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Full Scoreboard >> |
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Full Scoreboard >> |
![]() | Orlando Mounties 0-0-0, 0pts · 10th in World 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 | RW | 100.00 | 35 | 40 | 73 | 25 | 84 | 78 | 93 | 72 | 74 | 67 | 79 | 73 | 66 | 53 | 49 | 88 | 75 | 84 | 24 | 9,250,000$/5yrs | |||
![]() | 0 | LW/RW | 100.00 | 49 | 40 | 75 | 33 | 79 | 73 | 77 | 65 | 37 | 65 | 76 | 85 | 45 | 54 | 50 | 82 | 75 | 82 | 29 | 6,000,000$/2yrs | |||
![]() | 0 | C | 100.00 | 41 | 40 | 80 | 28 | 78 | 61 | 99 | 72 | 85 | 74 | 75 | 68 | 51 | 76 | 92 | 86 | 75 | 80 | 30 | 11,000,000$/3yrs | |||
![]() | 0 | LW | 100.00 | 75 | 87 | 78 | 33 | 84 | 50 | 70 | 66 | 40 | 67 | 75 | 83 | 45 | 62 | 54 | 82 | 75 | 79 | 29 | 4,700,000$/2yrs | |||
![]() | 0 | C | 100.00 | 37 | 40 | 80 | 35 | 82 | 57 | 99 | 65 | 72 | 58 | 77 | 75 | 66 | 67 | 57 | 80 | 75 | 77 | 29 | 8,100,000$/2yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 60 | 46 | 74 | 40 | 75 | 50 | 98 | 60 | 44 | 59 | 73 | 83 | 76 | 58 | 51 | 76 | 75 | 75 | 29 | 3,800,000$/2yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 34 | 40 | 78 | 37 | 66 | 50 | 99 | 68 | 70 | 61 | 73 | 65 | 38 | 43 | 39 | 79 | 75 | 73 | 22 | 885,833$/1yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 49 | 40 | 79 | 40 | 65 | 50 | 98 | 64 | 84 | 62 | 73 | 66 | 66 | 89 | 65 | 76 | 75 | 71 | 30 | 3,300,000$/1yrs | |||
![]() | 0 | C/RW | 100.00 | 50 | 40 | 79 | 42 | 71 | 50 | 80 | 62 | 57 | 59 | 75 | 68 | 47 | 40 | 37 | 75 | 75 | 71 | 24 | 925,000$/1yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 54 | 40 | 81 | 42 | 77 | 50 | 95 | 63 | 79 | 60 | 74 | 66 | 18 | 93 | 67 | 74 | 75 | 70 | 33 | 1,000,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 96 | 48 | 76 | 48 | 67 | 50 | 93 | 51 | 74 | 51 | 72 | 79 | 45 | 48 | 42 | 70 | 75 | 70 | 28 | 1,000,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 43 | 40 | 81 | 48 | 79 | 50 | 89 | 59 | 47 | 61 | 67 | 72 | 57 | 47 | 43 | 70 | 75 | 68 | 28 | 500,000$/2yrs | |||
![]() | 0 | D | 100.00 | 45 | 40 | 81 | 47 | 83 | 73 | 73 | 63 | 25 | 67 | 69 | 88 | 45 | 69 | 62 | 76 | 75 | 80 | 29 | 5,300,000$/3yrs | |||
![]() | 57 | D | 100.00 | 41 | 45 | 69 | 46 | 93 | 70 | 98 | 68 | 25 | 73 | 67 | 78 | 45 | 73 | 59 | 77 | 75 | 77 | 31 | 5,800,000$/4yrs | |||
![]() | 0 | D | 100.00 | 44 | 40 | 82 | 48 | 66 | 50 | 63 | 65 | 25 | 74 | 66 | 88 | 45 | 83 | 73 | 74 | 75 | 76 | 34 | 2,100,000$/1yrs | |||
![]() | 0 | D | 100.00 | 43 | 44 | 78 | 46 | 74 | 84 | 99 | 70 | 25 | 75 | 68 | 70 | 45 | 59 | 56 | 77 | 75 | 75 | 26 | 3,150,000$/1yrs | |||
![]() | 0 | D | 100.00 | 73 | 76 | 76 | 53 | 78 | 50 | 39 | 25 | 25 | 25 | 55 | 88 | 45 | 53 | 50 | 66 | 75 | 72 | 31 | 1,350,000$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 67 | LW/RW | 100.00 | 53 | 40 | 76 | 46 | 68 | 50 | 14 | 62 | 74 | 61 | 69 | 78 | 40 | 60 | 74 | 71 | 75 | 70 | 33 | 925,000$/1yrs | |||
![]() | 0 | C | 100.00 | 37 | 40 | 80 | 44 | 70 | 50 | 71 | 63 | 58 | 65 | 71 | 58 | 66 | 41 | 39 | 73 | 75 | 68 | 24 | 916,667$/1yrs | |||
![]() | 0 | D | 100.00 | 40 | 40 | 80 | 33 | 71 | 92 | 79 | 90 | 25 | 96 | 67 | 83 | 45 | 42 | 39 | 96 | 75 | 91 | 22 | 880,833$/1yrs | |||
![]() | 0 | D | 100.00 | 66 | 69 | 75 | 52 | 84 | 50 | 71 | 55 | 25 | 52 | 65 | 84 | 45 | 66 | 54 | 68 | 75 | 72 | 32 | 1,000,000$/2yrs | |||
![]() | 0 | D | 100.00 | 67 | 55 | 83 | 70 | 90 | 50 | 38 | 45 | 25 | 45 | 40 | 85 | 45 | 49 | 48 | 65 | 75 | 70 | 29 | 450,000$/2yrs | |||
