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Full Scoreboard »» |
Los Angeles Kings 45-15-9, 99pts · 1st 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 | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 86 | C/LW | 100.00 | 56 | 32 | 97 | 99 | 68 | 88 | 89 | 87 | 62 | 87 | 93 | 63 | 90 | 62 | 69 | 0 | 83 | 95 | 21 | 8,000,000$/8yrs | |||
![]() | 13 | LW | 100.00 | 54 | 31 | 89 | 91 | 62 | 87 | 90 | 85 | 65 | 92 | 85 | 61 | 85 | 75 | 74 | 0 | 83 | 93 | 29 | 7,000,000$/8yrs | |||
![]() | 28 | LW/RW | 100.00 | 84 | 34 | 80 | 93 | 85 | 88 | 90 | 83 | 60 | 82 | 87 | 73 | 85 | 70 | 68 | 0 | 83 | 92 | 26 | 6,000,000$/9yrs | |||
![]() | 11 | LW/RW | 100.00 | 68 | 57 | 51 | 87 | 67 | 88 | 89 | 87 | 61 | 84 | 89 | 84 | 88 | 69 | 65 | 0 | 82 | 92 | 26 | 5,500,000$/3yrs | |||
![]() | 14 | C | 100.00 | 73 | 33 | 80 | 82 | 83 | 86 | 90 | 88 | 88 | 79 | 81 | 86 | 81 | 69 | 67 | 0 | 83 | 91 | 26 | 2,750,000$/2yrs | |||
![]() | 0 | C/LW | 100.00 | 64 | 33 | 87 | 83 | 77 | 80 | 77 | 81 | 63 | 82 | 82 | 80 | 82 | 75 | 80 | 0 | 83 | 90 | 29 | 4,000,000$/3yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 63 | 33 | 91 | 77 | 78 | 86 | 88 | 75 | 83 | 80 | 74 | 80 | 75 | 74 | 73 | 0 | 82 | 86 | 28 | 3,500,000$/3yrs | |||
![]() | 15 | C/LW | 100.00 | 60 | 35 | 86 | 79 | 74 | 82 | 85 | 75 | 81 | 78 | 75 | 88 | 75 | 61 | 60 | 0 | 74 | 86 | 21 | 925,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 63 | 32 | 85 | 75 | 67 | 82 | 90 | 76 | 60 | 76 | 78 | 79 | 77 | 77 | 76 | 0 | 80 | 85 | 30 | 3,000,000$/1yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 76 | 36 | 77 | 74 | 71 | 80 | 90 | 76 | 60 | 76 | 77 | 71 | 76 | 67 | 64 | 0 | 83 | 83 | 24 | 2,000,000$/1yrs | |||
![]() | 83 | LW/RW | 100.00 | 64 | 34 | 82 | 75 | 63 | 82 | 89 | 75 | 60 | 78 | 74 | 64 | 74 | 70 | 68 | 0 | 83 | 83 | 27 | 3,500,000$/4yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 74 | 36 | 86 | 64 | 80 | 78 | 84 | 68 | 76 | 67 | 69 | 78 | 69 | 74 | 80 | 0 | 83 | 80 | 29 | 1,500,000$/2yrs | |||
![]() | 5 | D | 100.00 | 70 | 34 | 76 | 82 | 87 | 96 | 83 | 77 | 30 | 85 | 76 | 87 | 77 | 71 | 81 | 0 | 81 | 92 | 27 | 7,500,000$/3yrs | |||
![]() | 0 | D | 100.00 | 82 | 35 | 83 | 74 | 82 | 94 | 89 | 74 | 30 | 79 | 75 | 86 | 75 | 78 | 76 | 0 | 83 | 89 | 31 | 6,200,000$/4yrs | |||
![]() | 77 | D | 100.00 | 65 | 43 | 67 | 79 | 70 | 91 | 85 | 73 | 30 | 84 | 73 | 72 | 73 | 71 | 68 | 0 | 84 | 87 | 27 | 4,700,000$/3yrs | |||
![]() | 0 | D | 100.00 | 65 | 33 | 89 | 67 | 78 | 94 | 87 | 74 | 30 | 74 | 61 | 90 | 68 | 75 | 74 | 0 | 83 | 86 | 29 | 5,500,000$/4yrs | |||
![]() | 0 | D | 100.00 | 77 | 38 | 83 | 61 | 90 | 86 | 89 | 71 | 30 | 69 | 62 | 89 | 66 | 69 | 75 | 0 | 36 | 84 | 26 | 4,000,000$/3yrs | |||
![]() | 0 | D | 100.00 | 79 | 36 | 83 | 58 | 82 | 85 | 84 | 68 | 30 | 69 | 67 | 84 | 67 | 69 | 67 | 0 | 83 | 81 | 26 | 2,750,000$/6yrs | |||
Scratches | ||||||||||||||||||||||||||
TEAM AVERAGE | 100.00 | 69 | 36 | 82 | 78 | 76 | 86 | 87 | 77 | 56 | 79 | 77 | 79 | 77 | 71 | 71 | 0 | 80 | 88 |
Priority | Type | Description |
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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 | 95.00 | 89 | 95 | 83 | 73 | 93 | 86 | 93 | 94 | 93 | 94 | 93 | 71 | 76 | 0 | 36 | 92 | 27 | 2,750,000$/3yrs |
![]() | 0 | 100.00 | 87 | 90 | 79 | 84 | 87 | 81 | 88 | 93 | 83 | 94 | 88 | 77 | 82 | 0 | 59 | 90 | 31 | 5,000,000$/4yrs |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 97.50 | 88 | 93 | 81 | 79 | 90 | 84 | 91 | 94 | 88 | 94 | 91 | 74 | 79 | 0 | 48 | 91 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Andrew Brunette | 87 | 77 | 99 | 75 | 68 | 64 | 77 | CAN | 47 | 2 | 1,000,000$ |
General Manager | Yannick Vézina-Roy |
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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 | Timo Meier | 28 | LW/RW | 69 | 32 | 37 | 69 | 14 | 56 | 0 | 197 | 249 | 64 | 175 | 12.85% | 8 | 17.78 | 12 | 17 | 29 | 205 | 0 | 0 | 0 | 3 | 7 | 3 | 46.51% | 86 | 0 | 0 | 0 | 0 | 1.12 | 2 | 5 | |
