | 0 | 57 | 54 | 3 | 19 | 0.500 | 57 | 109 | 166 | 1 | 1 | 20 | 21 | 15 | 1 | 681 | 224 | 232 | 219 | 8 | 602 | 176 | 152 | 469 | 57 | 14 | 24.56% | 61 | 12 | 80.33% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 50.6% | 8.4% | 91.0% | 99.4 | Unlucky | |
Total | 19 | 8 | 9 | 0 | 0 | 1 | 1 | 0 | 57 | 54 | 3 | 19 | 0.500 | 57 | 109 | 166 | 1 | 1 | 20 | 21 | 15 | 1 | 681 | 224 | 232 | 219 | 8 | 602 | 176 | 152 | 469 | 57 | 14 | 24.56% | 61 | 12 | 80.33% | 0 | 364 | 725 | 50.21% | 343 | 676 | 50.74% | 163 | 323 | 50.46% | 443 | 295 | 440 | 148 | 265 | 132 | 50.6% | 8.4% | 91.0% | 99.4 | Unlucky |
Puck Time | |
---|---|
Offensive Zone | 23 |
Neutral Zone | 13 |
Defensive Zone | 23 |
Puck Time | |
---|---|
Offensive Zone Start | 725 |
Neutral Zone Start | 323 |
Defensive Zone Start | 676 |
Puck Time | |
---|---|
With Puck | 30 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 870 |
Faceoffs Lost | 854 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 11.8 | 9.57 |
2nd Period | 24.0 | 20.31 |
3rd Period | 35.5 | 30.68 |
Overtime | 35.9 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 1.1 | 0.64 |
2nd Period | 2.2 | 1.65 |
3rd Period | 2.9 | 2.67 |
Overtime | 3.0 | 2.83 |
Even Strenght Goal | 42 |
---|---|
PP Goal | 14 |
PK Goal | 0 |
Empty Net Goal | 1 |
Home | Away | |
---|---|---|
Win | 6 | 3 |
Lost | 3 | 6 |
Overtime Lost | 1 | 0 |
PP Attempt | 57 |
---|---|
PP Goal | 14 |
PK Attempt | 61 |
PK Goal Against | 12 |
Home | |
---|---|
Shots For | 35.8 |
Shots Against | 31.7 |
Goals For | 3.0 |
Goals Against | 2.8 |
Hits | 24.7 |
Shots Blocked | 9.3 |
Pim | 8.0 |
Date | Matchup | Result | Detail | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2024-10-09 | Bears | @ | Monsters | Bears0,Monsters4 | RECAP | |||||||||
2024-10-10 | Monsters | @ | Americans | Monsters5,Americans1 | RECAP | |||||||||
2024-10-12 | Bears | @ | Monsters | Bears3,Monsters4 | RECAP | |||||||||
2024-10-15 | Monsters | @ | Rocket | Monsters3,Rocket4 | RECAP | |||||||||
2024-10-16 | Stars | @ | Monsters | Stars5,Monsters3 | RECAP | |||||||||
2024-10-21 | Griffins | @ | Monsters | Griffins4,Monsters5 | RECAP | |||||||||
2024-10-25 | Monsters | @ | Silver Knights | Monsters3,Silver Knights1 | RECAP | |||||||||
2024-10-27 | Comets | @ | Monsters | Comets4,Monsters5 | RECAP | |||||||||
2024-10-29 | Monsters | @ | Griffins | Monsters2,Griffins4 | RECAP | |||||||||
2024-10-31 | Senators | @ | Monsters | Senators1,Monsters4 | RECAP | |||||||||
2024-11-01 | Monsters | @ | Comets | Monsters4,Comets3 | RECAP | |||||||||
2024-11-03 | Marlies | @ | Monsters | Marlies2,Monsters3 (SO) | RECAP | |||||||||
2024-11-06 | Monsters | @ | Crunch | Monsters1,Crunch3 | RECAP | |||||||||
2024-11-08 | Bears | @ | Monsters | Bears3,Monsters2 | RECAP | |||||||||
2024-11-12 | Monsters | @ | Bears | Monsters3,Bears4 | RECAP | |||||||||
2024-11-13 | Thunderbirds | @ | Monsters | Thunderbirds4,Monsters3 (OT) | RECAP | |||||||||
2024-11-15 | Monsters | @ | IceHogs | Monsters1,IceHogs2 | RECAP | |||||||||
2024-11-17 | Moose | @ | Monsters | Moose2,Monsters1 | RECAP | |||||||||
2024-11-19 | Monsters | @ | Wolves | Monsters1,Wolves4 | RECAP | |||||||||
2024-11-22 | Admirals | @ | Monsters | |||||||||||
2024-11-24 | Monsters | @ | Marlies | |||||||||||
2024-11-25 | Comets | @ | Monsters | |||||||||||
2024-11-27 | Monsters | @ | Crunch | |||||||||||
2024-11-29 | Monsters | @ | Penguins | |||||||||||
2024-12-01 | Bears | @ | Monsters | |||||||||||
