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Philadelphia Flyers 1-4-0, 2pts · 3rd 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 | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 91 | C/LW/RW | 100.00 | 70 | 33 | 86 | 90 | 76 | 86 | 90 | 86 | 84 | 89 | 86 | 67 | 86 | 80 | 98 | 0 | 78 | 94 | 32 | 8,500,000$/3yrs | |||
![]() | 93 | C | 100.00 | 70 | 33 | 91 | 84 | 80 | 88 | 90 | 80 | 87 | 84 | 83 | 87 | 82 | 75 | 83 | 0 | 80 | 92 | 29 | 5,350,000$/7yrs | |||
![]() | 17 | LW/RW | 100.00 | 69 | 33 | 72 | 78 | 78 | 86 | 90 | 79 | 57 | 79 | 79 | 76 | 79 | 81 | 88 | 0 | 78 | 87 | 32 | 4,450,000$/2yrs | |||
![]() | 71 | C/RW | 100.00 | 69 | 40 | 67 | 76 | 74 | 86 | 89 | 77 | 82 | 77 | 74 | 90 | 76 | 67 | 64 | 0 | 78 | 86 | 24 | 5,500,000$/5yrs | |||
![]() | 18 | LW/RW | 100.00 | 77 | 33 | 87 | 75 | 75 | 83 | 89 | 77 | 56 | 80 | 76 | 71 | 76 | 78 | 77 | 0 | 78 | 85 | 31 | 5,300,000$/1yrs | |||
![]() | 17 | RW | 100.00 | 76 | 32 | 94 | 64 | 74 | 80 | 89 | 70 | 59 | 73 | 69 | 73 | 69 | 76 | 76 | 0 | 78 | 81 | 30 | 2,000,000$/2yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 80 | 34 | 90 | 61 | 73 | 79 | 90 | 66 | 87 | 65 | 66 | 86 | 66 | 81 | 80 | 0 | 78 | 80 | 33 | 2,000,000$/1yrs | |||
![]() | 0 | C/LW | 100.00 | 78 | 35 | 87 | 62 | 80 | 79 | 86 | 65 | 75 | 65 | 66 | 83 | 65 | 70 | 69 | 0 | 81 | 79 | 26 | 2,250,000$/2yrs | |||
![]() | 0 | C | 100.00 | 61 | 37 | 92 | 66 | 62 | 72 | 83 | 65 | 66 | 69 | 63 | 64 | 66 | 61 | 61 | 0 | 53 | 74 | 22 | 850,000$/2yrs | |||
![]() | 0 | LW | 100.00 | 42 | 39 | 79 | 67 | 76 | 72 | 73 | 64 | 36 | 64 | 68 | 64 | 66 | 60 | 58 | 0 | 56 | 73 | 21 | 859,167$/4yrs | |||
![]() | 0 | C | 100.00 | 69 | 39 | 83 | 66 | 76 | 71 | 77 | 62 | 63 | 65 | 66 | 62 | 65 | 58 | 56 | 0 | 63 | 73 | 20 | 859,167$/4yrs | |||
![]() | 59 | D | 100.00 | 65 | 33 | 80 | 85 | 79 | 97 | 90 | 81 | 30 | 94 | 79 | 80 | 80 | 80 | 93 | 0 | 78 | 94 | 31 | 9,000,000$/7yrs | |||
![]() | 6 | D | 100.00 | 83 | 34 | 88 | 64 | 90 | 84 | 80 | 72 | 30 | 71 | 66 | 93 | 69 | 83 | 92 | 0 | 78 | 87 | 34 | 6,000,000$/2yrs | |||
![]() | 0 | D | 100.00 | 76 | 39 | 76 | 64 | 92 | 93 | 74 | 69 | 30 | 73 | 69 | 86 | 69 | 88 | 99 | 0 | 58 | 86 | 36 | 7,857,143$/5yrs | |||
![]() | 0 | D | 100.00 | 66 | 40 | 81 | 59 | 82 | 64 | 72 | 60 | 30 | 65 | 55 | 71 | 60 | 73 | 77 | 0 | 85 | 75 | 29 | 750,000$/3yrs | |||
![]() | 46 | D | 100.00 | 68 | 33 | 90 | 59 | 82 | 78 | 78 | 59 | 30 | 64 | 63 | 70 | 61 | 69 | 68 | 0 | 34 | 75 | 26 | 700,000$/2yrs | |||
![]() | 35 | D | 100.00 | 80 | 50 | 77 | 55 | 80 | 77 | 73 | 59 | 30 | 60 | 58 | 76 | 58 | 73 | 71 | 0 | 60 | 75 | 28 | 700,000$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 27 | D | 100.00 | 67 | 33 | 95 | 65 | 81 | 83 | 82 | 67 | 30 | 71 | 50 | 78 | 59 | 73 | 72 | 0 | 80 | 80 | 28 | 3,250,000$/4yrs | |||
