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Full Scoreboard »» |
Hartford Wolf Pack 0-0-0, 0pts · 13th in Eastern |
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/RW | 100.00 | 85 | 42 | 50 | 56 | 72 | 70 | 72 | 68 | 70 | 60 | 59 | 72 | 60 | 77 | 72 | 0 | 27 | 73 | 30 | 775,000$/1yrs | |||
![]() | 0 | C/LW | 100.00 | 82 | 36 | 94 | 55 | 84 | 72 | 83 | 56 | 61 | 59 | 59 | 68 | 58 | 73 | 73 | 0 | 27 | 71 | 29 | 775,000$/1yrs | |||
![]() | 0 | C | 100.00 | 63 | 32 | 89 | 58 | 71 | 74 | 79 | 59 | 61 | 64 | 62 | 54 | 61 | 65 | 64 | 0 | 37 | 71 | 24 | 900,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 82 | 43 | 55 | 57 | 86 | 67 | 68 | 64 | 37 | 57 | 58 | 67 | 58 | 68 | 64 | 0 | 42 | 71 | 25 | 900,000$/2yrs | |||
![]() | 0 | C | 100.00 | 66 | 39 | 81 | 57 | 75 | 67 | 72 | 64 | 70 | 54 | 61 | 67 | 58 | 68 | 66 | 0 | 58 | 70 | 25 | 802,500$/1yrs | |||
![]() | 0 | C | 100.00 | 72 | 41 | 71 | 56 | 83 | 66 | 70 | 64 | 47 | 57 | 57 | 67 | 57 | 68 | 65 | 0 | 18 | 70 | 26 | 775,000$/1yrs | |||
![]() | 0 | C | 100.00 | 64 | 38 | 83 | 61 | 67 | 67 | 69 | 59 | 44 | 62 | 59 | 62 | 60 | 59 | 58 | 0 | 50 | 70 | 21 | 918,333$/2yrs | |||
![]() | 19 | C | 100.00 | 63 | 37 | 96 | 55 | 84 | 71 | 77 | 57 | 78 | 58 | 58 | 61 | 57 | 66 | 66 | 0 | 41 | 69 | 25 | 800,000$/2yrs | |||
![]() | 0 | RW | 100.00 | 64 | 39 | 85 | 55 | 72 | 64 | 69 | 61 | 41 | 54 | 56 | 64 | 55 | 63 | 61 | 0 | 39 | 68 | 22 | 870,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 70 | 40 | 75 | 51 | 76 | 62 | 67 | 63 | 41 | 49 | 54 | 67 | 52 | 66 | 64 | 0 | 26 | 67 | 26 | 775,000$/1yrs | |||
![]() | 0 | C | 100.00 | 62 | 39 | 88 | 55 | 81 | 63 | 76 | 59 | 61 | 52 | 56 | 62 | 54 | 59 | 58 | 0 | 43 | 67 | 22 | 800,000$/2yrs | |||
![]() | 0 | C/RW | 100.00 | 55 | 38 | 99 | 53 | 75 | 61 | 65 | 61 | 72 | 45 | 58 | 64 | 52 | 61 | 61 | 0 | 48 | 66 | 24 | 836,667$/1yrs | |||
![]() | 0 | C/LW | 100.00 | 61 | 38 | 88 | 52 | 69 | 61 | 87 | 62 | 73 | 52 | 50 | 65 | 51 | 62 | 61 | 0 | 45 | 66 | 25 | 775,000$/1yrs | |||
![]() | 0 | D | 100.00 | 69 | 33 | 84 | 68 | 82 | 90 | 68 | 55 | 30 | 70 | 50 | 55 | 52 | 56 | 55 | 0 | 52 | 73 | 19 | 975,000$/3yrs | |||
![]() | 0 | D | 100.00 | 62 | 32 | 84 | 57 | 72 | 86 | 72 | 56 | 30 | 63 | 61 | 64 | 58 | 59 | 57 | 0 | 39 | 72 | 20 | 918,333$/2yrs | |||
![]() | 93 | D | 100.00 | 83 | 41 | 53 | 54 | 66 | 68 | 67 | 52 | 30 | 60 | 53 | 72 | 56 | 75 | 70 | 0 | 19 | 71 | 30 | 775,000$/1yrs | |||
![]() | 0 | D | 100.00 | 72 | 51 | 62 | 55 | 87 | 77 | 72 | 53 | 30 | 54 | 50 | 71 | 51 | 86 | 82 | 0 | 32 | 70 | 36 | 775,000$/1yrs | |||
![]() | 0 | D | 100.00 | 58 | 32 | 89 | 57 | 74 | 88 | 79 | 51 | 30 | 59 | 58 | 58 | 55 | 59 | 58 | 0 | 39 | 69 | 20 | 918,333$/2yrs | |||
![]() | 0 | D | 100.00 | 68 | 40 | 77 | 51 | 84 | 64 | 66 | 51 | 30 | 57 | 56 | 63 | 56 | 59 | 57 | 0 | 57 | 67 | 20 | 950,000$/2yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 26 | LW/RW | 100.00 | 61 | 38 | 89 | 64 | 73 | 63 | 60 | 61 | 65 | 57 | 56 | 62 | 64 | 61 | 60 | 0 | 20 | 69 | 25 | ||||
![]() | 0 | LW | 100.00 | 69 | 40 | 75 | 53 | 83 | 62 | 67 | 61 | 47 | 52 | 53 | 65 | 52 | 63 | 60 | 0 | 20 | 67 | 22 | 867,500$/2yrs | |||
![]() | 0 | LW | 100.00 | 99 | 45 | 50 | 53 | 73 | 62 | 65 | 61 | 50 | 53 | 51 | 64 | 52 | 61 | 56 | 0 | 40 | 67 | 22 | ||||
