|
Full Scoreboard »» |
|
Full Scoreboard »» |
Winnipeg Jets 1-4-0, 2pts · 7th 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 | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 21 | C | 100.00 | 66 | 39 | 90 | 89 | 70 | 88 | 88 | 84 | 82 | 82 | 89 | 66 | 87 | 71 | 70 | 0 | 66 | 91 | 27 | 9,000,000$/5yrs | |||
![]() | 0 | LW | 100.00 | 70 | 33 | 81 | 83 | 79 | 86 | 90 | 80 | 59 | 90 | 77 | 72 | 79 | 76 | 74 | 0 | 74 | 90 | 29 | 5,900,000$/1yrs | |||
![]() | 14 | C/RW | 100.00 | 68 | 34 | 86 | 82 | 79 | 90 | 90 | 77 | 87 | 81 | 78 | 82 | 78 | 65 | 74 | 0 | 74 | 88 | 23 | 7,125,000$/6yrs | |||
![]() | 6 | RW | 100.00 | 64 | 33 | 89 | 79 | 81 | 85 | 88 | 77 | 60 | 79 | 77 | 65 | 77 | 69 | 68 | 0 | 74 | 85 | 26 | 6,650,000$/3yrs | |||
![]() | 0 | LW/RW | 100.00 | 65 | 33 | 90 | 75 | 77 | 82 | 81 | 76 | 57 | 73 | 81 | 73 | 78 | 73 | 72 | 0 | 74 | 85 | 28 | 3,250,000$/2yrs | |||
![]() | 0 | C | 100.00 | 87 | 54 | 77 | 66 | 87 | 81 | 90 | 69 | 85 | 70 | 70 | 84 | 70 | 76 | 80 | 0 | 73 | 83 | 30 | 3,250,000$/4yrs | |||
![]() | 0 | RW | 100.00 | 75 | 31 | 84 | 70 | 57 | 83 | 87 | 72 | 59 | 73 | 74 | 76 | 73 | 66 | 65 | 0 | 74 | 82 | 24 | 1,250,000$/1yrs | |||
![]() | 0 | LW | 100.00 | 74 | 42 | 78 | 70 | 79 | 81 | 78 | 73 | 59 | 74 | 72 | 71 | 72 | 77 | 75 | 0 | 74 | 82 | 30 | 3,250,000$/2yrs | |||
![]() | 0 | RW | 100.00 | 58 | 33 | 94 | 74 | 82 | 81 | 85 | 71 | 57 | 73 | 73 | 66 | 72 | 62 | 61 | 0 | 74 | 80 | 22 | 2,300,000$/2yrs | |||
![]() | 10 | C/RW | 100.00 | 67 | 35 | 92 | 67 | 80 | 76 | 84 | 70 | 60 | 67 | 74 | 65 | 72 | 70 | 69 | 0 | 74 | 79 | 27 | 1,250,000$/3yrs | |||
![]() | 0 | LW/RW | 100.00 | 79 | 33 | 92 | 58 | 80 | 73 | 81 | 64 | 59 | 66 | 64 | 70 | 64 | 78 | 77 | 0 | 27 | 77 | 31 | 1,200,000$/2yrs | |||
![]() | 0 | C | 100.00 | 75 | 40 | 66 | 67 | 72 | 66 | 73 | 65 | 69 | 67 | 68 | 62 | 67 | 63 | 60 | 0 | 34 | 75 | 23 | 750,000$/1yrs | |||
![]() | 98 | D | 100.00 | 79 | 40 | 75 | 84 | 84 | 94 | 90 | 79 | 30 | 83 | 68 | 90 | 73 | 67 | 65 | 0 | 68 | 92 | 24 | 5,500,000$/2yrs | |||
![]() | 0 | D | 100.00 | 71 | 34 | 84 | 67 | 87 | 93 | 89 | 72 | 30 | 75 | 67 | 86 | 69 | 81 | 89 | 0 | 73 | 87 | 33 | 6,100,000$/3yrs | |||
![]() | 19 | D | 100.00 | 84 | 38 | 80 | 65 | 80 | 89 | 89 | 71 | 30 | 73 | 61 | 90 | 66 | 75 | 73 | 0 | 74 | 86 | 29 | 2,750,000$/1yrs | |||
![]() | 6 | D | 100.00 | 72 | 36 | 72 | 74 | 86 | 94 | 80 | 71 | 30 | 78 | 73 | 80 | 72 | 67 | 72 | 0 | 74 | 86 | 25 | 4,600,000$/3yrs | |||
![]() | 0 | D | 100.00 | 66 | 34 | 89 | 60 | 77 | 89 | 88 | 70 | 30 | 72 | 61 | 89 | 66 | 82 | 91 | 0 | 74 | 84 | 33 | 4,500,000$/3yrs | |||
![]() | 24 | D | 100.00 | 87 | 42 | 66 | 59 | 87 | 81 | 80 | 60 | 30 | 64 | 61 | 70 | 60 | 80 | 77 | 0 | 77 | 77 | 32 | 1,250,000$/2yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | LW/RW | 100.00 | 90 | 73 | 50 | 64 | 84 | 73 | 80 | 66 | 60 | 66 | 66 | 65 | 66 | 70 | 65 | 0 | 52 | 75 | 27 | 1,300,000$/2yrs | |||