TEAM AVERAGE | 100.00 | 70 | 36 | 84 | 69 | 78 | 81 | 83 | 70 | 53 | 73 | 69 | 77 | 70 | 74 | 77 | 0 | 71 | 82 |
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 | 93 | 95 | 85 | 85 | 91 | 86 | 92 | 96 | 89 | 96 | 92 | 74 | 79 | 0 | 73 | 93 | 28 | 6,166,666$/3yrs |
![]() | 0 | 100.00 | 82 | 78 | 73 | 89 | 84 | 82 | 84 | 87 | 83 | 87 | 84 | 69 | 73 | 0 | 78 | 85 | 26 | 1,500,000$/2yrs |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 100.00 | 88 | 87 | 79 | 87 | 88 | 84 | 88 | 92 | 86 | 92 | 88 | 72 | 76 | 0 | 76 | 89 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Darryl Sutter | 75 | 96 | 90 | 82 | 98 | 89 | 96 | CAN | 62 | 3 | 1,000,000$ |
General Manager | Pierre-Etienne Jobin |
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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 | AMG | PPG | PPA | PPP | PPM | PKG | PKA | PKP | PKM | GW | GT | FO% | FOT | GA | TA | EG | HT | P/20 | PSG | PSS |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Alex Killorn | 17 | LW/RW | 5 | 2 | 2 | 4 | -3 | 4 | 0 | 8 | 19 | 0 | 12 | 10.53% | 0 | 19.23 | 0 | 1 | 1 | 16 | 0 | 0 | 0 | 0 | 0 | 0 | 42.86% | 7 | 0 | 0 | 0 | 0 | 0.83 | 0 | 0 | ||
2 | Steven Stamkos | 91 | C/LW/RW | 5 | 3 | 1 | 4 | 2 | 0 | 0 | 6 | 15 | 5 | 7 | 20.00% | 2 | 22.55 | 0 | 0 | 0 | 15 | 0 | 0 | 0 | 0 | 0 | 0 | 66.67% | 9 | 0 | 0 | 0 | 0 | 0.71 | 0 | 0 | ||
3 | Anthony Cirelli | 71 | C/RW | 5 | 0 | 3 | 3 | -4 | 2 | 0 | 7 | 13 | 3 | 6 | 0.00% | 2 | 21.83 | 0 | 1 | 1 | 16 | 0 | 0 | 0 | 17 | 0 | 0 | 45.57% | 158 | 0 | 0 | 0 | 0 | 0.55 | 0 | 0 | ||
4 | Luke Glendening | 0 | C/LW/RW | 5 | 2 | 1 | 3 | 3 | 0 | 0 | 4 | 6 | 1 | 1 | 33.33% | 2 | 9.81 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 19 | 0 | 0 | 42.86% | 28 | 0 | 0 | 0 | 0 | 1.22 | 0 | 0 | ||
5 | Mika Zibanejad | 93 | C | 5 | 0 | 3 | 3 | 1 | 0 | 0 | 9 | 21 | 8 | 13 | 0.00% | 1 | 24.39 | 0 | 0 | 0 | 15 | 0 | 0 | 0 | 8 | 0 | 0 | 61.74% | 149 | 0 | 0 | 0 | 0 | 0.49 | 0 | 0 | ||
6 | Jason Dickinson | 0 | C/LW | 5 | 1 | 1 | 2 | 3 | 0 | 0 | 4 | 2 | 1 | 3 | 50.00% | 1 | 6.63 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0.00% | 5 | 0 | 0 | 0 | 0 | 1.21 | 0 | 0 | ||
7 | Jesper Fast | 17 | RW | 5 | 1 | 1 | 2 | 3 | 2 | 0 | 2 | 3 | 1 | 3 | 33.33% | 0 | 5.96 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 1.34 | 0 | 0 | ||
8 | Ondrej Palat | 18 | LW/RW | 5 | 1 | 1 | 2 | -3 | 0 | 0 | 8 | 7 | 5 | 7 | 14.29% | 0 | 17.87 | 1 | 0 | 1 | 15 | 0 | 0 | 0 | 0 | 0 | 0 | 50.00% | 6 | 0 | 0 | 0 | 0 | 0.45 | 0 | 0 | ||
9 | Roman Josi | 59 | D | 5 | 1 | 1 | 2 | 0 | 4 | 0 | 3 | 15 | 0 | 1 | 6.67% | 10 | 25.57 | 0 | 0 | 0 | 17 | 0 | 0 | 0 | 14 | 1 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.31 | 0 | 0 | ||
