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Full Scoreboard »» |
![]() | Toronto Marlies 13-1-1, 27pts · 2nd 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 | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Jani Nyman | 0 | LW/RW | 100.00 | 64 | 41 | 77 | 70 | 82 | 73 | 63 | 67 | 43 | 62 | 64 | 61 | 67 | 55 | 50 | 1 | 50 | 64 | 21 | 975,000$/2yrs | |||
Kevin Labanc (A) | 0 | LW/RW | 100.00 | 61 | 41 | 74 | 67 | 67 | 73 | 72 | 63 | 41 | 63 | 57 | 59 | 63 | 83 | 70 | 1 | 50 | 63 | 30 | 2,000,000$/3yrs | |||
Scott Sabourin | 0 | LW/RW | 100.00 | 69 | 72 | 54 | 66 | 76 | 74 | 73 | 65 | 41 | 62 | 60 | 60 | 64 | 73 | 64 | 1 | 50 | 63 | 33 | 1,000,000$/1yrs | |||
Ville Koivunen | 0 | LW/RW | 100.00 | 56 | 42 | 75 | 73 | 71 | 76 | 64 | 66 | 43 | 64 | 61 | 63 | 67 | 55 | 50 | 1 | 50 | 63 | 23 | 975,000$/1yrs | |||
Jake Lucchini | 0 | C | 100.00 | 54 | 43 | 71 | 66 | 61 | 73 | 71 | 66 | 64 | 64 | 60 | 54 | 64 | 64 | 56 | 1 | 50 | 62 | 31 | 1,000,000$/2yrs | |||
Georgii Merkulov | 0 | C/RW | 100.00 | 59 | 42 | 70 | 71 | 59 | 68 | 66 | 66 | 45 | 65 | 61 | 64 | 66 | 53 | 50 | 1 | 50 | 62 | 25 | 1,500,000$/2yrs | |||
Brett Seney | 0 | C/LW/RW | 100.00 | 53 | 47 | 62 | 69 | 53 | 72 | 70 | 65 | 44 | 65 | 58 | 58 | 64 | 63 | 58 | 1 | 50 | 61 | 30 | 1,000,000$/4yrs | |||
Dominic Toninato | 0 | C | 100.00 | 53 | 48 | 61 | 64 | 62 | 71 | 70 | 64 | 62 | 63 | 59 | 53 | 62 | 65 | 59 | 1 | 50 | 61 | 32 | 1,275,000$/2yrs | |||
Nikita Alexandrov | 0 | C | 100.00 | 57 | 42 | 72 | 67 | 64 | 67 | 65 | 66 | 52 | 65 | 60 | 55 | 64 | 53 | 50 | 1 | 50 | 61 | 25 | 1,000,000$/3yrs | |||
Gracyn Sawchyn (R) | 0 | C | 100.00 | 60 | 41 | 70 | 70 | 60 | 60 | 60 | 60 | 57 | 61 | 60 | 61 | 62 | 50 | 50 | 1 | 50 | 60 | 21 | 1,500,000$/4yrs | |||
Anthony Angello | 0 | C | 100.00 | 64 | 46 | 64 | 60 | 70 | 70 | 68 | 60 | 53 | 57 | 55 | 60 | 58 | 59 | 50 | 1 | 50 | 59 | 30 | 1,000,000$/1yrs | |||
Matyas Sapovaliv | 0 | C | 100.00 | 61 | 41 | 73 | 63 | 67 | 65 | 63 | 63 | 42 | 59 | 59 | 53 | 62 | 50 | 50 | 1 | 50 | 59 | 22 | 803,333$/1yrs | |||
Alec Regula | 0 | D | 100.00 | 59 | 51 | 60 | 68 | 82 | 78 | 70 | 64 | 40 | 60 | 57 | 67 | 63 | 73 | 62 | 1 | 50 | 66 | 25 | 1,800,000$/2yrs | |||
Vincent Iorio (A) | 0 | D | 100.00 | 63 | 41 | 77 | 70 | 82 | 77 | 67 | 66 | 40 | 61 | 58 | 70 | 65 | 59 | 53 | 1 | 50 | 66 | 23 | 975,000$/2yrs | |||
Trevor Carrick | 0 | D | 100.00 | 58 | 47 | 62 | 68 | 62 | 72 | 71 | 66 | 40 | 63 | 58 | 68 | 64 | 65 | 58 | 1 | 50 | 64 | 31 | 1,000,000$/1yrs | |||
William Wallinder | 0 | D | 100.00 | 66 | 42 | 73 | 65 | 69 | 65 | 63 | 63 | 40 | 61 | 53 | 67 | 60 | 51 | 50 | 1 | 50 | 62 | 23 | 975,000$/1yrs | |||
Maveric Lamoureux | 0 | D | 100.00 | 66 | 47 | 61 | 64 | 71 | 63 | 61 | 62 | 40 | 59 | 54 | 65 | 60 | 50 | 50 | 1 | 50 | 61 | 22 | 886,667$/1yrs | |||
Ronnie Attard (C) | 0 | D | 100.00 | 62 | 46 | 64 | 65 | 67 | 68 | 66 | 62 | 40 | 58 | 55 | 65 | 61 | 55 | 50 | 1 | 50 | 61 | 27 | 1,000,000$/3yrs | |||
| Scratches | ||||||||||||||||||||||||||
Jujhar Khaira | 0 | C | 100.00 | 58 | 44 | 65 | 57 | 69 | 70 | 68 | 58 | 56 | 54 | 52 | 53 | 56 | 65 | 55 | 1 | 50 | 57 | 31 | 1,250,000$/1yrs | |||
