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Full Scoreboard »» |
| Anaheim Ducks 28-13-4, 60pts · 3rd in Western |
| Player | # | POS | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Connor McDavid (C) | 97 | C/LW | 99.00 | 59 | 33 | 86 | 93 | 76 | 91 | 90 | 91 | 81 | 99 | 91 | 59 | 91 | 75 | 88 | 0 | 70 | 97 | 28 | 12,500,000$/9yrs | |||
Nikita Kucherov | 0 | RW | 99.00 | 58 | 34 | 80 | 90 | 70 | 90 | 89 | 85 | 58 | 96 | 85 | 54 | 85 | 81 | 79 | 0 | 75 | 93 | 32 | 9,500,000$/2yrs | |||
Wyatt Johnston | 0 | C/RW | 100.00 | 57 | 32 | 91 | 85 | 74 | 87 | 90 | 82 | 80 | 82 | 86 | 65 | 84 | 63 | 62 | 0 | 67 | 88 | 22 | 8,400,000$/4yrs | |||
Clayton Keller | 9 | C/LW/RW | 100.00 | 55 | 32 | 89 | 80 | 68 | 86 | 90 | 76 | 59 | 83 | 77 | 54 | 77 | 71 | 76 | 0 | 67 | 85 | 27 | 7,000,000$/2yrs | |||
Marco Rossi | 0 | C | 100.00 | 65 | 32 | 90 | 75 | 68 | 85 | 87 | 71 | 82 | 74 | 73 | 60 | 72 | 66 | 65 | 0 | 69 | 81 | 24 | 4,750,000$/2yrs | |||
Jake DeBrusk | 74 | LW/RW | 100.00 | 69 | 33 | 93 | 69 | 76 | 83 | 90 | 67 | 59 | 65 | 75 | 60 | 71 | 74 | 73 | 0 | 67 | 79 | 29 | 4,750,000$/2yrs | |||
Ethen Frank | 0 | C/RW | 100.00 | 65 | 32 | 87 | 65 | 71 | 74 | 84 | 66 | 58 | 66 | 69 | 58 | 67 | 72 | 70 | 0 | 68 | 76 | 27 | 825,000$/3yrs | |||
Dakota Joshua | 8 | C/LW | 100.00 | 94 | 40 | 76 | 59 | 83 | 75 | 90 | 61 | 57 | 59 | 66 | 71 | 63 | 75 | 72 | 0 | 67 | 75 | 29 | 3,250,000$/3yrs | |||
Colton Sissons | 0 | C/LW/RW | 100.00 | 73 | 35 | 87 | 59 | 79 | 77 | 87 | 58 | 83 | 61 | 60 | 78 | 59 | 79 | 78 | 0 | 67 | 74 | 32 | 2,857,143$/1yrs | |||
Drew O'Connor | 0 | LW/RW | 100.00 | 67 | 33 | 85 | 61 | 81 | 78 | 90 | 59 | 73 | 62 | 65 | 70 | 62 | 71 | 70 | 0 | 67 | 74 | 27 | 2,500,000$/2yrs | |||
Jesperi Kotkaniemi | 0 | C/LW | 100.00 | 68 | 38 | 80 | 62 | 80 | 77 | 86 | 60 | 81 | 66 | 64 | 54 | 62 | 67 | 65 | 0 | 57 | 73 | 25 | 2,500,000$/4yrs | |||
Nils Hoglander | 0 | LW/RW | 100.00 | 69 | 32 | 85 | 61 | 69 | 75 | 82 | 60 | 55 | 64 | 61 | 54 | 60 | 66 | 65 | 0 | 24 | 72 | 25 | 3,000,000$/3yrs | |||
Mike Matheson | 19 | D | 99.00 | 63 | 33 | 83 | 66 | 77 | 95 | 90 | 68 | 30 | 72 | 63 | 84 | 65 | 79 | 77 | 0 | 68 | 83 | 31 | 4,875,000$/1yrs | |||
Ryan Pulock | 6 | D | 100.00 | 65 | 34 | 97 | 66 | 85 | 89 | 90 | 67 | 30 | 73 | 54 | 83 | 61 | 78 | 78 | 0 | 67 | 82 | 31 | 5,000,000$/4yrs | |||
Darnell Nurse | 0 | D | 99.00 | 78 | 45 | 62 | 66 | 89 | 91 | 90 | 64 | 30 | 69 | 61 | 77 | 62 | 77 | 73 | 0 | 70 | 80 | 30 | 6,250,000$/3yrs | |||
Martin Fehervary | 42 | D | 100.00 | 74 | 37 | 87 | 59 | 79 | 86 | 90 | 63 | 30 | 66 | 59 | 80 | 61 | 69 | 68 | 0 | 67 | 78 | 26 | 4,125,000$/5yrs | |||
Ilya Lyubushkin | 0 | D | 100.00 | 75 | 42 | 71 | 55 | 80 | 82 | 84 | 58 | 30 | 65 | 55 | 74 | 57 | 78 | 75 | 0 | 67 | 75 | 31 | 3,400,000$/2yrs | |||
Jeremy Lauzon | 0 | D | 100.00 | 93 | 66 | 50 | 55 | 80 | 80 | 81 | 59 | 30 | 64 | 50 | 72 | 55 | 73 | 68 | 0 | 71 | 74 | 28 | 2,000,000$/1yrs | |||
| Scratches | ||||||||||||||||||||||||||
| TEAM AVERAGE | 99.78 | 69 | 37 | 82 | 68 | 77 | 83 | 88 | 68 | 56 | 71 | 67 | 67 | 67 | 73 | 72 | 0 | 65 | 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Darcy Kuemper | 0 | 99.00 | 91 | 95 | 81 | 89 | 95 | 85 | 94 | 93 | 92 | 94 | 94 | 86 | 90 | 0 | 78 | 94 | 35 | 5,250,000$/2yrs |
Jakub Dobes | 0 | 100.00 | 70 | 86 | 77 | 84 | 80 | 70 | 82 | 91 | 81 | 93 | 82 | 66 | 71 | 0 | 74 | 85 | 24 | 965,000$/2yrs |
| Scratches | ||||||||||||||||||||
| TEAM AVERAGE | 99.50 | 81 | 91 | 79 | 87 | 88 | 78 | 88 | 92 | 87 | 94 | 88 | 76 | 81 | 0 | 76 | 90 | |||
| Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Jared Bednar | 74 | 83 | 93 | 75 | 77 | 86 | 82 | CAN | 52 | 4 | 1,000,000$ |
| General Manager | Sou MMsaiphon |
