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Full Scoreboard ยป |
Florida Panthers 43-27-10, 96pts · 3rd in Eastern Conference |
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 | # | POS | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | C | 100.00 | 42 | 8 | 99 | 92 | 81 | 97 | 98 | 94 | 96 | 99 | 93 | 74 | 85 | 69 | 70 | 86 | 75 | 83 | 24 | 5,900,000$/2yrs | |||
![]() | 0 | C | 100.00 | 54 | 13 | 88 | 87 | 76 | 99 | 98 | 92 | 86 | 92 | 79 | 59 | 69 | 80 | 86 | 82 | 77 | 79 | 32 | 9,200,000$/3yrs | |||
![]() | 0 | C/LW | 100.00 | 53 | 10 | 92 | 87 | 71 | 96 | 89 | 86 | 77 | 88 | 88 | 68 | 61 | 73 | 73 | 81 | 77 | 78 | 27 | 6,000,000$/5yrs | |||
![]() | 0 | LW | 100.00 | 61 | 6 | 85 | 88 | 68 | 86 | 94 | 87 | 30 | 84 | 95 | 69 | 80 | 61 | 63 | 85 | 77 | 77 | 23 | 7,142,857$/4yrs | |||
![]() | 0 | LW | 100.00 | 46 | 10 | 88 | 91 | 73 | 91 | 99 | 88 | 65 | 76 | 95 | 45 | 41 | 78 | 78 | 78 | 77 | 75 | 28 | 9,000,000$/3yrs | |||
![]() | 0 | LW/RW | 100.00 | 61 | 24 | 84 | 84 | 73 | 84 | 99 | 72 | 30 | 72 | 73 | 69 | 38 | 72 | 76 | 76 | 77 | 71 | 30 | 4,450,000$/3yrs | |||
![]() | 0 | RW | 100.00 | 47 | 19 | 93 | 85 | 73 | 92 | 99 | 78 | 39 | 70 | 69 | 62 | 35 | 72 | 75 | 69 | 77 | 71 | 28 | 2,500,000$/4yrs | |||
![]() | 0 | C | 100.00 | 41 | 8 | 94 | 81 | 73 | 85 | 92 | 79 | 81 | 82 | 76 | 48 | 25 | 62 | 62 | 73 | 77 | 70 | 23 | 2,800,000$/4yrs | |||
![]() | 0 | C | 100.00 | 53 | 10 | 99 | 88 | 73 | 78 | 67 | 68 | 94 | 69 | 60 | 52 | 25 | 63 | 63 | 65 | 77 | 65 | 24 | 800,000$/4yrs | |||
![]() | 0 | LW/RW | 100.00 | 52 | 34 | 76 | 72 | 80 | 83 | 68 | 70 | 25 | 59 | 69 | 35 | 63 | 85 | 91 | 67 | 66 | 63 | 35 | 685,000$/3yrs | |||
![]() | 0 | LW/RW | 100.00 | 55 | 34 | 90 | 72 | 68 | 91 | 84 | 64 | 49 | 65 | 59 | 46 | 57 | 52 | 52 | 63 | 77 | 62 | 27 | 700,000$/2yrs | |||
![]() | 0 | C/LW | 100.00 | 55 | 10 | 96 | 75 | 70 | 76 | 44 | 59 | 31 | 58 | 54 | 39 | 25 | 63 | 64 | 59 | 66 | 57 | 24 | 950,000$/4yrs | |||
![]() | 0 | D | 99.00 | 70 | 15 | 81 | 89 | 75 | 99 | 99 | 93 | 25 | 68 | 60 | 76 | 50 | 74 | 75 | 73 | 76 | 77 | 29 | 8,250,000$/3yrs | |||
![]() | 0 | D | 99.00 | 63 | 12 | 96 | 87 | 77 | 92 | 88 | 65 | 25 | 57 | 47 | 90 | 25 | 67 | 70 | 64 | 75 | 74 | 25 | 4,083,333$/2yrs | |||
![]() | 0 | D | 100.00 | 51 | 9 | 91 | 84 | 72 | 96 | 95 | 63 | 25 | 52 | 47 | 89 | 25 | 73 | 75 | 62 | 77 | 73 | 27 | 4,166,667$/5yrs | |||