2024-12-04 | Monsters | @ | Wolf Pack | |||||||||||
2024-12-05 | Griffins | @ | Monsters | |||||||||||
2024-12-09 | Monsters | @ | Senators | |||||||||||
2024-12-13 | Eagles | @ | Monsters | |||||||||||
2024-12-18 | Wolf Pack | @ | Monsters | |||||||||||
2024-12-24 | Phantoms | @ | Monsters | |||||||||||
2024-12-27 | Monsters | @ | Phantoms | |||||||||||
2024-12-28 | Checkers | @ | Monsters | |||||||||||
2024-12-31 | Monsters | @ | Senators | |||||||||||
2025-01-02 | Monsters | @ | Admirals | |||||||||||
2025-01-04 | Senators | @ | Monsters | |||||||||||
2025-01-06 | Marlies | @ | Monsters | |||||||||||
2025-01-08 | Monsters | @ | Condors | |||||||||||
2025-01-12 | Rocket | @ | Monsters | |||||||||||
2025-01-14 | Monsters | @ | Thunderbirds | |||||||||||
2025-01-16 | Monsters | @ | Silver Knights | |||||||||||
2025-01-17 | Roadrunners | @ | Monsters | |||||||||||
2025-01-23 | Penguins | @ | Monsters | |||||||||||
2025-01-25 | Monsters | @ | Thunderbirds | |||||||||||
2025-01-26 | Monsters | @ | Americans | |||||||||||
2025-01-28 | Islanders | @ | Monsters | |||||||||||
2025-01-30 | Monsters | @ | Islanders | |||||||||||
2025-02-01 | Gulls | @ | Monsters | |||||||||||
2025-02-04 | Monsters | @ | Americans | |||||||||||
2025-02-06 | Monsters | @ | Checkers | |||||||||||
2025-02-07 | Wranglers | @ | Monsters | |||||||||||
2025-02-11 | Monsters | @ | Reign | |||||||||||
2025-02-12 | Stars | @ | Monsters | |||||||||||
2025-02-15 | Wolf Pack | @ | Monsters | |||||||||||
2025-02-18 | Monsters | @ | Marlies | |||||||||||
2025-02-20 | Monsters | @ | Rocket | |||||||||||
2025-02-21 | Crunch | @ | Monsters | |||||||||||
2025-02-25 | Monsters | @ | Rocket | |||||||||||
2025-02-26 | Americans | @ | Monsters | |||||||||||
2025-02-28 | Monsters | @ | Canucks | |||||||||||
2025-03-01 | Monsters | @ | Bruins | |||||||||||
2025-03-03 | Crunch | @ | Monsters | |||||||||||
2025-03-06 | Stars | @ | Monsters | |||||||||||
Trade Deadline --- Trades can’t be done after this day is simulated! | ||||||||||||||
2025-03-10 | Monsters | @ | Wild | |||||||||||
2025-03-13 | Monsters | @ | Firebirds | |||||||||||
2025-03-14 | Monsters | @ | Griffins | |||||||||||
2025-03-16 | Americans | @ | Monsters | |||||||||||
2025-03-18 | Monsters | @ | Firebirds | |||||||||||
2025-03-19 | Monsters | @ | Comets | |||||||||||
2025-03-21 | Barracuda | @ | Monsters | |||||||||||
2025-03-26 | Bruins | @ | Monsters | |||||||||||
2025-04-04 | Rocket | @ | Monsters |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
2,485,333$ | 0$ | 0$ | 75,000,000$ |
Arena | About us | |
---|---|---|
Name | ||
City | Cleveland | |
Capacity | 3000 | |
Season Ticket Holders | 0% |
Arena Capacity - Ticket Price Attendance - % | |||||
---|---|---|---|---|---|
Arena Capacity | 2000 | 1000 | |||
Ticket Price | 35$ | 0$ | $ | $ | $ |
Attendance | 0 | 0 | |||
Attendance PCT | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
Income | |||||
---|---|---|---|---|---|
Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
26 | 0 - 0.00% | 0$ | 0$ | 3000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
2,485,333$ | 2,485,333$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
851,606$ | 13,656$ | 598,878$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 150 | 19,150$ | 2,604,400$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
2,604,400$ | 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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