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Chicago Blackhawks 10-10-0, 20pts · 3rd 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 | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | C/LW/RW | 100.00 | 66 | 33 | 76 | 87 | 76 | 85 | 89 | 83 | 59 | 87 | 82 | 64 | 82 | 70 | 68 | 0 | 80 | 90 | 26 | 5,000,000$/2yrs | |||
![]() | 0 | C/LW/RW | 96.00 | 74 | 35 | 86 | 84 | 65 | 89 | 90 | 81 | 60 | 81 | 84 | 71 | 83 | 68 | 67 | 0 | 81 | 89 | 25 | 6,500,000$/3yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 80 | 41 | 80 | 79 | 78 | 86 | 88 | 79 | 81 | 83 | 79 | 73 | 79 | 79 | 85 | 0 | 81 | 89 | 31 | 6,500,000$/6yrs | |||
![]() | 0 | LW/RW | 100.00 | 55 | 33 | 90 | 86 | 77 | 84 | 89 | 82 | 59 | 83 | 84 | 63 | 83 | 67 | 66 | 0 | 80 | 89 | 25 | 3,300,000$/9yrs | |||
![]() | 0 | RW | 99.00 | 56 | 32 | 92 | 80 | 67 | 90 | 89 | 80 | 60 | 87 | 79 | 62 | 80 | 84 | 96 | 0 | 58 | 89 | 34 | 10,500,000$/5yrs | |||
![]() | 0 | C | 100.00 | 63 | 33 | 78 | 79 | 82 | 87 | 90 | 77 | 83 | 85 | 74 | 74 | 76 | 78 | 76 | 0 | 80 | 87 | 31 | 7,800,000$/3yrs | |||
![]() | 17 | C | 98.00 | 57 | 33 | 89 | 81 | 81 | 83 | 90 | 77 | 84 | 82 | 78 | 67 | 77 | 69 | 68 | 0 | 80 | 86 | 26 | 3,000,000$/2yrs | |||
![]() | 0 | C | 100.00 | 63 | 32 | 95 | 74 | 72 | 82 | 90 | 73 | 83 | 75 | 73 | 82 | 73 | 76 | 76 | 0 | 80 | 84 | 30 | 2,125,000$/2yrs | |||
![]() | 0 | C/LW | 100.00 | 77 | 47 | 73 | 68 | 81 | 81 | 90 | 69 | 79 | 72 | 69 | 86 | 69 | 76 | 81 | 0 | 80 | 83 | 30 | 3,641,667$/6yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 78 | 40 | 63 | 73 | 85 | 80 | 84 | 76 | 59 | 78 | 75 | 65 | 76 | 72 | 68 | 0 | 80 | 83 | 27 | 1,400,000$/1yrs | |||
![]() | 0 | C/RW | 100.00 | 84 | 33 | 81 | 64 | 76 | 78 | 85 | 69 | 86 | 70 | 71 | 89 | 70 | 81 | 79 | 0 | 80 | 83 | 33 | 1,300,000$/3yrs | |||
![]() | 0 | LW/RW | 100.00 | 74 | 34 | 91 | 65 | 73 | 79 | 87 | 68 | 59 | 66 | 71 | 83 | 69 | 74 | 74 | 0 | 80 | 81 | 29 | 2,500,000$/2yrs | |||
![]() | 0 | D | 100.00 | 86 | 35 | 81 | 75 | 78 | 98 | 87 | 76 | 30 | 85 | 72 | 85 | 74 | 87 | 96 | 0 | 79 | 92 | 36 | 7,250,000$/3yrs | |||
![]() | 0 | D | 99.00 | 73 | 33 | 79 | 76 | 78 | 98 | 85 | 71 | 30 | 81 | 70 | 75 | 71 | 69 | 75 | 0 | 80 | 86 | 26 | 8,000,000$/6yrs | |||
![]() | 0 | D | 98.00 | 86 | 42 | 81 | 60 | 87 | 88 | 89 | 72 | 30 | 70 | 58 | 92 | 65 | 80 | 78 | 0 | 81 | 85 | 32 | 2,850,000$/3yrs | |||
![]() | 0 | D | 99.00 | 67 | 33 | 83 | 72 | 84 | 91 | 90 | 68 | 30 | 73 | 76 | 81 | 72 | 74 | 73 | 0 | 79 | 84 | 29 | 5,250,000$/2yrs | |||
![]() | 0 | D | 100.00 | 78 | 33 | 94 | 69 | 76 | 86 | 69 | 69 | 30 | 78 | 68 | 73 | 69 | 81 | 80 | 0 | 31 | 84 | 32 | 800,000$/2yrs | |||