TEAM AVERAGE | 100.00 | 74 | 39 | 81 | 71 | 79 | 83 | 85 | 72 | 54 | 74 | 71 | 75 | 72 | 72 | 72 | 0 | 68 | 83 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 100.00 | 85 | 75 | 72 | 99 | 81 | 76 | 82 | 85 | 81 | 85 | 82 | 78 | 82 | 0 | 53 | 85 | 31 | 5,000,000$/3yrs |
![]() | 0 | 100.00 | 73 | 76 | 72 | 76 | 76 | 78 | 78 | 83 | 81 | 82 | 78 | 73 | 77 | 0 | 53 | 82 | 28 | 4,800,000$/2yrs |
Scratches | ||||||||||||||||||||
![]() | 30 | 100.00 | 66 | 68 | 69 | 82 | 74 | 74 | 76 | 83 | 77 | 83 | 76 | 69 | 73 | 0 | 27 | 79 | 26 | 750,000$/1yrs |
TEAM AVERAGE | 100.00 | 75 | 73 | 71 | 86 | 77 | 76 | 79 | 84 | 80 | 83 | 79 | 73 | 77 | 0 | 44 | 82 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Craig Berube | 74 | 79 | 97 | 89 | 81 | 75 | 79 | CAN | 55 | 2 | 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 | 5 | 2 | 3 | 5 | 2 | 0 | 0 | 3 | 15 | 7 | 13 | 13.33% | 1 | 20.95 | 0 | 1 | 1 | 14 | 0 | 0 | 0 | 10 | 0 | 0 | 52.46% | 122 | 0 | 0 | 0 | 0 | 0.95 | 0 | 0 | |
2 | Ilya Mikheyev | 0 | LW/RW | 5 | 1 | 3 | 4 | -4 | 2 | 0 | 7 | 12 | 7 | 11 | 8.33% | 0 | 19.89 | 0 | 1 | 1 | 11 | 0 | 0 | 0 | 20 | 0 | 0 | 55.56% | 9 | 0 | 0 | 0 | 0 | 0.80 | 0 | 0 | |
3 | Adam Lowry | 0 | C | 5 | 2 | 1 | 3 | 0 | 0 | 0 | 8 | 8 | 2 | 7 | 25.00% | 3 | 15.98 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 22 | 0 | 0 | 48.54% | 103 | 0 | 0 | 0 | 0 | 0.75 | 0 | 0 | |
4 | Christopher Tanev | 0 | D | 5 | 0 | 3 | 3 | 0 | 0 | 0 | 0 | 6 | 3 | 1 | 0.00% | 7 | 19.16 | 0 | 0 | 0 | 11 | 0 | 0 | 0 | 21 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.63 | 0 | 0 | |
5 | Jonathan Huberdeau | 0 | LW | 5 | 2 | 1 | 3 | 2 | 4 | 0 | 11 | 24 | 3 | 12 | 8.33% | 1 | 19.45 | 1 | 0 | 1 | 14 | 0 | 0 | 0 | 2 | 1 | 0 | 83.33% | 6 | 0 | 0 | 0 | 0 | 0.62 | 0 | 0 | |
6 | Mikhail Sergachev | 98 | D | 5 | 0 | 3 | 3 | -2 | 6 | 0 | 15 | 5 | 6 | 3 | 0.00% | 8 | 24.91 | 0 | 1 | 1 | 14 | 0 | 0 | 0 | 12 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.48 | 0 | 0 | |
7 | Nick Suzuki | 14 | C/RW | 5 | 3 | 0 | 3 | -2 | 0 | 0 | 7 | 9 | 2 | 10 | 33.33% | 3 | 17.72 | 1 | 0 | 1 | 11 | 0 | 0 | 0 | 9 | 0 | 0 | 55.56% | 99 | 0 | 0 | 0 | 0 | 0.68 | 0 | 0 | |
8 | Kailer Yamamoto | 0 | RW | 5 | 1 | 1 | 2 | 2 | 2 | 0 | 7 | 12 | 1 | 6 | 8.33% | 2 | 11.43 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 40.00% | 5 | 0 | 0 | 0 | 0 | 0.70 | 0 | 0 | |
9 | Jake McCabe | 19 | D | 5 | 0 | 2 | 2 | 1 | 6 | 0 | 14 | 1 | 1 | 2 | 0.00% | 14 | 19.18 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 14 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.42 | 0 | 0 | |
10 | Mattias Ekholm | 0 | D | 5 | 0 | 2 | 2 | -3 | 6 | 0 | 6 | 7 | 0 | 5 | 0.00% | 11 | 22.45 | 0 | 0 | 0 | 11 | 0 | 0 | 0 | 1 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.36 | 0 | 0 | |
11 | Tanner Pearson | 0 | LW | 5 | 0 | 2 | 2 | 2 | 2 | 0 | 3 | 10 | 2 | 4 | 0.00% | 0 | 11.32 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 66.67% | 3 | 0 | 0 | 0 | 0 | 0.71 | 0 | 0 | |
