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Full Scoreboard »» |
San Jose Sharks 20-23-6, 46pts · 12th 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 | LW | 100.00 | 79 | 33 | 74 | 86 | 75 | 89 | 90 | 82 | 77 | 87 | 82 | 78 | 82 | 60 | 58 | 0 | 49 | 90 | 21 | 925,000$/9yrs | |||
![]() | 0 | LW/RW | 98.00 | 96 | 33 | 55 | 81 | 83 | 88 | 77 | 81 | 59 | 80 | 86 | 68 | 84 | 79 | 74 | 0 | 45 | 89 | 31 | 7,000,000$/3yrs | |||
![]() | 0 | RW | 100.00 | 66 | 33 | 84 | 78 | 76 | 84 | 90 | 74 | 72 | 78 | 76 | 70 | 75 | 65 | 64 | 0 | 30 | 84 | 24 | 5,750,000$/3yrs | |||
![]() | 0 | LW/RW | 100.00 | 56 | 32 | 96 | 79 | 70 | 80 | 88 | 76 | 57 | 76 | 79 | 59 | 78 | 71 | 71 | 0 | 27 | 84 | 27 | 4,675,000$/4yrs | |||
![]() | 0 | C/LW | 100.00 | 77 | 37 | 78 | 73 | 71 | 84 | 77 | 74 | 74 | 72 | 79 | 63 | 77 | 70 | 68 | 0 | 41 | 82 | 27 | 4,000,000$/3yrs | |||
![]() | 0 | RW | 100.00 | 54 | 33 | 84 | 71 | 79 | 81 | 90 | 70 | 58 | 80 | 67 | 61 | 68 | 85 | 83 | 0 | 43 | 81 | 35 | 4,750,000$/1yrs | |||
![]() | 0 | C | 98.00 | 82 | 37 | 72 | 61 | 73 | 78 | 89 | 64 | 86 | 64 | 66 | 84 | 65 | 79 | 76 | 0 | 41 | 79 | 31 | 3,250,000$/2yrs | |||
![]() | 24 | RW | 100.00 | 64 | 38 | 84 | 67 | 77 | 70 | 72 | 68 | 41 | 67 | 71 | 65 | 69 | 72 | 71 | 0 | 40 | 77 | 28 | 750,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 97 | 60 | 64 | 57 | 88 | 74 | 88 | 62 | 59 | 64 | 61 | 66 | 62 | 82 | 78 | 0 | 24 | 76 | 33 | 1,500,000$/2yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 76 | 41 | 68 | 55 | 80 | 75 | 72 | 58 | 82 | 61 | 58 | 83 | 58 | 90 | 87 | 0 | 18 | 76 | 38 | 750,000$/1yrs | |||
![]() | 0 | LW | 100.00 | 69 | 47 | 59 | 67 | 93 | 77 | 69 | 68 | 55 | 71 | 66 | 58 | 67 | 66 | 62 | 0 | 47 | 76 | 24 | 850,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 73 | 34 | 93 | 63 | 91 | 71 | 70 | 67 | 73 | 69 | 64 | 61 | 66 | 70 | 69 | 0 | 33 | 76 | 26 | 1,000,000$/1yrs | |||
![]() | 8 | D | 97.00 | 62 | 33 | 90 | 80 | 84 | 98 | 83 | 76 | 30 | 82 | 73 | 83 | 75 | 68 | 74 | 0 | 48 | 89 | 25 | 7,500,000$/4yrs | |||
![]() | 0 | D | 98.00 | 67 | 39 | 80 | 67 | 76 | 68 | 71 | 65 | 30 | 73 | 59 | 71 | 66 | 70 | 68 | 0 | 30 | 79 | 27 | 900,000$/1yrs | |||
![]() | 0 | D | 99.00 | 83 | 57 | 74 | 63 | 77 | 80 | 81 | 65 | 30 | 69 | 58 | 76 | 62 | 66 | 64 | 0 | 48 | 79 | 24 | 1,500,000$/2yrs | |||
![]() | 0 | D | 100.00 | 69 | 33 | 89 | 62 | 75 | 83 | 83 | 63 | 30 | 68 | 66 | 73 | 64 | 68 | 67 | 0 | 35 | 78 | 25 | 4,000,000$/2yrs | |||
![]() | 0 | D | 100.00 | 79 | 41 | 60 | 62 | 74 | 67 | 74 | 62 | 30 | 68 | 61 | 71 | 65 | 72 | 68 | 0 | 43 | 77 | 28 | 1,000,000$/2yrs | |||
![]() | 68 | D | 100.00 | 71 | 33 | 71 | 63 | 77 | 74 | 69 | 65 | 30 | 71 | 50 | 67 | 58 | 73 | 70 | 0 | 42 | 77 | 28 | 1,000,000$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | LW | 100.00 | 69 | 33 | 99 | 61 | 85 | 75 | 69 | 64 | 55 | 65 | 66 | 58 | 65 | 85 | 84 | 0 | 30 | 75 | 35 | 2,000,000$/1yrs | |||
TEAM AVERAGE | 99.47 | 73 | 38 | 78 | 68 | 79 | 79 | 79 | 69 | 54 | 72 | 68 | 69 | 69 | 73 | 71 | 0 | 38 | 80 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 98.00 | 69 | 76 | 72 | 77 | 73 | 73 | 77 | 84 | 77 | 84 | 77 | 77 | 80 | 0 | 48 | 81 | 30 | 3,250,000$/1yrs |
![]() | 0 | 100.00 | 73 | 76 | 72 | 79 | 74 | 76 | 75 | 73 | 76 | 73 | 75 | 71 | 73 | 0 | 26 | 78 | 26 | 750,000$/1yrs |
Scratches | ||||||||||||||||||||
![]() | 0 | 95.00 | 87 | 88 | 78 | 79 | 84 | 80 | 86 | 91 | 85 | 90 | 86 | 80 | 84 | 0 | 42 | 88 | 32 | 2,875,000$/1yrs |
TEAM AVERAGE | 97.67 | 76 | 80 | 74 | 78 | 77 | 76 | 79 | 83 | 79 | 82 | 79 | 76 | 79 | 0 | 39 | 82 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Brad Larsen | 71 | 67 | 83 | 85 | 64 | 60 | 67 | CAN | 43 | 2 | 1,000,000$ |