Sam Honzek (R) | 0 | LW | 100.00 | 62 | 41 | 67 | 62 | 62 | 58 | 56 | 60 | 42 | 58 | 55 | 59 | 59 | 50 | 50 | 1 | 50 | 57 | 21 | 975,000$/2yrs | |||
Chad Hillebrand | 0 | LW | 100.00 | 61 | 42 | 68 | 58 | 66 | 63 | 60 | 54 | 41 | 51 | 51 | 58 | 55 | 54 | 50 | 1 | 50 | 56 | 27 | ||||
Miko Matikka | 0 | RW | 100.00 | 61 | 41 | 71 | 57 | 69 | 61 | 59 | 57 | 41 | 52 | 51 | 52 | 55 | 50 | 50 | 1 | 50 | 55 | 22 | 870,000$/1yrs | |||
Carl Berglund | 0 | C | 100.00 | 55 | 40 | 66 | 56 | 58 | 60 | 58 | 53 | 52 | 52 | 50 | 53 | 53 | 53 | 50 | 1 | 50 | 54 | 26 | ||||
Ty Glover | 0 | C | 100.00 | 58 | 41 | 65 | 56 | 60 | 57 | 55 | 53 | 42 | 51 | 51 | 54 | 53 | 52 | 50 | 1 | 50 | 54 | 25 | ||||
Carsen Twarynski | 0 | LW | 100.00 | 55 | 41 | 64 | 54 | 58 | 60 | 57 | 53 | 41 | 51 | 51 | 52 | 53 | 55 | 50 | 1 | 50 | 53 | 28 | ||||
Jaydon Dureau | 0 | LW | 100.00 | 55 | 40 | 64 | 60 | 56 | 57 | 55 | 53 | 40 | 51 | 51 | 53 | 54 | 51 | 50 | 1 | 50 | 53 | 25 | 975,000$/1yrs | |||
Andrew Gibson (R) | 0 | D | 100.00 | 64 | 50 | 60 | 64 | 69 | 64 | 62 | 62 | 40 | 60 | 60 | 63 | 60 | 50 | 50 | 1 | 50 | 61 | 21 | 1,400,000$/4yrs | |||
Scooter Brickey | 0 | D | 100.00 | 65 | 41 | 69 | 61 | 70 | 64 | 61 | 55 | 40 | 51 | 50 | 66 | 55 | 55 | 50 | 1 | 50 | 60 | 27 | 1,000,000$/1yrs | |||
Lassi Thomson (R) | 0 | D | 100.00 | 56 | 43 | 60 | 68 | 60 | 63 | 61 | 62 | 40 | 54 | 61 | 63 | 64 | 52 | 50 | 1 | 50 | 60 | 25 | 2,200,000$/3yrs | |||
Tommy Miller | 0 | D | 100.00 | 61 | 42 | 72 | 65 | 64 | 68 | 65 | 59 | 40 | 52 | 52 | 66 | 58 | 55 | 50 | 1 | 50 | 60 | 27 | 1,000,000$/1yrs | |||
Tyson Feist | 0 | D | 100.00 | 64 | 42 | 62 | 64 | 68 | 62 | 59 | 53 | 40 | 51 | 50 | 65 | 56 | 53 | 50 | 1 | 50 | 59 | 25 | ||||
Anton Malmström | 0 | D | 100.00 | 63 | 40 | 70 | 61 | 67 | 62 | 59 | 55 | 40 | 52 | 52 | 62 | 56 | 52 | 50 | 1 | 50 | 58 | 26 | ||||
Dillon Heatherington | 0 | D | 100.00 | 57 | 42 | 60 | 54 | 65 | 65 | 64 | 54 | 40 | 51 | 51 | 57 | 53 | 65 | 55 | 1 | 50 | 57 | 31 | 1,000,000$/1yrs | |||
Garrett Pyke | 0 | D | 100.00 | 54 | 40 | 64 | 57 | 57 | 57 | 55 | 52 | 40 | 50 | 50 | 55 | 52 | 53 | 50 | 1 | 50 | 54 | 26 | ||||
| Priority | Type | Description |
|---|---|---|
| 1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
| 2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
| 3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig) |
| 4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
| 5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter. |
| 6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
| 7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
| 8 | ? | Wildcard for a single, non-space character. |
| 8 | * | Wildcard for zero or more non-space characters. |
| 9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
| 10 | text | Any text entered in the filter will match text found within the column |
| Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Joel Blomqvist | 0 | 100.00 | 74 | 65 | 67 | 70 | 70 | 71 | 72 | 71 | 73 | 71 | 62 | 52 | 50 | 1 | 50 | 64 | 24 | 1,400,000$/3yrs |
Nikke Kokko | 0 | 100.00 | 67 | 61 | 66 | 65 | 67 | 68 | 72 | 68 | 70 | 67 | 57 | 50 | 50 | 1 | 50 | 62 | 22 | 975,000$/2yrs |
| Scratches | ||||||||||||||||||||