10 | Erik Johnson | 6 | D | 5 | 1 | 0 | 1 | -1 | 6 | 0 | 11 | 3 | 0 | 3 | 33.33% | 12 | 21.23 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 11 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.19 | 0 | 0 | ||
11 | Shea Weber | 0 | D | 5 | 0 | 0 | 0 | -2 | 10 | 0 | 12 | 3 | 2 | 4 | 0.00% | 7 | 23.79 | 0 | 0 | 0 | 14 | 0 | 0 | 0 | 11 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | ||
Team Total or Average | 55 | 12 | 14 | 26 | -1 | 28 | 0 | 74 | 107 | 26 | 60 | 11.21% | 37 | 18.08 | 1 | 2 | 3 | 112 | 0 | 0 | 0 | 86 | 1 | 0 | 51.93% | 362 | 0 | 0 | 0 | 0 | 0.52 | 0 | 0 |
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 | Connor Hellebuyck | 5 | 1 | 3 | 1 | 0.890 | 3.22 | 317 | 0 | 0 | 17 | 154 | 0 | 1 | 0 | 0.000 | 0 | 5 | 0 | 0 | 0 | 0 | |
Team Total or Average | 5 | 1 | 3 | 1 | 0.890 | 3.22 | 317 | 0 | 0 | 17 | 154 | 0 | 1 | 0 | 0.000 | 0 | 5 | 0 | 0 | 0 | 0 |
Projected Total Cap Hit | 0$ |
Projected Cap Space | 81,500,000$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 0$ |
Players In Salary Cap | 20 |
LTIR Players | 0 |
Flyers Roster | Pos | Age | Cap Hit | 2021-22 | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 |
---|---|---|---|---|---|---|---|---|---|---|---|
Adin Hill | G | 26 | 1,500,000$ | 1,500,000$ | 1,500,000$ | ![]() | |||||
Alex Killorn | LW/RW | 32 | 4,450,000$ | 4,450,000$ | 4,450,000$ | UFA | |||||
Anthony Cirelli | C/RW | 24 | 5,500,000$ | 5,500,000$ | 5,500,000$ | 5,500,000$ | 5,500,000$ | 5,500,000$ | UFA | ||
Bennett MacArthur ![]() | LW | 21 | 859,167$ | 859,167$ | 859,167$ | 859,167$ | 859,167$ | RFA | |||
Connor Hellebuyck | G | 28 | 6,166,666$ | 6,166,666$ | 6,166,666$ | 6,166,666$ | UFA | ||||
Erik Johnson | D | 34 | 6,000,000$ | 6,000,000$ | 6,000,000$ | UFA | |||||
Jake Walman ![]() | D | 26 | 700,000$ | 700,000$ | 700,000$ | ![]() | |||||
Jason Dickinson | C/LW | 26 | 2,250,000$ | 2,250,000$ | 2,250,000$ | ![]() | |||||
Jesper Fast | RW | 30 | 2,000,000$ | 2,000,000$ | 2,000,000$ | UFA | |||||
Jordan Frasca ![]() | C | 20 | 859,167$ | 859,167$ | 859,167$ | 859,167$ | 859,167$ | RFA | |||
Luke Glendening | C/LW/RW | 33 | 2,000,000$ | 2,000,000$ | UFA | ||||||
Mika Zibanejad | C | 29 | 5,350,000$ | 5,350,000$ | 8,500,000$ | 8,500,000$ | 8,500,000$ | 8,500,000$ | 8,500,000$ | 8,500,000$ | UFA |
Nick Abruzzese ![]() | C | 22 | 850,000$ | 850,000$ | 850,000$ | RFA | |||||
Nick Seeler ![]() | D | 28 | 700,000$ | 700,000$ | UFA | ||||||
Ondrej Palat | LW/RW | 31 | 5,300,000$ | 5,300,000$ | UFA | ||||||
Roman Josi | D | 31 | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ | UFA |
Ryan Murray | D | 28 | 3,250,000$ | 3,250,000$ | 3,250,000$ | 3,250,000$ | 3,250,000$ | UFA | |||
Shea Weber | D | 36 | 7,857,143$ | 7,857,143$ | 7,857,143$ | 7,857,143$ | 7,857,143$ | 7,857,143$ | UFA | ||
Steven Stamkos | C/LW/RW | 32 | 8,500,000$ | 8,500,000$ | 8,500,000$ | 8,500,000$ | UFA | ||||