General Manager | Charles-Antoine Sirois |
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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 | Evander Kane | 0 | LW/RW | 48 | 26 | 23 | 49 | 13 | 70 | 0 | 150 | 170 | 38 | 123 | 15.29% | 14 | 20.92 | 5 | 5 | 10 | 134 | 0 | 0 | 0 | 77 | 6 | 5 | 42.06% | 107 | 0 | 0 | 0 | 1 | 0.98 | 1 | 5 | |
2 | Tim Stutzle | 0 | LW | 48 | 15 | 15 | 30 | -3 | 31 | 5 | 83 | 163 | 49 | 111 | 9.20% | 21 | 19.36 | 4 | 2 | 6 | 125 | 0 | 0 | 0 | 75 | 3 | 2 | 45.12% | 164 | 0 | 0 | 0 | 1 | 0.65 | 1 | 3 | |
3 | Martin Necas | 0 | RW | 48 | 10 | 17 | 27 | 0 | 2 | 0 | 24 | 128 | 32 | 89 | 7.81% | 13 | 19.81 | 2 | 2 | 4 | 115 | 1 | 0 | 1 | 124 | 1 | 0 | 45.52% | 290 | 0 | 0 | 0 | 0 | 0.57 | 1 | 2 | |
4 | Zach Werenski | 8 | D | 47 | 4 | 22 | 26 | -7 | 10 | 0 | 33 | 58 | 20 | 49 | 6.90% | 68 | 22.48 | 2 | 2 | 4 | 84 | 0 | 0 | 0 | 129 | 0 | 0 | 0.00% | 0 | 0 | 0 | 1 | 0 | 0.49 | 0 | 0 | |
5 | Phil Kessel | 0 | RW | 49 | 6 | 19 | 25 | 6 | 0 | 0 | 0 | 108 | 23 | 79 | 5.56% | 5 | 16.09 | 0 | 4 | 4 | 111 | 0 | 0 | 0 | 51 | 0 | 1 | 46.34% | 123 | 0 | 0 | 0 | 0 | 0.63 | 1 | 2 | |
6 | Robby Fabbri | 0 | C/LW | 49 | 5 | 15 | 20 | -1 | 10 | 0 | 46 | 98 | 23 | 68 | 5.10% | 7 | 18.61 | 0 | 3 | 3 | 131 | 0 | 0 | 0 | 38 | 0 | 0 | 43.42% | 1101 | 0 | 0 | 0 | 0 | 0.44 | 0 | 2 | |
7 | Victor Olofsson | 0 | LW/RW | 46 | 8 | 11 | 19 | 2 | 0 | 0 | 3 | 94 | 27 | 78 | 8.51% | 3 | 16.85 | 2 | 2 | 4 | 54 | 0 | 0 | 0 | 65 | 2 | 0 | 33.73% | 83 | 0 | 0 | 0 | 0 | 0.49 | 0 | 0 | |
8 | Casey Cizikas | 0 | C | 49 | 6 | 8 | 14 | -4 | 14 | 0 | 53 | 45 | 14 | 45 | 13.33% | 3 | 10.21 | 0 | 3 | 3 | 21 | 0 | 0 | 0 | 78 | 3 | 1 | 51.27% | 591 | 0 | 0 | 0 | 0 | 0.56 | 0 | 0 | |
9 | Christian Wolanin | 0 | D | 33 | 3 | 11 | 14 | 6 | 14 | 0 | 32 | 17 | 6 | 9 | 17.65% | 44 | 16.86 | 1 | 1 | 2 | 28 | 0 | 0 | 0 | 85 | 0 | 2 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.50 | 0 | 0 | |
10 | Slater Koekkoek | 68 | D | 48 | 5 | 8 | 13 | -2 | 20 | 0 | 52 | 35 | 12 | 16 | 14.29% | 60 | 18.51 | 1 | 0 | 1 | 90 | 0 | 0 | 0 | 99 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.29 | 0 | 0 | |
11 | Ethan Bear | 0 | D | 47 | 2 | 10 | 12 | 0 | 36 | 0 | 71 | 24 | 14 | 30 | 8.33% | 73 | 20.92 | 0 | 3 | 3 | 122 | 0 | 0 | 0 | 155 | 1 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.24 | 0 | 0 | |
12 | Riley Stillman | 0 | D | 48 | 3 | 7 | 10 | -7 | 88 | 10 | 171 | 31 | 8 | 28 | 9.68% | 78 | 20.15 | 1 | 1 | 2 | 46 | 0 | 1 | 1 | 89 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.21 | 0 | 0 | |
13 | Connor Carrick | 0 | D | 49 | 3 | 6 | 9 | 5 | 86 | 10 | 128 | 29 | 8 | 26 | 10.34% | 60 | 19.13 | 0 | 0 | 0 | 98 | 0 | 0 | 0 | 104 | 1 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.19 | 0 | 0 | |
14 | Brett Murray | 0 | LW | 49 | 2 | 5 | 7 | -15 | 17 | 5 | 48 | 42 | 6 | 27 | 4.76% | 4 | 8.75 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 1 | 0 | 36.36% | 66 | 0 | 0 | 0 | 0 | 0.33 | 0 | 1 | |
15 | Matt Martin | 0 | LW/RW | 47 | 5 | 0 | 5 | -1 | 41 | 5 | 62 | 22 | 7 | 14 | 22.73% | 7 | 7.90 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 42.31% | 26 | 0 | 0 | 0 | 0 | 0.27 | 0 | 0 | |
16 | Nate Thompson | 0 | C/LW/RW | 15 | 3 | 2 | 5 | 3 | 2 | 0 | 5 | 20 | 3 | 9 | 15.00% | 6 | 8.51 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 2 | 0 | 0 | 49.66% | 145 | 0 | 0 | 0 | 0 | 0.78 | 0 | 1 | |
17 | James Neal | 0 | LW | 39 | 0 | 4 | 4 | -4 | 2 | 0 | 6 | 27 | 9 | 19 | 0.00% | 0 | 7.62 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 43.75% | 16 | 0 | 0 | 0 | 0 | 0.27 | 0 | 0 | |