|---|
| 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 | Nikita Kucherov | 0 | RW | 43 | 20 | 36 | 56 | 22 | 12 | 0 | 33 | 231 | 55 | 172 | 8.66% | 3 | 20.41 | 5 | 9 | 14 | 159 | 0 | 0 | 0 | 0 | 6 | 3 | 26.98% | 63 | 0 | 0 | 0 | 0 | 1.28 | 0 | 1 | |
| 2 | Connor McDavid | 97 | C/LW | 45 | 17 | 32 | 49 | 27 | 27 | 5 | 103 | 210 | 50 | 130 | 8.10% | 3 | 21.35 | 1 | 5 | 6 | 156 | 0 | 0 | 0 | 0 | 4 | 1 | 50.70% | 1221 | 0 | 0 | 0 | 2 | 1.02 | 0 | 2 | |
| 3 | Wyatt Johnston | 0 | C/RW | 45 | 24 | 23 | 47 | 18 | 12 | 0 | 41 | 194 | 51 | 137 | 12.37% | 7 | 20.07 | 8 | 5 | 13 | 143 | 0 | 0 | 0 | 0 | 3 | 1 | 45.74% | 129 | 0 | 0 | 0 | 0 | 1.04 | 0 | 2 | |
| 4 | Mike Matheson | 19 | D | 45 | 8 | 29 | 37 | 12 | 27 | 5 | 53 | 87 | 26 | 50 | 9.20% | 59 | 23.24 | 5 | 12 | 17 | 158 | 0 | 0 | 0 | 40 | 2 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.71 | 0 | 1 | |
| 5 | Clayton Keller | 9 | C/LW/RW | 45 | 15 | 16 | 31 | 26 | 10 | 0 | 38 | 111 | 37 | 78 | 13.51% | 4 | 21.88 | 2 | 4 | 6 | 154 | 0 | 0 | 0 | 33 | 6 | 0 | 38.14% | 97 | 0 | 0 | 0 | 0 | 0.63 | 1 | 2 | |
| 6 | Marco Rossi | 0 | C | 45 | 12 | 17 | 29 | -8 | 26 | 10 | 46 | 98 | 35 | 70 | 12.24% | 4 | 17.87 | 3 | 8 | 11 | 132 | 0 | 0 | 0 | 0 | 2 | 4 | 49.60% | 1002 | 0 | 0 | 0 | 0 | 0.72 | 0 | 1 | |
| 7 | Darnell Nurse | 0 | D | 45 | 8 | 19 | 27 | 18 | 51 | 15 | 116 | 68 | 21 | 41 | 11.76% | 54 | 24.02 | 5 | 2 | 7 | 156 | 0 | 2 | 2 | 134 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.50 | 1 | 1 | |
| 8 | Colton Sissons | 0 | C/LW/RW | 45 | 6 | 15 | 21 | 2 | 10 | 0 | 23 | 72 | 19 | 53 | 8.33% | 12 | 13.93 | 0 | 0 | 0 | 3 | 0 | 3 | 3 | 169 | 1 | 0 | 55.63% | 870 | 0 | 0 | 1 | 0 | 0.67 | 0 | 0 | |
| 9 | Martin Fehervary | 42 | D | 45 | 2 | 17 | 19 | 14 | 18 | 0 | 39 | 47 | 20 | 54 | 4.26% | 49 | 21.61 | 0 | 6 | 6 | 123 | 0 | 0 | 0 | 121 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.39 | 0 | 0 | |
| 10 | Ryan Pulock | 6 | D | 45 | 0 | 18 | 18 | 12 | 30 | 0 | 65 | 49 | 10 | 35 | 0.00% | 42 | 22.88 | 0 | 4 | 4 | 126 | 0 | 2 | 2 | 136 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.35 | 0 | 0 | |
| 11 | Nils Hoglander | 0 | LW/RW | 43 | 9 | 5 | 14 | 3 | 16 | 0 | 42 | 68 | 18 | 52 | 13.24% | 2 | 14.30 | 0 | 1 | 1 | 140 | 0 | 0 | 0 | 0 | 3 | 0 | 35.29% | 34 | 0 | 0 | 0 | 0 | 0.46 | 0 | 0 | |
| 12 | Jake DeBrusk | 74 | LW/RW | 45 | 6 | 6 | 12 | -4 | 18 | 0 | 49 | 87 | 27 | 43 | 6.90% | 2 | 14.78 | 1 | 2 | 3 | 79 | 0 | 0 | 0 | 0 | 3 | 1 | 32.61% | 46 | 0 | 0 | 0 | 0 | 0.36 | 0 | 1 | |
| 13 | Drew O'Connor | 0 | LW/RW | 45 | 5 | 6 | 11 | 2 | 4 | 0 | 18 | 48 | 13 | 24 | 10.42% | 6 | 10.56 | 0 | 0 | 0 | 0 | 3 | 0 | 3 | 163 | 0 | 0 | 30.00% | 30 | 0 | 0 | 0 | 0 | 0.46 | 0 | 1 | |
| 14 | Dakota Joshua | 8 | C/LW | 45 | 4 | 6 | 10 | -2 | 26 | 0 | 86 | 60 | 12 | 31 | 6.67% | 5 | 12.04 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 86 | 0 | 0 | 40.57% | 106 | 0 | 0 | 0 | 0 | 0.37 | 1 | 1 | |
| 15 | Jeremy Lauzon | 0 | D | 45 | 2 | 6 | 8 | -11 | 84 | 10 | 105 | 18 | 5 | 14 | 11.11% | 33 | 12.70 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.28 | 0 | 0 | |
| 16 | Ilya Lyubushkin | 0 | D | 45 | 1 | 5 | 6 | -9 | 6 | 0 | 25 | 17 | 11 | 19 | 5.88% | 58 | 16.11 | 0 | 1 | 1 | 15 | 0 | 0 | 0 | 134 | 1 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.17 | 0 | 0 | |
| 17 | Jesperi Kotkaniemi | 0 | C/LW | 45 | 0 | 4 | 4 | -1 | 0 | 0 | 24 | 21 | 6 | 16 | 0.00% | 2 | 6.13 | 0 | 1 | 1 | 14 | 0 | 0 | 0 | 27 | 0 | 0 | 48.33% | 329 | 0 | 0 | 0 | 0 | 0.29 | 0 | 0 | |
| 18 | Ethen Frank | 0 | C/RW | 5 | 1 | 0 | 1 | -1 | 0 | 0 | 2 | 13 | 1 | 5 | 7.69% | 0 | 9.67 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 16.67% | 6 | 0 | 0 | 0 | 0 | 0.41 | 0 | 0 | |