2 | Jack Hughes | 86 | C/LW | 69 | 22 | 37 | 59 | 3 | 8 | 0 | 23 | 218 | 57 | 167 | 10.09% | 5 | 18.66 | 7 | 15 | 22 | 197 | 0 | 0 | 0 | 28 | 4 | 1 | 44.45% | 1568 | 0 | 0 | 0 | 0 | 0.92 | 3 | 5 | |
3 | Aaron Ekblad | 5 | D | 69 | 17 | 41 | 58 | 5 | 50 | 10 | 122 | 121 | 44 | 77 | 14.05% | 74 | 23.33 | 9 | 16 | 25 | 207 | 0 | 0 | 0 | 190 | 2 | 2 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.72 | 0 | 0 | |
4 | Joel Eriksson Ek | 14 | C | 69 | 25 | 32 | 57 | 20 | 32 | 0 | 107 | 225 | 62 | 144 | 11.11% | 13 | 18.92 | 7 | 18 | 25 | 206 | 0 | 0 | 0 | 119 | 11 | 2 | 54.56% | 1710 | 0 | 0 | 0 | 0 | 0.87 | 0 | 0 | |
5 | Travis Konecny | 11 | LW/RW | 69 | 15 | 28 | 43 | 2 | 42 | 10 | 155 | 196 | 69 | 163 | 7.65% | 9 | 16.42 | 5 | 11 | 16 | 162 | 0 | 0 | 0 | 2 | 1 | 2 | 36.36% | 99 | 0 | 0 | 0 | 1 | 0.76 | 0 | 0 | |
6 | Johnny Gaudreau | 13 | LW | 69 | 16 | 25 | 41 | 4 | 2 | 0 | 8 | 194 | 60 | 145 | 8.25% | 7 | 18.44 | 4 | 9 | 13 | 202 | 0 | 0 | 0 | 25 | 4 | 1 | 42.41% | 158 | 0 | 0 | 0 | 0 | 0.64 | 0 | 5 | |
7 | Justin Faulk | 0 | D | 69 | 10 | 30 | 40 | 6 | 64 | 0 | 132 | 104 | 39 | 72 | 9.62% | 74 | 20.53 | 5 | 13 | 18 | 201 | 0 | 0 | 0 | 127 | 0 | 4 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.56 | 0 | 0 | |
8 | Andrew Copp | 0 | C/LW/RW | 69 | 17 | 20 | 37 | 22 | 19 | 5 | 59 | 151 | 49 | 105 | 11.26% | 12 | 15.91 | 3 | 0 | 3 | 43 | 0 | 0 | 0 | 119 | 2 | 2 | 51.16% | 129 | 0 | 0 | 1 | 0 | 0.67 | 0 | 1 | |
9 | Tony DeAngelo | 77 | D | 69 | 4 | 31 | 35 | 19 | 43 | 15 | 93 | 65 | 24 | 50 | 6.15% | 63 | 23.01 | 3 | 7 | 10 | 199 | 0 | 0 | 0 | 41 | 1 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.44 | 0 | 0 | |
10 | Alex Iafallo | 0 | C/LW | 69 | 13 | 19 | 32 | 6 | 10 | 0 | 44 | 145 | 46 | 108 | 8.97% | 18 | 17.12 | 5 | 4 | 9 | 86 | 1 | 0 | 1 | 218 | 2 | 1 | 33.98% | 103 | 0 | 0 | 0 | 0 | 0.54 | 0 | 0 | |
11 | Jonas Brodin | 0 | D | 69 | 8 | 22 | 30 | 14 | 24 | 0 | 50 | 63 | 22 | 29 | 12.70% | 77 | 20.22 | 4 | 7 | 11 | 99 | 0 | 0 | 0 | 193 | 0 | 1 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.43 | 0 | 0 | |
12 | Conor Sheary | 0 | LW/RW | 70 | 12 | 15 | 27 | 14 | 10 | 0 | 29 | 127 | 37 | 85 | 9.45% | 7 | 12.67 | 1 | 3 | 4 | 55 | 0 | 0 | 0 | 7 | 3 | 2 | 39.06% | 64 | 0 | 0 | 0 | 0 | 0.61 | 0 | 0 | |
13 | Anton Lundell | 15 | C/LW | 66 | 10 | 17 | 27 | 11 | 8 | 0 | 44 | 144 | 36 | 84 | 6.94% | 14 | 14.21 | 0 | 1 | 1 | 15 | 0 | 1 | 1 | 154 | 3 | 0 | 49.42% | 1200 | 0 | 0 | 0 | 0 | 0.58 | 0 | 0 | |
14 | Conor Garland | 83 | LW/RW | 69 | 9 | 17 | 26 | 5 | 14 | 0 | 60 | 100 | 42 | 53 | 9.00% | 5 | 13.57 | 0 | 4 | 4 | 108 | 0 | 0 | 0 | 5 | 2 | 1 | 44.93% | 69 | 0 | 0 | 0 | 0 | 0.56 | 0 | 0 | |
15 | Brandon Carlo | 0 | D | 67 | 5 | 17 | 22 | -14 | 30 | 0 | 82 | 39 | 16 | 36 | 12.82% | 99 | 18.21 | 0 | 2 | 2 | 51 | 0 | 0 | 0 | 105 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.36 | 0 | 0 | |
16 | Zach Whitecloud | 0 | D | 69 | 4 | 16 | 20 | 12 | 58 | 0 | 139 | 47 | 21 | 31 | 8.51% | 98 | 19.92 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 163 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.29 | 0 | 0 | |
17 | Dillon Dube | 0 | C/LW/RW | 69 | 6 | 6 | 12 | 4 | 20 | 0 | 56 | 74 | 24 | 44 | 8.11% | 1 | 8.88 | 0 | 0 | 0 | 11 | 0 | 0 | 0 | 45 | 3 | 0 | 29.82% | 57 | 0 | 0 | 0 | 0 | 0.39 | 0 | 0 | |
18 | Zemgus Girgensons | 0 | C/LW/RW | 69 | 3 | 4 | 7 | -1 | 14 | 0 | 41 | 49 | 22 | 29 | 6.12% | 5 | 7.72 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 47.23% | 559 | 0 | 0 | 0 | 0 | 0.26 | 0 | 0 | |
Team Total or Average | 1238 | 228 | 414 | 642 | 146 | 504 | 40 | 1441 | 2311 | 734 | 1597 | 9.87% | 589 | 16.97 | 65 | 127 | 192 | 2059 | 1 | 1 | 2 | 1552 | 46 | 22 | 48.33% | 5802 | 0 | 0 | 1 | 1 | 0.61 | 5 | 16 |
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 | Jack Campbell | 41 | 22 | 9 | 6 | 0.916 | 2.39 | 2311 | 2 | 5 | 92 | 1099 | 0 | 1 | 1 | 1.000 | 2 | 37 | 29 | 3 | 5 | 3 | |