18 | Radim Zohorna | 0 | LW/RW | 41 | 0 | 3 | 3 | -11 | 4 | 0 | 16 | 20 | 8 | 18 | 0.00% | 1 | 8.37 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 46.67% | 270 | 0 | 0 | 0 | 0 | 0.17 | 0 | 0 | |
19 | Riley Barber | 24 | RW | 11 | 0 | 0 | 0 | -1 | 0 | 0 | 4 | 10 | 3 | 8 | 0.00% | 1 | 9.37 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 22 | 0 | 0 | 33.33% | 24 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
Team Total or Average | 811 | 106 | 186 | 292 | -21 | 447 | 35 | 987 | 1141 | 310 | 846 | 9.29% | 468 | 15.93 | 18 | 28 | 46 | 1172 | 1 | 1 | 2 | 1206 | 18 | 11 | 45.41% | 3006 | 0 | 0 | 1 | 2 | 0.45 | 4 | 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 | Jake Allen | 27 | 11 | 11 | 4 | 0.927 | 2.62 | 1580 | 2 | 1 | 69 | 944 | 0 | 1 | 0 | 0.778 | 9 | 26 | 17 | 4 | 3 | 3 | |
2 | Petr Mrazek | 20 | 8 | 7 | 2 | 0.926 | 2.36 | 1093 | 0 | 0 | 43 | 578 | 0 | 0 | 1 | 0.714 | 7 | 17 | 26 | 4 | 1 | 0 | |
Team Total or Average | 47 | 19 | 18 | 6 | 0.926 | 2.51 | 2673 | 2 | 1 | 112 | 1522 | 0 | 1 | 1 | 0.750 | 16 | 43 | 43 | 8 | 4 | 3 |
Projected Total Cap Hit | 59,377,222$ |
Projected Cap Space | 23,122,778$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 35,812,174$ |
Players In Salary Cap | 21 |
LTIR Players | 1 |
Sharks Roster | Pos | Age | Cap Hit | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 |
---|---|---|---|---|---|---|---|---|---|---|---|
Brett Murray ![]() | LW | 24 | 850,000$ | 850,000$ | RFA | ||||||
Casey Cizikas | C | 31 | 3,250,000$ | 3,250,000$ | 3,250,000$ | UFA | |||||
Christian Wolanin ![]() | D | 27 | 900,000$ | 900,000$ | UFA | ||||||
Connor Carrick ![]() | D | 28 | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | |||||
Ethan Bear | D | 25 | 4,000,000$ | 4,000,000$ | 4,000,000$ | ![]() | |||||
Evander Kane | LW/RW | 31 | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ | UFA | ||||
Jake Allen ![]() | G | 32 | 2,875,000$ | 2,875,000$ | UFA | ||||||
James Neal | LW | 35 | 2,000,000$ | 2,000,000$ | UFA | ||||||
Joey Daccord ![]() | G | 26 | 750,000$ | 750,000$ | ![]() | ||||||
Martin Necas | RW | 24 | 5,750,000$ | 5,750,000$ | 5,750,000$ | 5,750,000$ | ![]() | ||||
Matt Martin | LW/RW | 33 | 1,500,000$ | 1,500,000$ | 1,500,000$ | UFA | |||||
Nate Thompson ![]() | C/LW/RW | 38 | 750,000$ | 750,000$ | UFA | ||||||
Petr Mrazek | G | 30 | 3,250,000$ | 3,250,000$ | UFA | ||||||
Phil Kessel | RW | 35 | 4,750,000$ | 4,750,000$ | UFA | ||||||
Radim Zohorna ![]() | LW/RW | 26 | 1,000,000$ | 1,000,000$ | ![]() | ||||||
Riley Barber ![]() | RW | 28 | 750,000$ | 750,000$ | 750,000$ | UFA | |||||
Riley Stillman | D | 24 | 1,500,000$ | 1,500,000$ | 1,500,000$ | ![]() | |||||
Robby Fabbri | C/LW | 27 | 4,000,000$ | 4,000,000$ | 4,000,000$ | 4,000,000$ | UFA | ||||
Slater Koekkoek ![]() | D | 28 | 1,000,000$ | 1,000,000$ | UFA | ||||||
Tim Stutzle ![]() | LW | 21 | 925,000$ | 925,000$ | 8,350,000$ | 8,350,000$ | 8,350,000$ | 8,350,000$ | 8,350,000$ | 8,350,000$ | 8,350,000$ |
Victor Olofsson | LW/RW | 27 | 4,675,000$ | 4,675,000$ | 4,675,000$ | 4,675,000$ | 4,675,000$ | UFA | |||
Zach Werenski | D | 25 | 7,500,000$ | 7,500,000$ | 7,500,000$ | 7,500,000$ | 7,500,000$ | UFA |
Non-Roster | Pos | Age | Cap Hit | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 |
---|---|---|---|---|---|---|---|---|---|---|---|
Alec Rauhausser ![]() | D | 27 | 775,000$ | 775,000$ | UFA | ||||||
Ben Thomson ![]() | LW | 30 | 750,000$ | 750,000$ | 750,000$ | 750,000$ | UFA | ||||
Bobby Brink ![]() | RW | 21 | 750,000$ | 750,000$ | RFA | ||||||
Brian Flynn ![]() ![]() | C/LW/RW | 34 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Chris Bigras ![]() | D | 27 | 750,000$ | 750,000$ | UFA | ||||||