![]() | 75 | D | 99.00 | 78 | 37 | 87 | 64 | 91 | 87 | 80 | 68 | 30 | 69 | 59 | 85 | 63 | 76 | 75 | 0 | 79 | 83 | 30 | 750,000$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 28 | D | 100.00 | 75 | 38 | 77 | 61 | 84 | 79 | 74 | 63 | 30 | 68 | 70 | 72 | 67 | 81 | 78 | 0 | 49 | 79 | 32 | 850,000$/1yrs | |||
TEAM AVERAGE | 99.37 | 72 | 36 | 83 | 74 | 78 | 86 | 86 | 74 | 56 | 78 | 73 | 76 | 74 | 76 | 77 | 0 | 75 | 86 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 97.00 | 82 | 89 | 78 | 87 | 84 | 81 | 85 | 90 | 87 | 89 | 85 | 88 | 92 | 0 | 80 | 89 | 37 | 5,800,000$/1yrs |
![]() | 0 | 100.00 | 84 | 87 | 77 | 84 | 89 | 84 | 89 | 89 | 89 | 91 | 89 | 69 | 74 | 0 | 81 | 89 | 26 | 766,667$/3yrs |
Scratches | ||||||||||||||||||||
![]() | 0 | 100.00 | 88 | 76 | 72 | 99 | 82 | 81 | 84 | 81 | 85 | 79 | 84 | 74 | 78 | 0 | 19 | 86 | 29 | 950,000$/1yrs |
TEAM AVERAGE | 99.00 | 85 | 84 | 76 | 90 | 85 | 82 | 86 | 87 | 87 | 86 | 86 | 77 | 81 | 0 | 60 | 88 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Jay Woodcroft | 81 | 76 | 99 | 83 | 80 | 76 | 76 | CAN | 59 | 3 | 1,000,000$ |
General Manager | Yan Turgeon |
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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 | Evgeny Kuznetsov | 0 | C | 20 | 6 | 13 | 19 | -6 | 6 | 0 | 21 | 45 | 14 | 40 | 13.33% | 9 | 18.82 | 2 | 7 | 9 | 63 | 0 | 0 | 0 | 0 | 2 | 1 | 51.32% | 493 | 0 | 0 | 0 | 0 | 1.01 | 0 | 0 | |
2 | Alex DeBrincat | 0 | C/LW/RW | 20 | 8 | 9 | 17 | -4 | 10 | 0 | 56 | 80 | 25 | 60 | 10.00% | 2 | 22.39 | 1 | 3 | 4 | 66 | 0 | 0 | 0 | 7 | 0 | 1 | 40.63% | 32 | 0 | 0 | 0 | 0 | 0.76 | 0 | 0 | |
3 | Dylan Strome | 17 | C | 20 | 7 | 8 | 15 | -1 | 2 | 0 | 9 | 50 | 9 | 38 | 14.00% | 2 | 20.85 | 3 | 4 | 7 | 58 | 0 | 0 | 0 | 0 | 1 | 0 | 50.99% | 506 | 0 | 0 | 0 | 0 | 0.72 | 0 | 0 | |
4 | Kris Letang | 0 | D | 20 | 2 | 10 | 12 | 3 | 16 | 0 | 31 | 33 | 8 | 19 | 6.06% | 20 | 23.91 | 2 | 1 | 3 | 61 | 0 | 0 | 0 | 24 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.50 | 0 | 0 | |
5 | Brayden McNabb | 0 | D | 20 | 1 | 10 | 11 | 6 | 31 | 5 | 28 | 26 | 8 | 16 | 3.85% | 49 | 23.14 | 1 | 2 | 3 | 43 | 0 | 0 | 0 | 46 | 1 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.48 | 0 | 0 | |
6 | Jordan Kyrou | 0 | LW/RW | 20 | 6 | 5 | 11 | -3 | 0 | 0 | 7 | 64 | 17 | 42 | 9.38% | 1 | 17.84 | 2 | 3 | 5 | 60 | 0 | 0 | 0 | 0 | 3 | 1 | 37.50% | 24 | 0 | 0 | 0 | 0 | 0.62 | 0 | 0 | |
7 | Patrick Kane | 0 | RW | 20 | 6 | 5 | 11 | -4 | 2 | 0 | 7 | 29 | 17 | 35 | 20.69% | 1 | 21.88 | 4 | 1 | 5 | 66 | 0 | 0 | 0 | 0 | 0 | 0 | 42.31% | 26 | 0 | 0 | 0 | 0 | 0.50 | 0 | 0 | |
8 | Jaycob Megna | 75 | D | 20 | 1 | 9 | 10 | -2 | 18 | 0 | 22 | 18 | 6 | 12 | 5.56% | 33 | 18.39 | 0 | 4 | 4 | 59 | 0 | 0 | 0 | 55 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.54 | 0 | 0 | |