| Team Total or Average | 766 | 140 | 260 | 400 | 120 | 377 | 45 | 908 | 1499 | 417 | 1024 | 9.34% | 345 | 17.24 | 30 | 60 | 90 | 1565 | 4 | 7 | 11 | 1053 | 31 | 10 | 49.63% | 3933 | 0 | 0 | 1 | 2 | 0.61 | 3 | 13 |
| 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 | Darcy Kuemper | 41 | 28 | 11 | 2 | 0.926 | 2.09 | 2471 | 2 | 3 | 86 | 1169 | 0 | 1 | 1 | 0.643 | 14 | 41 | 4 | 4 | 5 | 1 | |
| Team Total or Average | 41 | 28 | 11 | 2 | 0.926 | 2.09 | 2471 | 2 | 3 | 86 | 1169 | 0 | 1 | 1 | 0.643 | 14 | 41 | 4 | 4 | 5 | 1 |
| Projected Total Cap Hit | 93,613,067$ |
| Projected Cap Space | 1,886,933$ |
| Retains And Buyout Cap Hit | 0$ |
| Salary Cap To Date | 47,252,497$ |
| Players In Salary Cap | 20 |
| LTIR Players | 0 |
| Ducks Roster | Pos | Age | Cap Hit | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 | 2030-31 | 2031-32 | 2032-33 |
|---|---|---|---|---|---|---|---|---|---|---|---|
Clayton Keller ![]() | C/LW/RW | 27 | 7,000,000$ | 7,000,000$ | 7,000,000$ | ||||||
Colton Sissons ![]() | C/LW/RW | 32 | 2,857,143$ | 2,857,143$ | UFA | ||||||
Connor McDavid ![]() | C/LW | 28 | 12,500,000$ | 12,500,000$ | 18,500,000$ | 18,500,000$ | 18,500,000$ | 18,500,000$ | 18,500,000$ | 18,500,000$ | 18,500,000$ |
Dakota Joshua ![]() | C/LW | 29 | 3,250,000$ | 3,250,000$ | 3,250,000$ | 3,250,000$ | UFA | ||||
| Darcy Kuemper | G | 35 | 5,250,000$ | 5,250,000$ | 5,250,000$ | UFA | |||||
Darnell Nurse ![]() | D | 30 | 6,250,000$ | 6,250,000$ | 6,250,000$ | 6,250,000$ | UFA | ||||
Drew O'Connor ![]() | LW/RW | 27 | 2,500,000$ | 2,500,000$ | 2,500,000$ | UFA | |||||
Ethen Frank | C/RW | 27 | 825,000$ | 825,000$ | 825,000$ | 825,000$ | UFA | ||||
Ilya Lyubushkin ![]() | D | 31 | 3,400,000$ | 3,400,000$ | 3,400,000$ | UFA | |||||
Jake DeBrusk ![]() | LW/RW | 29 | 4,750,000$ | 4,750,000$ | 4,750,000$ | UFA | |||||
Jakub Dobes | G | 24 | 965,000$ | 965,000$ | 965,000$ | ||||||
Jeremy Lauzon ![]() | D | 28 | 2,000,000$ | 2,000,000$ | UFA | ||||||
Jesperi Kotkaniemi ![]() | C/LW | 25 | 2,500,000$ | 2,500,000$ | 2,500,000$ | 2,500,000$ | 2,500,000$ | ||||
Marco Rossi ![]() | C | 24 | 4,750,000$ | 4,750,000$ | 4,750,000$ | RFA | |||||
Martin Fehervary ![]() | D | 26 | 4,125,000$ | 4,125,000$ | 4,125,000$ | 4,125,000$ | 4,125,000$ | 4,125,000$ | UFA | ||
Mike Matheson ![]() | D | 31 | 4,875,000$ | 4,875,000$ | UFA | ||||||
Nikita Kucherov ![]() | RW | 32 | 9,500,000$ | 9,500,000$ | 9,500,000$ | UFA | |||||
Nils Hoglander ![]() | LW/RW | 25 | 3,000,000$ | 3,000,000$ | 3,000,000$ | 3,000,000$ | |||||
Ryan Pulock ![]() | D | 31 | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | UFA | |||
Wyatt Johnston ![]() | C/RW | 22 | 8,400,000$ | 8,400,000$ | 8,400,000$ | 8,400,000$ | 8,400,000$ |
| Non-Roster | Pos | Age | Cap Hit | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 | 2030-31 | 2031-32 | 2032-33 |
|---|---|---|---|---|---|---|---|---|---|---|---|
Akil Thomas | C/LW/RW | 24 | 950,000$ | 950,000$ | RFA | ||||||
Antonio Stranges | C/LW | 23 | 900,000$ | 900,000$ | 900,000$ | RFA | |||||
Cole Krygier | D | 27 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Colin Blackwell | C/LW/RW | 32 | 850,000$ | 850,000$ | UFA | ||||||
Connor Ingram ![]() | G | 28 | 2,000,000$ | 2,000,000$ | 2,000,000$ | 2,000,000$ | UFA | ||||
David Spacek | D | 22 | 862,500$ | 862,500$ | RFA | ||||||
Donovan Sebrango | D | 23 | 900,000$ | 900,000$ | 900,000$ | 900,000$ | |||||
Dylan Roobroeck | C/LW/RW | 21 | 850,000$ | 850,000$ | 850,000$ | RFA | |||||
Elmer Soderblom | C/LW/RW | 24 | 1,000,000$ | 1,000,000$ | 1,000,000$ | RFA | |||||
Ilya Protas | C/LW | 19 | 856,667$ | 856,667$ | 856,667$ | 856,667$ | |||||
Jakub Rychlovsky | LW/RW | 24 | 870,000$ | 870,000$ | RFA | ||||||
