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Full Scoreboard »» |
| Winnipeg Jets 5-4-3, 13pts · 6th in Western |
| Player | # | POS | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Brayden Point | 21 | C | 99.00 | 57 | 34 | 95 | 83 | 70 | 89 | 90 | 82 | 80 | 78 | 89 | 60 | 85 | 74 | 74 | 0 | 38 | 89 | 29 | 9,000,000$/2yrs | |||
Jonathan Huberdeau | 0 | LW | 100.00 | 64 | 34 | 82 | 73 | 79 | 87 | 90 | 69 | 59 | 75 | 71 | 66 | 70 | 79 | 77 | 0 | 38 | 81 | 32 | 9,500,000$/2yrs | |||
Matthew Knies | 0 | LW | 100.00 | 81 | 36 | 81 | 71 | 83 | 83 | 90 | 69 | 55 | 69 | 73 | 65 | 71 | 63 | 61 | 0 | 38 | 80 | 23 | 7,750,000$/6yrs | |||
Alexis Lafreniere | 0 | LW | 100.00 | 70 | 33 | 83 | 72 | 77 | 84 | 90 | 70 | 58 | 70 | 73 | 57 | 71 | 64 | 62 | 0 | 38 | 79 | 24 | 3,000,000$/1yrs | |||
Logan O'Connor | 0 | LW/RW | 100.00 | 67 | 39 | 85 | 61 | 69 | 80 | 86 | 63 | 60 | 62 | 66 | 77 | 64 | 73 | 72 | 0 | 38 | 76 | 29 | 4,000,000$/3yrs | |||
Ilya Mikheyev | 0 | LW/RW | 97.00 | 62 | 33 | 95 | 65 | 77 | 81 | 90 | 64 | 57 | 64 | 68 | 64 | 66 | 76 | 76 | 0 | 38 | 76 | 31 | 4,750,000$/1yrs | |||
Alex Laferriere | 0 | RW | 100.00 | 74 | 35 | 85 | 65 | 68 | 80 | 90 | 64 | 59 | 64 | 68 | 57 | 66 | 64 | 62 | 0 | 41 | 75 | 24 | 4,100,000$/3yrs | |||
Tanner Pearson | 0 | LW | 100.00 | 69 | 35 | 92 | 58 | 79 | 76 | 85 | 59 | 58 | 62 | 63 | 64 | 61 | 80 | 79 | 0 | 38 | 73 | 33 | 1,300,000$/2yrs | |||
Steven Lorentz | 0 | C/LW | 100.00 | 82 | 36 | 94 | 55 | 84 | 72 | 83 | 56 | 61 | 59 | 59 | 68 | 58 | 73 | 73 | 0 | 38 | 72 | 29 | 1,350,000$/3yrs | |||
Fyodor Svechkov (R) | 0 | C | 100.00 | 63 | 32 | 90 | 64 | 73 | 77 | 73 | 57 | 73 | 62 | 65 | 58 | 61 | 61 | 60 | 0 | 41 | 72 | 22 | 925,000$/1yrs | |||
Kailer Yamamoto | 0 | RW | 100.00 | 62 | 31 | 90 | 58 | 57 | 76 | 76 | 61 | 60 | 60 | 64 | 56 | 62 | 69 | 68 | 0 | 38 | 71 | 27 | 800,000$/2yrs | |||
Ivan Miroshnichenko | 0 | LW | 100.00 | 79 | 32 | 94 | 61 | 74 | 74 | 71 | 57 | 55 | 62 | 59 | 57 | 58 | 60 | 59 | 0 | 38 | 71 | 21 | 950,000$/1yrs | |||
Mikhail Sergachev | 98 | D | 98.00 | 66 | 33 | 85 | 74 | 84 | 97 | 82 | 69 | 30 | 77 | 66 | 81 | 67 | 70 | 69 | 0 | 38 | 85 | 27 | 8,500,000$/6yrs | |||
Jakob Chychrun | 6 | D | 98.00 | 66 | 34 | 75 | 66 | 86 | 92 | 89 | 60 | 30 | 70 | 71 | 64 | 65 | 70 | 68 | 0 | 38 | 79 | 27 | 9,000,000$/8yrs | |||
Henri Jokiharju | 0 | D | 100.00 | 69 | 33 | 90 | 58 | 77 | 87 | 86 | 56 | 30 | 62 | 56 | 64 | 56 | 68 | 67 | 0 | 38 | 73 | 26 | 2,000,000$/2yrs | |||
Calle Rosen | 48 | D | 100.00 | 61 | 38 | 89 | 54 | 74 | 68 | 67 | 52 | 30 | 60 | 53 | 73 | 56 | 77 | 76 | 0 | 38 | 72 | 31 | 800,000$/2yrs | |||
Logan Stanley | 0 | D | 100.00 | 74 | 58 | 56 | 55 | 99 | 81 | 79 | 54 | 30 | 61 | 54 | 66 | 54 | 70 | 65 | 0 | 38 | 72 | 27 | 1,000,000$/1yrs | |||
Dakota Mermis | 36 | D | 100.00 | 67 | 37 | 76 | 55 | 76 | 79 | 73 | 56 | 30 | 59 | 58 | 65 | 57 | 77 | 75 | 0 | 38 | 72 | 31 | 800,000$/2yrs | |||
| Scratches | ||||||||||||||||||||||||||
