Full Scoreboard »» |
Detroit Red Wings Team Overall:70 0-0-0, 0pts |
# | Player | Position | Height | Weight | Age | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | Overall | Condition | Contract | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Scratches | ||||||||||||||||||||||||||
0 | ![]() | C | 5' 11" | 175 | 22 | 65 | 40 | 93 | 99 | 69 | 83 | 86 | 85 | 56 | 89 | 86 | 67 | 57 | 62 | 65 | 0 | 40 | 84 | 100.00 | 3,775,000$/1yrs | |
0 | ![]() | LW | 5' 10" | 202 | 26 | 75 | 40 | 81 | 93 | 85 | 86 | 88 | 81 | 53 | 85 | 90 | 69 | 74 | 61 | 58 | 0 | 40 | 84 | 100.00 | 1,387,500$/2yrs | |
0 | ![]() | C | 6' 1" | 198 | 26 | 68 | 40 | 83 | 87 | 78 | 82 | 89 | 78 | 85 | 84 | 76 | 74 | 62 | 73 | 76 | 0 | 40 | 81 | 100.00 | 6,100,000$/1yrs | |
0 | ![]() | LW | 6' 2" | 179 | 26 | 68 | 40 | 86 | 79 | 67 | 85 | 92 | 78 | 53 | 85 | 77 | 65 | 59 | 69 | 59 | 0 | 40 | 78 | 100.00 | 7,142,857$/1yrs | |
0 | ![]() | C | 6' 3" | 195 | 22 | 76 | 64 | 81 | 83 | 74 | 75 | 91 | 74 | 77 | 80 | 78 | 69 | 54 | 61 | 58 | 0 | 40 | 78 | 100.00 | 1,744,167$/2yrs | |
0 | ![]() | LW | 6' 2" | 201 | 22 | 72 | 64 | 81 | 82 | 78 | 80 | 84 | 73 | 79 | 78 | 78 | 73 | 69 | 58 | 58 | 0 | 40 | 78 | 100.00 | 1,325,000$/2yrs | |
0 | ![]() | C | 6' 1" | 205 | 31 | 74 | 40 | 84 | 72 | 82 | 75 | 87 | 70 | 82 | 79 | 72 | 72 | 71 | 84 | 72 | 0 | 40 | 77 | 100.00 | 9,850,000$/1yrs | |
0 | ![]() | LW | 6' 1" | 196 | 34 | 75 | 40 | 75 | 70 | 77 | 76 | 91 | 70 | 52 | 78 | 74 | 69 | 68 | 89 | 67 | 0 | 40 | 76 | 100.00 | 4,000,000$/1yrs | |
0 | ![]() | C | 6' 2" | 178 | 20 | 75 | 40 | 99 | 79 | 66 | 76 | 78 | 71 | 68 | 80 | 73 | 72 | 54 | 57 | 58 | 0 | 40 | 76 | 100.00 | 1,850,000$/3yrs | |
0 | ![]() | LW | 5' 11" | 176 | 21 | 72 | 40 | 85 | 77 | 69 | 77 | 86 | 69 | 53 | 76 | 70 | 67 | 73 | 59 | 58 | 0 | 40 | 74 | 100.00 | 3,425,000$/3yrs | |
0 | ![]() | LW | 6' 4" | 212 | 28 | 82 | 71 | 84 | 67 | 81 | 68 | 73 | 61 | 73 | 72 | 63 | 79 | 54 | 65 | 59 | 0 | 40 | 72 | 100.00 | 1,200,000$/1yrs | |
0 | ![]() | LW | 5' 11" | 220 | 23 | 72 | 40 | 87 | 70 | 93 | 67 | 73 | 62 | 55 | 76 | 62 | 69 | 54 | 57 | 58 | 0 | 40 | 71 | 100.00 | 925,000$/1yrs | |
0 | ![]() | C | 6' 1" | 210 | 30 | 79 | 67 | 83 | 62 | 84 | 62 | 78 | 59 | 78 | 71 | 61 | 77 | 54 | 59 | 58 | 0 | 40 | 69 | 100.00 | 700,000$/1yrs | |
0 | ![]() | RW | 6' 0" | 190 | 23 | 68 | 41 | 83 | 65 | 75 | 66 | 71 | 57 | 53 | 70 | 60 | 70 | 58 | 60 | 58 | 0 | 40 | 67 | 100.00 | 1,774,167$/1yrs | |
0 | ![]() | RW | 5' 6" | 179 | 30 | 55 | 64 | 65 | 65 | 56 | 68 | 66 | 66 | 55 | 62 | 66 | 59 | 57 | 69 | 61 | 0 | 40 | 65 | 100.00 | 1,000,000$/1yrs | |
0 | ![]() | LW | 6' 1" | 195 | 24 | 70 | 45 | 81 | 61 | 73 | 58 | 62 | 55 | 53 | 63 | 59 | 66 | 55 | 58 | 57 | 0 | 40 | 64 | 100.00 | 1,106,666$/1yrs | |