TEAM AVERAGE | 100.00 | 51 | 47 | 78 | 43 | 77 | 59 | 79 | 62 | 50 | 63 | 69 | 77 | 49 | 60 | 55 | 76 | 75 | 75 |
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 | 81 | 95 | 74 | 75 | 81 | 91 | 81 | 79 | 81 | 80 | 69 | 52 | 50 | 66 | 75 | 68 | 35 | 1,550,000$/1yrs |
![]() | 0 | 100.00 | 81 | 69 | 74 | 65 | 81 | 88 | 84 | 81 | 82 | 81 | 74 | 40 | 36 | 61 | 75 | 64 | 30 | 600,000$/2yrs |
Scratches | ||||||||||||||||||||
![]() | 0 | 100.00 | 79 | 90 | 99 | 91 | 79 | 97 | 80 | 81 | 81 | 80 | 75 | 64 | 58 | 73 | 75 | 80 | 31 | 3,550,000$/1yrs |
TEAM AVERAGE | 100.00 | 80 | 85 | 82 | 77 | 80 | 92 | 82 | 80 | 81 | 80 | 73 | 52 | 48 | 67 | 75 | 71 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
John Tortorella | 81 | 90 | 82 | 89 | 92 | 85 | 53 | USA | 62 | 3 | 0$ |
General Manager | John Salerno |
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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 | MP | PPG | PPA | PPP | PKG | PKA | PKP | PKM | GW | GT | FO% | FOT | GA | TA | EG | HT | P/20 | PSG | PSS |
---|
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 |
---|
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 | nan | nan | nan | 0 | 0.000 | nan | nan | nan | 0 | 0 | 0 | 0 | 0 | 0 | nan | 0 | 0 | 0 | 0 | nan | nan | nan | nan | nan | nan | 0.00% | nan | nan | 0.00% | 0 | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0.00% | nan | nan | nan | nan | nan | nan | nan% | nan% | nan% | nan | Unlucky |
Puck Time | |
---|---|
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 | |
---|---|
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 |
---|---|
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 |
---|---|
PP Goal | 0 |
PK Attempt | 0 |
PK Goal Against | 0 |
Home | |
---|---|
Shots For | nan |
Shots Against | nan |
Goals For | nan |
Goals Against | nan |
Hits | nan |
Shots Blocked | nan |
Pim | nan |
![]() | |
Total Salaries | 80,308,833$ |
Projected Total Cap Hit | 0$ |
Projected Cap Space | 81,500,000$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 0$ |
Players Signed (45 – 60) | 55 |
Goalies Signed (min. 6) | 6 |
Defensemen Signed (min. 16) | 18 |
LTIR Players | 0 |
Mounties Roster | Pos | Age | Base Salary |
Cap Hit Remaining |
Season 40 |
Season 41 |
Season 42 |
Season 43 |
Season 44 |
Season 45 |
Season 46 |
Season 47 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Adam Gaudette | C | 24 | 916,667$ | 163,691$ | 916,667$ | RFA | ||||||
Blake Coleman | C/LW/RW | 29 | 3,800,000$ | 678,571$ | 3,800,000$ | 3,800,000$ | UFA | |||||
Brian Dumoulin | D | 29 | 5,300,000$ | 946,429$ | 5,300,000$ | 5,300,000$ | 5,300,000$ | UFA | ||||
Brock Nelson | C | 29 | 8,100,000$ | 1,446,429$ | 8,100,000$ | 8,100,000$ | UFA | |||||
Cale Makar | D | 22 | 880,833$ | 157,292$ | 880,833$ | RFA | ||||||
Carter Hutton | G | 35 | 1,550,000$ | 276,786$ | 1,550,000$ | UFA | ||||||
Clayton Keller | C/LW/RW | 22 | 885,833$ | 158,184$ | 885,833$ | RFA | ||||||
Colin White | C/RW | 24 | 925,000$ | 165,179$ | 925,000$ | RFA | ||||||
Derick Brassard | C/LW/RW | 33 | 1,000,000$ | 178,571$ | 1,000,000$ | 1,000,000$ | UFA | |||||
Gustaf Lindvall | G | 30 | 600,000$ | 107,143$ | 600,000$ | 600,000$ | UFA | |||||
Jacob Markstrom | G | 31 | 3,550,000$ | 633,929$ | 3,550,000$ | UFA | ||||||
Jarred Tinordi | D | 29 | 450,000$ | 80,357$ | 450,000$ | 450,000$ | UFA | |||||
Jimmy Vesey | LW/RW | 28 | 500,000$ | 89,286$ | 500,000$ | 500,000$ | UFA | |||||