2 | Alexandar Georgiev | 39 | 18 | 15 | 4 | 0.911 | 2.46 | 2266 | 4 | 2 | 93 | 1044 | 0 | 1 | 0 | 0.571 | 7 | 36 | 28 | 2 | 1 | 3 | |
Team Total or Average | 80 | 40 | 24 | 10 | 0.914 | 2.43 | 4577 | 6 | 7 | 185 | 2143 | 0 | 2 | 1 | 0.667 | 9 | 73 | 57 | 5 | 6 | 6 |
Projected Total Cap Hit | 80,114,027$ |
Projected Cap Space | 2,385,973$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 68,210,456$ |
Players In Salary Cap | 19 |
LTIR Players | 1 |
Kings Roster | Pos | Age | Cap Hit | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 |
---|---|---|---|---|---|---|---|---|---|---|---|
Aaron Ekblad | D | 27 | 7,500,000$ | 7,500,000$ | 7,500,000$ | 7,500,000$ | UFA | ||||
Alex Iafallo | C/LW | 29 | 4,000,000$ | 4,000,000$ | 4,000,000$ | 4,000,000$ | UFA | ||||
Alexandar Georgiev ![]() | G | 27 | 2,750,000$ | 2,750,000$ | 3,400,000$ | 3,400,000$ | UFA | ||||
Andrew Copp | C/LW/RW | 28 | 3,500,000$ | 3,500,000$ | 3,500,000$ | 3,500,000$ | UFA | ||||
Anton Lundell ![]() | C/LW | 21 | 925,000$ | 925,000$ | 925,000$ | RFA | |||||
Brandon Carlo | D | 26 | 4,000,000$ | 4,000,000$ | 4,000,000$ | 4,000,000$ | UFA | ||||
Conor Garland | LW/RW | 27 | 3,500,000$ | 3,500,000$ | 4,950,000$ | 4,950,000$ | 4,950,000$ | UFA | |||
Conor Sheary | LW/RW | 30 | 3,000,000$ | 3,000,000$ | UFA | ||||||
Dillon Dube | C/LW/RW | 24 | 2,000,000$ | 2,000,000$ | RFA | ||||||
Jack Campbell | G | 31 | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | UFA | |||
Jack Hughes | C/LW | 21 | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ |
Joel Eriksson Ek | C | 26 | 2,750,000$ | 2,750,000$ | 2,750,000$ | ||||||
Johnny Gaudreau | LW | 29 | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ |
Jonas Brodin | D | 29 | 5,500,000$ | 5,500,000$ | 5,500,000$ | 5,500,000$ | 5,500,000$ | UFA | |||
Justin Faulk | D | 31 | 6,200,000$ | 6,200,000$ | 6,200,000$ | 6,200,000$ | 6,200,000$ | UFA | |||
Timo Meier | LW/RW | 26 | 6,000,000$ | 6,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ | 8,000,000$ |
Tony DeAngelo | D | 27 | 4,700,000$ | 4,700,000$ | 4,700,000$ | 4,700,000$ | UFA | ||||
Travis Konecny | LW/RW | 26 | 5,500,000$ | 5,500,000$ | 5,500,000$ | 5,500,000$ | UFA | ||||
Zach Whitecloud | D | 26 | 2,750,000$ | 2,750,000$ | 2,750,000$ | 2,750,000$ | 2,750,000$ | 2,750,000$ | 2,750,000$ | UFA | |
Zemgus Girgensons | C/LW/RW | 29 | 1,500,000$ | 1,500,000$ | 1,500,000$ | UFA |
Non-Roster | Pos | Age | Cap Hit | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 |
---|---|---|---|---|---|---|---|---|---|---|---|
Alexei Melnichuk ![]() | G | 24 | 925,000$ | 925,000$ | 925,000$ | 925,000$ | ![]() | ||||
Brad Richardson ![]() | C/LW | 38 | 1,000,000$ | 1,000,000$ | UFA | ||||||
Brett Brochu ![]() | G | 20 | 750,000$ | 750,000$ | 750,000$ | RFA | |||||
Brinson Pasichnuk ![]() | D | 25 | 925,000$ | 925,000$ | 925,000$ | ![]() | |||||
Calen Addison ![]() | D | 22 | 795,000$ | 795,000$ | RFA | ||||||
Charles Hudon ![]() ![]() | LW/RW | 28 | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | |||||
Darren Helm ![]() | C/LW/RW | 36 | 1,250,000$ | 1,250,000$ | UFA | ||||||
Emil Heineman ![]() | LW | 21 | 897,500$ | 897,500$ | 897,500$ | 897,500$ | RFA | ||||
Gabriel Carlsson ![]() | D | 26 | 950,000$ | 950,000$ | 950,000$ | ![]() | |||||
German Rubtsov ![]() | C | 24 | 850,000$ | 850,000$ | 850,000$ | 850,000$ | ![]() | ||||
Jack Drury ![]() | C | 23 | 925,000$ | 925,000$ | 925,000$ | RFA | |||||
Jack Dugan ![]() | LW/RW | 24 | 750,000$ | 750,000$ | 750,000$ | 750,000$ | ![]() | ||||
Jaret Anderson-Dolan ![]() | C | 23 | 900,000$ | 900,000$ | RFA | ||||||
John Beecher ![]() | C | 21 | 925,000$ | 925,000$ | 925,000$ | 925,000$ | RFA | ||||
Juraj Slafkovsky ![]() ![]() | LW | 18 | 950,000$ | 950,000$ | 950,000$ | 950,000$ | RFA | ||||
Kristian Vesalainen ![]() | LW/RW | 23 | 900,000$ | 900,000$ | 900,000$ | 900,000$ | ![]() | ||||
Lukas Rousek ![]() | RW | 23 | 830,000$ | 830,000$ | RFA | ||||||
Mads Sogaard ![]() ![]() | G | 22 | 925,000$ | 925,000$ | 925,000$ | RFA | |||||