9 | Kevin Fiala | 0 | C/LW/RW | 20 | 3 | 7 | 10 | -3 | 6 | 0 | 32 | 61 | 11 | 44 | 4.92% | 3 | 17.92 | 1 | 3 | 4 | 60 | 0 | 0 | 0 | 0 | 1 | 0 | 35.00% | 20 | 0 | 0 | 0 | 0 | 0.56 | 0 | 0 | |
10 | Thomas Chabot | 0 | D | 20 | 2 | 7 | 9 | -12 | 4 | 0 | 32 | 23 | 5 | 19 | 8.70% | 23 | 22.93 | 1 | 3 | 4 | 30 | 0 | 0 | 0 | 50 | 1 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.39 | 0 | 0 | |
11 | Brayden Schenn | 0 | C/LW/RW | 20 | 0 | 6 | 6 | -1 | 4 | 0 | 19 | 40 | 13 | 33 | 0.00% | 1 | 11.38 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 0 | 0 | 55.00% | 20 | 0 | 0 | 0 | 0 | 0.53 | 0 | 0 | |
12 | Brock McGinn | 0 | LW/RW | 20 | 3 | 3 | 6 | -1 | 2 | 0 | 7 | 18 | 3 | 12 | 16.67% | 3 | 7.26 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 32 | 0 | 0 | 50.00% | 6 | 0 | 0 | 2 | 0 | 0.83 | 0 | 0 | |
13 | Frederick Gaudreau | 0 | C | 20 | 4 | 2 | 6 | -1 | 0 | 0 | 1 | 30 | 20 | 32 | 13.33% | 4 | 12.50 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 33 | 1 | 0 | 50.71% | 280 | 0 | 0 | 0 | 0 | 0.48 | 0 | 0 | |
14 | Brady Skjei | 0 | D | 20 | 1 | 4 | 5 | -9 | 4 | 0 | 23 | 28 | 10 | 22 | 3.57% | 34 | 23.76 | 0 | 3 | 3 | 59 | 0 | 0 | 0 | 56 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.21 | 0 | 0 | |
15 | Mason Marchment | 0 | C/LW/RW | 20 | 3 | 2 | 5 | -1 | 12 | 0 | 24 | 27 | 11 | 22 | 11.11% | 1 | 11.15 | 0 | 0 | 0 | 6 | 0 | 0 | 0 | 0 | 0 | 1 | 23.08% | 26 | 0 | 0 | 0 | 0 | 0.45 | 0 | 0 | |
16 | Barclay Goodrow | 0 | C/LW | 20 | 1 | 2 | 3 | -1 | 4 | 0 | 7 | 12 | 2 | 7 | 8.33% | 2 | 9.35 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 74 | 0 | 0 | 35.29% | 17 | 0 | 0 | 0 | 0 | 0.32 | 0 | 0 | |
17 | Nic Dowd | 0 | C/RW | 20 | 2 | 1 | 3 | -1 | 2 | 0 | 20 | 21 | 8 | 14 | 9.52% | 5 | 9.42 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 75 | 0 | 0 | 50.34% | 294 | 0 | 0 | 0 | 0 | 0.32 | 0 | 0 | |
18 | Michael Del Zotto | 0 | D | 20 | 0 | 0 | 0 | -4 | 10 | 0 | 17 | 9 | 2 | 7 | 0.00% | 16 | 12.47 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
Team Total or Average | 360 | 56 | 103 | 159 | -45 | 133 | 5 | 363 | 614 | 189 | 474 | 9.12% | 209 | 16.97 | 17 | 34 | 51 | 636 | 0 | 0 | 0 | 467 | 10 | 4 | 49.71% | 1744 | 0 | 0 | 2 | 0 | 0.52 | 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 | Logan Thompson | 11 | 6 | 3 | 2 | 0.917 | 2.47 | 705 | 4 | 1 | 29 | 350 | 0 | 0 | 0 | 0.000 | 0 | 11 | 8 | 1 | 0 | 0 | |
2 | Jonathan Quick | 9 | 4 | 4 | 1 | 0.895 | 3.01 | 539 | 0 | 0 | 27 | 258 | 0 | 0 | 0 | 0.000 | 0 | 9 | 11 | 0 | 1 | 0 | |
Team Total or Average | 20 | 10 | 7 | 3 | 0.908 | 2.70 | 1245 | 4 | 1 | 56 | 608 | 0 | 0 | 0 | 0.000 | 0 | 20 | 19 | 1 | 1 | 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 |
Blackhawks Roster | Pos | Age | Cap Hit | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 |
---|---|---|---|---|---|---|---|---|---|---|---|