Magnus Chrona | 0 | 100.00 | 67 | 64 | 66 | 72 | 68 | 67 | 69 | 66 | 67 | 67 | 56 | 53 | 50 | 1 | 50 | 62 | 25 | 975,000$/1yrs |
Jiri Patera | 0 | 100.00 | 69 | 64 | 66 | 67 | 67 | 66 | 68 | 65 | 67 | 67 | 59 | 55 | 50 | 1 | 50 | 61 | 27 | 1,000,000$/1yrs |
Domenic DiVincentiis | 0 | 100.00 | 66 | 61 | 65 | 65 | 66 | 67 | 70 | 66 | 68 | 66 | 55 | 50 | 50 | 1 | 50 | 60 | 22 | 975,000$/1yrs |
Jakub Malek | 0 | 100.00 | 66 | 58 | 64 | 61 | 64 | 65 | 67 | 64 | 66 | 65 | 56 | 52 | 50 | 1 | 50 | 59 | 24 | 2,000,000$/1yrs |
| Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Marco Sturm | 81 | 79 | 82 | 76 | 65 | 59 | 1 | GER | 47 | 4 | 500,000$ |
| General Manager |
|---|
| 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 | Jani Nyman | Marlies (TOR) | LW/RW | 15 | 7 | 9 | 16 | 4 | 2 | 0 | 18 | 49 | 18 | 32 | 14.29% | 3 | 17.53 | 4 | 3 | 7 | 0 | 0 | 0 | 0 | 0 | 0 | 52.63% | 0 | 0 | 1.07 | 0 | 2 | 1.16 | |||
| 2 | Georgii Merkulov | Marlies (TOR) | C/RW | 15 | 5 | 9 | 14 | 10 | 10 | 0 | 23 | 58 | 19 | 37 | 8.62% | 9 | 17.10 | 1 | 3 | 4 | 1 | 0 | 1 | 7 | 2 | 0 | 48.39% | 0 | 0 | 0.93 | 0 | 0 | 1.17 | |||
| 3 | Jake Lucchini | Marlies (TOR) | C | 15 | 5 | 8 | 13 | 4 | 9 | 5 | 26 | 35 | 8 | 28 | 14.29% | 8 | 17.39 | 1 | 3 | 4 | 0 | 0 | 0 | 0 | 1 | 0 | 54.20% | 0 | 0 | 0.87 | 0 | 0 | 0.88 | |||
| 4 | Nikita Alexandrov | Marlies (TOR) | C | 15 | 5 | 7 | 12 | 12 | 0 | 0 | 14 | 57 | 24 | 36 | 8.77% | 4 | 15.96 | 1 | 1 | 2 | 0 | 0 | 0 | 3 | 3 | 0 | 51.49% | 0 | 0 | 0.80 | 0 | 2 | 1.23 | |||
| 5 | Ville Koivunen | Marlies (TOR) | LW/RW | 15 | 4 | 8 | 12 | 4 | 10 | 10 | 20 | 49 | 14 | 38 | 8.16% | 2 | 17.93 | 1 | 4 | 5 | 0 | 0 | 0 | 10 | 1 | 1 | 46.67% | 0 | 0 | 0.80 | 0 | 2 | 0.88 | |||
| 6 | Kevin Labanc | Marlies (TOR) | LW/RW | 15 | 7 | 3 | 10 | 11 | 4 | 0 | 29 | 35 | 8 | 20 | 20.00% | 6 | 17.03 | 0 | 1 | 1 | 0 | 0 | 0 | 2 | 1 | 2 | 30.00% | 0 | 0 | 0.67 | 0 | 0 | 0.95 | |||
| 7 | Alec Regula | Marlies (TOR) | D | 15 | 2 | 7 | 9 | 13 | 7 | 5 | 23 | 20 | 4 | 13 | 10.00% | 16 | 22.92 | 1 | 1 | 2 | 0 | 0 | 0 | 17 | 0 | 0 | 0.00% | 0 | 0 | 0.60 | 0 | 0 | 0.81 | |||
| 8 | Brett Seney | Marlies (TOR) | C/LW/RW | 15 | 0 | 8 | 8 | 5 | 2 | 0 | 16 | 44 | 17 | 36 | 0.00% | 2 | 12.59 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 0 | 0 | 0.00% | 0 | 0 | 0.53 | 0 | 0 | 0.76 | |||
| 9 | Scott Sabourin | Marlies (TOR) | LW/RW | 15 | 5 | 3 | 8 | 3 | 4 | 0 | 43 | 33 | 11 | 23 | 15.15% | 1 | 13.02 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 20.00% | 0 | 0 | 0.53 | 1 | 1 | 0.68 | |||
| 10 | Dominic Toninato | Marlies (TOR) | C | 15 | 5 | 3 | 8 | 4 | 6 | 0 | 10 | 26 | 11 | 17 | 19.23% | 1 | 13.00 | 0 | 0 | 0 | 0 | 0 | 0 | 11 | 3 | 0 | 50.00% | 0 | 0 | 0.53 | 0 | 0 | 0.58 | |||
| 11 | Matyas Sapovaliv | Marlies (TOR) | C | 15 | 5 | 3 | 8 | 6 | 0 | 0 | 20 | 34 | 10 | 13 | 14.71% | 3 | 11.20 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 36.51% | 0 | 0 | 0.53 | 0 | 0 | 0.74 | |||
| 12 | Maveric Lamoureux | Marlies (TOR) | D | 15 | 0 | 8 | 8 | 6 | 4 | 0 | 17 | 16 | 7 | 2 | 0.00% | 8 | 17.82 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 0 | 0 | 0.00% | 0 | 0 | 0.53 | 0 | 0 | 0.55 | |||