Mason Primeau ![]() | C | 21 | 825,000$ | 825,000$ | 825,000$ | RFA | |||||
Matej Blumel ![]() | LW | 22 | 925,000$ | 925,000$ | 925,000$ | RFA | |||||
Matt Kiersted ![]() | D | 24 | 925,000$ | 925,000$ | 925,000$ | 925,000$ | ![]() | ||||
Max Jones ![]() | LW | 25 | 900,000$ | 900,000$ | ![]() | ||||||
Michael McNiven ![]() ![]() | G | 25 | 800,000$ | 800,000$ | 800,000$ | ![]() | |||||
Nikolai Knyzhov ![]() ![]() | D | 25 | 850,000$ | 850,000$ | ![]() | ||||||
Noel Hoefenmayer ![]() ![]() | D | 24 | 750,000$ | 750,000$ | 750,000$ | ![]() | |||||
Otto Koivula ![]() | LW | 24 | 925,000$ | 925,000$ | RFA | ||||||
Philip Broberg ![]() | D | 21 | 863,333$ | 863,333$ | 863,333$ | RFA | |||||
Reilly Walsh ![]() | D | 23 | 925,000$ | 925,000$ | RFA | ||||||
Roni Hirvonen ![]() | C | 21 | 856,667$ | 856,667$ | 856,667$ | 856,667$ | RFA | ||||
Seth Jarvis ![]() | C/LW/RW | 21 | 894,167$ | 894,167$ | 894,167$ | RFA | |||||
Troy Stecher ![]() | D | 28 | 1,250,000$ | 1,250,000$ | UFA | ||||||
Tyler Benson ![]() | LW | 25 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | ![]() | ||||
Ville Heinola ![]() | D | 22 | 863,333$ | 863,333$ | 863,333$ | RFA |
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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 | 4 | 4 | 0 | 3 | 0.750 | 4 | 7 | 11 | 0 | 0 | 2 | 1 | 1 | 0 | 59 | 20 | 20 | 17 | 2 | 49 | 26 | 18 | 44 | 8 | 2 | 25.00% | 8 | 0 | 100.00% | 1 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 51 | 35 | 47 | 14 | 25 | 12 | 33.3% | 6.8% | 91.8% | 98.6 | DULL | |
2 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 1 | 6 | 4 | 1.000 | 7 | 13 | 20 | 0 | 1 | 2 | 4 | 1 | 0 | 62 | 22 | 20 | 20 | 0 | 43 | 14 | 14 | 44 | 9 | 1 | 11.11% | 7 | 0 | 100.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 49 | 35 | 46 | 14 | 24 | 12 | 85.7% | 11.3% | 97.7% | 109.0 | LUCKY | |
3 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 7 | 6 | 1 | 2 | 0.500 | 7 | 11 | 18 | 1 | 0 | 5 | 2 | 0 | 0 | 54 | 18 | 20 | 16 | 0 | 56 | 16 | 19 | 42 | 6 | 3 | 50.00% | 7 | 2 | 71.43% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 46 | 31 | 46 | 14 | 27 | 13 | 50.0% | 13.0% | 89.3% | 102.2 | FUN | |
4 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 5 | 6 | -1 | 2 | 0.500 | 5 | 10 | 15 | 0 | 0 | 0 | 4 | 1 | 0 | 62 | 20 | 25 | 17 | 0 | 40 | 14 | 6 | 52 | 10 | 3 | 30.00% | 3 | 0 | 100.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 52 | 37 | 44 | 13 | 23 | 12 | 25.0% | 8.1% | 85.0% | 93.1 | Unlucky | |
5 | 2 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 10 | 6 | 4 | 3 | 0.750 | 10 | 18 | 28 | 0 | 1 | 3 | 4 | 3 | 0 | 62 | 21 | 20 | 20 | 1 | 74 | 23 | 18 | 42 | 5 | 1 | 20.00% | 9 | 1 | 88.89% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 48 | 33 | 49 | 13 | 25 | 13 | 64.3% | 16.1% | 91.9% | 108.0 | LUCKY | |
6 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 6 | 6 | 0 | 2 | 0.500 | 6 | 12 | 18 | 0 | 0 | 2 | 1 | 3 | 0 | 55 | 13 | 23 | 19 | 0 | 46 | 16 | 14 | 46 | 6 | 3 | 50.00% | 6 | 2 | 66.67% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 54 | 38 | 41 | 14 | 24 | 11 | 42.9% | 10.9% | 87.0% | 97.9 | FUN | |
7 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 2 | 8 | 4 | 1.000 | 10 | 18 | 28 | 0 | 0 | 4 | 3 | 3 | 0 | 84 | 29 | 24 | 31 | 0 | 40 | 12 | 20 | 41 | 6 | 4 | 66.67% | 5 | 0 | 100.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 50 | 36 | 44 | 13 | 25 | 12 | 75.0% | 11.9% | 95.0% | 106.9 | LUCKY | |
8 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 5 | 3 | 4 | 1.000 | 8 | 14 | 22 | 0 | 0 | 1 | 5 | 2 | 0 | 56 | 20 | 20 | 16 | 0 | 40 | 14 | 16 | 46 | 6 | 1 | 16.67% | 7 | 0 | 100.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 51 | 36 | 42 | 14 | 26 | 12 | 58.3% | 14.3% | 87.5% | 101.8 | FUN | |
9 | 2 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 6 | 4 | 2 | 4 | 1.000 | 6 | 10 | 16 | 0 | 0 | 0 | 2 | 2 | 2 | 57 | 23 | 20 | 12 | 2 | 66 | 16 | 12 | 41 | 7 | 2 | 28.57% | 6 | 1 | 83.33% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 47 | 32 | 50 | 16 | 27 | 13 | 57.1% | 10.5% | 93.9% | 104.5 | LUCKY | |
