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Minnesota Wild 0-0-0, 0pts · 4th in Western Conference |
Player | # | POS | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | C/LW | 100.00 | 62 | 35 | 90 | 77 | 76 | 87 | 90 | 75 | 78 | 80 | 69 | 67 | 79 | 68 | 70 | 83 | 75 | 0 | 25 | 5,750,000$/3yrs | |||
![]() | 53 | C | 100.00 | 79 | 45 | 84 | 67 | 71 | 84 | 89 | 65 | 83 | 66 | 61 | 85 | 63 | 83 | 74 | 37 | 75 | 0 | 33 | 2,500,000$/3yrs | |||
![]() | 0 | C/RW | 100.00 | 69 | 41 | 77 | 80 | 90 | 89 | 70 | 77 | 57 | 78 | 72 | 67 | 75 | 64 | 66 | 88 | 75 | 0 | 23 | 3,362,500$/2yrs | |||
![]() | 14 | C | 100.00 | 68 | 41 | 88 | 70 | 88 | 86 | 73 | 74 | 83 | 75 | 65 | 78 | 71 | 82 | 89 | 53 | 75 | 0 | 31 | 7,750,000$/6yrs | |||
![]() | 0 | C/LW | 100.00 | 71 | 37 | 85 | 77 | 86 | 90 | 85 | 76 | 86 | 79 | 75 | 71 | 78 | 79 | 73 | 65 | 75 | 0 | 30 | 8,600,000$/5yrs | |||
![]() | 0 | C/LW | 100.00 | 89 | 72 | 54 | 63 | 80 | 76 | 85 | 62 | 57 | 61 | 58 | 63 | 59 | 70 | 72 | 35 | 75 | 0 | 29 | 1,000,000$/3yrs | |||
![]() | 32 | C/LW/RW | 100.00 | 76 | 78 | 74 | 67 | 82 | 80 | 90 | 64 | 80 | 65 | 60 | 84 | 62 | 76 | 73 | 34 | 75 | 0 | 31 | 3,000,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 60 | 33 | 87 | 77 | 67 | 88 | 74 | 76 | 57 | 78 | 79 | 65 | 77 | 75 | 73 | 47 | 75 | 0 | 31 | 4,500,000$/2yrs | |||
![]() | 1 | RW | 100.00 | 91 | 82 | 76 | 66 | 84 | 78 | 89 | 63 | 57 | 61 | 62 | 60 | 64 | 68 | 70 | 56 | 75 | 0 | 27 | 1,400,000$/1yrs | |||
![]() | 29 | LW/RW | 100.00 | 62 | 38 | 91 | 76 | 92 | 89 | 73 | 79 | 57 | 77 | 80 | 66 | 79 | 69 | 73 | 86 | 75 | 0 | 26 | 7,625,000$/2yrs | |||
![]() | 0 | D | 100.00 | 72 | 54 | 75 | 63 | 82 | 90 | 89 | 61 | 30 | 70 | 56 | 89 | 48 | 84 | 75 | 43 | 75 | 0 | 35 | 3,500,000$/1yrs | |||
![]() | 0 | D | 100.00 | 77 | 35 | 88 | 67 | 73 | 92 | 89 | 64 | 30 | 73 | 58 | 87 | 51 | 66 | 70 | 59 | 75 | 0 | 25 | 4,125,000$/7yrs | |||
![]() | 0 | D | 100.00 | 71 | 34 | 83 | 68 | 72 | 87 | 85 | 66 | 30 | 70 | 57 | 77 | 52 | 68 | 66 | 79 | 75 | 0 | 26 | 2,500,000$/1yrs | |||
![]() | 74 | D | 100.00 | 69 | 37 | 87 | 74 | 86 | 95 | 83 | 75 | 30 | 83 | 72 | 87 | 58 | 87 | 77 | 43 | 75 | 0 | 34 | 8,000,000$/2yrs | |||
![]() | 0 | D | 100.00 | 63 | 40 | 90 | 67 | 84 | 87 | 73 | 65 | 30 | 72 | 62 | 64 | 54 | 75 | 71 | 43 | 75 | 0 | 31 | 975,000$/2yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 18 | C/RW | 100.00 | 64 | 62 | 71 | 76 | 74 | 87 | 90 | 73 | 75 | 77 | 66 | 64 | 71 | 80 | 72 | 68 | 75 | 0 | 31 | ||||
![]() | 0 | RW | 100.00 | 72 | 42 | 81 | 67 | 80 | 79 | 72 | 68 | 57 | 66 | 64 | 61 | 69 | 64 | 65 | 83 | 75 | 0 | 24 | ||||
![]() | 0 | LW | 100.00 | 63 | 37 | 83 | 60 | 83 | 70 | 60 | 62 | 50 | 52 | 62 | 61 | 62 | 63 | 64 | 78 | 75 | 0 | 23 | ||||
![]() | 0 | C/RW | 100.00 | 70 | 38 | 90 | 66 | 77 | 79 | 86 | 65 | 79 | 66 | 67 | 71 | 64 | 75 | 76 | 26 | 75 | 0 | 33 | ||||
![]() | 0 | LW/RW | 100.00 | 62 | 39 | 83 | 70 | 72 | 87 | 86 | 69 | 70 | 67 | 68 | 63 | 70 | 64 | 68 | 75 | 75 | 0 | 24 | ||||
![]() | 0 | D | 100.00 | 58 | 38 | 83 | 67 | 65 | 78 | 74 | 64 | 30 | 66 | 58 | 63 | 50 | 67 | 68 | 59 | 75 | 0 | 26 | ||||
TEAM AVERAGE | 100.00 | 70 | 46 | 82 | 70 | 79 | 85 | 81 | 69 | 57 | 71 | 65 | 71 | 65 | 73 | 72 | 59 | 75 | 0 |
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 | 100.00 | 94 | 86 | 82 | 77 | 93 | 92 | 94 | 93 | 92 | 94 | 93 | 67 | 75 | 67 | 75 | 0 | 26 | 3,750,000$/2yrs |
![]() | 0 | 100.00 | 75 | 70 | 65 | 98 | 74 | 73 | 75 | 74 | 73 | 75 | 74 | 67 | 81 | 57 | 75 | 0 | 27 | 3,275,000$/2yrs |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 100.00 | 85 | 78 | 74 | 88 | 84 | 83 | 85 | 84 | 83 | 85 | 84 | 67 | 78 | 62 | 75 | 0 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Andre Tourigny | 87 | 80 | 85 | 80 | 75 | 70 | 76 | CAN | 50 | 3 | 3,000,000$ |