Jaxsen Wiebe | C/RW | 23 | 852,500$ | 852,500$ | RFA | ||||||
John Parker-Jones | RW/D | 25 | 800,000$ | 800,000$ | |||||||
Josh Brown | D | 31 | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | |||||
Juraj Pekarcik | C/LW/RW | 20 | 838,333$ | 838,333$ | 838,333$ | 838,333$ | RFA | ||||
Justin Dowling | C/LW/RW | 35 | 775,000$ | 775,000$ | 775,000$ | UFA | |||||
Leo Loof | D | 23 | 867,500$ | 867,500$ | RFA | ||||||
Matt Tomkins | G | 31 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Matt Villalta | G | 26 | 850,000$ | 850,000$ | 850,000$ | ||||||
Max Sasson | C/LW/RW | 25 | 800,000$ | 800,000$ | 800,000$ | 800,000$ | |||||
Mitchell Gibson | G | 26 | 800,000$ | 800,000$ | 800,000$ | ||||||
Nicolas Beaudin | D | 26 | 0$ | ||||||||
Nikita Chibrikov | LW/RW | 22 | 875,833$ | 875,833$ | RFA | ||||||
Nikita Prishchepov | C/LW | 21 | 806,667$ | 806,667$ | 806,667$ | RFA | |||||
Noah Juulsen | D | 28 | 1,100,000$ | 1,100,000$ | 1,100,000$ | 1,100,000$ | UFA | ||||
Ole Bjorgvik-Holm | D | 23 | 800,000$ | 800,000$ | 800,000$ | RFA | |||||
Phillip Di Giuseppe | LW/RW | 32 | 800,000$ | 800,000$ | 800,000$ | UFA | |||||
Ryan Greene | C/RW | 22 | 950,000$ | 950,000$ | 950,000$ | RFA | |||||
Spencer Martin | G | 30 | 950,000$ | 950,000$ | UFA | ||||||
Spencer Stastney | D | 26 | 850,000$ | 850,000$ | |||||||
Stephen Halliday | C/LW | 23 | 950,000$ | 950,000$ | RFA | ||||||
Ty Glover | C | 25 | 800,000$ | 800,000$ | 800,000$ | ||||||
Ty Murchison | D | 22 | 860,000$ | 860,000$ | 860,000$ | RFA | |||||
Uvis Balinskis | D | 29 | 850,000$ | 850,000$ | UFA | ||||||
Vitali Kravtsov ![]() | LW/RW | 26 | 1,255,000$ | 1,255,000$ | |||||||
Zach Aston-Reese | LW/RW | 31 | 800,000$ | 800,000$ | 800,000$ | UFA |
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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 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 0 | 1 | 0 | 35 | 14 | 13 | 8 | 0 | 38 | 12 | 8 | 20 | 3 | 0 | 0.00% | 4 | 1 | 75.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 25 | 17 | 22 | 6 | 11 | 5 | 25.0% | 2.9% | 89.5% | 92.3 | Unlucky | |
| 2 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 3 | 5 | 4 | 1.000 | 8 | 16 | 24 | 0 | 0 | 6 | 1 | 1 | 0 | 69 | 31 | 12 | 26 | 0 | 41 | 17 | 14 | 35 | 7 | 0 | 0.00% | 5 | 0 | 100.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 53 | 38 | 41 | 14 | 25 | 13 | 72.7% | 11.6% | 92.7% | 104.3 | LUCKY | |
| 3 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 4 | -1 | 0 | 0.000 | 3 | 6 | 9 | 0 | 0 | 1 | 2 | 0 | 0 | 30 | 11 | 13 | 6 | 0 | 29 | 7 | 6 | 19 | 6 | 0 | 0.00% | 3 | 0 | 100.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 26 | 19 | 21 | 6 | 11 | 6 | 42.9% | 10.0% | 86.2% | 96.2 | FUN | |
| 4 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 2 | -1 | 1 | 0.500 | 1 | 2 | 3 | 0 | 0 | 0 | 0 | 1 | 0 | 28 | 8 | 8 | 10 | 2 | 29 | 16 | 11 | 21 | 3 | 1 | 33.33% | 3 | 1 | 66.67% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 24 | 17 | 24 | 6 | 12 | 6 | 0.0% | 3.6% | 93.1% | 96.7 | DULL | |
| 5 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 5 | 6 | -1 | 2 | 0.500 | 5 | 8 | 13 | 1 | 0 | 2 | 2 | 1 | 0 | 70 | 15 | 25 | 30 | 0 | 74 | 18 | 23 | 55 | 6 | 1 | 16.67% | 9 | 1 | 88.89% | 1 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 44 | 29 | 50 | 14 | 24 | 12 | 44.4% | 7.1% | 91.9% | 99.0 | DULL | |
| 6 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 3 | 2 | 1.000 | 3 | 5 | 8 | 0 | 1 | 1 | 0 | 2 | 0 | 25 | 11 | 7 | 7 | 0 | 25 | 3 | 8 | 20 | 5 | 1 | 20.00% | 4 | 0 | 100.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 24 | 15 | 22 | 7 | 13 | 7 | 100.0% | 12.0% | 100.0% | 112.0 | LUCKY | |