10 | 2 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 9 | 5 | 4 | 4 | 1.000 | 9 | 16 | 25 | 0 | 0 | 5 | 3 | 0 | 1 | 68 | 21 | 27 | 18 | 5 | 48 | 12 | 10 | 50 | 7 | 3 | 42.86% | 4 | 0 | 100.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 52 | 38 | 46 | 14 | 26 | 13 | 54.5% | 13.2% | 89.6% | 102.8 | FUN | |
11 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 7 | 4 | 3 | 3 | 0.750 | 7 | 13 | 20 | 0 | 1 | 3 | 4 | 0 | 0 | 73 | 25 | 19 | 26 | 6 | 45 | 20 | 27 | 39 | 7 | 2 | 28.57% | 6 | 0 | 100.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 50 | 34 | 46 | 16 | 28 | 15 | 55.6% | 9.6% | 91.1% | 100.7 | Unlucky | |
12 | 3 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 5 | 6 | -1 | 4 | 0.667 | 5 | 9 | 14 | 0 | 0 | 1 | 2 | 2 | 1 | 76 | 26 | 26 | 23 | 5 | 87 | 23 | 23 | 67 | 9 | 1 | 11.11% | 8 | 1 | 87.50% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 73 | 51 | 74 | 21 | 38 | 19 | 44.4% | 6.6% | 93.1% | 99.7 | DULL | |
13 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 3 | 3 | 2 | 1.000 | 6 | 10 | 16 | 0 | 0 | 4 | 2 | 0 | 0 | 42 | 14 | 20 | 8 | 0 | 30 | 4 | 4 | 26 | 6 | 2 | 33.33% | 2 | 0 | 100.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 27 | 20 | 20 | 6 | 12 | 6 | 57.1% | 14.3% | 90.0% | 104.3 | FUN | |
14 | 3 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 16 | 13 | 3 | 4 | 0.667 | 16 | 28 | 44 | 0 | 0 | 9 | 3 | 4 | 0 | 99 | 45 | 32 | 22 | 0 | 96 | 19 | 26 | 57 | 12 | 5 | 41.67% | 12 | 6 | 50.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 73 | 52 | 66 | 20 | 39 | 20 | 61.1% | 16.2% | 86.5% | 102.6 | FUN | |
15 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 3 | 5 | 4 | 1.000 | 8 | 13 | 21 | 0 | 1 | 5 | 1 | 2 | 0 | 93 | 33 | 30 | 30 | 0 | 63 | 16 | 12 | 44 | 13 | 1 | 7.69% | 6 | 2 | 66.67% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 52 | 36 | 42 | 15 | 25 | 13 | 87.5% | 8.6% | 95.2% | 103.8 | DULL | |
16 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 1 | 5 | 4 | 1.000 | 6 | 10 | 16 | 0 | 1 | 1 | 2 | 3 | 0 | 56 | 15 | 14 | 27 | 0 | 44 | 4 | 10 | 30 | 5 | 1 | 20.00% | 4 | 0 | 100.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 51 | 35 | 44 | 14 | 24 | 12 | 83.3% | 10.7% | 97.7% | 108.4 | LUCKY | |
17 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 4 | 5 | -1 | 2 | 0.500 | 4 | 8 | 12 | 0 | 0 | 0 | 2 | 2 | 0 | 57 | 17 | 16 | 24 | 0 | 51 | 14 | 12 | 33 | 7 | 0 | 0.00% | 6 | 2 | 66.67% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 46 | 31 | 48 | 14 | 25 | 12 | 57.1% | 7.0% | 90.2% | 97.2 | Unlucky | |
18 | 3 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 13 | 5 | 8 | 6 | 1.000 | 13 | 24 | 37 | 0 | 0 | 3 | 8 | 2 | 0 | 86 | 27 | 34 | 25 | 0 | 74 | 21 | 25 | 66 | 20 | 7 | 35.00% | 10 | 2 | 80.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 78 | 55 | 65 | 21 | 35 | 18 | 66.7% | 15.1% | 93.2% | 108.4 | LUCKY | |
19 | 2 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 7 | 6 | 1 | 3 | 0.750 | 7 | 12 | 19 | 0 | 0 | 3 | 2 | 2 | 0 | 52 | 21 | 17 | 14 | 0 | 69 | 18 | 18 | 41 | 8 | 3 | 37.50% | 8 | 2 | 75.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 46 | 31 | 47 | 14 | 25 | 13 | 50.0% | 13.5% | 91.3% | 104.8 | LUCKY | |
20 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 4 | 4 | 0 | 2 | 0.500 | 4 | 8 | 12 | 0 | 0 | 0 | 3 | 1 | 0 | 43 | 11 | 12 | 20 | 0 | 64 | 15 | 23 | 40 | 5 | 1 | 20.00% | 8 | 0 | 100.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 43 | 30 | 50 | 16 | 26 | 11 | 42.9% | 9.3% | 93.8% | 103.1 | LUCKY | |
21 | 3 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 9 | 7 | 2 | 2 | 0.333 | 9 | 18 | 27 | 0 | 1 | 3 | 3 | 3 | 0 | 97 | 36 | 32 | 29 | 0 | 83 | 25 | 20 | 49 | 9 | 3 | 33.33% | 10 | 1 | 90.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 69 | 48 | 72 | 21 | 37 | 19 | 50.0% | 9.3% | 91.6% | 100.8 | LUCKY | |