General Manager | Xavier Cameron |
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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 |
# | Player Name | Team Name | # | POS | GP | G | A | P | +/- | PIM | PIM5 | HIT | SHT | OSB | OSM | SHT% | SB | MP | AMG | PPG | PPA | PPP | PPM | PKG | PKA | PKP | PKM | GW | GT | FO% | FOT | GA | TA | EG | HT | P/20 | PSG | PSS |
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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 |
# | 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 |
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Projected Total Cap Hit | 79,554,211$ |
Projected Cap Space | 8,445,789$ |
Retains And Buyout Cap Hit | 7,941,667$ |
Salary Cap To Date | 0$ |
Players In Salary Cap | 18 |
LTIR Players | 0 |
Player Name | Pos | Age | Cap Hit | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 | 2030-31 | 2031-32 |
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Barclay Goodrow | C/LW/RW | 31 | 3,000,000$ | 3,000,000$ | 3,000,000$ | UFA | |||||
Ben Hutton | D | 31 | 975,000$ | 975,000$ | 975,000$ | UFA | |||||
Casey Cizikas | C | 33 | 2,500,000$ | 2,500,000$ | 2,500,000$ | 2,500,000$ | UFA | ||||
Casey Mittelstadt | C/LW | 25 | 5,750,000$ | 5,750,000$ | 5,750,000$ | 5,750,000$ | RFA | ||||
Dante Fabbro | D | 26 | 2,500,000$ | 2,500,000$ | RFA | ||||||
Filip Gustavsson | C/RW/G | 26 | 3,750,000$ | 3,750,000$ | 3,750,000$ | UFA | |||||
Ian Cole | D | 35 | 3,500,000$ | 3,500,000$ | UFA | ||||||
Ivan Fedotov | D/G | 27 | 3,275,000$ | 3,275,000$ | 3,275,000$ | ||||||
John Carlson | D | 34 | 8,000,000$ | 8,000,000$ | 8,000,000$ | UFA | |||||
Jonatan Berggren ![]() | LW/RW | 24 | 0$ | RFA | |||||||
Keegan Kolesar | RW | 27 | 1,400,000$ | 1,400,000$ | RFA | ||||||
Kirby Dach | C/RW | 23 | 3,362,500$ | 3,362,500$ | 3,362,500$ | RFA | |||||
Liam O'Brien | C/LW | 29 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | |||||
Mikey Anderson | D | 25 | 4,125,000$ | 4,125,000$ | 4,125,000$ | 4,125,000$ | 4,125,000$ | 4,125,000$ | 4,125,000$ | 4,125,000$ | |
Nolan Foote ![]() | LW | 23 | 0$ | RFA | |||||||
Oliver Wahlstrom ![]() | RW | 24 | 0$ | RFA | |||||||
Patrik Laine | LW/RW | 26 | 7,625,000$ | 7,625,000$ | 7,625,000$ | RFA | |||||
Ryan Carpenter ![]() | C/RW | 33 | 0$ | UFA | |||||||
Ryan Strome | C/RW | 31 | 0$ | ||||||||
Sean Couturier ![]() | C | 31 | 7,750,000$ | 7,750,000$ | 7,750,000$ | 7,750,000$ | 7,750,000$ | 7,750,000$ | 7,750,000$ | UFA | |
Tomas Hertl ![]() | C/LW | 30 | 8,600,000$ | 8,600,000$ | 8,600,000$ | 8,600,000$ | 8,600,000$ | 8,600,000$ | UFA | ||
Victor Mete | D | 26 | 0$ | RFA | |||||||
Viktor Arvidsson | LW/RW | 31 | 4,500,000$ | 4,500,000$ | 4,500,000$ | UFA |
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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 |
# | 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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Total | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.000 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0 | 0.0% | 0.0% | 0.0% | 0.0 | Unlucky |
Puck Time | |
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Offensive Zone | 0 |
Neutral Zone | 0 |
Defensive Zone | 0 |
Puck Time | |
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Offensive Zone Start | 0 |
Neutral Zone Start | 0 |
Defensive Zone Start | 0 |
Puck Time | |
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With Puck | 0 |
Without Puck | 0 |
Faceoffs | |
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Faceoffs Won | 0 |
Faceoffs Lost | 0 |