Alex DeBrincat | C/LW/RW | 25 | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | |||||
Anthony Stolarz ![]() ![]() | G | 29 | 950,000$ | 950,000$ | UFA | ||||||
Barclay Goodrow | C/LW | 30 | 3,641,667$ | 3,641,667$ | 3,641,667$ | 3,641,667$ | 3,641,667$ | 3,641,667$ | 3,641,667$ | UFA | |
Brady Skjei | D | 29 | 5,250,000$ | 5,250,000$ | 5,250,000$ | UFA | |||||
Brayden McNabb | D | 32 | 2,850,000$ | 2,850,000$ | 2,850,000$ | 2,850,000$ | UFA | ||||
Brayden Schenn | C/LW/RW | 31 | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | UFA | |
Brock McGinn | LW/RW | 29 | 2,500,000$ | 2,500,000$ | 2,500,000$ | UFA | |||||
Dylan Strome | C | 26 | 3,000,000$ | 3,000,000$ | 3,000,000$ | ||||||
Evgeny Kuznetsov | C | 31 | 7,800,000$ | 7,800,000$ | 7,800,000$ | 7,800,000$ | UFA | ||||
Frederick Gaudreau | C | 30 | 2,125,000$ | 2,125,000$ | 2,125,000$ | UFA | |||||
Jaycob Megna ![]() | D | 30 | 750,000$ | 750,000$ | UFA | ||||||
Jonathan Quick | G | 37 | 5,800,000$ | 5,800,000$ | UFA | ||||||
Jordan Kyrou | LW/RW | 25 | 3,300,000$ | 3,300,000$ | 8,125,000$ | 8,125,000$ | 8,125,000$ | 8,125,000$ | 8,125,000$ | 8,125,000$ | 8,125,000$ |
Kevin Fiala | C/LW/RW | 26 | 5,000,000$ | 5,000,000$ | 5,000,000$ | ||||||
Kris Letang ![]() | D | 36 | 7,250,000$ | 7,250,000$ | 7,250,000$ | 7,250,000$ | UFA | ||||
Logan Thompson ![]() ![]() | G | 26 | 766,667$ | 766,667$ | 766,667$ | 766,667$ | UFA | ||||
Mason Marchment | C/LW/RW | 27 | 1,400,000$ | 1,400,000$ | UFA | ||||||
Michael Del Zotto ![]() ![]() | D | 32 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Michael Stone ![]() | D | 32 | 850,000$ | 850,000$ | UFA | ||||||
Nic Dowd | C/RW | 33 | 1,300,000$ | 1,300,000$ | 1,300,000$ | 1,300,000$ | UFA | ||||
Patrick Kane | RW | 34 | 10,500,000$ | 10,500,000$ | 8,500,000$ | 8,500,000$ | 8,500,000$ | 8,500,000$ | UFA | ||
Thomas Chabot | D | 26 | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | UFA |
Non-Roster | Pos | Age | Cap Hit | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 |
---|---|---|---|---|---|---|---|---|---|---|---|
Adam Brooks ![]() | C | 27 | 1,000,000$ | 1,000,000$ | ![]() | ||||||
Alex Petrovic ![]() | D | 31 | 750,000$ | 750,000$ | 750,000$ | UFA | |||||
Blade Jenkins ![]() | LW | 22 | 803,333$ | 803,333$ | RFA | ||||||
Brad Hunt ![]() | D | 34 | 800,000$ | 800,000$ | UFA | ||||||
Brendan Guhle ![]() | D | 25 | 750,000$ | 750,000$ | ![]() | ||||||
Brett Harrison ![]() | C | 19 | 859,167$ | 859,167$ | 859,167$ | 859,167$ | RFA | ||||
CJ Suess ![]() | LW | 29 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Cameron Gaunce ![]() | D | 33 | 750,000$ | 750,000$ | UFA | ||||||
Cameron Hillis ![]() | C | 22 | 838,333$ | 838,333$ | RFA | ||||||
Chad Krys ![]() | D | 25 | 750,000$ | 750,000$ | ![]() | ||||||