| 13 | Trevor Carrick | Marlies (TOR) | D | 15 | 0 | 7 | 7 | 6 | 9 | 5 | 27 | 10 | 10 | 8 | 0.00% | 11 | 19.48 | 0 | 1 | 1 | 0 | 0 | 0 | 11 | 0 | 0 | 0.00% | 0 | 0 | 0.47 | 0 | 0 | 0.47 | |||
| 14 | Gracyn Sawchyn | Marlies (TOR) | C | 15 | 2 | 3 | 5 | 3 | 0 | 0 | 14 | 32 | 12 | 22 | 6.25% | 1 | 13.78 | 0 | 0 | 0 | 0 | 1 | 1 | 20 | 0 | 0 | 43.56% | 0 | 0 | 0.33 | 0 | 0 | 0.50 | |||
| 15 | Vincent Iorio | Marlies (TOR) | D | 15 | 1 | 4 | 5 | 13 | 0 | 0 | 16 | 18 | 7 | 11 | 5.56% | 16 | 23.13 | 1 | 0 | 1 | 0 | 0 | 0 | 18 | 0 | 0 | 0.00% | 0 | 0 | 0.33 | 0 | 0 | 0.68 | |||
| 16 | Anthony Angello | Marlies (TOR) | C | 15 | 3 | 0 | 3 | 7 | 0 | 0 | 24 | 14 | 5 | 8 | 21.43% | 1 | 12.33 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 1 | 1 | 38.46% | 0 | 0 | 0.20 | 0 | 0 | 0.43 | |||
| 17 | William Wallinder | Marlies (TOR) | D | 15 | 1 | 1 | 2 | 4 | 5 | 5 | 24 | 18 | 3 | 6 | 5.56% | 11 | 20.40 | 1 | 0 | 1 | 0 | 0 | 0 | 20 | 0 | 0 | 0.00% | 0 | 0 | 0.13 | 0 | 0 | 0.28 | |||
| 18 | Ronnie Attard | Marlies (TOR) | D | 15 | 0 | 2 | 2 | 7 | 4 | 0 | 14 | 14 | 6 | 7 | 0.00% | 13 | 17.02 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0.13 | 0 | 0 | 0.33 | |||
| Team Total or Average | 270 | 57 | 93 | 150 | 122 | 76 | 30 | 378 | 562 | 194 | 357 | 10.14% | 116 | 16.65 | 11 | 17 | 28 | 259 | 1 | 1 | 2 | 151 | 12 | 6 | 48.82% | 805 | 113 | 86 | 0 | 0 | 0.67 | 1 | 7 |
| 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 | Marlies (TOR) | 10 | 9 | 1 | 0 | 0.935 | 1.59 | 605 | 0 | 1 | 16 | 245 | 134 | 3 | 0 | 1.000 | 4 | 10 | 5 | 1 | 1 | 1 |
| 2 | Nikke Kokko | Marlies (TOR) | 5 | 4 | 0 | 1 | 0.889 | 1.97 | 305 | 0 | 2 | 10 | 90 | 50 | 2 | 0 | 0.667 | 3 | 5 | 10 | 0 | 0 | 2 |
| Team Total or Average | 15 | 13 | 1 | 1 | 0.922 | 1.71 | 910 | 0 | 3 | 26 | 335 | 184 | 5 | 0 | 0.857 | 7 | 15 | 15 | 1 | 1 | 3 |
| 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 | 25 | 1,800,000$ | 1,800,000$ | 1,800,000$ | UFA | |||||
| Andrew Gibson | D | 21 | 1,400,000$ | 1,400,000$ | 1,400,000$ | 1,400,000$ | 1,400,000$ | ||||
| Anthony Angello | C | 30 | 1,000,000$ | 1,000,000$ | UFA | ||||||
| Anton Malmström | D | 26 | 0$ | ||||||||
| Brett Seney | C/LW/RW | 30 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | |||
| Carl Berglund | C | 26 | 0$ | ||||||||
| Carsen Twarynski | LW | 28 | 0$ | UFA | |||||||
| Chad Hillebrand | LW | 27 | 0$ | UFA | |||||||
| Dillon Heatherington | D | 31 | 1,000,000$ | 1,000,000$ | UFA | ||||||
| Domenic DiVincentiis | G | 22 | 975,000$ | 975,000$ | RFA | ||||||
| Dominic Toninato | C | 32 | 1,275,000$ | 1,275,000$ | 1,275,000$ | UFA | |||||
| Garrett Pyke | D | 26 | 0$ | UFA | |||||||
| Georgii Merkulov | C/RW | 25 | 1,500,000$ | 1,500,000$ | 1,500,000$ | UFA | |||||
| Gracyn Sawchyn | C | 21 | 1,500,000$ | 1,500,000$ | 1,500,000$ | 1,500,000$ | 1,500,000$ | ||||
| Jake Lucchini | C | 31 | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | |||||
| Jakub Malek | G | 24 | 2,000,000$ | 2,000,000$ | |||||||
| Jani Nyman | LW/RW | 21 | 975,000$ | 975,000$ | 975,000$ | RFA | |||||
| Jaydon Dureau | LW | 25 | 975,000$ | 975,000$ | |||||||
| Jiri Patera | G | 27 | 1,000,000$ | 1,000,000$ | UFA | ||||||
| Joel Blomqvist | G | 24 | 1,400,000$ | 1,400,000$ | 1,400,000$ | 1,400,000$ | |||||
