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Colorado Avalanche 0-0-0, 0pts · 16th 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 | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 77 | C/LW/RW | 100.00 | 74 | 37 | 71 | 80 | 72 | 88 | 90 | 76 | 56 | 71 | 79 | 78 | 76 | 75 | 74 | 35 | 75 | 0 | 30 | 2,700,000$/1yrs | |||
![]() | 28 | C/LW/RW | 100.00 | 66 | 34 | 89 | 79 | 70 | 92 | 90 | 82 | 88 | 81 | 78 | 74 | 83 | 89 | 80 | 39 | 75 | 0 | 36 | 6,555,000$/1yrs | |||
![]() | 0 | RW | 100.00 | 62 | 37 | 90 | 76 | 70 | 88 | 90 | 74 | 58 | 78 | 71 | 66 | 73 | 87 | 78 | 44 | 75 | 0 | 34 | 4,750,000$/2yrs | |||
![]() | 71 | C | 100.00 | 65 | 41 | 81 | 83 | 77 | 90 | 88 | 80 | 84 | 82 | 83 | 78 | 81 | 75 | 88 | 70 | 75 | 0 | 27 | 8,700,000$/7yrs | |||
![]() | 63 | LW/RW | 100.00 | 64 | 33 | 95 | 85 | 65 | 89 | 90 | 81 | 57 | 83 | 79 | 68 | 84 | 69 | 73 | 47 | 75 | 0 | 25 | 7,875,000$/7yrs | |||
![]() | 63 | LW | 100.00 | 72 | 76 | 71 | 76 | 65 | 91 | 89 | 78 | 58 | 81 | 77 | 72 | 75 | 88 | 96 | 31 | 75 | 0 | 36 | 6,125,000$/1yrs | |||
![]() | 0 | LW | 100.00 | 79 | 77 | 70 | 68 | 66 | 76 | 89 | 63 | 58 | 55 | 61 | 62 | 66 | 71 | 72 | 35 | 75 | 0 | 29 | 2,000,000$/2yrs | |||
![]() | 23 | LW/RW | 100.00 | 72 | 37 | 92 | 64 | 72 | 81 | 78 | 62 | 56 | 60 | 63 | 82 | 61 | 74 | 72 | 58 | 75 | 0 | 30 | 3,650,000$/1yrs | |||
![]() | 0 | LW | 100.00 | 63 | 36 | 93 | 71 | 68 | 84 | 89 | 66 | 70 | 69 | 63 | 67 | 71 | 62 | 68 | 83 | 75 | 0 | 22 | 1,200,000$/2yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 72 | 36 | 91 | 70 | 79 | 81 | 86 | 69 | 57 | 68 | 67 | 70 | 66 | 72 | 71 | 48 | 75 | 0 | 29 | 2,250,000$/2yrs | |||
![]() | 0 | C | 100.00 | 67 | 35 | 94 | 71 | 77 | 81 | 86 | 68 | 62 | 65 | 70 | 63 | 67 | 71 | 72 | 53 | 75 | 0 | 28 | 2,600,000$/3yrs | |||
![]() | 0 | C | 100.00 | 74 | 40 | 82 | 64 | 81 | 79 | 80 | 62 | 66 | 67 | 61 | 63 | 64 | 70 | 71 | 47 | 75 | 0 | 30 | 775,000$/1yrs | |||
![]() | 0 | D | 100.00 | 69 | 37 | 86 | 67 | 87 | 92 | 88 | 65 | 30 | 73 | 64 | 91 | 53 | 71 | 73 | 40 | 75 | 0 | 28 | 5,875,000$/1yrs | |||
![]() | 0 | D | 100.00 | 67 | 36 | 85 | 69 | 66 | 88 | 86 | 66 | 30 | 74 | 58 | 64 | 52 | 73 | 71 | 53 | 75 | 0 | 30 | 2,750,000$/1yrs | |||
![]() | 0 | D | 100.00 | 68 | 37 | 88 | 66 | 77 | 83 | 81 | 65 | 30 | 68 | 59 | 62 | 51 | 70 | 71 | 35 | 75 | 0 | 29 | 775,000$/1yrs | |||
![]() | 49 | D | 100.00 | 70 | 33 | 94 | 74 | 64 | 91 | 85 | 70 | 30 | 78 | 62 | 81 | 54 | 69 | 67 | 69 | 75 | 0 | 26 | 5,000,000$/3yrs | |||
![]() | 55 | D | 100.00 | 71 | 38 | 72 | 73 | 89 | 93 | 83 | 71 | 30 | 77 | 72 | 84 | 58 | 75 | 70 | 76 | 75 | 0 | 28 | 7,500,000$/1yrs | |||
![]() | 0 | D | 100.00 | 84 | 40 | 76 | 62 | 82 | 81 | 76 | 61 | 30 | 66 | 60 | 67 | 52 | 71 | 72 | 60 | 75 | 0 | 29 | 775,000$/1yrs | |||
![]() | 0 | D | 100.00 | 70 | 36 | 78 | 76 | 81 | 93 | 84 | 75 | 30 | 79 | 74 | 64 | 62 | 69 | 72 | 80 | 75 | 0 | 26 | 4,600,000$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | LW/RW | 100.00 | 64 | 34 | 85 | 71 | 69 | 82 | 61 | 64 | 59 | 69 | 50 | 58 | 57 | 71 | 70 | 39 | 75 | 0 | 29 | ||||