Chad Yetman ![]() | RW | 23 | 850,000$ | 850,000$ | RFA | ||||||
Christian Jaros ![]() | D | 27 | 1,050,000$ | 1,050,000$ | 1,050,000$ | UFA | |||||
Cole Reinhardt ![]() | LW | 23 | 813,333$ | 813,333$ | 813,333$ | RFA | |||||
Connor Corcoran ![]() | D | 22 | 925,000$ | 925,000$ | RFA | ||||||
Curtis McKenzie ![]() | LW | 32 | 900,000$ | 900,000$ | UFA | ||||||
Derrick Pouliot ![]() | D | 29 | 800,000$ | 800,000$ | UFA | ||||||
Devin Shore ![]() | C | 28 | 900,000$ | 900,000$ | UFA | ||||||
Dryden McKay ![]() ![]() | G | 25 | 750,000$ | 750,000$ | ![]() | ||||||
Garret Sparks ![]() | G | 29 | 1,250,000$ | 1,250,000$ | UFA | ||||||
Jake Virtanen ![]() | RW | 26 | 1,200,000$ | 1,200,000$ | ![]() | ||||||
Jaxson Stauber ![]() ![]() | G | 24 | 883,750$ | 883,750$ | RFA | ||||||
John Ludvig ![]() | D | 22 | 853,333$ | 853,333$ | RFA | ||||||
Logan Shaw ![]() ![]() | C/RW | 30 | 950,000$ | 950,000$ | UFA | ||||||
Louie Belpedio ![]() | D | 27 | 800,000$ | 800,000$ | ![]() | ||||||
Lucas Edmonds ![]() | LW/RW | 22 | 861,667$ | 861,667$ | 861,667$ | 861,667$ | RFA | ||||
Marc-Andre Gaudet ![]() | D | 20 | 849,167$ | 849,167$ | 849,167$ | 849,167$ | RFA | ||||
Markus Phillips ![]() | D | 24 | 796,667$ | 796,667$ | 796,667$ | ![]() | |||||
Michael McLeod ![]() ![]() | C/RW | 25 | 1,200,000$ | 1,200,000$ | ![]() | ||||||
Nolan Patrick ![]() | C | 24 | 1,250,000$ | 1,250,000$ | RFA | ||||||
Ruslan Iskhakov ![]() | C | 22 | 855,000$ | 855,000$ | 855,000$ | RFA | |||||
Sam Anas ![]() | RW | 29 | 825,000$ | 825,000$ | UFA | ||||||
Tanner Dickinson ![]() | C | 21 | 848,333$ | 848,333$ | 848,333$ | RFA | |||||
Taylor Ward ![]() | RW | 25 | 842,500$ | 842,500$ | ![]() | ||||||
Tyler Angle ![]() | LW | 22 | 850,833$ | 850,833$ | 850,833$ | RFA | |||||
Tyler Ennis ![]() ![]() | LW/RW | 33 | 900,000$ | 900,000$ | UFA | ||||||
Tyler Sikura ![]() ![]() | C | 31 | 750,000$ | 750,000$ | 750,000$ | UFA | |||||
Victor Lodin ![]() | C/LW | 23 | 830,000$ | 830,000$ | RFA | ||||||
Victor Mete ![]() | D | 24 | 1,100,000$ | 1,100,000$ | ![]() |
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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 |
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1 | 6 | 2 | 4 | 0 | 0 | 0 | 0 | 0 | 17 | 19 | -2 | 4 | 0.333 | 17 | 31 | 48 | 0 | 0 | 7 | 5 | 5 | 0 | 182 | 44 | 56 | 76 | 6 | 188 | 73 | 46 | 110 | 21 | 5 | 23.81% | 21 | 4 | 80.95% | 0 | 364 | 725 | 50.21% | 334 | 695 | 48.06% | 169 | 324 | 52.16% | 145 | 101 | 147 | 44 | 75 | 37 | 44.4% | 9.3% | 89.9% | 99.2 | FUN | |
2 | 7 | 4 | 3 | 0 | 0 | 0 | 0 | 0 | 21 | 17 | 4 | 8 | 0.571 | 21 | 41 | 62 | 0 | 1 | 4 | 6 | 9 | 2 | 240 | 74 | 66 | 77 | 23 | 203 | 68 | 53 | 130 | 30 | 8 | 26.67% | 24 | 4 | 83.33% | 0 | 364 | 725 | 50.21% | 334 | 695 | 48.06% | 169 | 324 | 52.16% | 194 | 137 | 166 | 53 | 96 | 50 | 50.0% | 8.8% | 91.6% | 100.4 | DULL | |