0 | ![]() | C | 5' 9" | 190 | 30 | 55 | 62 | 66 | 60 | 60 | 68 | 66 | 64 | 55 | 62 | 60 | 58 | 57 | 69 | 61 | 0 | 40 | 63 | 100.00 | 725,000$/1yrs | |
0 | ![]() | RW | 6' 2" | 214 | 25 | 65 | 74 | 71 | 55 | 79 | 56 | 65 | 55 | 53 | 64 | 57 | 62 | 54 | 59 | 57 | 0 | 40 | 62 | 100.00 | 913,333$/1yrs | |
0 | ![]() | C | 5' 11" | 170 | 25 | 54 | 58 | 67 | 59 | 57 | 63 | 62 | 62 | 70 | 61 | 60 | 61 | 54 | 61 | 56 | 0 | 40 | 62 | 100.00 | 1,350,000$/1yrs | |
0 | ![]() | RW | 6' 2" | 203 | 24 | 55 | 56 | 71 | 62 | 67 | 63 | 62 | 57 | 54 | 59 | 58 | 62 | 54 | 58 | 56 | 0 | 40 | 62 | 100.00 | 900,000$/2yrs | |
0 | ![]() | C | 6' 2" | 214 | 24 | 55 | 55 | 66 | 58 | 69 | 65 | 63 | 58 | 55 | 56 | 58 | 59 | 54 | 59 | 55 | 0 | 40 | 61 | 100.00 | 925,000$/3yrs | |
0 | ![]() | C | 5' 10" | 173 | 22 | 55 | 55 | 67 | 59 | 57 | 64 | 62 | 60 | 70 | 59 | 58 | 60 | 54 | 57 | 54 | 0 | 40 | 61 | 100.00 | 766,667$/3yrs | |
0 | ![]() | RW | 6' 1" | 201 | 25 | 55 | 54 | 67 | 56 | 65 | 56 | 56 | 55 | 55 | 54 | 56 | 62 | 54 | 61 | 56 | 0 | 40 | 59 | 100.00 | 1,775,000$/1yrs | |
0 | ![]() | C/LW | 6' 2" | 201 | 23 | 56 | 55 | 66 | 56 | 66 | 59 | 59 | 56 | 55 | 56 | 56 | 59 | 57 | 59 | 55 | 0 | 40 | 59 | 100.00 | 830,000$/2yrs | |
0 | ![]() | C | 6' 2" | 201 | 24 | 54 | 54 | 54 | 54 | 54 | 54 | 54 | 54 | 54 | 54 | 54 | 54 | 54 | 54 | 54 | 0 | 40 | 56 | 100.00 | 3,575,000$/1yrs | |
0 | ![]() | D | 5' 10" | 180 | 23 | 65 | 40 | 81 | 96 | 73 | 97 | 90 | 77 | 40 | 93 | 62 | 84 | 54 | 63 | 64 | 0 | 40 | 82 | 100.00 | 1,604,167$/1yrs | |
0 | ![]() | D | 6' 2" | 213 | 25 | 65 | 40 | 93 | 96 | 85 | 92 | 67 | 66 | 40 | 79 | 68 | 82 | 54 | 68 | 65 | 0 | 40 | 80 | 100.00 | 5,000,000$/1yrs | |
0 | ![]() | D | 6' 2" | 220 | 25 | 68 | 40 | 75 | 89 | 88 | 90 | 76 | 70 | 40 | 82 | 65 | 80 | 58 | 67 | 66 | 0 | 40 | 79 | 100.00 | 4,600,000$/1yrs | |
0 | ![]() | D | 5' 9" | 166 | 33 | 71 | 40 | 88 | 82 | 66 | 88 | 89 | 64 | 40 | 76 | 65 | 94 | 54 | 82 | 73 | 0 | 40 | 79 | 100.00 | 5,187,500$/1yrs | |
0 | ![]() | D | 6' 4" | 204 | 22 | 78 | 40 | 79 | 85 | 77 | 91 | 91 | 66 | 40 | 80 | 60 | 90 | 54 | 59 | 58 | 0 | 40 | 78 | 100.00 | 1,775,000$/1yrs | |
0 | ![]() | D | 5' 11" | 173 | 23 | 63 | 40 | 83 | 72 | 67 | 74 | 71 | 65 | 40 | 78 | 60 | 77 | 54 | 57 | 58 | 0 | 40 | 71 | 100.00 | 910,833$/3yrs | |
0 | ![]() | D | 6' 3" | 205 | 21 | 60 | 60 | 70 | 65 | 68 | 66 | 62 | 58 | 40 | 62 | 57 | 66 | 54 | 55 | 54 | 0 | 40 | 64 | 100.00 | 925,000$/3yrs | |
0 | ![]() | D | 6' 1" | 198 | 23 | 55 | 60 | 64 | 63 | 65 | 67 | 65 | 61 | 40 | 59 | 62 | 59 | 54 | 59 | 55 | 0 | 40 | 63 | 100.00 | 810,000$/1yrs | |
0 | ![]() | D | 6' 0" | 193 | 23 | 59 | 51 | 72 | 63 | 66 | 66 | 61 | 58 | 40 | 63 | 57 | 65 | 54 | 58 | 56 | 0 | 40 | 63 | 100.00 | 925,000$/2yrs | |