22 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 7 | 7 | 0 | 3 | 0.750 | 7 | 12 | 19 | 0 | 0 | 4 | 3 | 0 | 1 | 59 | 20 | 21 | 18 | 3 | 60 | 15 | 18 | 35 | 4 | 0 | 0.00% | 8 | 1 | 87.50% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 50 | 34 | 47 | 15 | 27 | 13 | 53.8% | 11.9% | 88.3% | 100.2 | FUN | |
23 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 5 | 4 | 1 | 2 | 0.500 | 5 | 10 | 15 | 0 | 0 | 1 | 1 | 3 | 0 | 55 | 16 | 22 | 17 | 0 | 66 | 18 | 14 | 36 | 4 | 1 | 25.00% | 6 | 1 | 83.33% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 42 | 29 | 49 | 15 | 27 | 12 | 57.1% | 9.1% | 93.9% | 103.0 | LUCKY | |
24 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 2 | 7 | -5 | 0 | 0.000 | 2 | 3 | 5 | 0 | 0 | 2 | 0 | 0 | 0 | 60 | 14 | 22 | 24 | 0 | 56 | 14 | 17 | 33 | 6 | 2 | 33.33% | 6 | 4 | 33.33% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 47 | 34 | 47 | 14 | 24 | 12 | 0.0% | 3.3% | 87.5% | 90.8 | Unlucky | |
25 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 4 | -1 | 2 | 0.500 | 3 | 6 | 9 | 0 | 0 | 0 | 3 | 0 | 0 | 67 | 27 | 27 | 13 | 0 | 46 | 14 | 16 | 32 | 10 | 1 | 10.00% | 7 | 0 | 100.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 53 | 38 | 43 | 13 | 23 | 11 | 33.3% | 4.5% | 91.3% | 95.8 | DULL | |
26 | 3 | 2 | 0 | 0 | 0 | 0 | 1 | 0 | 10 | 4 | 6 | 6 | 1.000 | 10 | 17 | 27 | 0 | 1 | 3 | 4 | 2 | 2 | 134 | 45 | 46 | 39 | 7 | 63 | 14 | 20 | 69 | 12 | 1 | 8.33% | 9 | 0 | 100.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 84 | 62 | 64 | 19 | 36 | 19 | 69.2% | 7.5% | 93.7% | 101.1 | DULL | |
27 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 5 | 7 | -2 | 2 | 0.500 | 5 | 10 | 15 | 0 | 0 | 2 | 2 | 1 | 0 | 69 | 27 | 21 | 21 | 0 | 71 | 14 | 8 | 45 | 6 | 2 | 33.33% | 4 | 1 | 75.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 48 | 34 | 46 | 14 | 24 | 12 | 33.3% | 7.2% | 90.1% | 97.4 | Unlucky | |
28 | 2 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 6 | 3 | 3 | 4 | 1.000 | 6 | 11 | 17 | 0 | 0 | 1 | 2 | 2 | 1 | 79 | 23 | 31 | 23 | 2 | 60 | 16 | 6 | 36 | 8 | 2 | 25.00% | 3 | 0 | 100.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 50 | 34 | 45 | 14 | 25 | 13 | 57.1% | 7.6% | 95.0% | 102.6 | DULL | |
29 | 3 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 9 | 6 | 3 | 5 | 0.833 | 9 | 17 | 26 | 0 | 1 | 4 | 2 | 3 | 0 | 108 | 38 | 34 | 34 | 2 | 89 | 13 | 21 | 67 | 11 | 3 | 27.27% | 7 | 2 | 71.43% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 79 | 57 | 65 | 20 | 38 | 20 | 60.0% | 8.3% | 93.3% | 101.6 | DULL | |
30 | 3 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 6 | 8 | -2 | 2 | 0.333 | 6 | 11 | 17 | 0 | 0 | 3 | 1 | 2 | 0 | 96 | 30 | 37 | 29 | 0 | 80 | 28 | 24 | 57 | 8 | 0 | 0.00% | 11 | 2 | 81.82% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 76 | 56 | 66 | 21 | 36 | 18 | 50.0% | 6.3% | 90.0% | 96.3 | Unlucky | |
31 | 3 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 11 | 9 | 2 | 5 | 0.833 | 11 | 21 | 32 | 0 | 0 | 4 | 5 | 1 | 1 | 109 | 29 | 35 | 36 | 9 | 78 | 29 | 16 | 61 | 12 | 4 | 33.33% | 8 | 2 | 75.00% | 0 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 80 | 59 | 69 | 22 | 38 | 20 | 50.0% | 10.1% | 88.5% | 98.6 | FUN | |
_Vs Division | 16 | 9 | 3 | 0 | 1 | 3 | 0 | 0 | 45 | 35 | 10 | 23 | 0.719 | 45 | 82 | 127 | 0 | 2 | 18 | 16 | 10 | 1 | 537 | 173 | 187 | 164 | 13 | 416 | 118 | 109 | 317 | 60 | 13 | 21.67% | 47 | 6 | 87.23% | 1 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 418 | 302 | 357 | 114 | 199 | 102 | 52.5% | 8.4% | 91.6% | 100.0 | DULL | |
_Vs Conference | 37 | 21 | 9 | 0 | 1 | 4 | 1 | 1 | 114 | 84 | 30 | 51 | 0.689 | 114 | 207 | 321 | 0 | 4 | 43 | 41 | 28 | 4 | 1230 | 412 | 419 | 381 | 25 | 966 | 260 | 272 | 732 | 141 | 36 | 25.53% | 113 | 22 | 80.53% | 1 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 943 | 674 | 842 | 260 | 461 | 238 | 55.7% | 9.3% | 91.3% | 100.6 | LUCKY | |