3 | 7 | 4 | 3 | 0 | 0 | 0 | 0 | 0 | 18 | 20 | -2 | 8 | 0.571 | 18 | 31 | 49 | 0 | 0 | 7 | 4 | 7 | 0 | 192 | 64 | 59 | 69 | 0 | 217 | 68 | 38 | 123 | 25 | 4 | 16.00% | 19 | 0 | 100.00% | 0 | 364 | 725 | 50.21% | 334 | 695 | 48.06% | 169 | 324 | 52.16% | 160 | 111 | 175 | 50 | 84 | 41 | 41.2% | 9.4% | 90.8% | 100.2 | FUN | |
_Vs Division | 14 | 8 | 6 | 0 | 0 | 0 | 0 | 0 | 39 | 37 | 2 | 16 | 0.571 | 39 | 72 | 111 | 0 | 1 | 11 | 10 | 16 | 2 | 432 | 138 | 125 | 146 | 23 | 420 | 136 | 91 | 253 | 55 | 12 | 21.82% | 43 | 4 | 90.70% | 0 | 364 | 725 | 50.21% | 334 | 695 | 48.06% | 169 | 324 | 52.16% | 354 | 249 | 342 | 104 | 180 | 92 | 45.0% | 9.0% | 91.2% | 100.2 | LUCKY | |
_Vs Conference | 20 | 10 | 10 | 0 | 0 | 0 | 0 | 0 | 56 | 56 | 0 | 20 | 0.500 | 56 | 103 | 159 | 0 | 1 | 18 | 15 | 21 | 2 | 614 | 182 | 181 | 222 | 29 | 608 | 209 | 137 | 363 | 76 | 17 | 22.37% | 64 | 8 | 87.50% | 0 | 364 | 725 | 50.21% | 334 | 695 | 48.06% | 169 | 324 | 52.16% | 499 | 350 | 489 | 148 | 256 | 129 | 44.8% | 9.1% | 90.8% | 99.9 | FUN | |
_Since Last GM Reset | 20 | 10 | 10 | 0 | 0 | 0 | 0 | 0 | 56 | 56 | 0 | 20 | 0.500 | 56 | 103 | 159 | 0 | 1 | 18 | 15 | 21 | 2 | 614 | 182 | 181 | 222 | 29 | 608 | 209 | 137 | 363 | 76 | 17 | 22.37% | 64 | 8 | 87.50% | 0 | 364 | 725 | 50.21% | 334 | 695 | 48.06% | 169 | 324 | 52.16% | 499 | 350 | 489 | 148 | 256 | 129 | 44.8% | 9.1% | 90.8% | 99.9 | FUN | |
Total | 20 | 10 | 10 | 0 | 0 | 0 | 0 | 0 | 56 | 56 | 0 | 20 | 0.500 | 56 | 103 | 159 | 0 | 1 | 18 | 15 | 21 | 2 | 614 | 182 | 181 | 222 | 29 | 608 | 209 | 137 | 363 | 76 | 17 | 22.37% | 64 | 8 | 87.50% | 0 | 364 | 725 | 50.21% | 334 | 695 | 48.06% | 169 | 324 | 52.16% | 499 | 350 | 489 | 148 | 256 | 129 | 44.8% | 9.1% | 90.8% | 99.9 | FUN |
Puck Time | |
---|---|
Offensive Zone | 24 |
Neutral Zone | 12 |
Defensive Zone | 24 |
Puck Time | |
---|---|
Offensive Zone Start | 725 |
Neutral Zone Start | 324 |
Defensive Zone Start | 695 |
Puck Time | |
---|---|
With Puck | 31 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 867 |
Faceoffs Lost | 877 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 9.1 | 9.57 |
2nd Period | 18.2 | 20.31 |
3rd Period | 29.3 | 30.68 |
Overtime | 30.7 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.9 | 0.64 |
2nd Period | 1.7 | 1.65 |
3rd Period | 2.7 | 2.67 |
Overtime | 2.8 | 2.83 |
Even Strenght Goal | 39 |
---|---|
PP Goal | 17 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 6 | 4 |
Lost | 4 | 6 |
Overtime Lost | 0 | 0 |
PP Attempt | 76 |
---|---|
PP Goal | 17 |
PK Attempt | 64 |
PK Goal Against | 8 |
Home | |
---|---|
Shots For | 30.7 |
Shots Against | 30.4 |
Goals For | 2.8 |
Goals Against | 2.8 |
Hits | 18.2 |
Shots Blocked | 10.5 |