Tyler Wotherspoon ![]() | D | 29 | 750,000$ | 750,000$ | 750,000$ | 750,000$ | UFA |
Non-Roster | Pos | Age | Cap Hit | 2021-22 | 2022-23 | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 |
---|---|---|---|---|---|---|---|---|---|---|---|
Adam Fox ![]() | D | 24 | 925,000$ | 925,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ |
Adam Scheel ![]() | G | 23 | 925,000$ | 925,000$ | 925,000$ | RFA | |||||
Alexander Petrovic ![]() | D | 30 | 700,000$ | 700,000$ | 700,000$ | 700,000$ | UFA | ||||
Amir Miftakhov ![]() | G | 22 | 838,333$ | 838,333$ | 838,333$ | 838,333$ | RFA | ||||
Andrew Agozzino ![]() | C/LW | 31 | 800,000$ | 800,000$ | UFA | ||||||
Andrew Poturalski ![]() | C/RW | 28 | 700,000$ | 700,000$ | 700,000$ | UFA | |||||
Cavan Fitzgerald ![]() | D | 25 | 750,000$ | 750,000$ | ![]() | ||||||
Curtis Douglas ![]() | C | 22 | 750,000$ | 750,000$ | 750,000$ | RFA | |||||
Dmitry Kulikov ![]() | D | 31 | 1,250,000$ | 1,250,000$ | 1,250,000$ | UFA | |||||
Dylan Sikura ![]() | C/LW/RW | 26 | 750,000$ | 750,000$ | ![]() | ||||||
Erik Gudbranson ![]() | D | 30 | 1,250,000$ | 1,250,000$ | 1,250,000$ | 1,250,000$ | UFA | ||||
Greg McKegg ![]() | C/LW | 29 | 1,000,000$ | 1,000,000$ | 1,000,000$ | UFA | |||||
Harri Sateri ![]() | G | 32 | 750,000$ | 750,000$ | UFA | ||||||
Hayden Hodgson ![]() | RW | 26 | 750,000$ | 750,000$ | 750,000$ | ![]() | |||||
Jeff Malott ![]() | LW | 25 | 750,000$ | 750,000$ | ![]() | ||||||
Kirill Ustimenko ![]() | G | 23 | 825,833$ | 825,833$ | RFA | ||||||
Kyle Olson ![]() | RW | 23 | 750,000$ | 750,000$ | RFA | ||||||
Lane Pederson ![]() | C/RW | 24 | 900,000$ | 900,000$ | 900,000$ | ![]() | |||||
Luke Schenn ![]() | D | 32 | 1,000,000$ | 1,000,000$ | UFA | ||||||
Mareks Mitens ![]() | G | 24 | 700,000$ | 700,000$ | RFA | ||||||
Mason Shaw ![]() | C/LW | 23 | 800,000$ | 800,000$ | 800,000$ | RFA | |||||
Michael Bunting ![]() | LW/RW | 26 | 950,000$ | 950,000$ | 950,000$ | ![]() | |||||
Michael Stone ![]() | D | 31 | 1,000,000$ | 1,000,000$ | UFA | ||||||
Nick Bjugstad ![]() | C/RW | 29 | 900,000$ | 900,000$ | UFA | ||||||
Nick Paul ![]() | C/LW/RW | 27 | 1,000,000$ | 1,000,000$ | 1,700,000$ | 1,700,000$ | 1,700,000$ | UFA | |||
Nikita Scherbak ![]() | LW/RW | 26 | 700,000$ | 700,000$ | ![]() | ||||||
Nolan Stevens ![]() | C/LW | 25 | 700,000$ | 700,000$ | 700,000$ | ![]() | |||||
Ostap Safin ![]() | LW/RW | 23 | 775,000$ | 775,000$ | RFA | ||||||
Paul Cotter ![]() | C | 22 | 760,000$ | 760,000$ | 760,000$ | RFA | |||||
Peetro Seppala ![]() | D | 21 | 855,000$ | 855,000$ | 855,000$ | 855,000$ | RFA | ||||
Robin Salo ![]() | D | 23 | 842,500$ | 842,500$ | RFA | ||||||
Scott Wedgewood ![]() | G | 29 | 700,000$ | 700,000$ | 700,000$ | UFA | |||||
Simon Johansson ![]() | D | 22 | 855,000$ | 855,000$ | 855,000$ | 855,000$ | ![]() | ||||