_Since Last GM Reset | 69 | 39 | 15 | 0 | 4 | 6 | 2 | 3 | 221 | 161 | 60 | 99 | 0.717 | 221 | 400 | 621 | 1 | 8 | 80 | 84 | 51 | 9 | 2229 | 746 | 767 | 688 | 44 | 1877 | 517 | 507 | 1411 | 252 | 65 | 25.79% | 211 | 35 | 83.41% | 1 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 1730 | 1226 | 1583 | 499 | 877 | 446 | 55.3% | 9.9% | 91.4% | 101.3 | LUCKY | |
Total | 69 | 39 | 15 | 0 | 4 | 6 | 2 | 3 | 221 | 161 | 60 | 99 | 0.717 | 221 | 400 | 621 | 1 | 8 | 80 | 84 | 51 | 9 | 2229 | 746 | 767 | 688 | 44 | 1877 | 517 | 507 | 1411 | 252 | 65 | 25.79% | 211 | 35 | 83.41% | 1 | 1212 | 2460 | 49.27% | 1113 | 2254 | 49.38% | 509 | 1053 | 48.34% | 1730 | 1226 | 1583 | 499 | 877 | 446 | 55.3% | 9.9% | 91.4% | 101.3 | LUCKY |
Puck Time | |
---|---|
Offensive Zone | 25 |
Neutral Zone | 12 |
Defensive Zone | 22 |
Puck Time | |
---|---|
Offensive Zone Start | 2460 |
Neutral Zone Start | 1053 |
Defensive Zone Start | 2254 |
Puck Time | |
---|---|
With Puck | 31 |
Without Puck | 29 |
Faceoffs | |
---|---|
Faceoffs Won | 2834 |
Faceoffs Lost | 2933 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 10.8 | 9.57 |
2nd Period | 21.9 | 20.31 |
3rd Period | 31.9 | 30.68 |
Overtime | 32.5 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 1.2 | 0.64 |
2nd Period | 2.4 | 1.65 |
3rd Period | 3.1 | 2.67 |
Overtime | 3.2 | 2.83 |
Even Strenght Goal | 154 |
---|---|
PP Goal | 65 |
PK Goal | 1 |
Empty Net Goal | 1 |
Home | Away | |
---|---|---|
Win | 20 | 25 |
Lost | 9 | 6 |
Overtime Lost | 5 | 4 |
PP Attempt | 252 |
---|---|
PP Goal | 65 |
PK Attempt | 211 |
PK Goal Against | 35 |
Home | |
---|---|
Shots For | 32.3 |
Shots Against | 27.2 |
Goals For | 3.2 |
Goals Against | 2.3 |
Hits | 20.4 |
Shots Blocked | 7.5 |
Pim | 7.3 |
Date | Matchup | Result | Detail | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2022-10-11 | @ | Golden Knights3,Kings0 | RECAP | |||||||||||
2022-10-13 | @ | Kraken3,Kings5 | RECAP | |||||||||||
2022-10-15 | @ | Kings2,Wild1 | RECAP | |||||||||||
2022-10-17 | @ | Kings3,Red Wings2 (OT) | RECAP | |||||||||||
2022-10-18 | @ | Kings6,Predators2 | RECAP | |||||||||||
2022-10-20 | @ | Kings3,Penguins2 (OT) | RECAP | |||||||||||
2022-10-22 | @ | Kings3,Capitals4 (SO) | RECAP | |||||||||||
2022-10-25 | @ | Lightning0,Kings4 | RECAP | |||||||||||
2022-10-27 | @ | Jets3,Kings1 | RECAP | |||||||||||
2022-10-29 | @ | Maple Leafs4,Kings1 | RECAP | |||||||||||
2022-10-31 | @ | Kings2,Blues1 | RECAP | |||||||||||
2022-11-01 | @ | Kings4,Stars3 (SO) | RECAP | |||||||||||
2022-11-03 | @ | Kings2,Blackhawks3 | RECAP | |||||||||||
2022-11-05 | @ | Panthers3,Kings4 | RECAP | |||||||||||
2022-11-08 | @ | Wild3,Kings2 (OT) | RECAP | |||||||||||
2022-11-10 | @ | Blackhawks4,Kings3 | RECAP | |||||||||||
2022-11-12 | @ | Red Wings2,Kings3 (OT) | RECAP | |||||||||||
2022-11-14 | @ | Kings2,Flames1 | RECAP | |||||||||||
2022-11-16 | @ | Kings4,Oilers1 | RECAP | |||||||||||
2022-11-18 | @ | Kings6,Canucks3 | RECAP | |||||||||||
2022-11-19 | @ | Kings3,Kraken2 (OT) | RECAP | |||||||||||
2022-11-22 | @ | Rangers2,Kings4 | RECAP | |||||||||||
2022-11-25 | @ | Kings3,Sharks2 | RECAP | |||||||||||
2022-11-27 | @ | Senators4,Kings1 | RECAP | |||||||||||
2022-11-29 | @ | Kraken4,Kings3 (OT) | RECAP | |||||||||||
2022-12-01 | @ | Coyotes1,Kings5 | RECAP | |||||||||||
2022-12-03 | @ | Hurricanes4,Kings2 | RECAP | |||||||||||
2022-12-06 | @ | Kings4,Senators2 | RECAP | |||||||||||
2022-12-08 | @ | Kings4,Maple Leafs3 | RECAP | |||||||||||
2022-12-10 | @ | Kings5,Canadiens4 (SO) | RECAP | |||||||||||
2022-12-11 | @ | Kings1,Blue Jackets2 | RECAP | |||||||||||
2022-12-13 | @ | Kings1,Sabres2 | RECAP | |||||||||||
2022-12-15 | @ | Kings4,Bruins2 | RECAP | |||||||||||
2022-12-17 | @ | Sharks4,Kings3 (OT) | RECAP | |||||||||||
2022-12-20 | @ | Ducks3,Kings1 | RECAP | |||||||||||
2022-12-22 | @ | Flames3,Kings2 (OT) | RECAP | |||||||||||
2022-12-23 | @ | Kings4,Coyotes2 | RECAP | |||||||||||
2022-12-27 | @ | Golden Knights1,Kings5 | RECAP | |||||||||||