| 7 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 6 | 9 | 0 | 0 | 3 | 0 | 0 | 0 | 25 | 11 | 9 | 5 | 0 | 23 | 7 | 6 | 15 | 2 | 0 | 0.00% | 3 | 0 | 100.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 25 | 19 | 22 | 6 | 11 | 5 | 60.0% | 12.0% | 91.3% | 103.3 | LUCKY | |
| 8 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 4 | 4 | 0 | 2 | 0.500 | 4 | 8 | 12 | 0 | 0 | 2 | 2 | 0 | 0 | 55 | 23 | 16 | 16 | 0 | 32 | 12 | 8 | 37 | 4 | 0 | 0.00% | 3 | 0 | 100.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 49 | 34 | 44 | 14 | 26 | 12 | 50.0% | 7.3% | 87.5% | 94.8 | Unlucky | |
| 9 | 2 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 5 | 5 | 0 | 2 | 0.500 | 5 | 9 | 14 | 0 | 0 | 0 | 2 | 2 | 1 | 71 | 20 | 21 | 24 | 6 | 58 | 13 | 16 | 30 | 10 | 1 | 10.00% | 6 | 1 | 83.33% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 55 | 40 | 45 | 13 | 24 | 13 | 50.0% | 7.0% | 91.4% | 98.4 | DULL | |
| 10 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 4 | 2 | 4 | 1.000 | 6 | 11 | 17 | 0 | 0 | 3 | 2 | 1 | 0 | 60 | 25 | 15 | 20 | 0 | 62 | 12 | 26 | 38 | 5 | 0 | 0.00% | 11 | 0 | 100.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 49 | 33 | 46 | 13 | 24 | 12 | 60.0% | 10.0% | 93.5% | 103.5 | LUCKY | |
| 11 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 3 | 2 | 1.000 | 4 | 8 | 12 | 0 | 0 | 2 | 2 | 0 | 0 | 38 | 10 | 17 | 11 | 0 | 29 | 6 | 2 | 20 | 3 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 26 | 19 | 19 | 7 | 13 | 6 | 80.0% | 10.5% | 96.6% | 107.1 | LUCKY | |
| 12 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 9 | 8 | 1 | 2 | 0.500 | 9 | 13 | 22 | 0 | 0 | 3 | 2 | 4 | 0 | 46 | 16 | 16 | 14 | 0 | 64 | 15 | 16 | 46 | 7 | 1 | 14.29% | 8 | 0 | 100.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 46 | 30 | 47 | 15 | 25 | 12 | 50.0% | 19.6% | 87.5% | 107.1 | FUN | |
| 13 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 1 | 0 | 0 | 31 | 7 | 11 | 13 | 0 | 30 | 10 | 20 | 26 | 3 | 1 | 33.33% | 5 | 1 | 80.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 22 | 15 | 25 | 6 | 11 | 6 | 0.0% | 3.2% | 86.7% | 89.9 | Unlucky | |
| 14 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 1 | 8 | 4 | 1.000 | 9 | 15 | 24 | 0 | 1 | 1 | 7 | 1 | 0 | 79 | 14 | 36 | 29 | 0 | 46 | 14 | 16 | 39 | 8 | 0 | 0.00% | 8 | 0 | 100.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 51 | 36 | 44 | 14 | 23 | 12 | 90.0% | 11.4% | 97.8% | 109.2 | LUCKY | |
| 15 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 0 | 1 | 0 | 19 | 4 | 9 | 6 | 0 | 24 | 7 | 8 | 23 | 2 | 0 | 0.00% | 4 | 1 | 75.00% | 1 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 21 | 14 | 26 | 7 | 12 | 5 | 25.0% | 5.3% | 83.3% | 88.6 | Unlucky | |
| 16 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 9 | 8 | 1 | 2 | 0.500 | 9 | 16 | 25 | 0 | 0 | 3 | 2 | 4 | 0 | 61 | 17 | 28 | 16 | 0 | 54 | 10 | 14 | 30 | 12 | 4 | 33.33% | 7 | 2 | 71.43% | 1 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 52 | 36 | 43 | 13 | 24 | 12 | 45.5% | 14.8% | 85.2% | 99.9 | FUN | |
| 17 | 2 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 4 | 4 | 0 | 2 | 0.500 | 4 | 5 | 9 | 0 | 0 | 1 | 1 | 1 | 1 | 65 | 24 | 27 | 12 | 5 | 74 | 18 | 10 | 47 | 2 | 0 | 0.00% | 5 | 1 | 80.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 44 | 32 | 55 | 14 | 25 | 12 | 57.1% | 6.2% | 94.6% | 100.7 | DULL | |
| 18 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 2 | 3 | -1 | 1 | 0.500 | 2 | 4 | 6 | 0 | 0 | 0 | 2 | 0 | 0 | 45 | 7 | 14 | 21 | 5 | 45 | 3 | 4 | 18 | 3 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 27 | 19 | 23 | 7 | 14 | 7 | 40.0% | 4.4% | 93.3% | 97.8 | DULL | |