T.J. Tynan ![]() | C | 30 | 900,000$ | 900,000$ | 900,000$ | UFA | |||||
Ty Dellandrea ![]() | C/RW | 21 | 894,167$ | 894,167$ | RFA | ||||||
Vladislav Kolyachonok ![]() | D | 20 | 800,000$ | 800,000$ | 800,000$ | RFA | |||||
Wade Allison ![]() | RW | 24 | 925,000$ | 925,000$ | RFA | ||||||
Will Cranley ![]() | G | 20 | 700,000$ | 700,000$ | 700,000$ | 700,000$ | 700,000$ | RFA |
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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 | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 12 | 17 | -5 | 2 | 0.200 | 12 | 20 | 32 | 0 | 0 | 4 | 3 | 5 | 0 | 168 | 46 | 48 | 66 | 8 | 154 | 56 | 40 | 117 | 17 | 1 | 5.88% | 19 | 6 | 68.42% | 0 | 90 | 181 | 49.72% | 93 | 176 | 52.84% | 38 | 74 | 51.35% | 127 | 88 | 124 | 38 | 65 | 33 | 50.0% | 7.1% | 89.0% | 96.1 | Unlucky | |
_Vs Division | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 12 | 17 | -5 | 2 | 0.200 | 12 | 20 | 32 | 0 | 0 | 4 | 3 | 5 | 0 | 168 | 46 | 48 | 66 | 8 | 154 | 56 | 40 | 117 | 17 | 1 | 5.88% | 19 | 6 | 68.42% | 0 | 90 | 181 | 49.72% | 93 | 176 | 52.84% | 38 | 74 | 51.35% | 127 | 88 | 124 | 38 | 65 | 33 | 50.0% | 7.1% | 89.0% | 96.1 | Unlucky | |
_Vs Conference | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 12 | 17 | -5 | 2 | 0.200 | 12 | 20 | 32 | 0 | 0 | 4 | 3 | 5 | 0 | 168 | 46 | 48 | 66 | 8 | 154 | 56 | 40 | 117 | 17 | 1 | 5.88% | 19 | 6 | 68.42% | 0 | 90 | 181 | 49.72% | 93 | 176 | 52.84% | 38 | 74 | 51.35% | 127 | 88 | 124 | 38 | 65 | 33 | 50.0% | 7.1% | 89.0% | 96.1 | Unlucky | |
_Since Last GM Reset | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 12 | 17 | -5 | 2 | 0.200 | 12 | 20 | 32 | 0 | 0 | 4 | 3 | 5 | 0 | 168 | 46 | 48 | 66 | 8 | 154 | 56 | 40 | 117 | 17 | 1 | 5.88% | 19 | 6 | 68.42% | 0 | 90 | 181 | 49.72% | 93 | 176 | 52.84% | 38 | 74 | 51.35% | 127 | 88 | 124 | 38 | 65 | 33 | 50.0% | 7.1% | 89.0% | 96.1 | Unlucky | |
Total | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 12 | 17 | -5 | 2 | 0.200 | 12 | 20 | 32 | 0 | 0 | 4 | 3 | 5 | 0 | 168 | 46 | 48 | 66 | 8 | 154 | 56 | 40 | 117 | 17 | 1 | 5.88% | 19 | 6 | 68.42% | 0 | 90 | 181 | 49.72% | 93 | 176 | 52.84% | 38 | 74 | 51.35% | 127 | 88 | 124 | 38 | 65 | 33 | 50.0% | 7.1% | 89.0% | 96.1 | Unlucky |
Puck Time | |
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Offensive Zone | 25 |
Neutral Zone | 13 |
Defensive Zone | 24 |
Puck Time | |
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Offensive Zone Start | 181 |
Neutral Zone Start | 74 |
Defensive Zone Start | 176 |
Puck Time | |
---|---|
With Puck | 31 |
Without Puck | 31 |
Faceoffs | |
---|---|
Faceoffs Won | 221 |
Faceoffs Lost | 210 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 9.2 | 9.57 |
2nd Period | 18.8 | 20.31 |
3rd Period | 32.0 | 30.68 |