12 | Kaapo Kakko | 0 | RW | 5 | 0 | 2 | 2 | -2 | 0 | 0 | 5 | 7 | 4 | 3 | 0.00% | 0 | 15.62 | 0 | 1 | 1 | 11 | 0 | 0 | 0 | 0 | 0 | 0 | 50.00% | 2 | 0 | 0 | 0 | 0 | 0.51 | 0 | 0 | |
13 | Brock Boeser | 6 | RW | 5 | 1 | 0 | 1 | 2 | 0 | 0 | 3 | 14 | 3 | 12 | 7.14% | 0 | 18.86 | 0 | 0 | 0 | 14 | 0 | 0 | 0 | 0 | 0 | 0 | 63.64% | 11 | 0 | 0 | 0 | 0 | 0.21 | 0 | 0 | |
14 | Jakob Chychrun | 6 | D | 5 | 0 | 1 | 1 | 1 | 2 | 0 | 8 | 2 | 1 | 5 | 0.00% | 2 | 20.01 | 0 | 0 | 0 | 14 | 0 | 0 | 0 | 4 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.20 | 0 | 0 | |
15 | Michael Amadio | 10 | C/RW | 5 | 0 | 0 | 0 | -1 | 0 | 0 | 0 | 4 | 1 | 3 | 0.00% | 0 | 7.49 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 45.00% | 40 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
16 | Tyler Pitlick | 0 | LW/RW | 5 | 0 | 0 | 0 | -1 | 0 | 0 | 3 | 2 | 0 | 2 | 0.00% | 0 | 7.48 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 100.00% | 2 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
17 | Zach Bogosian | 24 | D | 5 | 0 | 0 | 0 | 1 | 8 | 0 | 13 | 1 | 1 | 0 | 0.00% | 3 | 14.68 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 11 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
18 | Linus Karlsson | 0 | C | 5 | 0 | 0 | 0 | -1 | 2 | 0 | 3 | 3 | 0 | 0 | 0.00% | 0 | 7.47 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 50.00% | 4 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
Team Total or Average | 90 | 12 | 24 | 36 | -3 | 40 | 0 | 116 | 142 | 44 | 99 | 8.45% | 55 | 16.34 | 2 | 4 | 6 | 132 | 0 | 0 | 0 | 131 | 1 | 0 | 52.46% | 406 | 0 | 0 | 0 | 0 | 0.49 | 0 | 0 |
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 | Robin Lehner | 3 | 1 | 1 | 0 | 0.900 | 3.53 | 136 | 0 | 0 | 8 | 80 | 0 | 0 | 0 | 0.000 | 0 | 3 | 2 | 0 | 0 | 0 | |
2 | Cal Petersen | 3 | 0 | 3 | 0 | 0.904 | 3.31 | 163 | 0 | 0 | 9 | 94 | 0 | 0 | 0 | 0.000 | 0 | 2 | 3 | 0 | 0 | 0 | |
Team Total or Average | 6 | 1 | 4 | 0 | 0.902 | 3.40 | 300 | 0 | 0 | 17 | 174 | 0 | 0 | 0 | 0.000 | 0 | 5 | 5 | 0 | 0 | 0 |
Projected Total Cap Hit | 0$ |
Projected Cap Space | 82,500,000$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 0$ |
Players In Salary Cap | 18 |
LTIR Players | 4 |
Jets Roster | Pos | Age | Cap Hit | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 |
---|---|---|---|---|---|---|---|---|---|---|---|
Adam Lowry | C | 30 | 3,250,000$ | 3,250,000$ | 3,250,000$ | 3,250,000$ | 3,250,000$ | UFA | |||
Brayden Point ![]() | C | 27 | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ | UFA | ||
Brendan Lemieux ![]() | LW/RW | 27 | 1,300,000$ | 1,300,000$ | 1,300,000$ | UFA | |||||
Brock Boeser | RW | 26 | 6,650,000$ | 6,650,000$ | 6,650,000$ | 6,650,000$ | UFA | ||||
Cal Petersen ![]() | G | 28 | 4,800,000$ | 4,800,000$ | 4,800,000$ | UFA | |||||
Christopher Tanev | D | 33 | 4,500,000$ | 4,500,000$ | 4,500,000$ | 4,500,000$ | UFA | ||||