John Tavares | C | 30 | 11,000,000$ | 1,964,286$ | 11,000,000$ | 11,000,000$ | 11,000,000$ | UFA | ||||
Josh Archibald | LW/RW | 28 | 1,000,000$ | 178,571$ | 1,000,000$ | 1,000,000$ | UFA | |||||
Josh Morrissey | D | 26 | 3,150,000$ | 562,500$ | 3,150,000$ | RFA | ||||||
Kris Russell | D | 34 | 2,100,000$ | 375,000$ | 2,100,000$ | UFA | ||||||
Marcus Foligno | LW | 29 | 4,700,000$ | 839,286$ | 4,700,000$ | 4,700,000$ | UFA | |||||
Mark Borowiecki | D | 31 | 1,350,000$ | 241,071$ | 1,350,000$ | UFA | ||||||
Michael Frolik | LW/RW | 33 | 925,000$ | 165,179$ | 925,000$ | UFA | ||||||
Mikko Rantanen | RW | 24 | 9,250,000$ | 1,651,786$ | 9,250,000$ | 9,250,000$ | 9,250,000$ | 9,250,000$ | 9,250,000$ | UFA | ||
Robert Bortuzzo | D | 32 | 1,000,000$ | 178,571$ | 1,000,000$ | 1,000,000$ | UFA | |||||
Tyler Johnson | C/LW/RW | 30 | 3,300,000$ | 589,286$ | 3,300,000$ | UFA | ||||||
Tyler Myers | D | 31 | 5,800,000$ | 1,035,714$ | 5,800,000$ | 5,800,000$ | 5,800,000$ | 5,800,000$ | UFA | |||
Zach Hyman | LW/RW | 29 | 6,000,000$ | 1,071,429$ | 6,000,000$ | 6,000,000$ | UFA |
Farm Roster | Pos | Age | Base Salary |
Cap Hit Remaining |
Season 40 |
Season 41 |
Season 42 |
Season 43 |
Season 44 |
Season 45 |
Season 46 |
Season 47 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
A.J. Greer | LW | 24 | 735,000$ | 13,125$ | 73,500$ | 73,500$ | RFA | |||||
Albin Eriksson | LW/RW | 20 | 725,000$ | 12,946$ | 72,500$ | RFA | ||||||
Alexander Samonov | G | 25 | 500,000$ | 8,929$ | 50,000$ | RFA | ||||||
Anthony Bitetto | D | 30 | 800,000$ | 14,286$ | 80,000$ | 80,000$ | UFA | |||||
Carter Berger | D | 21 | 550,000$ | 9,821$ | 55,000$ | 55,000$ | RFA | |||||
Connor Ingram | G | 24 | 759,167$ | 13,557$ | 75,917$ | 75,917$ | RFA | |||||
Dennis Busby | D | 21 | 475,000$ | 8,482$ | 47,500$ | RFA | ||||||
Gavin Hain | C | 21 | 450,000$ | 8,036$ | 45,000$ | RFA | ||||||
Jack Gorniak | C/LW | 21 | 500,000$ | 8,929$ | 50,000$ | RFA | ||||||
Jonah Gadjovich | LW | 22 | 783,333$ | 13,988$ | 78,333$ | 78,333$ | RFA | |||||
Jonathan Dahlen | LW | 23 | 925,000$ | 16,518$ | 92,500$ | 92,500$ | RFA | |||||
Jonathan Gruden | LW | 21 | 550,000$ | 9,821$ | 55,000$ | RFA | ||||||
Kasper Kotkansalo | D | 22 | 450,000$ | 8,036$ | 45,000$ | RFA | ||||||
Keean Washkurak | C | 19 | 475,000$ | 8,482$ | 47,500$ | 47,500$ | RFA | |||||
Kevin Gravel | D | 29 | 450,000$ | 8,036$ | 45,000$ | UFA | ||||||
Markus Nurmi | LW/RW | 23 | 625,000$ | 11,161$ | 62,500$ | 62,500$ | RFA | |||||
Matt Irwin | D | 33 | 500,000$ | 89,286$ | 500,000$ | UFA | ||||||
Matt Puempel | LW | 28 | 675,000$ | 12,054$ | 67,500$ | 67,500$ | UFA | |||||
Max Lajoie | D | 23 | 710,000$ | 12,679$ | 71,000$ | 71,000$ | RFA | |||||
Miles Gendron | D | 25 | 475,000$ | 8,482$ | 47,500$ | 47,500$ | RFA | |||||
Nate Clurman | D | 23 | 500,000$ | 8,929$ | 50,000$ | 50,000$ | RFA | |||||
Nick Sorensen | RW | 26 | 0$ | 8,929$ | 50,000$ | 50,000$ | UFA | |||||
Nikolai Prokhorkin | C | 27 | 925,000$ | 16,518$ | 92,500$ | 92,500$ | UFA | |||||
Noah Cates | LW | 22 | 450,000$ | 8,036$ | 45,000$ | RFA | ||||||
Robin Salo | D | 22 | 842,500$ | 15,045$ | 84,250$ | 84,250$ | RFA | |||||
Santeri Virtanen | C | 22 | 450,000$ | 8,036$ | 45,000$ | RFA | ||||||
Todd Burgess | C/RW | 25 | 525,000$ | 9,375$ | 52,500$ | 52,500$ | RFA | |||||
Vladislav Kamenev | C/LW/RW | 24 | 500,000$ | 8,929$ | 50,000$ | 50,000$ | RFA | |||||