Overtime | 33.6 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.8 | 0.64 |
2nd Period | 1.4 | 1.65 |
3rd Period | 2.4 | 2.67 |
Overtime | 2.4 | 2.83 |
Even Strenght Goal | 11 |
---|---|
PP Goal | 1 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 1 | 0 |
Lost | 2 | 2 |
Overtime Lost | 0 | 0 |
PP Attempt | 17 |
---|---|
PP Goal | 1 |
PK Attempt | 19 |
PK Goal Against | 6 |
Home | |
---|---|
Shots For | 33.6 |
Shots Against | 30.8 |
Goals For | 2.4 |
Goals Against | 3.4 |
Hits | 23.4 |
Shots Blocked | 11.2 |
Pim | 8.0 |
Date | Matchup | Result | Detail | ||
---|---|---|---|---|---|
2022-04-14 | @ | Islanders3,Flyers2 | RECAP | ||
2022-04-16 | @ | Islanders3,Flyers4 | RECAP | ||
2022-04-18 | @ | Flyers2,Islanders3 (OT) | RECAP | ||
2022-04-20 | @ | Flyers2,Islanders5 | RECAP | ||
2022-04-22 | @ | Islanders3,Flyers2 | RECAP |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
73,842,143$ | 0$ | 0$ | 7,657,857$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | Wells Fargo Center | |
City | Philadelphia | ||
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 | 18000 | 15000 | 6000 | 12000 | 3000 |
Attendance PCT | 100.00% | 100.00% | 100.00% | 100.00% | 100.00% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
38 | 18000 - 100.00% | 1,587,500$ | 4,762,500$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
73,842,143$ | 73,842,143$ | 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$ | 12 | 0$ | 0$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
0$ | 73,842,143$ | 35,566,447$ | 35,566,447$ |
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Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
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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 |
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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. |
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10 | text | Any text entered in the filter will match text found within the column |
Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
---|---|---|---|---|---|
Aidan Hreschuk | 2021 | 82 | |||
Brayden Peters | 2020 | 187 | |||
Bryce Montgomery | 2021 | 172 | |||
Chase McLane | |||||
Dru Krebs | 2021 | 162 | |||
Garin Bjorklund | 2020 | 145 | |||
Henry Thrun | 2019 | 104 | |||
Jake Boltmann | |||||
Joni Jurmo | 2020 | 63 | |||
Juho Markkanen | 2020 | 181 | |||
Justin Janicke | 2021 | 183 | |||
Kasper Puutio | 2020 | 119 | |||
Kirill Gerasimyuk | 2021 | 119 | |||
Logan Neaton | 2019 | 166 | |||
Marcus Davidsson | 6.0 - 5.0 | ||||
Matvey Petrov | 2021 | 151 | |||
Maxim Cajkovic | 2019 | 73 | 6.5 - 5.0 | ||
Olof Lindbom | 7.5 - 4.5 | ||||
Ryan Ufko | 2021 | 87 | |||
Ty Smilanic | 2020 | 57 | |||
Yaroslav Likhachyov | 2019 | 197 |
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