Dillon Dube | 0 | C/LW/RW | 100.00 | 66 | 32 | 93 | 55 | 71 | 74 | 72 | 56 | 75 | 58 | 58 | 60 | 57 | 69 | 69 | 0 | 28 | 69 | 27 | ||||
Philippe Myers | 0 | D | 100.00 | 80 | 40 | 85 | 55 | 91 | 82 | 71 | 50 | 30 | 56 | 57 | 66 | 53 | 72 | 70 | 0 | 28 | 71 | 28 | 850,000$/2yrs | |||
| TEAM AVERAGE | 99.60 | 69 | 36 | 86 | 63 | 77 | 81 | 82 | 61 | 51 | 65 | 65 | 64 | 63 | 70 | 69 | 0 | 37 | 75 | |||||||
| Priority | Type | Description |
|---|---|---|
| 1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
| 2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
| 3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig) |
| 4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
| 5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter. |
| 6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
| 7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
| 8 | ? | Wildcard for a single, non-space character. |
| 8 | * | Wildcard for zero or more non-space characters. |
| 9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
| 10 | text | Any text entered in the filter will match text found within the column |
| Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Ukko-Pekka Luukkonen | 0 | 97.00 | 84 | 95 | 83 | 89 | 87 | 79 | 88 | 92 | 88 | 93 | 88 | 69 | 74 | 0 | 31 | 90 | 26 | 5,000,000$/3yrs |
Gage Alexander | 0 | 100.00 | 72 | 69 | 68 | 86 | 58 | 73 | 71 | 72 | 73 | 74 | 72 | 60 | 60 | 0 | 44 | 75 | 23 | 800,000$/3yrs |
| Scratches | ||||||||||||||||||||
Damian Clara | 0 | 100.00 | 74 | 74 | 71 | 89 | 61 | 77 | 73 | 74 | 77 | 78 | 75 | 58 | 66 | 0 | 34 | 78 | 20 | 878,333$/2yrs |
| TEAM AVERAGE | 99.00 | 77 | 79 | 74 | 88 | 69 | 76 | 77 | 79 | 79 | 82 | 78 | 62 | 67 | 0 | 36 | 81 | |||
| Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Craig Berube | 83 | 84 | 88 | 76 | 75 | 85 | 79 | CAN | 58 | 4 | 1,000,000$ |
| General Manager | Nathan Mourot |
|---|
| 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 | Brayden Point | 21 | C | 12 | 9 | 9 | 18 | 11 | 2 | 0 | 5 | 54 | 14 | 33 | 16.67% | 2 | 22.09 | 3 | 2 | 5 | 42 | 0 | 0 | 0 | 51 | 0 | 2 | 53.00% | 400 | 0 | 0 | 0 | 0 | 1.36 | 0 | 1 | |
| 2 | Matthew Knies | 0 | LW | 12 | 5 | 8 | 13 | 13 | 10 | 0 | 28 | 41 | 9 | 13 | 12.20% | 2 | 17.94 | 1 | 1 | 2 | 31 | 0 | 0 | 0 | 19 | 0 | 0 | 40.00% | 10 | 0 | 0 | 0 | 0 | 1.21 | 0 | 1 | |
| 3 | Mikhail Sergachev | 98 | D | 12 | 3 | 8 | 11 | -3 | 10 | 0 | 11 | 30 | 8 | 21 | 10.00% | 25 | 26.32 | 2 | 4 | 6 | 40 | 0 | 0 | 0 | 41 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.70 | 0 | 0 | |
| 4 | Logan O'Connor | 0 | LW/RW | 12 | 5 | 4 | 9 | 14 | 10 | 0 | 17 | 29 | 10 | 16 | 17.24% | 4 | 18.19 | 0 | 0 | 0 | 41 | 0 | 0 | 0 | 9 | 0 | 2 | 31.58% | 19 | 0 | 0 | 0 | 0 | 0.82 | 0 | 0 | |
| 5 | Ilya Mikheyev | 0 | LW/RW | 12 | 5 | 3 | 8 | -4 | 6 | 0 | 17 | 33 | 13 | 22 | 15.15% | 2 | 22.31 | 0 | 2 | 2 | 33 | 0 | 0 | 0 | 0 | 3 | 0 | 42.86% | 14 | 0 | 0 | 0 | 0 | 0.60 | 0 | 0 | |
| 6 | Logan Stanley | 0 | D | 12 | 2 | 4 | 6 | 3 | 18 | 0 | 30 | 9 | 4 | 5 | 22.22% | 11 | 20.18 | 1 | 1 | 2 | 35 | 0 | 0 | 0 | 23 | 1 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.50 | 0 | 0 | |