![]() | 0 | LW | 100.00 | 66 | 38 | 81 | 52 | 60 | 62 | 84 | 62 | 36 | 54 | 50 | 66 | 52 | 64 | 62 | 0 | 31 | 66 | 26 | 775,000$/1yrs | |||
![]() | 0 | C | 100.00 | 70 | 40 | 74 | 54 | 81 | 62 | 67 | 61 | 63 | 53 | 52 | 64 | 53 | 61 | 58 | 0 | 20 | 66 | 22 | 867,500$/2yrs | |||
![]() | 0 | C | 100.00 | 56 | 38 | 97 | 52 | 76 | 61 | 76 | 61 | 63 | 49 | 52 | 64 | 51 | 61 | 60 | 0 | 19 | 65 | 23 | 895,000$/2yrs | |||
![]() | 0 | D | 100.00 | 73 | 39 | 78 | 62 | 69 | 70 | 60 | 62 | 48 | 58 | 51 | 65 | 63 | 66 | 64 | 0 | 20 | 71 | 28 | ||||
![]() | 52 | D | 100.00 | 56 | 38 | 92 | 60 | 79 | 66 | 60 | 57 | 30 | 54 | 46 | 64 | 58 | 61 | 60 | 0 | 19 | 68 | 25 | ||||
![]() | 0 | D | 100.00 | 77 | 41 | 63 | 50 | 73 | 61 | 75 | 47 | 30 | 55 | 47 | 65 | 51 | 62 | 59 | 0 | 19 | 66 | 24 | ||||
![]() | 0 | D | 100.00 | 65 | 39 | 82 | 44 | 72 | 60 | 77 | 44 | 30 | 49 | 49 | 66 | 49 | 64 | 62 | 0 | 20 | 63 | 25 | ||||
![]() | 0 | D | 100.00 | 76 | 40 | 64 | 44 | 72 | 58 | 69 | 43 | 30 | 49 | 47 | 64 | 48 | 61 | 57 | 0 | 19 | 62 | 23 | 859,167$/1yrs | |||
![]() | 0 | D | 100.00 | 62 | 38 | 88 | 45 | 66 | 59 | 81 | 44 | 30 | 50 | 46 | 65 | 48 | 62 | 61 | 0 | 20 | 62 | 24 | 859,167$/1yrs |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 100.00 | 71 | 80 | 66 | 74 | 65 | 69 | 69 | 71 | 69 | 71 | 70 | 55 | 56 | 0 | 34 | 73 | 21 | 798,333$/1yrs |
![]() | 0 | 100.00 | 60 | 62 | 66 | 81 | 53 | 60 | 60 | 61 | 60 | 63 | 60 | 71 | 74 | 0 | 23 | 68 | 27 | 880,000$/1yrs |
Scratches |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Jessica Campbell | 65 | 68 | 75 | 70 | 53 | 48 | 84 | CAN | 32 | 5 | 500,000$ |
General Manager |
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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 |
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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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Player Name | POS | Age | Cap Hit | 2020-21 | 2021-22 | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 |
---|---|---|---|---|---|---|---|---|---|---|---|
Alex Turcotte | C | 24 | 900,000$ | 900,000$ | 900,000$ | ||||||
Artyom Levshunov | D | 19 | 975,000$ | 975,000$ | 975,000$ | 975,000$ | RFA | ||||
Ben King | C | 22 | 800,000$ | 800,000$ | 800,000$ | RFA | |||||
Bobby Trivigno | LW | 26 | 775,000$ | 775,000$ | |||||||
Bode Wilde | D | 25 | 0$ | ||||||||
Calle Sjalin | D | 25 | 0$ | ||||||||
Cedric Pare | C | 26 | 775,000$ | 775,000$ | |||||||
David Gustafsson | C | 25 | 800,000$ | 800,000$ | 800,000$ | ||||||
David Reinbacher | D | 20 | 950,000$ | 950,000$ | 950,000$ | RFA | |||||
Denton Mateychuk | D | 20 | 918,333$ | 918,333$ | 918,333$ | RFA | |||||
Devin Cooley | G | 27 | 880,000$ | 880,000$ | UFA | ||||||
Dominik Bokk | LW/RW | 25 | 0$ | ||||||||
Eetu Liukas | LW | 22 | 867,500$ | 867,500$ | 867,500$ | RFA | |||||
Jayden Grubbe | C | 22 | 867,500$ | 867,500$ | 867,500$ | RFA | |||||
Joseph Blandisi | LW/RW | 30 | 775,000$ | 775,000$ | UFA | ||||||
Kevin Korchinski | D | 20 | 918,333$ | 918,333$ | 918,333$ | RFA | |||||
Kim Nousiainen | D | 24 | 859,167$ | 859,167$ | |||||||
Matthew Maggio | RW | 22 | 870,000$ | 870,000$ | 870,000$ | RFA | |||||
Matthew Savoie | C | 21 | 918,333$ | 918,333$ | 918,333$ | RFA | |||||
Max McCue | LW | 22 | 0$ | RFA | |||||||
Michael Joyaux | D | 28 | 0$ | UFA | |||||||