Team Average Shots after | League Average Shots after | |
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1st Period | 0.0 | 9.57 |
2nd Period | 0.0 | 20.31 |
3rd Period | 0.0 | 30.68 |
Overtime | 0.0 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
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1st Period | 0.0 | 0.64 |
2nd Period | 0.0 | 1.65 |
3rd Period | 0.0 | 2.67 |
Overtime | 0.0 | 2.83 |
Even Strenght Goal | 0 |
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PP Goal | 0 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
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Win | 0 | 0 |
Lost | 0 | 0 |
Overtime Lost | 0 | 0 |
PP Attempt | 0 |
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PP Goal | 0 |
PK Attempt | 0 |
PK Goal Against | 0 |
Home | |
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Shots For | 0.0 |
Shots Against | 0.0 |
Goals For | 0.0 |
Goals Against | 0.0 |
Hits | 0.0 |
Shots Blocked | 0.0 |
Pim | 0.0 |
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Salary Cap | |||
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Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
72,387,500$ | 7,941,667$ | 79,554,211$ | 8,445,789$ |
Arena | Goal Horn | About us | |
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![]() | Name | Xcel Energy Center | |
City | Minnesota | ||
Capacity | 18064 | ||
Season Ticket Holders | 35% |
Arena Capacity - Ticket Price Attendance - % | |||||
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Arena Capacity | 6000 | 5000 | 2000 | 4000 | 1064 |
Ticket Price | 125$ | 103$ | 76$ | 52$ | 206$ |
Attendance | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
Attendance PCT | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
41 | 0 - 0.00% | 0$ | 0$ | 18064 | 100 |
Expenses | |||
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Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
72,387,500$ | 72,387,500$ | 0$ | 7,941,667$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
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0$ | 372,982$ | 0$ | 0$ |
Estimate | |||
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Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 192 | 392,643$ | 75,387,456$ |
Team Total Estimate | |||
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Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
77,249,706$ | 79,554,211$ | 187,507,051$ | 110,257,345$ |
Left Wing | Center | Right Wing | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
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2025 | |||||||
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2028 | |||||||
2029 |
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 |
---|---|---|---|---|---|
Axel Landen | 2023 | 135 | |||
Blake Montgomery | 2024 | 147 | |||
Connor Hvidston | 2022 | 167 | |||
Daniil Bourosh | 2022 | 213 | |||
Danila Yurov | 2022 | 9 | |||
Domenic Divincentiis | 2022 | 219 | ELC 2023-24 (slide) | Link | |
Ethan Haider | 2019 | 151 | |||
Felix Nilsson | 2023 | 62 | |||
Garrett Brown | 2022 | 186 | |||
Ilya Ivantsov | 2024 | 194 | |||
Ilya Nabokov | 2024 | 80 | |||
Jacob Truscott | 2020 | 82 | |||
Jesse Nurmi | 2023 | 103 | |||
Liam Greentree | 2024 | 18 | ELC 2024-25 | Link | |
Lucas Forsell | 2021 | 223 | |||
Marcus Kearsey | 2024 | 162 | |||
Maxim Vehovsky | 2023 | 199 | |||
Nick Lardis | 2023 | 60 | ELC 2024-25 | Link | |
Niks Fenenko | 2022 | 220 | |||
Ryan Greene | 2022 | 59 | |||
Ryan Healey | 2022 | 157 | |||
Sam O'Reilly | 2024 | 44 | |||
Sawyer Mynio | 2023 | 167 | |||
Tanner Adams | 2023 | 118 | |||
Theo Wallberg | 2022 | 174 | |||
Vladimir Grudinin | 2022 | 82 | |||
William Zellers | 2024 | 117 | |||
Zam Plante | 2022 | 110 |
|