| 7 | Jonathan Huberdeau | 0 | LW | 12 | 1 | 5 | 6 | -6 | 2 | 0 | 22 | 36 | 9 | 16 | 2.78% | 0 | 18.61 | 1 | 3 | 4 | 42 | 0 | 0 | 0 | 49 | 0 | 0 | 47.83% | 23 | 0 | 0 | 0 | 0 | 0.54 | 0 | 1 | |
| 8 | Jakob Chychrun | 6 | D | 12 | 1 | 4 | 5 | -1 | 14 | 0 | 18 | 22 | 2 | 12 | 4.55% | 18 | 25.76 | 1 | 2 | 3 | 40 | 0 | 0 | 0 | 36 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.32 | 0 | 0 | |
| 9 | Henri Jokiharju | 0 | D | 12 | 0 | 4 | 4 | 3 | 4 | 0 | 6 | 8 | 4 | 6 | 0.00% | 13 | 21.57 | 0 | 1 | 1 | 35 | 0 | 0 | 0 | 41 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.31 | 0 | 0 | |
| 10 | Tanner Pearson | 0 | LW | 12 | 2 | 2 | 4 | 0 | 0 | 0 | 15 | 10 | 3 | 10 | 20.00% | 1 | 10.16 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 43.23% | 155 | 0 | 0 | 0 | 0 | 0.66 | 0 | 0 | |
| 11 | Steven Lorentz | 0 | C/LW | 12 | 2 | 2 | 4 | -4 | 6 | 0 | 21 | 21 | 7 | 16 | 9.52% | 3 | 17.59 | 0 | 1 | 1 | 32 | 0 | 0 | 0 | 20 | 0 | 0 | 37.20% | 250 | 0 | 0 | 0 | 0 | 0.38 | 0 | 0 | |
| 12 | Kailer Yamamoto | 0 | RW | 12 | 0 | 2 | 2 | 0 | 2 | 0 | 7 | 10 | 3 | 12 | 0.00% | 2 | 10.03 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 75.00% | 4 | 0 | 0 | 0 | 0 | 0.33 | 0 | 0 | |
| 13 | Calle Rosen | 48 | D | 12 | 0 | 2 | 2 | 3 | 2 | 0 | 3 | 4 | 2 | 5 | 0.00% | 12 | 13.74 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.24 | 0 | 0 | |
| 14 | Alexis Lafreniere | 0 | LW | 12 | 0 | 2 | 2 | -5 | 4 | 0 | 12 | 25 | 8 | 11 | 0.00% | 1 | 13.25 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 26.67% | 15 | 0 | 0 | 0 | 0 | 0.25 | 0 | 0 | |
| 15 | Alex Laferriere | 0 | RW | 12 | 2 | 0 | 2 | -5 | 4 | 0 | 11 | 18 | 3 | 12 | 11.11% | 0 | 13.35 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 57.14% | 14 | 0 | 0 | 0 | 0 | 0.25 | 0 | 0 | |
| 16 | Fyodor Svechkov | 0 | C | 12 | 0 | 2 | 2 | -4 | 2 | 0 | 5 | 6 | 6 | 9 | 0.00% | 1 | 10.31 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 43.20% | 169 | 0 | 0 | 0 | 0 | 0.32 | 0 | 0 | |
| 17 | Dakota Mermis | 36 | D | 12 | 0 | 1 | 1 | 3 | 2 | 0 | 22 | 7 | 0 | 2 | 0.00% | 12 | 12.90 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.13 | 0 | 0 | |
| 18 | Ivan Miroshnichenko | 0 | LW | 12 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0.00 | 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 | 216 | 37 | 62 | 99 | 18 | 98 | 0 | 250 | 363 | 105 | 221 | 10.19% | 109 | 16.35 | 9 | 17 | 26 | 376 | 0 | 0 | 0 | 307 | 5 | 4 | 45.39% | 1073 | 0 | 0 | 0 | 0 | 0.56 | 0 | 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 | Ukko-Pekka Luukkonen | 12 | 4 | 4 | 3 | 0.898 | 3.29 | 656 | 4 | 0 | 36 | 352 | 0 | 1 | 0 | 0.667 | 3 | 12 | 0 | 1 | 0 | 0 | |
| 2 | Gage Alexander | 2 | 1 | 0 | 0 | 0.946 | 1.74 | 69 | 0 | 0 | 2 | 37 | 0 | 0 | 0 | 0.000 | 0 | 0 | 12 | 0 | 0 | 0 | |
| Team Total or Average | 14 | 5 | 4 | 3 | 0.902 | 3.15 | 725 | 4 | 0 | 38 | 389 | 0 | 1 | 0 | 0.667 | 3 | 12 | 12 | 1 | 0 | 0 |
| Projected Total Cap Hit | 76,200,821$ |
| Projected Cap Space | 19,299,179$ |