0 | ![]() | D | 6' 1" | 190 | 25 | 55 | 55 | 65 | 60 | 63 | 67 | 65 | 59 | 40 | 59 | 57 | 61 | 54 | 61 | 56 | 0 | 40 | 62 | 100.00 | 761,666$/1yrs | |
0 | ![]() | D | 6' 6" | 240 | 25 | 57 | 54 | 59 | 60 | 77 | 68 | 67 | 58 | 40 | 58 | 55 | 62 | 54 | 61 | 56 | 0 | 40 | 62 | 100.00 | 700,000$/1yrs | |
0 | ![]() | D | 6' 3" | 177 | 23 | 57 | 51 | 72 | 59 | 62 | 64 | 60 | 57 | 40 | 62 | 54 | 64 | 54 | 56 | 55 | 0 | 40 | 61 | 100.00 | 786,667$/2yrs | |
0 | ![]() | D | 6' 3" | 201 | 30 | 55 | 54 | 66 | 58 | 67 | 63 | 62 | 55 | 40 | 56 | 54 | 59 | 54 | 71 | 62 | 0 | 40 | 60 | 100.00 | 725,000$/1yrs | |
0 | ![]() | D | 6' 2" | 205 | 25 | 55 | 54 | 66 | 56 | 67 | 61 | 60 | 56 | 40 | 56 | 54 | 57 | 54 | 61 | 56 | 0 | 40 | 59 | 100.00 | 1,913,333$/2yrs |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | Goalie | Height | Weight | Age | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | Overall | Condition | Contract |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Scratches | ||||||||||||||||||||||||
0 | ![]() | 6' 1" | 189 | 27 | 88 | 95 | 95 | 73 | 91 | 93 | 63 | 61 | 0 | 40 | 86 | 100.00 | 3,775,000$/1yrs | |||||||
0 | ![]() | 6' 4" | 203 | 33 | 78 | 85 | 87 | 78 | 80 | 74 | 77 | 71 | 0 | 40 | 79 | 100.00 | 5,750,000$/1yrs | |||||||
0 | ![]() | 6' 3" | 215 | 30 | 67 | 61 | 60 | 57 | 74 | 67 | 67 | 59 | 0 | 40 | 68 | 100.00 | 1,225,000$/1yrs | |||||||
0 | ![]() | 6' 5" | 196 | 24 | 58 | 62 | 61 | 66 | 73 | 77 | 57 | 55 | 0 | 40 | 66 | 100.00 | 925,000$/3yrs | |||||||
0 | ![]() | 6' 2" | 176 | 23 | 65 | 66 | 65 | 64 | 70 | 57 | 58 | 54 | 0 | 40 | 66 | 100.00 | 925,000$/3yrs |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Darryl Sutter | 82 | 91 | 87 | 83 | 95 | 89 | 49 | CAN | 65 | 1 | 6,400,000$ |
General Manager | Robert Martens |
---|
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 | AMG | PPG | PPA | PPP | PPM | PKG | PKA | PKP | PKM | GW | GT | FO% | FOT | GA | TA | EG | HT | P/20 | PSG | PSS |
---|
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 |
---|
Projected Total Cap Hit | 0$ |
Projected Cap Space | 91,500,000$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 0$ |
Players In Salary Cap | 44 |
LTIR Players | 0 |
Player Name | Pos | Age | Cap Hit | 2022-2023 | 2023-2024 | 2024-2025 | 2025-2026 | 2026-2027 | 2027-2028 | 2028-2029 | 2029-2030 |
---|---|---|---|---|---|---|---|---|---|---|---|
Ben Gleason ![]() | D | 25 | 761,666$ | 761,666$ | |||||||
Brandon Biro ![]() | C | 25 | 1,350,000$ | 1,350,000$ | |||||||
Calen Addison ![]() | D | 23 | 910,833$ | 910,833$ | 910,833$ | 910,833$ | |||||
Daniil Tarasov ![]() | C | 24 | 925,000$ | 925,000$ | 925,000$ | 925,000$ | |||||
David Perron ![]() | LW | 34 | 4,000,000$ | 4,000,000$ | |||||||