| 19 | 3 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 4 | 5 | 6 | 1.000 | 9 | 15 | 24 | 0 | 1 | 6 | 2 | 1 | 0 | 107 | 33 | 36 | 38 | 0 | 60 | 18 | 21 | 55 | 15 | 4 | 26.67% | 7 | 1 | 85.71% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 79 | 55 | 60 | 22 | 39 | 19 | 62.5% | 8.4% | 93.3% | 101.7 | DULL | |
| 20 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 2 | 6 | 4 | 1.000 | 8 | 14 | 22 | 0 | 0 | 4 | 3 | 1 | 0 | 51 | 12 | 22 | 17 | 0 | 65 | 15 | 29 | 45 | 6 | 1 | 16.67% | 12 | 1 | 91.67% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 48 | 34 | 46 | 14 | 24 | 12 | 87.5% | 15.7% | 96.9% | 112.6 | LUCKY | |
| 21 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 3 | 4 | 4 | 1.000 | 7 | 13 | 20 | 0 | 0 | 0 | 3 | 4 | 0 | 77 | 15 | 34 | 28 | 0 | 78 | 21 | 16 | 40 | 9 | 3 | 33.33% | 7 | 0 | 100.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 51 | 37 | 45 | 12 | 22 | 12 | 57.1% | 9.1% | 96.2% | 105.2 | LUCKY | |
| 22 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 3 | 4 | -1 | 1 | 0.500 | 3 | 5 | 8 | 0 | 0 | 1 | 0 | 2 | 0 | 39 | 9 | 16 | 12 | 2 | 39 | 7 | 10 | 22 | 6 | 1 | 16.67% | 5 | 0 | 100.00% | 1 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 28 | 20 | 22 | 7 | 13 | 6 | 33.3% | 7.7% | 89.7% | 97.4 | Unlucky | |
| 23 | 2 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 6 | 8 | -2 | 1 | 0.250 | 6 | 11 | 17 | 0 | 0 | 4 | 0 | 2 | 4 | 53 | 20 | 10 | 19 | 15 | 50 | 16 | 20 | 54 | 6 | 3 | 50.00% | 10 | 1 | 90.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 48 | 32 | 49 | 16 | 27 | 12 | 30.0% | 11.3% | 84.0% | 95.3 | FUN | |
| 24 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 4 | -1 | 2 | 0.500 | 3 | 6 | 9 | 0 | 0 | 1 | 0 | 2 | 0 | 52 | 16 | 18 | 18 | 0 | 68 | 24 | 14 | 44 | 10 | 1 | 10.00% | 7 | 1 | 85.71% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 45 | 31 | 49 | 14 | 25 | 12 | 40.0% | 5.8% | 94.1% | 99.9 | DULL | |
| 25 | 2 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 8 | 5 | 3 | 4 | 1.000 | 8 | 15 | 23 | 0 | 0 | 3 | 1 | 3 | 1 | 71 | 23 | 23 | 24 | 1 | 47 | 16 | 15 | 38 | 7 | 2 | 28.57% | 5 | 0 | 100.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 52 | 37 | 42 | 13 | 25 | 13 | 54.5% | 11.3% | 89.4% | 100.6 | FUN | |
| 26 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 2 | 6 | 4 | 1.000 | 8 | 14 | 22 | 0 | 0 | 3 | 3 | 2 | 0 | 68 | 28 | 18 | 22 | 0 | 58 | 17 | 27 | 43 | 10 | 4 | 40.00% | 10 | 2 | 80.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 46 | 32 | 49 | 14 | 23 | 11 | 100.0% | 11.8% | 96.6% | 108.3 | LUCKY | |
| 27 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 5 | 4 | 1 | 2 | 0.500 | 5 | 9 | 14 | 0 | 0 | 2 | 3 | 0 | 0 | 81 | 32 | 32 | 17 | 0 | 65 | 22 | 13 | 45 | 9 | 2 | 22.22% | 4 | 1 | 75.00% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 52 | 39 | 41 | 14 | 25 | 12 | 50.0% | 6.2% | 93.8% | 100.0 | DULL | |
| _Vs Division | 9 | 6 | 2 | 0 | 1 | 0 | 0 | 0 | 34 | 20 | 14 | 14 | 0.778 | 34 | 59 | 93 | 0 | 0 | 13 | 11 | 9 | 1 | 304 | 109 | 106 | 88 | 1 | 263 | 76 | 73 | 192 | 36 | 9 | 25.00% | 28 | 3 | 89.29% | 0 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 225 | 159 | 201 | 64 | 113 | 57 | 59.5% | 11.2% | 92.4% | 103.6 | LUCKY | |
| _Vs Conference | 22 | 13 | 6 | 0 | 1 | 1 | 0 | 1 | 72 | 56 | 16 | 30 | 0.682 | 72 | 126 | 198 | 0 | 2 | 31 | 18 | 22 | 5 | 699 | 235 | 238 | 219 | 18 | 607 | 159 | 200 | 460 | 90 | 23 | 25.56% | 81 | 9 | 88.89% | 3 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 552 | 384 | 497 | 159 | 280 | 140 | 51.0% | 10.3% | 90.8% | 101.1 | FUN | |
| _Since Last GM Reset | 45 | 25 | 13 | 0 | 2 | 2 | 1 | 2 | 135 | 103 | 32 | 60 | 0.667 | 135 | 240 | 375 | 1 | 3 | 52 | 43 | 37 | 7 | 1451 | 456 | 506 | 469 | 36 | 1307 | 356 | 381 | 925 | 169 | 31 | 18.34% | 156 | 16 | 89.74% | 4 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 1126 | 792 | 1036 | 322 | 564 | 287 | 54.5% | 9.3% | 92.1% | 101.4 | LUCKY | |