| Retains And Buyout Cap Hit | 0$ |
| Salary Cap To Date | 10,341,151$ |
| Players In Salary Cap | 22 |
| LTIR Players | 0 |
| Jets Roster | Pos | Age | Cap Hit | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 | 2030-31 | 2031-32 | 2032-33 |
|---|---|---|---|---|---|---|---|---|---|---|---|
Alex Laferriere ![]() | RW | 24 | 4,100,000$ | 4,100,000$ | 4,100,000$ | 4,100,000$ | |||||
Alexis Lafreniere ![]() | LW | 24 | 3,000,000$ | 3,000,000$ | RFA | ||||||
Brayden Point ![]() | C | 29 | 9,000,000$ | 9,000,000$ | 9,000,000$ | UFA | |||||
Calle Rosen | D | 31 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Dakota Mermis | D | 31 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Damian Clara | G | 20 | 878,333$ | 878,333$ | 878,333$ | RFA | |||||
Dillon Dube | C/LW/RW | 27 | 0$ | ||||||||
Fyodor Svechkov | C | 22 | 925,000$ | 925,000$ | RFA | ||||||
Gage Alexander | G | 23 | 800,000$ | 800,000$ | 800,000$ | 800,000$ | RFA | ||||
Henri Jokiharju ![]() | D | 26 | 2,000,000$ | 2,000,000$ | 2,000,000$ | ||||||
Ilya Mikheyev ![]() | LW/RW | 31 | 4,750,000$ | 4,750,000$ | UFA | ||||||
Ivan Miroshnichenko | LW | 21 | 950,000$ | 950,000$ | RFA | ||||||
Jakob Chychrun ![]() | D | 27 | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ |
Jonathan Huberdeau ![]() | LW | 32 | 9,500,000$ | 9,500,000$ | 9,500,000$ | UFA | |||||
Kailer Yamamoto | RW | 27 | 800,000$ | 800,000$ | 800,000$ | ||||||
Logan O'Connor ![]() | LW/RW | 29 | 4,000,000$ | 4,000,000$ | 4,000,000$ | 4,000,000$ | UFA | ||||
Logan Stanley | D | 27 | 1,000,000$ | 1,000,000$ | |||||||
Matthew Knies ![]() | LW | 23 | 7,750,000$ | 7,750,000$ | 7,750,000$ | 7,750,000$ | 7,750,000$ | 7,750,000$ | 7,750,000$ | ||
Mikhail Sergachev ![]() | D | 27 | 8,500,000$ | 8,500,000$ | 8,500,000$ | 8,500,000$ | 8,500,000$ | 8,500,000$ | 8,500,000$ | UFA | |
Philippe Myers | D | 28 | 850,000$ | 850,000$ | 850,000$ | UFA | |||||
Steven Lorentz ![]() | C/LW | 29 | 1,350,000$ | 1,350,000$ | 1,350,000$ | 1,350,000$ | UFA | ||||
Tanner Pearson ![]() | LW | 33 | 1,300,000$ | 1,300,000$ | 1,300,000$ | UFA | |||||
Ukko-Pekka Luukkonen ![]() | G | 26 | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | UFA |
| Non-Roster | Pos | Age | Cap Hit | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 | 2030-31 | 2031-32 | 2032-33 |
|---|---|---|---|---|---|---|---|---|---|---|---|
Andrew Perrott | D | 24 | 900,000$ | 900,000$ | RFA | ||||||
Brendan Furry | LW | 27 | 800,000$ | 800,000$ | 800,000$ | ||||||
Dmitri Osipov | D | 29 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Dryden McKay | G | 27 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Dylan Ferguson | G | 27 | 900,000$ | 900,000$ | |||||||
Dylan McIlrath | D | 33 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Eduard Sale | RW | 20 | 886,666$ | 886,666$ | 886,666$ | 886,666$ | RFA | ||||
Fabian Lysell | RW | 22 | 863,333$ | 863,333$ | RFA | ||||||
Givani Smith | LW/RW | 27 | 775,000$ | 775,000$ | |||||||