TEAM AVERAGE | 100.00 | 70 | 41 | 84 | 72 | 74 | 86 | 84 | 70 | 52 | 72 | 68 | 71 | 65 | 74 | 74 | 52 | 75 | 0 |
Priority | Type | Description |
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1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 100.00 | 89 | 80 | 75 | 81 | 88 | 87 | 89 | 88 | 87 | 89 | 88 | 74 | 86 | 50 | 75 | 0 | 31 | 1,500,000$/2yrs |
![]() | 74 | 100.00 | 96 | 95 | 90 | 68 | 95 | 94 | 96 | 95 | 94 | 96 | 95 | 76 | 83 | 56 | 75 | 0 | 29 | 5,250,000$/2yrs |
Scratches | ||||||||||||||||||||
![]() | 32 | 100.00 | 87 | 78 | 73 | 78 | 86 | 85 | 87 | 86 | 85 | 87 | 86 | 70 | 83 | 56 | 75 | 0 | 29 | |
TEAM AVERAGE | 100.00 | 91 | 84 | 79 | 76 | 90 | 89 | 91 | 90 | 89 | 91 | 90 | 73 | 84 | 54 | 75 | 0 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Travis Green | 84 | 80 | 89 | 85 | 80 | 74 | 69 | CAN | 53 | 4 | 1,500,000$ |
General Manager | Jerimi Fournier |
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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 |
---|---|---|
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 | 86,107,428$ |
Projected Cap Space | 1,892,572$ |
Retains And Buyout Cap Hit | 2,902,500$ |
Salary Cap To Date | 0$ |
Players In Salary Cap | 21 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|
Aaron Ekblad | D | 28 | 7,500,000$ | 7,500,000$ | RFA | ||||||
Andreas Johnsson | LW/RW/G | 29 | 0$ | ||||||||
Brad Marchand ![]() | LW | 36 | 6,125,000$ | 6,125,000$ | UFA | ||||||
Brock McGinn | LW/RW | 30 | 3,650,000$ | 3,650,000$ | |||||||
Claude Giroux ![]() | C/LW/RW/G | 36 | 6,555,000$ | 6,555,000$ | UFA | ||||||
Danton Heinen | C/LW/RW | 29 | 2,250,000$ | 2,250,000$ | 2,250,000$ | ||||||
Dominic Toninato ![]() | C | 30 | 775,000$ | 775,000$ | |||||||
Dylan Larkin ![]() | C/G | 27 | 8,700,000$ | 8,700,000$ | 8,700,000$ | 8,700,000$ | 8,700,000$ | 8,700,000$ | 8,700,000$ | 8,700,000$ | UFA |
Frank Vatrano | C/LW/RW/G | 30 | 2,700,000$ | 2,700,000$ | |||||||
Jakob Chychrun | D | 26 | 4,600,000$ | 4,600,000$ | RFA | ||||||
Jesper Bratt ![]() | LW/RW | 25 | 7,875,000$ | 7,875,000$ | 7,875,000$ | 7,875,000$ | 7,875,000$ | 7,875,000$ | 7,875,000$ | 7,875,000$ | |
Jordan Eberle | RW/G | 34 | 4,750,000$ | 4,750,000$ | 4,750,000$ | UFA | |||||
Juuse Saros | RW/G | 29 | 5,250,000$ | 5,250,000$ | 5,250,000$ | RFA | |||||
Kevin Lankinen | D/G | 29 | 0$ | RFA | |||||||
Lukas Reichel | LW | 22 | 1,200,000$ | 1,200,000$ | 1,200,000$ | ||||||
Matt Grzelcyk | D | 30 | 2,750,000$ | 2,750,000$ | |||||||
Michael Amadio | C | 28 | 2,600,000$ | 2,600,000$ | 2,600,000$ | 2,600,000$ | |||||
Nick DeSimone | D | 29 | 775,000$ | 775,000$ | |||||||
Robert Hagg | D | 29 | 775,000$ | 775,000$ | |||||||
Ryan Lomberg | LW | 29 | 2,000,000$ | 2,000,000$ | 2,000,000$ | ||||||
Samuel Girard | D | 26 | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | RFA | ||||
Scott Wedgewood | C/LW/G | 31 | 1,500,000$ | 1,500,000$ | 1,500,000$ | ||||||
Vladislav Gavrikov ![]() | D/G | 28 | 5,875,000$ | 5,875,000$ | RFA |
Forward Lines | |||||||