Clay Hanus ![]() | D | 21 | 900,000$ | 900,000$ | 900,000$ | 900,000$ | RFA | ||||
Daniil Chechelev ![]() | G | 21 | 750,000$ | 750,000$ | RFA | ||||||
Darien Kielb ![]() | D | 23 | 750,000$ | 750,000$ | RFA | ||||||
Evan Cormier ![]() | G | 25 | 750,000$ | 750,000$ | 750,000$ | ![]() | |||||
Filip Hallander ![]() | C | 22 | 764,167$ | 764,167$ | RFA | ||||||
Ilya Usau ![]() | C | 21 | 897,500$ | 897,500$ | 897,500$ | 897,500$ | RFA | ||||
Jacob Ingham ![]() | G | 22 | 1,250,000$ | 1,250,000$ | RFA | ||||||
Jayson Megna ![]() | C | 32 | 750,000$ | 750,000$ | 750,000$ | UFA | |||||
Joel Blomqvist ![]() | G | 21 | 750,000$ | 750,000$ | RFA | ||||||
John Hayden ![]() | RW | 27 | 750,000$ | 750,000$ | UFA | ||||||
Justin Richards ![]() | C/RW | 24 | 925,000$ | 925,000$ | 925,000$ | ![]() | |||||
Kevin Mandolese ![]() | G | 22 | 825,000$ | 825,000$ | 825,000$ | RFA | |||||
Kody Clark ![]() | RW | 23 | 803,333$ | 803,333$ | RFA | ||||||
Lias Andersson ![]() | C | 24 | 1,000,000$ | 1,000,000$ | RFA | ||||||
Linus Sandin ![]() | RW | 26 | 750,000$ | 750,000$ | ![]() | ||||||
Luke Prokop ![]() | D | 20 | 811,667$ | 811,667$ | 811,667$ | RFA | |||||
Michael Hutchinson ![]() ![]() | G | 32 | 800,000$ | 800,000$ | UFA | ||||||
Nathan Clurman ![]() | D | 24 | 842,500$ | 842,500$ | ![]() | ||||||
Nick Cicek ![]() | D | 22 | 835,000$ | 835,000$ | 835,000$ | RFA | |||||
Nick Wolff ![]() | D | 26 | 850,000$ | 850,000$ | 850,000$ | ![]() | |||||
Robert Carpenter ![]() | C | 26 | 800,000$ | 800,000$ | ![]() | ||||||
Skyler McKenzie ![]() | LW | 25 | 775,000$ | 775,000$ | ![]() | ||||||
Tanner Laczynski ![]() | C | 25 | 925,000$ | 925,000$ | ![]() | ||||||
Tim Berni ![]() | D | 22 | 925,000$ | 925,000$ | RFA | ||||||
Vasili Ponomaryov ![]() | C | 20 | 818,333$ | 818,333$ | RFA | ||||||
Will Cuylle ![]() | LW | 20 | 850,833$ | 850,833$ | 850,833$ | 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 |
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1 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 4 | 6 | -2 | 0 | 0.000 | 4 | 6 | 10 | 0 | 0 | 0 | 3 | 1 | 0 | 40 | 9 | 17 | 14 | 0 | 65 | 16 | 19 | 39 | 7 | 1 | 14.29% | 7 | 2 | 71.43% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 41 | 29 | 56 | 15 | 21 | 10 | 42.9% | 10.0% | 90.8% | 100.8 | FUN | |
2 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 3 | 9 | -6 | 0 | 0.000 | 3 | 6 | 9 | 0 | 0 | 0 | 2 | 1 | 0 | 49 | 18 | 14 | 17 | 0 | 73 | 25 | 20 | 45 | 7 | 1 | 14.29% | 9 | 0 | 100.00% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 39 | 25 | 57 | 13 | 22 | 10 | 18.2% | 6.1% | 87.7% | 93.8 | Unlucky | |
3 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 2 | 6 | -4 | 0 | 0.000 | 2 | 3 | 5 | 0 | 0 | 1 | 0 | 1 | 0 | 33 | 12 | 11 | 10 | 0 | 67 | 24 | 14 | 46 | 5 | 0 | 0.00% | 7 | 0 | 100.00% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 42 | 28 | 54 | 15 | 22 | 11 | 25.0% | 6.1% | 91.0% | 97.1 | Unlucky | |
4 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 4 | 7 | -3 | 0 | 0.000 | 4 | 6 | 10 | 0 | 0 | 1 | 1 | 2 | 0 | 63 | 24 | 19 | 20 | 0 | 58 | 15 | 22 | 41 | 6 | 1 | 16.67% | 10 | 3 | 70.00% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 48 | 33 | 46 | 13 | 25 | 12 | 42.9% | 6.3% | 87.9% | 94.3 | Unlucky | |
5 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 3 | 2 | 1.000 | 4 | 7 | 11 | 0 | 0 | 2 | 2 | 0 | 0 | 32 | 15 | 7 | 10 | 0 | 45 | 17 | 9 | 20 | 2 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 18 | 12 | 29 | 7 | 11 | 5 | 80.0% | 12.5% | 97.8% | 110.3 | LUCKY | |