Jack Becker | C | 28 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Jake Elmer | RW | 25 | 800,000$ | 800,000$ | 800,000$ | ||||||
Jeremy Brodeur | G | 29 | 900,000$ | 900,000$ | 900,000$ | UFA | |||||
Joe Carroll | LW | 24 | 800,000$ | 800,000$ | 800,000$ | ||||||
Jordan Papirny | G | 29 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Justin Pearson | LW | 27 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Kirill Tyutyayev | LW | 25 | 800,000$ | 800,000$ | 800,000$ | ||||||
Kyle MacLean | LW | 26 | 900,000$ | 900,000$ | |||||||
Linus Karlsson | C | 25 | 775,000$ | 775,000$ | |||||||
Lucas Johansen | D | 27 | 800,000$ | 800,000$ | |||||||
Luke Rowe | D | 27 | 800,000$ | 800,000$ | 800,000$ | ||||||
Marc Johnstone | RW | 29 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Matt Kessel | D | 25 | 900,000$ | 900,000$ | 900,000$ | ||||||
Matthew Strome | LW | 26 | 800,000$ | 800,000$ | 800,000$ | ||||||
Michal Teply | RW | 24 | 800,000$ | 800,000$ | RFA | ||||||
Miko Matikka | C/LW/RW | 22 | 870,000$ | 870,000$ | 870,000$ | RFA | |||||
Nils Aman | C | 25 | 950,000$ | 950,000$ | |||||||
Sam Dickinson | D | 19 | 975,000$ | 975,000$ | 975,000$ | RFA | |||||
Vasili Ponomaryov | C | 23 | 800,000$ | 800,000$ | 800,000$ | RFA | |||||
Ville Heinola | D | 24 | 900,000$ | 900,000$ | RFA | ||||||
Zack MacEwen | C/RW | 29 | 775,000$ | 775,000$ | UFA |
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| Priority | Type | Description |
|---|---|---|
| 1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
| 2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
| 3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig) |
| 4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
| 5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter. |
| 6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
| 7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
| 8 | ? | Wildcard for a single, non-space character. |
| 8 | * | Wildcard for zero or more non-space characters. |
| 9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
| 10 | text | Any text entered in the filter will match text found within the column |
| # | VS Team | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | P | PCT | G | A | TP | SO | EG | GP1 | GP2 | GP3 | GP4 | SHF | SH1 | SP2 | SP3 | SP4 | SHA | SHB | Pim | Hit | PPA | PPG | PP% | PKA | PK GA | PK% | PK GF | W OF FO | T OF FO | OF FO% | W DF FO | T DF FO | DF FO% | W NT FO | T NT FO | NT FO% | PZ DF | PZ OF | PZ NT | PC DF | PC OF | PC NT | GF% | SH% | SV% | PDO | PDOBRK |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 7 | 4 | 3 | 3 | 0.750 | 7 | 10 | 17 | 0 | 0 | 3 | 3 | 1 | 0 | 55 | 11 | 25 | 19 | 0 | 55 | 12 | 6 | 43 | 6 | 2 | 33.33% | 3 | 0 | 100.00% | 0 | 188 | 430 | 43.72% | 209 | 435 | 48.05% | 90 | 197 | 45.69% | 48 | 32 | 43 | 15 | 28 | 14 | 55.6% | 12.7% | 92.7% | 105.5 | LUCKY | |
| 2 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 6 | -5 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 1 | 0 | 0 | 18 | 3 | 6 | 9 | 0 | 31 | 12 | 10 | 15 | 4 | 0 | 0.00% | 5 | 3 | 40.00% | 0 | 188 | 430 | 43.72% | 209 | 435 | 48.05% | 90 | 197 | 45.69% | 19 | 12 | 25 | 8 | 14 | 6 | 25.0% | 5.6% | 80.6% | 86.2 | Unlucky | |