Dylan Cozens ![]() | C | 22 | 1,744,167$ | 1,744,167$ | 1,744,167$ | ||||||
Dylan Larkin ![]() | C | 26 | 6,100,000$ | 6,100,000$ | |||||||
Egor Zamula ![]() | D | 23 | 786,667$ | 786,667$ | 786,667$ | ||||||
Fabian Zetterlund ![]() | LW | 23 | 925,000$ | 925,000$ | |||||||
Filip Zadina ![]() | RW | 23 | 1,774,167$ | 1,774,167$ | |||||||
Givani Smith ![]() | RW | 25 | 913,333$ | 913,333$ | |||||||
Igor Shesterkin ![]() | C | 27 | 3,775,000$ | 3,775,000$ | |||||||
Isaak Phillips ![]() | D | 21 | 925,000$ | 925,000$ | 925,000$ | 925,000$ | |||||
Jack Hughes ![]() | C | 22 | 3,775,000$ | 3,775,000$ | |||||||
Jake Christiansen ![]() | D | 23 | 925,000$ | 925,000$ | 925,000$ | ||||||
Jakob Chychrun ![]() | D | 25 | 4,600,000$ | 4,600,000$ | |||||||
Jared Spurgeon ![]() | D | 33 | 5,187,500$ | 5,187,500$ | |||||||
Jonas Rondbjerg ![]() | RW | 24 | 900,000$ | 900,000$ | 900,000$ | ||||||
Jujhar Khaira ![]() | LW | 28 | 1,200,000$ | 1,200,000$ | |||||||
Keaton Middleton ![]() | D | 25 | 700,000$ | 700,000$ | |||||||
Kieffer Bellows ![]() | LW | 24 | 1,106,666$ | 1,106,666$ | |||||||
Kirill Kaprizov ![]() | LW | 26 | 1,387,500$ | 1,387,500$ | 1,387,500$ | ||||||
Kyle Connor ![]() | LW | 26 | 7,142,857$ | 7,142,857$ | |||||||
Laurent Brossoit ![]() | C | 30 | 1,225,000$ | 1,225,000$ | |||||||
Leon Gawanke ![]() | D | 23 | 810,000$ | 810,000$ | |||||||
Lucas Raymond ![]() | LW | 21 | 3,425,000$ | 3,425,000$ | 3,425,000$ | 3,425,000$ | |||||
Martin Jones ![]() | D | 33 | 5,750,000$ | 5,750,000$ | |||||||
Matt Boldy ![]() | LW | 22 | 1,325,000$ | 1,325,000$ | 1,325,000$ | ||||||
Matty Beniers ![]() | C | 20 | 1,850,000$ | 1,850,000$ | 1,850,000$ | 1,850,000$ | |||||
Mitchell Chaffee ![]() | RW | 25 | 1,775,000$ | 1,775,000$ | |||||||
Moritz Seider ![]() | D | 22 | 1,775,000$ | 1,775,000$ | |||||||
Nolan Patrick ![]() | C | 24 | 3,575,000$ | 3,575,000$ | |||||||
Olli Juolevi ![]() | D | 25 | 1,913,333$ | 1,913,333$ | 1,913,333$ | ||||||
Patrick Brown ![]() | C | 30 | 700,000$ | 700,000$ | |||||||
Paul Ladue ![]() | D | 30 | 750,000$ | 750,000$ | |||||||
Quinn Hughes ![]() | D | 23 | 1,604,167$ | 1,604,167$ | |||||||
Rocco Grimaldi ![]() | RW | 30 | 1,000,000$ | 1,000,000$ | |||||||
Samuel Ersson ![]() | D | 23 | 925,000$ | 925,000$ | 925,000$ | 925,000$ | |||||
Scott Reedy ![]() | C | 24 | 925,000$ | 925,000$ | 925,000$ | 925,000$ | |||||
Semyon Der-Arguchintsev ![]() | C | 22 | 766,667$ | 766,667$ | 766,667$ | 766,667$ | |||||
Seth Griffith ![]() | C | 30 | 725,000$ | 725,000$ | |||||||
Tyler Seguin ![]() | C | 31 | 9,850,000$ | 9,850,000$ | |||||||
Viktor Lodin ![]() | C/LW | 23 | 830,000$ | 830,000$ | 830,000$ | ||||||