6 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 5 | 4 | 1 | 2 | 1.000 | 5 | 6 | 11 | 0 | 0 | 3 | 0 | 1 | 1 | 43 | 14 | 10 | 15 | 6 | 33 | 13 | 14 | 22 | 5 | 1 | 20.00% | 7 | 3 | 57.14% | 1 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 22 | 14 | 29 | 8 | 13 | 6 | 80.0% | 11.6% | 87.9% | 99.5 | FUN | |
7 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 4 | 4 | 4 | 1.000 | 8 | 15 | 23 | 0 | 0 | 4 | 3 | 1 | 0 | 60 | 20 | 28 | 12 | 0 | 43 | 14 | 6 | 45 | 4 | 0 | 0.00% | 3 | 1 | 66.67% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 47 | 33 | 47 | 15 | 25 | 13 | 72.7% | 13.3% | 90.7% | 104.0 | FUN | |
8 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 8 | 6 | 2 | 3 | 0.750 | 8 | 15 | 23 | 0 | 0 | 4 | 3 | 1 | 1 | 56 | 13 | 27 | 13 | 6 | 89 | 37 | 27 | 41 | 9 | 1 | 11.11% | 11 | 3 | 72.73% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 43 | 29 | 56 | 15 | 25 | 12 | 70.0% | 14.3% | 93.3% | 107.5 | LUCKY | |
9 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 24 | 6 | 10 | 8 | 0 | 33 | 11 | 4 | 18 | 2 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 21 | 14 | 27 | 6 | 11 | 5 | 20.0% | 4.2% | 87.9% | 92.0 | Unlucky | |
10 | 2 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 4 | 8 | -4 | 2 | 0.500 | 4 | 6 | 10 | 0 | 0 | 0 | 1 | 2 | 1 | 44 | 12 | 18 | 12 | 6 | 62 | 11 | 12 | 34 | 7 | 0 | 0.00% | 6 | 1 | 83.33% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 43 | 28 | 54 | 15 | 26 | 12 | 36.4% | 9.1% | 87.1% | 96.2 | FUN | |
11 | 3 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 8 | 6 | 2 | 3 | 0.500 | 8 | 13 | 21 | 0 | 0 | 4 | 3 | 1 | 0 | 78 | 29 | 28 | 18 | 3 | 103 | 33 | 22 | 69 | 11 | 1 | 9.09% | 11 | 2 | 81.82% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 65 | 43 | 76 | 22 | 39 | 19 | 63.6% | 10.3% | 94.2% | 104.4 | LUCKY | |
12 | 3 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 6 | 9 | -3 | 2 | 0.333 | 6 | 10 | 16 | 0 | 0 | 1 | 1 | 3 | 1 | 89 | 26 | 25 | 35 | 3 | 108 | 37 | 39 | 53 | 7 | 2 | 28.57% | 11 | 3 | 72.73% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 65 | 44 | 79 | 22 | 38 | 18 | 40.0% | 6.7% | 91.7% | 98.4 | DULL | |
13 | 2 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 4 | 6 | -2 | 1 | 0.250 | 4 | 7 | 11 | 0 | 0 | 2 | 1 | 1 | 0 | 67 | 15 | 20 | 30 | 6 | 96 | 23 | 10 | 52 | 4 | 1 | 25.00% | 4 | 0 | 100.00% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 39 | 26 | 60 | 15 | 25 | 11 | 33.3% | 6.0% | 93.8% | 99.7 | DULL | |
14 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 | 3 | -1 | 1 | 0.500 | 2 | 4 | 6 | 0 | 0 | 1 | 1 | 0 | 0 | 19 | 5 | 8 | 5 | 1 | 34 | 16 | 8 | 20 | 3 | 0 | 0.00% | 4 | 2 | 50.00% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 22 | 14 | 27 | 8 | 13 | 6 | 66.7% | 10.5% | 91.2% | 101.7 | LUCKY | |
15 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 3 | 2 | 1.000 | 4 | 7 | 11 | 0 | 0 | 1 | 2 | 1 | 0 | 24 | 5 | 5 | 14 | 0 | 36 | 7 | 12 | 18 | 2 | 0 | 0.00% | 6 | 1 | 83.33% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 22 | 14 | 25 | 7 | 12 | 5 | 100.0% | 16.7% | 97.2% | 113.9 | LUCKY | |
16 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 4 | 3 | 1 | 2 | 1.000 | 4 | 8 | 12 | 0 | 0 | 0 | 2 | 1 | 1 | 34 | 14 | 10 | 6 | 4 | 31 | 12 | 12 | 31 | 3 | 1 | 33.33% | 6 | 1 | 83.33% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 22 | 15 | 28 | 8 | 12 | 5 | 60.0% | 11.8% | 90.3% | 102.1 | FUN | |
17 | 2 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 9 | 7 | 2 | 4 | 1.000 | 9 | 15 | 24 | 0 | 0 | 3 | 1 | 3 | 3 | 58 | 21 | 15 | 13 | 12 | 78 | 23 | 10 | 62 | 4 | 1 | 25.00% | 5 | 2 | 60.00% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 46 | 33 | 55 | 14 | 24 | 11 | 61.5% | 15.5% | 91.0% | 106.5 | FUN | |