Erik Kallgren ![]() | G | 26 | 750,000$ | 750,000$ | |||||||
Ilya Mikheyev | LW/RW | 28 | 3,250,000$ | 3,250,000$ | 3,250,000$ | UFA | |||||
Jake McCabe | D | 29 | 2,750,000$ | 2,750,000$ | UFA | ||||||
Jakob Chychrun | D | 25 | 4,600,000$ | 4,600,000$ | 4,600,000$ | 4,600,000$ | |||||
Jonathan Huberdeau | LW | 29 | 5,900,000$ | 5,900,000$ | UFA | ||||||
Kaapo Kakko | RW | 22 | 2,300,000$ | 2,300,000$ | 2,300,000$ | RFA | |||||
Kailer Yamamoto ![]() | RW | 24 | 1,250,000$ | 1,250,000$ | RFA | ||||||
Linus Karlsson ![]() ![]() | C | 23 | 750,000$ | 750,000$ | RFA | ||||||
Mattias Ekholm | D | 33 | 6,100,000$ | 6,100,000$ | 6,100,000$ | 6,100,000$ | UFA | ||||
Michael Amadio ![]() | C/RW | 27 | 1,250,000$ | 1,250,000$ | 1,250,000$ | 1,250,000$ | UFA | ||||
Mikhail Sergachev | D | 24 | 5,500,000$ | 5,500,000$ | 5,500,000$ | ||||||
Nick Suzuki | C/RW | 23 | 7,125,000$ | 7,125,000$ | 7,125,000$ | 7,125,000$ | 7,125,000$ | 7,125,000$ | 7,125,000$ | UFA | |
Robin Lehner ![]() | G | 31 | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | UFA | ||||
Tanner Pearson | LW | 30 | 3,250,000$ | 3,250,000$ | 3,250,000$ | UFA | |||||
Tyler Pitlick ![]() | LW/RW | 31 | 1,200,000$ | 1,200,000$ | 1,200,000$ | UFA | |||||
Zach Bogosian ![]() | D | 32 | 1,250,000$ | 1,250,000$ | 1,250,000$ | UFA |
Non-Roster | Pos | Age | Cap Hit | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 |
---|---|---|---|---|---|---|---|---|---|---|---|
Adam Gaudette ![]() ![]() | C | 26 | 900,000$ | 900,000$ | 900,000$ | 900,000$ | UFA | ||||
Andrej Sustr ![]() | D | 32 | 750,000$ | 750,000$ | UFA | ||||||
Andrew Sturtz ![]() | RW | 28 | 850,000$ | 850,000$ | 850,000$ | UFA | |||||
Austin Poganski ![]() ![]() | RW | 27 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Brandon Baddock ![]() ![]() | LW | 28 | 750,000$ | 750,000$ | UFA | ||||||
Cale Morris ![]() ![]() | G | 27 | 750,000$ | 750,000$ | ![]() | ||||||
Cole Cassels ![]() | C | 28 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Danny O'Regan ![]() | C | 29 | 900,000$ | 900,000$ | UFA | ||||||
Doyle Somerby ![]() | D | 28 | 750,000$ | 750,000$ | UFA | ||||||
Dylan Ferguson ![]() ![]() | G | 24 | 750,000$ | 750,000$ | RFA | ||||||
Dylan Holloway ![]() | C/LW/RW | 21 | 925,000$ | 925,000$ | 925,000$ | RFA | |||||
Jacob Doty ![]() | RW | 29 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Jake Bischoff ![]() | D | 28 | 750,000$ | 750,000$ | 750,000$ | UFA | |||||
Kaden Fulcher ![]() | G | 24 | 800,000$ | 800,000$ | 800,000$ | ![]() | |||||
Kale Kessy ![]() | LW | 30 | 800,000$ | 800,000$ | UFA | ||||||
Kevin Hancock ![]() | LW | 25 | 750,000$ | 750,000$ | ![]() | ||||||
Lucas Johansen ![]() | D | 25 | 750,000$ | 750,000$ | 750,000$ | ![]() | |||||
Matthew Strome ![]() ![]() | LW | 24 | 750,000$ | 750,000$ | 750,000$ | ![]() | |||||
Michal Teply ![]() ![]() | RW | 22 | 820,000$ | 820,000$ | 820,000$ | RFA | |||||