Milos Kelemen | LW/RW | 25 | 900,000$ | 900,000$ | 900,000$ | ||||||
Mitchell Russell | C/RW | 24 | 836,667$ | 836,667$ | |||||||
Nathan Burke | LW/RW | 26 | 775,000$ | 775,000$ | |||||||
Nikolas Brouillard | D | 30 | 775,000$ | 775,000$ | UFA | ||||||
Nolan Lalonde | G | 21 | 798,333$ | 798,333$ | RFA | ||||||
Robert Bortuzzo | D | 36 | 775,000$ | 775,000$ | UFA | ||||||
Ryan Merkley | D | 24 | 0$ | ||||||||
Ryder Rolston | C | 23 | 895,000$ | 895,000$ | 895,000$ | ||||||
Steven Lorentz | C/LW | 29 | 775,000$ | 775,000$ | UFA | ||||||
Ville Petman | C/LW | 25 | 775,000$ | 775,000$ | |||||||
Wyatt Bongiovanni | C | 25 | 802,500$ | 802,500$ | |||||||
Zach Uens | D | 23 | 859,167$ | 859,167$ | RFA |
Forward Lines | |||||||
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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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 | nan% | nan% | nan% | nan | Unlucky |
Puck Time | |
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Offensive Zone | NAN |
Neutral Zone | NAN |
Defensive Zone | NAN |
Puck Time | |
---|---|
Offensive Zone Start | 0 |
Neutral Zone Start | 0 |
Defensive Zone Start | 0 |
Puck Time | |
---|---|
With Puck | NAN |
Without Puck | NAN |
Faceoffs | |
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Faceoffs Won | 0 |
Faceoffs Lost | 0 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | nan | 9.57 |
2nd Period | nan | 20.31 |
3rd Period | nan | 30.68 |
Overtime | nan | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | nan | 0.64 |
2nd Period | nan | 1.65 |
3rd Period | nan | 2.67 |
Overtime | nan | 2.83 |
Even Strenght Goal | 0 |
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PP Goal | 0 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
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 | nan |
Shots Against | nan |
Goals For | nan |
Goals Against | nan |
Hits | nan |
Shots Blocked | nan |
Pim | nan |
Date | Matchup | Result | Detail |
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Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
2,281,583$ | 0$ | 0$ | 75,000,000$ |
Arena | About us | |
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![]() | Name | |
City | Hartford | |
Capacity | 3000 | |
Season Ticket Holders | 0% |
Arena Capacity - Ticket Price Attendance - % | |||||
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Arena Capacity | 2000 | 1000 | |||
Ticket Price | 35$ | 0$ | $ | $ | $ |
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 |
36 | 0 - 0.00% | 0$ | 0$ | 3000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
2,281,583$ | 2,281,583$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
0$ | 0$ | 0$ | 0$ |
Estimate | |||
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Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 12 | 0$ | 0$ |
Team Total Estimate | |||
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Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
0$ | 0$ | 0$ | 0$ |
Sponsors | |||
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TV Rights | Primary Sponsor | Secondary Sponsor | Secondary Sponsor |
Left Wing | Center | Right Wing |
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Defense #1 | Defense #2 | Goalie |
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