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Defensive Pairings | |||||||
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1st Power Play Unit | |||||||
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2nd Power Play Unit | |||||||
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Goalies | |||||||
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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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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 |
---|---|---|
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 |
Salary Cap | |||
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Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
83,205,000$ | 2,902,500$ | 86,107,428$ | 1,892,572$ |
Arena | Goal Horn | About us | |
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![]() | Name | Ball Arena | |
City | Colorado | ||
Capacity | 18007 | ||
Season Ticket Holders | 35% |
Arena Capacity - Ticket Price Attendance - % | |||||
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Arena Capacity | 6007 | 5000 | 2000 | 4000 | 1000 |
Ticket Price | 125$ | 100$ | 75$ | 50$ | 200$ |
Attendance | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
Attendance PCT | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
Income | |||||
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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$ | 18007 | 85 |
Expenses | |||
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Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
83,205,000$ | 83,205,000$ | 0$ | 2,902,500$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
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0$ | 433,359$ | 0$ | 0$ |
Estimate | |||
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Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 192 | 441,172$ | 84,705,024$ |
Team Total Estimate | |||
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Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
86,499,024$ | 86,107,428$ | 147,561,920$ | 61,062,896$ |
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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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2025 | |||||||
2026 | |||||||
2027 | |||||||
2028 | |||||||
2029 |
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 |
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Ayrton Martino | 2021 | 64 | |||
Charlie Stramel | 2023 | 40 | |||
Declan McDonnell | 2020 | 173 | Link | ||
Denver Barkey | 2023 | 83 | ELC 2024-25 | Link | |
Eric Pohlkamp | 2023 | 217 | |||
Jimi Suomi | 2021 | 147 | |||
Kieran Ruscheinski | 2019 | 209 | |||
Mats Lindgren | 2022 | 62 | |||
Nicholas Mouldenhauer | 2022 | 97 | |||
Ondrej Becher | 2024 | 103 | |||
Ondrej Molnar | 2023 | 153 | |||
Ryan Kirwan | 2020 | 213 | |||
Ryder Donovan | 2019 | 116 | |||
Sasha Teleguine | 2021 | 152 | |||
Timur Kol | 2024 | 120 | |||
Ty Gallagher | 2021 | 200 | |||
Tyler Duke | 2022 | 162 |
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