Nathan Beaulieu ![]() | D | 30 | 750,000$ | 750,000$ | 750,000$ | UFA | |||||
Radim Simek ![]() | D | 30 | 1,200,000$ | 1,200,000$ | UFA | ||||||
Ross Johnston ![]() ![]() | LW | 29 | 900,000$ | 900,000$ | 900,000$ | UFA | |||||
Steven Kampfer ![]() ![]() | D | 34 | 750,000$ | 750,000$ | UFA | ||||||
Will Bitten ![]() | RW | 24 | 900,000$ | 900,000$ | 900,000$ | ![]() | |||||
Zack MacEwen ![]() ![]() | C/RW | 26 | 950,000$ | 950,000$ | ![]() |
Forward Lines | |||||||
---|---|---|---|---|---|---|---|
|
|
| |||||
|
|
| |||||
|
|
| |||||
|
|
|
Defensive Pairings | |||||||
---|---|---|---|---|---|---|---|
|
| ||||||
|
| ||||||
|
|
1st Power Play Unit | |||||||
---|---|---|---|---|---|---|---|
|
|
| |||||
|
|
2nd Power Play Unit | |||||||
---|---|---|---|---|---|---|---|
|
|
| |||||
|
|
Goalies | |||||||
---|---|---|---|---|---|---|---|
|
|
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 | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 12 | 17 | -5 | 2 | 0.200 | 12 | 24 | 36 | 0 | 0 | 6 | 4 | 1 | 1 | 142 | 51 | 45 | 44 | 2 | 174 | 55 | 40 | 116 | 15 | 2 | 13.33% | 19 | 6 | 68.42% | 0 | 73 | 142 | 51.41% | 99 | 191 | 51.83% | 41 | 73 | 56.16% | 118 | 82 | 121 | 35 | 60 | 31 | 47.6% | 8.5% | 90.2% | 98.7 | Unlucky | |
_Vs Division | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 12 | 17 | -5 | 2 | 0.200 | 12 | 24 | 36 | 0 | 0 | 6 | 4 | 1 | 1 | 142 | 51 | 45 | 44 | 2 | 174 | 55 | 40 | 116 | 15 | 2 | 13.33% | 19 | 6 | 68.42% | 0 | 73 | 142 | 51.41% | 99 | 191 | 51.83% | 41 | 73 | 56.16% | 118 | 82 | 121 | 35 | 60 | 31 | 47.6% | 8.5% | 90.2% | 98.7 | Unlucky | |
_Vs Conference | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 12 | 17 | -5 | 2 | 0.200 | 12 | 24 | 36 | 0 | 0 | 6 | 4 | 1 | 1 | 142 | 51 | 45 | 44 | 2 | 174 | 55 | 40 | 116 | 15 | 2 | 13.33% | 19 | 6 | 68.42% | 0 | 73 | 142 | 51.41% | 99 | 191 | 51.83% | 41 | 73 | 56.16% | 118 | 82 | 121 | 35 | 60 | 31 | 47.6% | 8.5% | 90.2% | 98.7 | Unlucky | |
_Since Last GM Reset | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 12 | 17 | -5 | 2 | 0.200 | 12 | 24 | 36 | 0 | 0 | 6 | 4 | 1 | 1 | 142 | 51 | 45 | 44 | 2 | 174 | 55 | 40 | 116 | 15 | 2 | 13.33% | 19 | 6 | 68.42% | 0 | 73 | 142 | 51.41% | 99 | 191 | 51.83% | 41 | 73 | 56.16% | 118 | 82 | 121 | 35 | 60 | 31 | 47.6% | 8.5% | 90.2% | 98.7 | Unlucky | |
Total | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 12 | 17 | -5 | 2 | 0.200 | 12 | 24 | 36 | 0 | 0 | 6 | 4 | 1 | 1 | 142 | 51 | 45 | 44 | 2 | 174 | 55 | 40 | 116 | 15 | 2 | 13.33% | 19 | 6 | 68.42% | 0 | 73 | 142 | 51.41% | 99 | 191 | 51.83% | 41 | 73 | 56.16% | 118 | 82 | 121 | 35 | 60 | 31 | 47.6% | 8.5% | 90.2% | 98.7 | Unlucky |
Puck Time | |
---|---|
Offensive Zone | 23 |
Neutral Zone | 12 |
Defensive Zone | 24 |
Puck Time | |
---|---|
Offensive Zone Start | 142 |
Neutral Zone Start | 73 |
Defensive Zone Start | 191 |
Puck Time | |
---|---|
With Puck | 29 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 213 |