| Jujhar Khaira | C | 31 | 1,250,000$ | 1,250,000$ | UFA | ||||||
| Kevin Labanc | LW/RW | 30 | 2,000,000$ | 2,000,000$ | 2,000,000$ | 2,000,000$ | UFA | ||||
| Lassi Thomson | D | 25 | 2,200,000$ | 2,200,000$ | 2,200,000$ | 2,200,000$ | UFA | ||||
| Magnus Chrona | G | 25 | 975,000$ | 975,000$ | |||||||
| Matyas Sapovaliv | C | 22 | 803,333$ | 975,000$ | RFA | ||||||
| Maveric Lamoureux | D | 22 | 886,667$ | 975,000$ | RFA | ||||||
| Miko Matikka | RW | 22 | 870,000$ | 975,000$ | RFA | ||||||
| Nikita Alexandrov | C | 25 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | ||||
| Nikke Kokko | G | 22 | 975,000$ | 975,000$ | 975,000$ | RFA | |||||
| Ronnie Attard | D | 27 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | ||||
| Sam Honzek | LW | 21 | 975,000$ | 975,000$ | 975,000$ | RFA | |||||
| Scooter Brickey | D | 27 | 1,000,000$ | 1,000,000$ | UFA | ||||||
| Scott Sabourin | LW/RW | 33 | 1,000,000$ | 1,000,000$ | UFA | ||||||
| Tommy Miller | D | 27 | 1,000,000$ | 1,000,000$ | UFA | ||||||
| Trevor Carrick | D | 31 | 1,000,000$ | 1,000,000$ | UFA | ||||||
| Ty Glover | C | 25 | 0$ | ||||||||
| Tyson Feist | D | 25 | 0$ | ||||||||
| Ville Koivunen | LW/RW | 23 | 975,000$ | 975,000$ | RFA | ||||||
| Vincent Iorio | D | 23 | 975,000$ | 975,000$ | 975,000$ | ||||||
| William Wallinder | D | 23 | 975,000$ | 975,000$ |
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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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Bruins | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 6 | 7 | -1 | 1 | 0.500 | 6 | 10 | 16 | 0 | 0 | 8 | 25 | 23 | 2 | 38 | 170 | 214 | 176 | 9 | 32 | 12 | 6 | 22 | 3 | 1 | 33.33% | 3 | 0 | 100.00% | 0 | 183 | 371 | 49.33% | 107 | 231 | 46.32% | 103 | 196 | 52.55% | 352 | 206 | 265 | 140 | 292 | 140 | 41.7% | 15.8% | 78.1% | 93.9 | FUN |
| 2 | Americans | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 4 | -2 | 0 | 0.000 | 2 | 4 | 6 | 0 | 0 | 8 | 25 | 23 | 2 | 41 | 170 | 214 | 176 | 9 | 27 | 8 | 0 | 21 | 2 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 183 | 371 | 49.33% | 107 | 231 | 46.32% | 103 | 196 | 52.55% | 352 | 206 | 265 | 140 | 292 | 140 | 33.3% | 4.9% | 85.2% | 90.1 | Unlucky |
| 3 | Monsters | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 2 | 5 | 4 | 1.000 | 7 | 11 | 18 | 0 | 1 | 8 | 25 | 23 | 2 | 68 | 170 | 214 | 176 | 9 | 47 | 15 | 8 | 38 | 6 | 3 | 50.00% | 4 | 2 | 50.00% | 0 | 183 | 371 | 49.33% | 107 | 231 | 46.32% | 103 | 196 | 52.55% | 352 | 206 | 265 | 140 | 292 | 140 | 100.0% | 10.3% | 95.7% | 106.0 | LUCKY |
| 4 | Condors | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 4 | 7 | 0 | 0 | 8 | 25 | 23 | 2 | 42 | 170 | 214 | 176 | 9 | 23 | 10 | 2 | 26 | 1 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 183 | 371 | 49.33% | 107 | 231 | 46.32% | 103 | 196 | 52.55% | 352 | 206 | 265 | 140 | 292 | 140 | 60.0% | 7.1% | 91.3% | 98.4 | DULL |
| 5 | Rocket | 3 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 16 | 3 | 13 | 6 | 1.000 | 16 | 25 | 41 | 0 | 1 | 8 | 25 | 23 | 2 | 118 | 170 | 214 | 176 | 9 | 57 | 30 | 20 | 79 | 6 | 3 | 50.00% | 5 | 1 | 80.00% | 0 | 183 | 371 | 49.33% | 107 | 231 | 46.32% | 103 | 196 | 52.55% | 352 | 206 | 265 | 140 | 292 | 140 | 86.7% | 13.6% | 94.7% | 108.3 | LUCKY |