18 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | 3 | 1 | 3 | 0.750 | 4 | 8 | 12 | 0 | 1 | 1 | 1 | 2 | 0 | 45 | 13 | 15 | 17 | 3 | 71 | 21 | 26 | 41 | 4 | 1 | 25.00% | 13 | 1 | 92.31% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 39 | 24 | 58 | 16 | 26 | 12 | 60.0% | 8.9% | 95.8% | 104.7 | Unlucky | |
19 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | -2 | 0 | 0.000 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 20 | 10 | 3 | 7 | 0 | 31 | 10 | 10 | 15 | 4 | 0 | 0.00% | 5 | 1 | 80.00% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 21 | 14 | 25 | 7 | 12 | 6 | 0.0% | 0.0% | 93.5% | 93.5 | DULL | |
20 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 5 | 6 | -1 | 2 | 0.500 | 5 | 10 | 15 | 0 | 0 | 1 | 1 | 3 | 0 | 61 | 15 | 20 | 26 | 0 | 76 | 18 | 29 | 58 | 8 | 2 | 25.00% | 6 | 0 | 100.00% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 37 | 24 | 56 | 15 | 25 | 11 | 33.3% | 8.2% | 92.1% | 100.3 | DULL | |
21 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 4 | -1 | 0 | 0.000 | 3 | 6 | 9 | 0 | 0 | 1 | 1 | 1 | 0 | 34 | 11 | 15 | 8 | 0 | 24 | 14 | 10 | 10 | 2 | 0 | 0.00% | 5 | 1 | 80.00% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 25 | 17 | 21 | 6 | 13 | 6 | 50.0% | 8.8% | 83.3% | 92.2 | Unlucky | |
22 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | -2 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 0 | 1 | 0 | 13 | 4 | 3 | 6 | 0 | 45 | 15 | 22 | 19 | 0 | 0 | 0.00% | 11 | 3 | 72.73% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 15 | 9 | 31 | 8 | 12 | 4 | 100.0% | 7.7% | 93.3% | 101.0 | DULL | |
23 | 4 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 7 | 11 | -4 | 4 | 0.500 | 7 | 11 | 18 | 0 | 0 | 0 | 4 | 3 | 0 | 102 | 31 | 29 | 42 | 0 | 155 | 40 | 38 | 90 | 15 | 0 | 0.00% | 16 | 3 | 81.25% | 1 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 82 | 54 | 108 | 30 | 48 | 23 | 46.7% | 6.9% | 92.9% | 99.8 | DULL | |
24 | 3 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 9 | 6 | 3 | 5 | 0.833 | 9 | 18 | 27 | 0 | 0 | 3 | 1 | 5 | 0 | 84 | 26 | 22 | 36 | 0 | 69 | 31 | 36 | 69 | 14 | 3 | 21.43% | 18 | 1 | 94.44% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 70 | 46 | 72 | 22 | 38 | 18 | 54.5% | 10.7% | 91.3% | 102.0 | LUCKY | |
25 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 4 | 10 | -6 | 0 | 0.000 | 4 | 8 | 12 | 0 | 0 | 3 | 0 | 1 | 0 | 50 | 20 | 11 | 19 | 0 | 70 | 22 | 20 | 41 | 7 | 1 | 14.29% | 10 | 2 | 80.00% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 41 | 27 | 54 | 14 | 24 | 11 | 27.3% | 8.0% | 85.7% | 93.7 | Unlucky | |
26 | 2 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 5 | 5 | 0 | 2 | 0.500 | 5 | 9 | 14 | 0 | 0 | 1 | 1 | 2 | 1 | 59 | 25 | 16 | 17 | 1 | 75 | 13 | 23 | 44 | 4 | 1 | 25.00% | 8 | 0 | 100.00% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 42 | 27 | 52 | 16 | 25 | 11 | 44.4% | 8.5% | 93.3% | 101.8 | DULL | |
27 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 2 | 1.000 | 3 | 6 | 9 | 0 | 0 | 1 | 1 | 1 | 0 | 17 | 5 | 9 | 3 | 0 | 32 | 9 | 10 | 10 | 4 | 0 | 0.00% | 5 | 1 | 80.00% | 0 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 20 | 13 | 26 | 7 | 12 | 5 | 100.0% | 17.6% | 96.9% | 114.5 | LUCKY | |
_Vs Division | 16 | 5 | 8 | 0 | 2 | 1 | 0 | 0 | 37 | 39 | -2 | 15 | 0.469 | 37 | 62 | 99 | 0 | 0 | 8 | 15 | 12 | 2 | 409 | 130 | 129 | 143 | 7 | 574 | 155 | 163 | 323 | 50 | 5 | 10.00% | 64 | 12 | 81.25% | 1 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 341 | 227 | 425 | 121 | 199 | 94 | 54.2% | 9.0% | 93.2% | 102.3 | LUCKY | |