Wade Allison | RW | 23 | 550,000$ | 9,821$ | 55,000$ | 55,000$ | RFA | |||||
Yevgeni Alikin | G | 26 | 900,000$ | 16,071$ | 90,000$ | 90,000$ | 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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Total | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | nan | nan | nan | 0 | 0.000 | nan | nan | nan | 0 | 0 | 0 | 0 | 0 | 0 | nan | 0 | 0 | 0 | 0 | nan | nan | nan | nan | nan | nan | 0.00% | nan | nan | 0.00% | 0 | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0.00% | nan | nan | nan | nan | nan | nan | nan% | nan% | nan% | nan | Unlucky |
Puck Time | |
---|---|
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 | |
---|---|
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 |
---|---|
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 |
---|---|
PP Goal | 0 |
PK Attempt | 0 |
PK Goal Against | 0 |
Home | |
---|---|
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 |
78,533,333$ | 0$ | 0$ | 81,500,000$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | Rougeau Center | |
City | Orlando | ||
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$ | 20$ | 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$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
78,533,333$ | 78,533,333$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
0$ | 0$ | 0$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 5 | 0$ | 0$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
0$ | 0$ | 81,612,343$ | 81,612,343$ |
Left Wing | Center | Right Wing | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Defense #1 | Defense #2 | Goalie | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Year | Round 1 | Round 2 | Round 3 | Round 4 | Round 5 | Round 6 | Round 7 |
---|---|---|---|---|---|---|---|
2022 | ![]() | ![]() | ![]() | ![]() | ![]() ![]() | ||
2023 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2024 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2025 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2026 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
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 |
---|---|---|---|---|---|
Aleksi Heimosalmi | ![]() | 2021 | 47 | ||
Cal Thomas | ![]() | 2021 | 187 | ||
Cross Hanas | ![]() | 2020 | 67 | ||
Jackson Kunz | ![]() | 2020 | 123 | ||
Jakub Brabenec | ![]() | 2021 | 110 | ||
Jesper Wallstedt | ![]() | 2021 | 19 | ||
Matteo Costantini | ![]() | 2020 | 151 | ||
Nolan Allan | ![]() | 2021 | 35 | ||
Tristan Broz | ![]() | 2021 | 63 | ||
Yaroslav Askarov | ![]() | 2020 | 11 |
Year | Round 1 | Round 2 | Round 3 | Round 4 | Round 5 | Round 6 | Round 7 |
---|---|---|---|---|---|---|---|
2022 | ![]() | ![]() | ![]() | ![]() | ![]() ![]() | ||
2023 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2024 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2025 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2026 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
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 |
---|---|---|---|---|---|
Aleksi Heimosalmi | ![]() | 2021 | 47 | ||
Cal Thomas | ![]() | 2021 | 187 | ||
Cross Hanas | ![]() | 2020 | 67 | ||
Jackson Kunz | ![]() | 2020 | 123 | ||
Jakub Brabenec | ![]() | 2021 | 110 | ||
Jesper Wallstedt | ![]() | 2021 | 19 | ||
Matteo Costantini | ![]() | 2020 | 151 | ||
Nolan Allan | ![]() | 2021 | 35 | ||
Tristan Broz | ![]() | 2021 | 63 | ||
Yaroslav Askarov | ![]() | 2020 | 11 |
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