| 6 | Admirals | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 3 | 6 | 4 | 1.000 | 9 | 16 | 25 | 0 | 0 | 8 | 25 | 23 | 2 | 75 | 170 | 214 | 176 | 9 | 57 | 12 | 7 | 54 | 5 | 1 | 20.00% | 1 | 0 | 100.00% | 0 | 183 | 371 | 49.33% | 107 | 231 | 46.32% | 103 | 196 | 52.55% | 352 | 206 | 265 | 140 | 292 | 140 | 72.7% | 12.0% | 94.7% | 106.7 | LUCKY |
| 7 | Comets | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 2 | 3 | 4 | 1.000 | 5 | 7 | 12 | 0 | 0 | 8 | 25 | 23 | 2 | 64 | 170 | 214 | 176 | 9 | 41 | 13 | 16 | 57 | 4 | 0 | 0.00% | 3 | 1 | 66.67% | 1 | 183 | 371 | 49.33% | 107 | 231 | 46.32% | 103 | 196 | 52.55% | 352 | 206 | 265 | 140 | 292 | 140 | 83.3% | 7.8% | 95.1% | 102.9 | DULL |
| 8 | Phantoms | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 4 | 2 | 1.000 | 4 | 7 | 11 | 0 | 1 | 8 | 25 | 23 | 2 | 39 | 170 | 214 | 176 | 9 | 11 | 4 | 5 | 29 | 3 | 1 | 33.33% | 0 | 0 | 0.00% | 0 | 183 | 371 | 49.33% | 107 | 231 | 46.32% | 103 | 196 | 52.55% | 352 | 206 | 265 | 140 | 292 | 140 | 100.0% | 10.3% | 100.0% | 110.3 | LUCKY |
| 9 | Roadrunners | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 4 | 3 | 1 | 2 | 1.000 | 4 | 6 | 10 | 0 | 0 | 8 | 25 | 23 | 2 | 36 | 170 | 214 | 176 | 9 | 11 | 3 | 12 | 24 | 2 | 2 | 100.00% | 6 | 1 | 83.33% | 0 | 183 | 371 | 49.33% | 107 | 231 | 46.32% | 103 | 196 | 52.55% | 352 | 206 | 265 | 140 | 292 | 140 | 50.0% | 11.1% | 72.7% | 83.8 | FUN |
| 10 | Crunch | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 1 | 1 | 2 | 1.000 | 2 | 3 | 5 | 0 | 0 | 8 | 25 | 23 | 2 | 41 | 170 | 214 | 176 | 9 | 29 | 9 | 0 | 28 | 3 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 183 | 371 | 49.33% | 107 | 231 | 46.32% | 103 | 196 | 52.55% | 352 | 206 | 265 | 140 | 292 | 140 | 66.7% | 4.9% | 96.6% | 101.4 | DULL |
| _Vs Division | 5 | 8 | 1 | 0 | 0 | 0 | 0 | 0 | 16 | 4 | 12 | 16 | 1.600 | 16 | 25 | 41 | 0 | 2 | 8 | 25 | 23 | 2 | 171 | 170 | 214 | 176 | 9 | 99 | 32 | 29 | 124 | 13 | 4 | 30.77% | 7 | 3 | 57.14% | 1 | 183 | 371 | 49.33% | 107 | 231 | 46.32% | 103 | 196 | 52.55% | 352 | 206 | 265 | 140 | 292 | 140 | 92.3% | 9.4% | 96.0% | 105.3 | LUCKY | |
| _Vs Conference | 11 | 9 | 1 | 0 | 0 | 0 | 0 | 1 | 42 | 19 | 23 | 19 | 0.864 | 42 | 67 | 109 | 0 | 3 | 8 | 25 | 23 | 2 | 409 | 170 | 214 | 176 | 9 | 244 | 91 | 55 | 274 | 27 | 8 | 29.63% | 15 | 4 | 73.33% | 1 | 183 | 371 | 49.33% | 107 | 231 | 46.32% | 103 | 196 | 52.55% | 352 | 206 | 265 | 140 | 292 | 140 | 69.4% | 10.3% | 92.2% | 102.5 | LUCKY | |
| _Since Last GM Reset | 15 | 11 | 1 | 0 | 1 | 0 | 1 | 1 | 58 | 27 | 31 | 27 | 0.900 | 58 | 93 | 151 | 0 | 3 | 8 | 25 | 23 | 2 | 562 | 170 | 214 | 176 | 9 | 335 | 116 | 76 | 378 | 35 | 11 | 31.43% | 23 | 5 | 78.26% | 1 | 183 | 371 | 49.33% | 107 | 231 | 46.32% | 103 | 196 | 52.55% | 352 | 206 | 265 | 140 | 292 | 140 | 68.1% | 10.3% | 91.9% | 102.3 | LUCKY | |
| Total | 15 | 11 | 1 | 0 | 1 | 0 | 1 | 1 | 58 | 27 | 31 | 27 | 0.900 | 58 | 93 | 151 | 0 | 3 | 8 | 25 | 23 | 2 | 562 | 170 | 214 | 176 | 9 | 335 | 116 | 76 | 378 | 35 | 11 | 31.43% | 23 | 5 | 78.26% | 1 | 183 | 371 | 49.33% | 107 | 231 | 46.32% | 103 | 196 | 52.55% | 352 | 206 | 265 | 140 | 292 | 140 | 68.1% | 10.3% | 91.9% | 102.3 | LUCKY |