| Total | 45 | 25 | 13 | 0 | 2 | 2 | 1 | 2 | 135 | 103 | 32 | 60 | 0.667 | 135 | 240 | 375 | 1 | 3 | 52 | 43 | 37 | 7 | 1451 | 456 | 506 | 469 | 36 | 1307 | 356 | 381 | 925 | 169 | 31 | 18.34% | 156 | 16 | 89.74% | 4 | 854 | 1646 | 51.88% | 747 | 1536 | 48.63% | 330 | 660 | 50.00% | 1126 | 792 | 1036 | 322 | 564 | 287 | 54.5% | 9.3% | 92.1% | 101.4 | LUCKY |
| Puck Time | |
|---|---|
| Offensive Zone | 25 |
| Neutral Zone | 12 |
| Defensive Zone | 23 |
| Puck Time | |
|---|---|
| Offensive Zone Start | 1646 |
| Neutral Zone Start | 660 |
| Defensive Zone Start | 1536 |
| Puck Time | |
|---|---|
| With Puck | 31 |
| Without Puck | 29 |
| Faceoffs | |
|---|---|
| Faceoffs Won | 1931 |
| Faceoffs Lost | 1911 |
| Team Average Shots after | League Average Shots after | |
|---|---|---|
| 1st Period | 10.1 | 9.57 |
| 2nd Period | 21.4 | 20.31 |
| 3rd Period | 31.8 | 30.68 |
| Overtime | 32.6 | 31.4 |
| Goals in | Team Average Goals after | League Average Goals after |
|---|---|---|
| 1st Period | 1.2 | 0.64 |
| 2nd Period | 2.1 | 1.65 |
| 3rd Period | 2.9 | 2.67 |
| Overtime | 3.1 | 2.83 |
| Even Strenght Goal | 99 |
|---|---|
| PP Goal | 31 |
| PK Goal | 4 |
| Empty Net Goal | 1 |
| Home | Away | |
|---|---|---|
| Win | 14 | 14 |
| Lost | 6 | 7 |
| Overtime Lost | 1 | 3 |
| PP Attempt | 169 |
|---|---|
| PP Goal | 31 |
| PK Attempt | 156 |
| PK Goal Against | 16 |
| Home | |
|---|---|
| Shots For | 32.2 |
| Shots Against | 29.0 |
| Goals For | 3.0 |
| Goals Against | 2.3 |
| Hits | 20.6 |
| Shots Blocked | 7.9 |
| Pim | 8.5 |
| Date | Matchup | Result | Detail | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2025-10-10 | @ | Ducks1,Kraken2 | RECAP | |||||||||||
| 2025-10-12 | @ | Ducks3,Sharks2 (OT) | RECAP | |||||||||||
| 2025-10-15 | @ | Penguins2,Ducks3 | RECAP | |||||||||||
| 2025-10-17 | @ | Hurricanes1,Ducks2 | RECAP | |||||||||||
| 2025-10-20 | @ | Ducks2,Blackhawks1 | RECAP | |||||||||||
| 2025-10-22 | @ | Ducks1,Predators4 | RECAP | |||||||||||
| 2025-10-24 | @ | Ducks2,Bruins1 (SO) | RECAP | |||||||||||
| 2025-10-26 | @ | Ducks3,Lightning1 | RECAP | |||||||||||
| 2025-10-29 | @ | Ducks5,Panthers1 | RECAP | |||||||||||
| 2025-11-01 | @ | Red Wings1,Ducks3 | RECAP | |||||||||||
| 2025-11-03 | @ | Devils2,Ducks5 | RECAP | |||||||||||
| 2025-11-05 | @ | Panthers1,Ducks3 | RECAP | |||||||||||
| 2025-11-07 | @ | Ducks4,Stars5 (SO) | RECAP | |||||||||||
| 2025-11-09 | @ | Ducks3,Golden Knights1 | RECAP | |||||||||||
| 2025-11-10 | @ | Jets4,Ducks3 (OT) | RECAP | |||||||||||
| 2025-11-12 | @ | Ducks3,Avalanche0 | RECAP | |||||||||||
| 2025-11-14 | @ | Ducks1,Red Wings3 | RECAP | |||||||||||
| 2025-11-16 | @ | Ducks3,Wild2 | RECAP | |||||||||||
| 2025-11-18 | @ | Mammoth4,Ducks7 | RECAP | |||||||||||
| 2025-11-20 | @ | Bruins3,Ducks2 | RECAP | |||||||||||
| 2025-11-21 | @ | Senators4,Ducks3 | RECAP | |||||||||||
| 2025-11-23 | @ | Golden Knights1,Ducks5 | RECAP | |||||||||||
| 2025-11-27 | @ | Canucks1,Ducks4 | RECAP | |||||||||||
| 2025-11-29 | @ | Kings5,Ducks3 | RECAP | |||||||||||
| 2025-12-01 | @ | Ducks4,Blackhawks3 | RECAP | |||||||||||
| 2025-12-02 | @ | Ducks1,Blues4 | RECAP | |||||||||||
| 2025-12-04 | @ | Mammoth4,Ducks2 | RECAP | |||||||||||
| 2025-12-06 | @ | Capitals3,Ducks2 | RECAP | |||||||||||
| 2025-12-08 | @ | Blackhawks0,Ducks3 | RECAP | |||||||||||
| 2025-12-10 | @ | Ducks0,Penguins2 | RECAP | |||||||||||
| 2025-12-12 | @ | Ducks1,Islanders2 (OT) | RECAP | |||||||||||
| 2025-12-14 | @ | Ducks3,Devils1 | RECAP | |||||||||||
| 2025-12-16 | @ | Ducks3,Rangers2 | RECAP | |||||||||||