_Vs Conference | 28 | 8 | 11 | 0 | 4 | 2 | 2 | 1 | 72 | 75 | -3 | 31 | 0.554 | 72 | 126 | 198 | 0 | 0 | 17 | 22 | 27 | 7 | 757 | 233 | 234 | 266 | 35 | 986 | 273 | 272 | 629 | 90 | 13 | 14.44% | 109 | 17 | 84.40% | 1 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 601 | 402 | 753 | 213 | 352 | 166 | 50.4% | 9.5% | 92.4% | 101.9 | LUCKY | |
_Since Last GM Reset | 49 | 13 | 23 | 0 | 4 | 3 | 3 | 3 | 121 | 141 | -20 | 46 | 0.469 | 121 | 214 | 335 | 0 | 1 | 39 | 36 | 39 | 9 | 1298 | 418 | 415 | 433 | 51 | 1702 | 527 | 484 | 1053 | 150 | 19 | 12.67% | 208 | 37 | 82.21% | 2 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 1050 | 701 | 1322 | 371 | 613 | 290 | 49.5% | 9.3% | 91.7% | 101.0 | LUCKY | |
Total | 49 | 13 | 23 | 0 | 4 | 3 | 3 | 3 | 121 | 141 | -20 | 46 | 0.469 | 121 | 214 | 335 | 0 | 1 | 39 | 36 | 39 | 9 | 1298 | 418 | 415 | 433 | 51 | 1702 | 527 | 484 | 1053 | 150 | 19 | 12.67% | 208 | 37 | 82.21% | 2 | 703 | 1552 | 45.30% | 848 | 1867 | 45.42% | 343 | 722 | 47.51% | 1050 | 701 | 1322 | 371 | 613 | 290 | 49.5% | 9.3% | 91.7% | 101.0 | LUCKY |
Puck Time | |
---|---|
Offensive Zone | 21 |
Neutral Zone | 12 |
Defensive Zone | 26 |
Puck Time | |
---|---|
Offensive Zone Start | 1552 |
Neutral Zone Start | 722 |
Defensive Zone Start | 1867 |
Puck Time | |
---|---|
With Puck | 27 |
Without Puck | 33 |
Faceoffs | |
---|---|
Faceoffs Won | 1894 |
Faceoffs Lost | 2247 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 8.5 | 9.57 |
2nd Period | 17.0 | 20.31 |
3rd Period | 25.8 | 30.68 |
Overtime | 26.9 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.8 | 0.64 |
2nd Period | 1.5 | 1.65 |
3rd Period | 2.3 | 2.67 |
Overtime | 2.5 | 2.83 |
Even Strenght Goal | 100 |
---|---|
PP Goal | 19 |
PK Goal | 2 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 10 | 10 |
Lost | 11 | 12 |
Overtime Lost | 3 | 3 |
PP Attempt | 150 |
---|---|
PP Goal | 19 |
PK Attempt | 208 |
PK Goal Against | 37 |
Home | |
---|---|
Shots For | 26.5 |
Shots Against | 34.7 |
Goals For | 2.5 |
Goals Against | 2.9 |
Hits | 21.5 |
Shots Blocked | 10.8 |
Pim | 9.9 |
Date | Matchup | Result | Detail | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2022-10-07 | @ | Sharks2,Predators3 | RECAP | |||||||||||
2022-10-08 | @ | Predators3,Sharks2 (SO) | RECAP | |||||||||||
2022-10-14 | @ | Hurricanes4,Sharks5 (SO) | RECAP | |||||||||||
2022-10-15 | @ | Blackhawks3,Sharks0 | RECAP | |||||||||||
2022-10-18 | @ | Sharks4,Islanders1 | RECAP | |||||||||||
2022-10-20 | @ | Sharks3,Rangers1 | RECAP | |||||||||||
2022-10-22 | @ | Sharks0,Devils3 | RECAP | |||||||||||
2022-10-23 | @ | Sharks1,Flyers5 | RECAP | |||||||||||
2022-10-25 | @ | Golden Knights3,Sharks2 | RECAP | |||||||||||
2022-10-27 | @ | Maple Leafs4,Sharks1 | RECAP | |||||||||||
2022-10-29 | @ | Lightning3,Sharks2 (OT) | RECAP | |||||||||||
2022-11-01 | @ | Ducks2,Sharks1 | RECAP | |||||||||||
2022-11-03 | @ | Panthers4,Sharks3 | RECAP | |||||||||||
2022-11-05 | @ | Ducks2,Sharks3 | RECAP | |||||||||||
2022-11-10 | @ | Sharks4,Blues3 (OT) | RECAP | |||||||||||
2022-11-11 | @ | Sharks3,Stars4 (OT) | RECAP | |||||||||||
2022-11-13 | @ | Sharks1,Wild6 | RECAP | |||||||||||
2022-11-15 | @ | Sharks3,Golden Knights2 (OT) | RECAP | |||||||||||
2022-11-17 | @ | Red Wings2,Sharks5 | RECAP | |||||||||||
2022-11-19 | @ | Rangers3,Sharks5 | RECAP | |||||||||||
2022-11-21 | @ | Senators4,Sharks2 | RECAP | |||||||||||
2022-11-23 | @ | Sharks3,Kraken1 | RECAP | |||||||||||
2022-11-25 | @ | Kings3,Sharks2 | RECAP | |||||||||||
2022-11-27 | @ | Canucks2,Sharks1 (OT) | RECAP | |||||||||||
2022-11-29 | @ | Sharks1,Canadiens4 | RECAP | |||||||||||
2022-11-30 | @ | Sharks3,Maple Leafs6 | RECAP | |||||||||||
2022-12-03 | @ | Sharks2,Senators3 | RECAP | |||||||||||