| 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | 5 | -1 | 1 | 0.500 | 4 | 6 | 10 | 0 | 0 | 0 | 2 | 2 | 0 | 33 | 12 | 8 | 11 | 5 | 32 | 7 | 12 | 14 | 4 | 1 | 25.00% | 6 | 2 | 66.67% | 0 | 188 | 430 | 43.72% | 209 | 435 | 48.05% | 90 | 197 | 45.69% | 23 | 15 | 28 | 8 | 13 | 6 | 50.0% | 12.1% | 84.4% | 96.5 | FUN | |
| 4 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 4 | 2 | 2 | 1.000 | 6 | 11 | 17 | 0 | 0 | 1 | 4 | 1 | 0 | 35 | 14 | 16 | 5 | 0 | 38 | 12 | 6 | 26 | 5 | 2 | 40.00% | 3 | 1 | 66.67% | 0 | 188 | 430 | 43.72% | 209 | 435 | 48.05% | 90 | 197 | 45.69% | 20 | 13 | 26 | 7 | 13 | 6 | 57.1% | 17.1% | 89.5% | 106.6 | FUN | |
| 5 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 | 3 | -1 | 1 | 0.500 | 2 | 4 | 6 | 0 | 0 | 0 | 1 | 1 | 0 | 30 | 12 | 6 | 12 | 0 | 37 | 7 | 8 | 22 | 4 | 0 | 0.00% | 4 | 1 | 75.00% | 0 | 188 | 430 | 43.72% | 209 | 435 | 48.05% | 90 | 197 | 45.69% | 23 | 16 | 24 | 7 | 12 | 6 | 50.0% | 6.7% | 91.9% | 98.6 | DULL | |
| 6 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | -1 | 0 | 0.000 | 2 | 4 | 6 | 0 | 0 | 1 | 0 | 1 | 0 | 22 | 6 | 7 | 9 | 0 | 32 | 7 | 14 | 17 | 2 | 1 | 50.00% | 6 | 2 | 66.67% | 0 | 188 | 430 | 43.72% | 209 | 435 | 48.05% | 90 | 197 | 45.69% | 23 | 14 | 23 | 7 | 13 | 6 | 50.0% | 9.1% | 90.6% | 99.7 | FUN | |
| 7 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 5 | -2 | 0 | 0.000 | 3 | 5 | 8 | 0 | 0 | 1 | 0 | 2 | 0 | 28 | 5 | 10 | 13 | 0 | 39 | 12 | 8 | 20 | 3 | 0 | 0.00% | 4 | 3 | 25.00% | 0 | 188 | 430 | 43.72% | 209 | 435 | 48.05% | 90 | 197 | 45.69% | 23 | 15 | 24 | 7 | 12 | 6 | 60.0% | 10.7% | 87.2% | 97.9 | FUN | |
| 8 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 1 | 0 | 2 | 0 | 48 | 23 | 11 | 14 | 0 | 29 | 14 | 10 | 17 | 3 | 1 | 33.33% | 4 | 0 | 100.00% | 0 | 188 | 430 | 43.72% | 209 | 435 | 48.05% | 90 | 197 | 45.69% | 25 | 17 | 23 | 6 | 11 | 5 | 50.0% | 6.3% | 93.1% | 99.4 | DULL | |
| 9 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 4 | 7 | 0 | 0 | 2 | 0 | 1 | 0 | 19 | 5 | 12 | 2 | 0 | 29 | 4 | 6 | 27 | 3 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 188 | 430 | 43.72% | 209 | 435 | 48.05% | 90 | 197 | 45.69% | 20 | 12 | 26 | 7 | 13 | 6 | 60.0% | 15.8% | 93.1% | 108.9 | LUCKY | |
| 10 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 4 | -1 | 0 | 0.000 | 3 | 6 | 9 | 0 | 0 | 1 | 0 | 2 | 0 | 40 | 18 | 11 | 11 | 0 | 31 | 14 | 14 | 30 | 3 | 2 | 66.67% | 7 | 0 | 100.00% | 0 | 188 | 430 | 43.72% | 209 | 435 | 48.05% | 90 | 197 | 45.69% | 21 | 13 | 25 | 7 | 12 | 6 | 20.0% | 7.5% | 87.1% | 94.6 | Unlucky | |
| 11 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 35 | 12 | 13 | 10 | 0 | 36 | 8 | 8 | 19 | 7 | 0 | 0.00% | 4 | 1 | 75.00% | 0 | 188 | 430 | 43.72% | 209 | 435 | 48.05% | 90 | 197 | 45.69% | 22 | 15 | 25 | 8 | 12 | 6 | 100.0% | 8.6% | 97.2% | 105.8 | DULL | |