| Puck Time | |
|---|---|
| Offensive Zone | 23 |
| Neutral Zone | 19 |
| Defensive Zone | 17 |
| Puck Time | |
|---|---|
| Offensive Zone Start | 371 |
| Neutral Zone Start | 196 |
| Defensive Zone Start | 231 |
| Puck Time | |
|---|---|
| With Puck | 32 |
| Without Puck | 28 |
| Faceoffs | |
|---|---|
| Faceoffs Won | 393 |
| Faceoffs Lost | 405 |
| Team Average Shots after | League Average Shots after | |
|---|---|---|
| 1st Period | 11.3 | 9.57 |
| 2nd Period | 25.6 | 20.31 |
| 3rd Period | 37.3 | 30.68 |
| Overtime | 37.9 | 31.4 |
| Goals in | Team Average Goals after | League Average Goals after |
|---|---|---|
| 1st Period | 0.5 | 0.64 |
| 2nd Period | 2.2 | 1.65 |
| 3rd Period | 3.7 | 2.67 |
| Overtime | 3.9 | 2.83 |
| Even Strenght Goal | 46 |
|---|---|
| PP Goal | 11 |
| PK Goal | 1 |
| Empty Net Goal | 0 |
| Home | Away | |
|---|---|---|
| Win | 6 | 7 |
| Lost | 1 | 0 |
| Overtime Lost | 0 | 1 |
| PP Attempt | 35 |
|---|---|
| PP Goal | 11 |
| PK Attempt | 23 |
| PK Goal Against | 5 |
| Home | |
|---|---|
| Shots For | 37.5 |
| Shots Against | 22.3 |
| Goals For | 3.9 |
| Goals Against | 1.8 |
| Hits | 25.2 |
| Shots Blocked | 7.7 |
| Pim | 5.1 |
| Date | Matchup | Result | Detail | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Sun, Oct 11 | NJD | @ | TOR | NJD1,TOR2 | RECAP | |||||||||
| Mon, Oct 12 | TOR | @ | TAM | TOR2,TAM1 | RECAP | |||||||||
| Wed, Oct 14 | MTL | @ | TOR | MTL0,TOR6 | RECAP | |||||||||
| Fri, Oct 16 | TOR | @ | PHO | TOR4,PHO3 (OT) | RECAP | |||||||||
| Sun, Oct 18 | NAS | @ | TOR | NAS2,TOR5 | RECAP | |||||||||
| Tue, Oct 20 | TOR | @ | NJD | TOR3,NJD1 | RECAP | |||||||||
| Thu, Oct 22 | TOR | @ | BOS | TOR6,BOS7 (SO) | RECAP | |||||||||
| Sat, Oct 24 | TOR | @ | NAS | TOR4,NAS1 | RECAP | |||||||||
| Mon, Oct 26 | TOR | @ | MTL | TOR6,MTL2 | RECAP | |||||||||
| Wed, Oct 28 | MTL | @ | TOR | MTL1,TOR4 | RECAP | |||||||||
| Fri, Oct 30 | BUF | @ | TOR | BUF4,TOR2 | RECAP | |||||||||
| Sun, Nov 1 | TOR | @ | CLB | TOR5,CLB2 | RECAP | |||||||||
| Tue, Nov 3 | CLB | @ | TOR | CLB0,TOR2 | RECAP | |||||||||
| Thu, Nov 5 | EDM | @ | TOR | EDM2,TOR3 (SO) | RECAP | |||||||||
| Sat, Nov 7 | TOR | @ | PHI | TOR4,PHI0 | RECAP | |||||||||
| Mon, Nov 9 | CHI | @ | TOR | |||||||||||
| Wed, Nov 11 | TOR | @ | WAS | |||||||||||
| Fri, Nov 13 | TOR | @ | NYI | |||||||||||
| Sun, Nov 15 | CLB | @ | TOR | |||||||||||
| Tue, Nov 17 | WPG | @ | TOR | |||||||||||
| Thu, Nov 19 | PHI | @ | TOR | |||||||||||
| Sun, Nov 22 | TOR | @ | S J | |||||||||||
| Wed, Nov 25 | NJD | @ | TOR | |||||||||||
| Fri, Nov 27 | TOR | @ | ANA | |||||||||||
| Sat, Nov 28 | SEA | @ | TOR | |||||||||||
| Mon, Nov 30 | TOR | @ | MTL | |||||||||||
| Wed, Dec 2 | STL | @ | TOR | |||||||||||
| Fri, Dec 4 | MIN | @ | TOR | |||||||||||
| Sun, Dec 6 | TOR | @ | CLB | |||||||||||
| Mon, Dec 7 | TAM | @ | TOR | |||||||||||
| Wed, Dec 9 | TOR | @ | CHI | |||||||||||
| Fri, Dec 11 | MTL | @ | TOR | |||||||||||
| Sun, Dec 13 | TOR | @ | TAM | |||||||||||
| Tue, Dec 15 | TOR | @ | COL | |||||||||||
| Wed, Dec 16 | TOR | @ | CAL | |||||||||||
| Fri, Dec 18 | ANA | @ | TOR | |||||||||||