Zach Werenski ![]() | D | 25 | 5,000,000$ | 5,000,000$ |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Total | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.000 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0 | nan% | nan% | nan% | nan | Unlucky |
Puck Time | |
---|---|
Offensive Zone | NAN |
Neutral Zone | NAN |
Defensive Zone | NAN |
Puck Time | |
---|---|
Offensive Zone Start | 0 |
Neutral Zone Start | 0 |
Defensive Zone Start | 0 |
Puck Time | |
---|---|
With Puck | NAN |
Without Puck | NAN |
Faceoffs | |
---|---|
Faceoffs Won | 0 |
Faceoffs Lost | 0 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | nan | 9.57 |
2nd Period | nan | 20.31 |
3rd Period | nan | 30.68 |
Overtime | nan | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | nan | 0.64 |
2nd Period | nan | 1.65 |
3rd Period | nan | 2.67 |
Overtime | nan | 2.83 |
Even Strenght Goal | 0 |
---|---|
PP Goal | 0 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 0 | 0 |
Lost | 0 | 0 |
Overtime Lost | 0 | 0 |
PP Attempt | 0 |
---|---|
PP Goal | 0 |
PK Attempt | 0 |
PK Goal Against | 0 |
Home | |
---|---|
Shots For | nan |
Shots Against | nan |
Goals For | nan |
Goals Against | nan |
Hits | nan |
Shots Blocked | nan |
Pim | nan |
Date | Matchup | Result | Detail |
---|
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
98,314,523$ | 0$ | 0$ | 91,500,000$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | Little Caesars Arena | |
City | Detroit | ||
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 | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
Attendance PCT | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
Income | |||||
---|---|---|---|---|---|
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
41 | 0 - 0.00% | 0$ | 0$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
98,314,523$ | 98,289,523$ | 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$ | 0 | 0$ | 0$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
0$ | 0$ | 9,999,997$ | 9,999,997$ |
FOWARD | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
DEFENSE | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
GOALIE | ||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
---|---|---|---|---|---|---|---|
2023 | |||||||
2024 | |||||||
2025 | |||||||
2026 |
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 |
---|---|---|---|---|---|
Dylan Guenther | |||||
Jesper Wallstedt | |||||
Kent Johnson | |||||
Luke Hughes | |||||
Matias Maccelli | |||||
Simon Edvinsson |
Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
---|---|---|---|---|---|---|---|
2023 | |||||||
2024 | |||||||
2025 | |||||||
2026 |
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 |
---|---|---|---|---|---|
Dylan Guenther | |||||
Jesper Wallstedt | |||||
Kent Johnson | |||||
Luke Hughes | |||||
Matias Maccelli | |||||
Simon Edvinsson |