| _Vs Division | 5 | 3 | 2 | 0 | 0 | 0 | 0 | 0 | 17 | 16 | 1 | 6 | 0.600 | 17 | 29 | 46 | 0 | 0 | 6 | 4 | 7 | 0 | 152 | 53 | 56 | 43 | 0 | 167 | 49 | 44 | 107 | 16 | 4 | 25.00% | 19 | 6 | 68.42% | 0 | 188 | 430 | 43.72% | 209 | 435 | 48.05% | 90 | 197 | 45.69% | 112 | 73 | 124 | 36 | 63 | 31 | 56.5% | 11.2% | 90.4% | 101.6 | FUN | |
| _Vs Conference | 9 | 5 | 2 | 0 | 0 | 2 | 0 | 0 | 29 | 24 | 5 | 12 | 0.667 | 29 | 48 | 77 | 0 | 0 | 10 | 9 | 10 | 0 | 272 | 88 | 100 | 84 | 0 | 295 | 76 | 66 | 191 | 33 | 6 | 18.18% | 30 | 8 | 73.33% | 0 | 188 | 430 | 43.72% | 209 | 435 | 48.05% | 90 | 197 | 45.69% | 206 | 137 | 217 | 67 | 117 | 58 | 59.0% | 10.7% | 91.9% | 102.5 | LUCKY | |
| _Since Last GM Reset | 12 | 5 | 4 | 0 | 0 | 2 | 0 | 1 | 37 | 39 | -2 | 13 | 0.542 | 37 | 62 | 99 | 0 | 0 | 11 | 12 | 14 | 0 | 363 | 121 | 125 | 115 | 5 | 389 | 109 | 102 | 250 | 44 | 9 | 20.45% | 48 | 13 | 72.92% | 0 | 188 | 430 | 43.72% | 209 | 435 | 48.05% | 90 | 197 | 45.69% | 271 | 179 | 297 | 90 | 157 | 78 | 51.9% | 10.2% | 90.0% | 100.2 | FUN | |
| Total | 12 | 5 | 4 | 0 | 0 | 2 | 0 | 1 | 37 | 39 | -2 | 13 | 0.542 | 37 | 62 | 99 | 0 | 0 | 11 | 12 | 14 | 0 | 363 | 121 | 125 | 115 | 5 | 389 | 109 | 102 | 250 | 44 | 9 | 20.45% | 48 | 13 | 72.92% | 0 | 188 | 430 | 43.72% | 209 | 435 | 48.05% | 90 | 197 | 45.69% | 271 | 179 | 297 | 90 | 157 | 78 | 51.9% | 10.2% | 90.0% | 100.2 | FUN |
| Puck Time | |
|---|---|
| Offensive Zone | 22 |
| Neutral Zone | 13 |
| Defensive Zone | 24 |
| Puck Time | |
|---|---|
| Offensive Zone Start | 430 |
| Neutral Zone Start | 197 |
| Defensive Zone Start | 435 |
| Puck Time | |
|---|---|
| With Puck | 29 |
| Without Puck | 31 |
| Faceoffs | |
|---|---|
| Faceoffs Won | 487 |
| Faceoffs Lost | 575 |
| Team Average Shots after | League Average Shots after | |
|---|---|---|
| 1st Period | 10.1 | 9.57 |
| 2nd Period | 20.5 | 20.31 |
| 3rd Period | 30.1 | 30.68 |
| Overtime | 30.5 | 31.4 |
| Goals in | Team Average Goals after | League Average Goals after |
|---|---|---|
| 1st Period | 0.9 | 0.64 |
| 2nd Period | 1.9 | 1.65 |
| 3rd Period | 3.1 | 2.67 |
| Overtime | 3.1 | 2.83 |
| Even Strenght Goal | 28 |
|---|---|
| PP Goal | 9 |
| PK Goal | 0 |
| Empty Net Goal | 0 |
| Home | Away | |
|---|---|---|
| Win | 4 | 1 |
| Lost | 3 | 1 |
| Overtime Lost | 1 | 2 |
| PP Attempt | 44 |
|---|---|
| PP Goal | 9 |
| PK Attempt | 48 |
| PK Goal Against | 13 |
| Home | |
|---|---|
| Shots For | 30.3 |
| Shots Against | 32.4 |
| Goals For | 3.1 |
| Goals Against | 3.3 |
| Hits | 20.8 |
| Shots Blocked | 9.1 |
| Pim | 8.5 |
| Date | Matchup | Result | Detail | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2025-10-10 | @ | Stars2,Jets3 | RECAP | |||||||||||
| 2025-10-12 | @ | Kings3,Jets2 (OT) | RECAP | |||||||||||
| 2025-10-14 | @ | Jets4,Islanders5 (SO) | RECAP | |||||||||||
| 2025-10-17 | @ | Jets1,Flyers6 | RECAP | |||||||||||
| 2025-10-19 | @ | Predators3,Jets2 | RECAP | |||||||||||
| 2025-10-21 | @ | Jets2,Flames3 (OT) | RECAP | |||||||||||
| 2025-10-24 | @ | Kraken1,Jets3 | RECAP | |||||||||||
| 2025-10-25 | @ | Flames1,Jets5 | RECAP | |||||||||||