Faceoffs Lost | 193 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 10.2 | 9.57 |
2nd Period | 19.2 | 20.31 |
3rd Period | 28.0 | 30.68 |
Overtime | 28.4 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 1.2 | 0.64 |
2nd Period | 2.0 | 1.65 |
3rd Period | 2.2 | 2.67 |
Overtime | 2.4 | 2.83 |
Even Strenght Goal | 10 |
---|---|
PP Goal | 2 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 0 | 1 |
Lost | 2 | 2 |
Overtime Lost | 0 | 0 |
PP Attempt | 15 |
---|---|
PP Goal | 2 |
PK Attempt | 19 |
PK Goal Against | 6 |
Home | |
---|---|
Shots For | 28.4 |
Shots Against | 34.8 |
Goals For | 2.4 |
Goals Against | 3.4 |
Hits | 23.2 |
Shots Blocked | 11.0 |
Pim | 8.0 |
Date | Matchup | Result | Detail | ||
---|---|---|---|---|---|
2023-04-19 | @ | Jets3,Coyotes2 (OT) | RECAP | ||
2023-04-21 | @ | Jets4,Coyotes5 | RECAP | ||
2023-04-23 | @ | Coyotes2,Jets1 | RECAP | ||
2023-04-25 | @ | Coyotes5,Jets3 | RECAP | ||
2023-04-27 | @ | Jets1,Coyotes3 | RECAP |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
81,725,000$ | 0$ | 0$ | 775,000$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | Bell MTS Centre | |
City | Winnipeg | ||
Capacity | 18000 | ||
Season Ticket Holders | 40% |
Arena Capacity - Ticket Price Attendance - % | |||||
---|---|---|---|---|---|
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
Arena Capacity | 6000 | 5000 | 2000 | 4000 | 1000 |
Ticket Price | 100$ | 60$ | 35$ | 25$ | 200$ |
Attendance | 12000 | 10000 | 4000 | 8000 | 2000 |
Attendance PCT | 100.00% | 100.00% | 100.00% | 100.00% | 100.00% |
Income | |||||
---|---|---|---|---|---|
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
39 | 18000 - 100.00% | 1,587,500$ | 3,175,000$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
81,725,000$ | 81,725,000$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
0$ | 0$ | 0$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 2 | 0$ | 0$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
0$ | 81,725,000$ | 47,455,390$ | 47,455,390$ |
Left Wing | Center | Right Wing | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
|
|
Defense #1 | Defense #2 | Goalie | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
|
|
Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
---|---|---|---|---|---|---|---|
2023 | |||||||
2024 | |||||||
2025 | |||||||
2026 | |||||||
2027 |
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 | |||
Andong Song | |||||
Artur Cholach | 2021 | 206 | |||
Ben Brinkman | 2019 | 167 | |||
David Ma | 2020 | 169 | |||
Fyodor Svechkov | 2021 | 14 | |||
Gage Alexander | 2021 | 150 | |||
Ivan Miroshnichenko | 2022 | 17 | |||
Kalle Loponen | 2019 | 213 | 5.5 - 3.5 | ||
Kirill Tyutyayev | |||||
Lucas Mercuri | |||||
Lucas Ramberg | 2020 | 189 | |||
Matthew Knies | 2021 | 64 | |||
Simon Gamache | |||||
Tuukka Tieksola | 2019 | 128 | 7.0 - 4.5 | ||
Valentin Nussbaumer | 2019 | 190 | |||
Xavier Bourgeault | 2021 | 27 |
|