2022-12-04 | @ | Sharks0,Sabres2 | RECAP | |||||||||||
2022-12-07 | @ | Canucks1,Sharks5 | RECAP | |||||||||||
2022-12-09 | @ | Sharks1,Ducks6 | RECAP | |||||||||||
2022-12-13 | @ | Coyotes3,Sharks4 (SO) | RECAP | |||||||||||
2022-12-17 | @ | Sharks4,Kings3 (OT) | RECAP | |||||||||||
2022-12-18 | @ | Flames4,Sharks3 | RECAP | |||||||||||
2022-12-20 | @ | Flames2,Sharks1 | RECAP | |||||||||||
2022-12-22 | @ | Wild2,Sharks3 (SO) | RECAP | |||||||||||
2022-12-27 | @ | Sharks2,Canucks3 | RECAP | |||||||||||
2022-12-29 | @ | Flyers4,Sharks2 | RECAP | |||||||||||
2022-12-31 | @ | Sharks4,Stars1 | RECAP | |||||||||||
2023-01-01 | @ | Sharks5,Blackhawks3 | RECAP | |||||||||||
2023-01-06 | @ | Sharks2,Ducks1 | RECAP | |||||||||||
2023-01-07 | @ | Bruins0,Sharks2 | RECAP | |||||||||||
2023-01-10 | @ | Sharks5,Coyotes4 (OT) | RECAP | |||||||||||
2023-01-11 | @ | Sharks0,Kings3 | RECAP | |||||||||||
2023-01-13 | @ | Oilers1,Sharks4 | RECAP | |||||||||||
2023-01-16 | @ | Devils3,Sharks2 | RECAP | |||||||||||
2023-01-18 | @ | Stars1,Sharks2 | RECAP | |||||||||||
2023-01-21 | @ | Sharks1,Blue Jackets3 | RECAP | |||||||||||
2023-01-22 | @ | Sharks2,Bruins3 (SO) | RECAP | |||||||||||
2023-01-24 | @ | Sharks3,Red Wings4 (SO) | RECAP | |||||||||||
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Trade Deadline --- Trades can’t be done after this day is simulated! | ||||||||||||||
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Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
59,975,000$ | 0$ | 59,377,222$ | 22,525,000$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | HP Pavilion at San Jose | |
City | San Jose | ||
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 | 136789 | 113898 | 45637 | 91063 | 22774 |
Attendance PCT | 94.99% | 94.92% | 95.08% | 94.86% | 94.89% |
Income | |||||
---|---|---|---|---|---|
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
17 | 17090 - 94.94% | 1,507,367$ | 36,176,815$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
59,975,000$ | 59,975,000$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
36,414,687$ | 302,116$ | 35,812,174$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
25,625,244$ | 78 | 322,619$ | 25,164,282$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
26,302,341$ | 59,975,000$ | 45,184,807$ | 44,507,710$ |
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. |
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 |
---|---|---|---|---|---|
Aatu Raty | 2021 | 15 | |||
Amadeus Lombardi | 2022 | 132 | |||
Ben Boyd | 2021 | 194 | |||
Brendan Brisson | 2020 | 25 | |||
Cameron Whitehead | 2022 | 126 | |||
Chandler Romeo | 2021 | 217 | |||
Cole Huckins | 2021 | 85 | |||
Cruz Lucius | 2022 | 109 | |||
Dominic James | 2022 | 198 | |||
Ethan Bowen | 2020 | 175 | |||
Ethan Del Mastro | 2021 | 90 | |||
Evan Vierling | 2020 | 105 | |||
Filip Barklund | |||||
Gavin White | 2022 | 134 | |||
Ivan Telegin | |||||
Jack Malone | 2019 | 169 | 5.5 - 5.0 | ||
Jordan Gustafson | 2022 | 92 | |||
Kasper Kulonummi | 2022 | 95 | |||
Lane Hutson | 2022 | 38 | |||
Ludvig Jansson | 2022 | 139 | |||
Martin Chromiak | 2020 | 42 | |||
Matthew Poitras | 2022 | 80 | |||
Nick Malik | 2020 | 85 | |||
Noah Ostlund | 2022 | 25 | |||
Olen Zellweger | 2021 | 37 | |||
Oskar Pettersson | 2022 | 84 | |||
Owen Beck | 2022 | 40 | |||
Paul Ludwinski | 2022 | 78 | |||
Quinn Finley | 2022 | 98 | |||
Quinn Olson | 2019 | 98 | |||
Samu Salminen | 2021 | 53 | |||
Talyn Boyko | 2021 | 110 | |||
Tristan Luneau | 2022 | 31 | |||
Viktor Hurtig | 2021 | 185 | |||
Ville Ottavainen | 2020 | 184 | |||
Ville Pokka | 4.0 - 2.0 |
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