| 2025-10-27 | @ | Mammoth5,Jets3 | RECAP | |||||||||||
| 2025-10-29 | @ | Jets6,Wild4 | RECAP | |||||||||||
| 2025-10-31 | @ | Blackhawks2,Jets3 | RECAP | |||||||||||
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| Salary Cap | |||
|---|---|---|---|
| Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
| 76,175,000$ | 0$ | 76,200,821$ | 19,325,000$ |
| Arena | Goal Horn | About us | |
|---|---|---|---|
| Name | Bell MTS Centre | |
| City | Winnipeg | ||
| Capacity | 18000 | ||
| Season Ticket Holders | 40% | ||
| Arena Capacity - Ticket Price Attendance - % | |||||
|---|---|---|---|---|---|
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| Arena Capacity | 6000 | 5000 | 2000 | 4000 | 1000 |
| Ticket Price | 100$ | 60$ | 35$ | 25$ | 200$ |
| Attendance | 45378 | 36521 | 15458 | 30507 | 7605 |
| Attendance PCT | 94.54% | 91.30% | 96.61% | 95.33% | 95.06% |
| Income | |||||
|---|---|---|---|---|---|
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| Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
| 33 | 16934 - 94.08% | 1,552,487$ | 12,419,895$ | 18000 | 100 |
| Expenses | |||
|---|---|---|---|
| Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
| 76,175,000$ | 76,175,000$ | 0$ | 0$ |
| Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
|---|---|---|---|
| 10,476,559$ | 396,745$ | 10,341,151$ | 0$ |
| Estimate | |||
|---|---|---|---|
| Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
| 51,232,067$ | 166 | 401,953$ | 66,724,198$ |
| Team Total Estimate | |||
|---|---|---|---|
| Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
| 69,083,016$ | 76,175,000$ | 74,007,539$ | 56,156,590$ |
Rookie
Injured
Cold Streak
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| Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 | Ronde 8 |
|---|---|---|---|---|---|---|---|---|
| 2026 | ||||||||
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| 2029 | ||||||||
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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 |
| Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
|---|---|---|---|---|---|
| Abram Wiebe | 2022 | 222 | |||
| Artur Cholach | 2021 | 206 | |||
| Austin Burnevik | 2024 | 199 | |||
| Ben Brinkman | 2019 | 167 | |||
| Brent Solomon | 2025 | 136 | |||
| Bryce Pickford | 2025 | 55 | |||
| Carter Yakemchuk | 2024 | 12 | |||
| Charlie Cerrato | 2025 | 72 | |||
| Cooper Simpson | 2025 | 23 | |||
| David Ma | 2020 | 169 | |||
| Kalle Loponen | 2019 | 213 | 5.5 - 3.5 | ||
| Lasse Boelius | 2025 | 53 | |||
| Lucas Mercuri | |||||
| Lucas Ramberg | 2020 | 189 | |||
| Matous Kucharcik | 2025 | 118 | |||
| Matthew Wood | 2023 | 14 | |||
| Nathan Villeneuve | 2024 | 74 | |||
| Ryan Leonard | 2023 | 7 | |||
| Sigge Holmgren | 2025 | 200 | |||
| Stepan Zvyagin | 2023 | 210 | |||
| Trevor Hoskin | 2024 | 135 | |||
| Valentin Nussbaumer | 2019 | 190 | |||
| Viktor Eklund | 2025 | 8 | |||
| Will Reynolds | 2025 | 104 |
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