| 2025-12-17 | @ | Ducks4,Blue Jackets2 | RECAP | |||||||||||
| 2025-12-20 | @ | Stars3,Ducks2 | RECAP | |||||||||||
| 2025-12-21 | @ | Blue Jackets1,Ducks3 | RECAP | |||||||||||
| 2025-12-23 | @ | Kraken2,Ducks4 | RECAP | |||||||||||
| 2025-12-28 | @ | Ducks6,Kings3 | RECAP | |||||||||||
| 2025-12-30 | @ | Sharks3,Ducks5 | RECAP | |||||||||||
| 2026-01-01 | @ | Lightning0,Ducks6 | RECAP | |||||||||||
| 2026-01-03 | @ | Wild2,Ducks3 | RECAP | |||||||||||
| 2026-01-06 | @ | Ducks3,Capitals2 (OT) | RECAP | |||||||||||
| 2026-01-07 | @ | Ducks1,Flyers4 | RECAP | |||||||||||
| 2026-01-09 | @ | Ducks3,Hurricanes5 | RECAP | |||||||||||
| 2026-01-11 | @ | Ducks2,Sabres3 (SO) | RECAP | |||||||||||
| 2026-01-14 | @ | |||||||||||||
| 2026-01-17 | @ | |||||||||||||
| 2026-01-18 | @ | |||||||||||||
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| Trade Deadline --- Trades can’t be done after this day is simulated! | ||||||||||||||
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| 2026-04-02 | @ | |||||||||||||
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| Salary Cap | |||
|---|---|---|---|
| Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
| 93,697,143$ | 0$ | 93,613,067$ | 1,802,857$ |
| Arena | Goal Horn | About us | |
|---|---|---|---|
| Name | Honda Center | |
| City | Anaheim | ||
| 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 | 120898 | 100282 | 40342 | 80549 | 19509 |
| Attendance PCT | 95.95% | 95.51% | 96.05% | 95.89% | 92.90% |
| Income | |||||
|---|---|---|---|---|---|
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|
| Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
| 20 | 17218 - 95.66% | 1,574,499$ | 33,064,480$ | 18000 | 100 |
| Expenses | |||
|---|---|---|---|
| Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
| 93,697,143$ | 93,697,143$ | 0$ | 0$ |
| Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
|---|---|---|---|
| 47,757,735$ | 488,006$ | 47,252,497$ | 0$ |
| Estimate | |||
|---|---|---|---|
| Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
| 31,489,981$ | 95 | 493,214$ | 46,855,330$ |
| Team Total Estimate | |||
|---|---|---|---|
| Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
| 48,474,743$ | 93,697,143$ | 43,959,833$ | 26,975,071$ |
Rookie
Injured
Cold Streak
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| Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 | Ronde 8 |
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| 2026 | ||||||||
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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 |
| Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
|---|---|---|---|---|---|
| Adam Jecho | 2024 | 64 | |||
| Albert Wikman | 2023 | 120 | |||
| Alexander Zetterberg | 2024 | 202 | |||
| Andre Gasseau | 2021 | 181 | |||
| Arseni Sergeev | 2021 | 149 | |||
| Francesco Arcuri | 2021 | 213 | |||
| Grant Slukynsky | 2020 | 190 | |||
| Jack Ivankovic | 2025 | 50 | |||
| Jacob Truscott | 2020 | 183 | |||
| Jaden Lipinski | 2023 | 115 | |||
| Kalem Parker | 2023 | 179 | |||
| Kim Saarinen | 2024 | 96 | |||
| Kristian Kostadinski | 2023 | 211 | |||
| Lev Katzin | 2025 | 206 | |||
| Logan Sawyer | 2024 | 99 | |||
| Makar Khanin | 2024 | 224 | |||
| Maxim Barbashev | 2022 | 165 | |||
| Maxim Schafer | 2025 | 114 | |||
| Maximilian Glotzl | 2020 | 215 | |||
| Mikkel Eriksen | 2025 | 94 | |||
| Oskar Jellvik | 2021 | 171 | |||
| Paul Fischer | 2023 | 147 | |||
| Quentin Miller | 2023 | 91 | |||
| Quinn Beauchesne | 2025 | 146 | |||
| Rody Ross | 2019 | 183 | |||
| Ryan Miller | 2025 | 130 | |||
| Teddy Stiga | 2024 | 32 | |||
| Ty Henricks | 2023 | 185 |
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