| Mon, Dec 21 | BOS | @ | TOR | |||||||||||
| Tue, Dec 22 | TOR | @ | CHI | |||||||||||
| Thu, Dec 24 | CHI | @ | TOR | |||||||||||
| Sun, Dec 27 | LOS | @ | TOR | |||||||||||
| Tue, Dec 29 | TOR | @ | DAL | |||||||||||
| Wed, Dec 30 | NYR | @ | TOR | |||||||||||
| Fri, Jan 1 | TOR | @ | NYR | |||||||||||
| Sun, Jan 3 | PIT | @ | TOR | |||||||||||
| Mon, Jan 4 | TOR | @ | CAR | |||||||||||
| Wed, Jan 6 | NYI | @ | TOR | |||||||||||
| Fri, Jan 8 | TOR | @ | PHO | |||||||||||
| Sat, Jan 9 | MIN | @ | TOR | |||||||||||
| Mon, Jan 11 | TOR | @ | FLO | |||||||||||
| Wed, Jan 13 | FLO | @ | TOR | |||||||||||
| Thu, Jan 14 | TOR | @ | TAM | |||||||||||
| Sun, Jan 17 | TOR | @ | WPG | |||||||||||
| Mon, Jan 18 | CAR | @ | TOR | |||||||||||
| Wed, Jan 20 | TOR | @ | MIN | |||||||||||
| Thu, Jan 21 | TOR | @ | NJD | |||||||||||
| Sat, Jan 23 | WAS | @ | TOR | |||||||||||
| Mon, Jan 25 | DAL | @ | TOR | |||||||||||
| Tue, Jan 26 | TOR | @ | LOS | |||||||||||
| Thu, Jan 28 | VAN | @ | TOR | |||||||||||
| Fri, Jan 29 | TOR | @ | PIT | |||||||||||
| Sun, Jan 31 | TOR | @ | BUF | |||||||||||
| Tue, Feb 2 | TAM | @ | TOR | |||||||||||
| Thu, Feb 4 | TOR | @ | BUF | |||||||||||
| Sat, Feb 6 | CHI | @ | TOR | |||||||||||
| Mon, Feb 8 | VAN | @ | TOR | |||||||||||
| Wed, Feb 10 | BUF | @ | TOR | |||||||||||
| Thu, Feb 11 | TOR | @ | OTT | |||||||||||
| Sun, Feb 14 | TOR | @ | DET | |||||||||||
| Mon, Feb 15 | PHO | @ | TOR | |||||||||||
| Wed, Feb 17 | TOR | @ | EDM | |||||||||||
| Thu, Feb 18 | TOR | @ | OTT | |||||||||||
| Sat, Feb 20 | CAL | @ | TOR | |||||||||||
| Wed, Feb 24 | MTL | @ | TOR | |||||||||||
| Fri, Feb 26 | S J | @ | TOR | |||||||||||
| Tue, Mar 2 | COL | @ | TOR | |||||||||||
| Wed, Mar 3 | TOR | @ | VAN | |||||||||||
| Fri, Mar 5 | TOR | @ | EDM | |||||||||||
| Mon, Mar 8 | DET | @ | TOR | |||||||||||
| Fri, Mar 12 | OTT | @ | TOR | |||||||||||
| Sun, Mar 14 | TOR | @ | SEA | |||||||||||
| Mon, Mar 15 | OTT | @ | TOR | |||||||||||
| Trade Deadline --- Trades can’t be done after this day is simulated! | ||||||||||||||
| Wed, Mar 17 | TOR | @ | VAN | |||||||||||
| Fri, Mar 19 | TOR | @ | STL | |||||||||||
| Sat, Mar 20 | TOR | @ | SEA | |||||||||||
| Salary Cap | |||
|---|---|---|---|
| Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
| 3,902,500$ | 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 |
| 35 | 0 - 0.00% | 0$ | 0$ | 3000 | 100 |
| Expenses | |||
|---|---|---|---|
| Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
| 3,902,500$ | 3,902,500$ | 0$ | 0$ |
| Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
|---|---|---|---|
| 784,400$ | 0$ | 694,906$ | 0$ |
| Estimate | |||
|---|---|---|---|
| Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
| 0$ | 156 | 27,176$ | 3,614,408$ |
| Team Total Estimate | |||
|---|---|---|---|
| Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
| 3,614,408$ | 0$ | 0$ | 0$ |
| Sponsors | |||
|---|---|---|---|
| TV Rights | Primary Sponsor | Secondary Sponsor | Secondary Sponsor |
Rookie
Injured
Cold Streak
Hot Streak | Left Wing | Center | Right Wing |
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| Defense #1 | Defense #2 | Goalie |
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