2022-12-29 | @ | Kings4,Avalanche1 | RECAP | |||||||||||
2022-12-31 | @ | Flyers0,Kings3 | RECAP | |||||||||||
2023-01-03 | @ | Stars0,Kings2 | RECAP | |||||||||||
2023-01-05 | @ | Bruins4,Kings3 (OT) | RECAP | |||||||||||
2023-01-07 | @ | Kings1,Golden Knights4 | RECAP | |||||||||||
2023-01-09 | @ | Oilers0,Kings2 | RECAP | |||||||||||
2023-01-11 | @ | Sharks0,Kings3 | RECAP | |||||||||||
2023-01-14 | @ | Devils5,Kings3 | RECAP | |||||||||||
2023-01-19 | @ | Stars1,Kings4 | RECAP | |||||||||||
2023-01-21 | @ | Kings4,Predators6 | RECAP | |||||||||||
2023-01-22 | @ | Kings4,Blackhawks0 | RECAP | |||||||||||
2023-01-24 | @ | Kings4,Flyers1 | RECAP | |||||||||||
2023-01-27 | @ | Kings3,Panthers4 (SO) | RECAP | |||||||||||
2023-01-28 | @ | Kings4,Lightning3 | RECAP | |||||||||||
2023-01-31 | @ | Kings4,Hurricanes2 | RECAP | |||||||||||
2023-02-11 | @ | Penguins1,Kings3 | RECAP | |||||||||||
2023-02-13 | @ | Sabres2,Kings3 | RECAP | |||||||||||
2023-02-17 | @ | Kings2,Ducks1 | RECAP | |||||||||||
2023-02-18 | @ | Coyotes2,Kings4 | RECAP | |||||||||||
2023-02-21 | @ | Kings1,Wild2 (SO) | RECAP | |||||||||||
2023-02-23 | @ | Kings4,Devils1 | RECAP | |||||||||||
2023-02-24 | @ | Kings5,Islanders6 (OT) | RECAP | |||||||||||
2023-02-26 | @ | Kings4,Rangers3 | RECAP | |||||||||||
2023-02-28 | @ | Kings1,Jets4 | RECAP | |||||||||||
2023-03-02 | @ | Canadiens1,Kings4 | RECAP | |||||||||||
2023-03-04 | @ | Blues4,Kings2 | RECAP | |||||||||||
Trade Deadline --- Trades can’t be done after this day is simulated! | ||||||||||||||
2023-03-06 | @ | Capitals0,Kings4 | RECAP | |||||||||||
2023-03-09 | @ | Kings6,Avalanche1 | RECAP | |||||||||||
2023-03-11 | @ | Predators5,Kings6 | RECAP | |||||||||||
2023-03-14 | @ | Islanders0,Kings5 | RECAP | |||||||||||
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Salary Cap | |||
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Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
86,075,000$ | 0$ | 80,114,027$ | -3,575,000$ |
Arena | Goal Horn | About us | |
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![]() | Name | Staples Center | |
City | Los Angeles | ||
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 | 191035 | 160969 | 64756 | 129838 | 32501 |
Attendance PCT | 93.64% | 94.69% | 95.23% | 95.47% | 95.59% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
7 | 17032 - 94.62% | 1,499,053$ | 50,967,811$ | 18000 | 100 |
Expenses | |||
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Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
86,075,000$ | 86,075,000$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
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70,116,676$ | 440,873$ | 68,210,456$ | 0$ |
Estimate | |||
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Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
10,493,373$ | 27 | 460,714$ | 12,439,278$ |
Team Total Estimate | |||
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Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
12,859,598$ | 86,075,000$ | 45,456,613$ | 43,090,388$ |
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 | |||||||
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Priority | Type | Description |
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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 |
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Alex Jefferies | |||||
Alexander Nikishin | 2020 | 99 | |||
Bear Hughes | |||||
Cameron Lund | 2022 | 66 | |||
Connor Hvidston | 2022 | 184 | |||
Frederik Nissen | 2019 | 140 | |||
Jake Lee | 2019 | 118 | |||
Jakub Vondras | 2022 | 190 | |||
Jani Nyman | 2022 | 50 | |||
Mans Forsfjall | 2020 | 153 | |||
Mason Lohrei | |||||
Redmond Savage | 2021 | 107 | |||
Rieger Lorenz | 2022 | 53 | |||
Simon Kubicek | 2020 | 138 | |||
Timofey Spitserov | |||||
Trevor Janicke | 2019 | 138 | |||
Veeti Miettinen | 2020 | 83 | |||
Zion Nybeck | 2020 | 33 |
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