Pim | 6.9 |
Date | Matchup | Result | Detail | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2023-04-19 | @ | Blues4,Blackhawks3 | RECAP | |||||||||||
2023-04-21 | @ | Blues1,Blackhawks3 | RECAP | |||||||||||
2023-04-23 | @ | Blackhawks2,Blues3 | RECAP | |||||||||||
2023-04-25 | @ | Blackhawks3,Blues4 (OT) | RECAP | |||||||||||
2023-04-27 | @ | Blues0,Blackhawks3 | RECAP | |||||||||||
2023-04-29 | @ | Blackhawks2,Blues1 (OT) | RECAP | |||||||||||
2023-05-01 | @ | Blues4,Blackhawks5 (OT) | RECAP | |||||||||||
2023-05-03 | @ | Blackhawks1,Coyotes4 | RECAP | |||||||||||
2023-05-05 | @ | Blackhawks4,Coyotes2 | RECAP | |||||||||||
2023-05-07 | @ | Coyotes5,Blackhawks2 | RECAP | |||||||||||
2023-05-09 | @ | Coyotes2,Blackhawks3 | RECAP | |||||||||||
2023-05-11 | @ | Blackhawks1,Coyotes3 | RECAP | |||||||||||
2023-05-13 | @ | Coyotes2,Blackhawks4 | RECAP | |||||||||||
2023-05-15 | @ | Blackhawks3,Coyotes2 | RECAP | |||||||||||
2023-05-17 | @ | Canucks3,Blackhawks2 (OT) | RECAP | |||||||||||
2023-05-19 | @ | Canucks4,Blackhawks2 | RECAP | |||||||||||
Trade Deadline --- Trades can’t be done after this day is simulated! | ||||||||||||||
2023-05-21 | @ | Blackhawks3,Canucks4 | RECAP | |||||||||||
2023-05-23 | @ | Blackhawks4,Canucks2 | RECAP | |||||||||||
2023-05-25 | @ | Canucks2,Blackhawks3 | RECAP | |||||||||||
2023-05-27 | @ | Blackhawks3,Canucks4 (OT) | RECAP |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
86,833,334$ | 0$ | 0$ | -4,333,334$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | United Center | |
City | Chicago | ||
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 | 60000 | 50000 | 20000 | 40000 | 10000 |
Attendance PCT | 100.00% | 100.00% | 100.00% | 100.00% | 100.00% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
31 | 18000 - 100.00% | 1,587,500$ | 15,875,000$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
86,833,334$ | 86,833,334$ | 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$ | 86,833,334$ | 55,507,309$ | 55,507,309$ |
Left Wing | Center | Right Wing | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Defense #1 | Defense #2 | Goalie | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
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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. |
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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 |
Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
---|---|---|---|---|---|
Cedric Guindon | 2022 | 107 | |||
Charlie Leddy | 2022 | 146 | |||
Cole O'Hara | 2022 | 125 | |||
Cole Spicer | 2022 | 120 | |||
Connor Kurth | 2022 | 183 | |||
Samuel Savoie | 2022 | 99 | |||
Zakhar Bardakov | 2021 | 218 |
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