![]() | 0 | D | 100.00 | 56 | 11 | 93 | 87 | 72 | 99 | 87 | 71 | 25 | 70 | 49 | 84 | 25 | 62 | 63 | 67 | 77 | 73 | 25 | 1,000,000$/3yrs | |||
![]() | 0 | D | 100.00 | 43 | 8 | 94 | 85 | 74 | 93 | 91 | 82 | 25 | 68 | 60 | 77 | 75 | 62 | 64 | 65 | 77 | 72 | 25 | 5,200,000$/3yrs | |||
![]() | 0 | D | 100.00 | 65 | 24 | 87 | 83 | 75 | 80 | 89 | 64 | 25 | 52 | 48 | 79 | 25 | 63 | 63 | 59 | 77 | 70 | 26 | 2,200,000$/4yrs | |||
Scratches | ||||||||||||||||||||||||||
TEAM AVERAGE | 99.89 | 54 | 15 | 90 | 84 | 74 | 90 | 88 | 76 | 47 | 71 | 68 | 65 | 46 | 68 | 70 | 71 | 76 | 72 |
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 | 82 | 90 | 99 | 84 | 82 | 80 | 83 | 80 | 81 | 81 | 89 | 64 | 64 | 79 | 77 | 79 | 30 | 5,000,000$/4yrs |
![]() | 0 | 100.00 | 83 | 80 | 75 | 65 | 78 | 87 | 91 | 95 | 90 | 86 | 86 | 43 | 43 | 92 | 77 | 77 | 25 | 925,000$/2yrs |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 100.00 | 83 | 85 | 87 | 75 | 80 | 84 | 87 | 88 | 86 | 84 | 88 | 54 | 54 | 86 | 77 | 78 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Rick Tocchet | 88 | 89 | 62 | 93 | 74 | 51 | 74 | CAN | 54 | 4 | 2,500,000$ |
General Manager | Shane Powell |
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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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Aleksander Barkov | 0 | C | 77 | 33 | 64 | 97 | 9 | 0 | 0 | 18 | 299 | 106 | 206 | 11.04% | 34 | 20.06 | 7 | 18 | 25 | 202 | 0 | 0 | 0 | 30 | 8 | 1 | 55.85% | 2025 | 80 | 31 | 0 | 2 | 1.26 | 1 | 6 | |
2 | Jeff Skinner | 0 | LW | 80 | 36 | 34 | 70 | 10 | 2 | 0 | 52 | 305 | 88 | 197 | 11.80% | 32 | 16.99 | 15 | 11 | 26 | 212 | 0 | 0 | 0 | 2 | 7 | 1 | 48.08% | 52 | 78 | 22 | 0 | 0 | 1.03 | 1 | 1 | |
3 | Kyle Connor | 0 | LW | 80 | 36 | 31 | 67 | 4 | 14 | 0 | 110 | 332 | 90 | 183 | 10.84% | 35 | 19.23 | 2 | 8 | 10 | 201 | 0 | 0 | 0 | 0 | 8 | 2 | 28.70% | 108 | 92 | 37 | 0 | 2 | 0.87 | 2 | 7 | |
4 | Nicklas Backstrom | 0 | C | 80 | 31 | 33 | 64 | 5 | 12 | 0 | 93 | 283 | 72 | 152 | 10.95% | 35 | 17.44 | 9 | 7 | 16 | 206 | 0 | 1 | 1 | 29 | 4 | 5 | 53.31% | 1208 | 48 | 19 | 1 | 0 | 0.92 | 1 | 3 | |
5 | Ryan Nugent-Hopkins | 0 | C/LW | 80 | 23 | 35 | 58 | -10 | 0 | 0 | 80 | 256 | 78 | 184 | 8.98% | 34 | 16.50 | 5 | 8 | 13 | 207 | 0 | 0 | 0 | 34 | 1 | 1 | 51.43% | 838 | 66 | 33 | 0 | 0 | 0.88 | 0 | 2 | |
6 | Oliver Ekman-Larsson | 0 | D | 80 | 4 | 33 | 37 | -19 | 16 | 0 | 199 | 183 | 76 | 94 | 2.19% | 118 | 24.62 | 3 | 8 | 11 | 211 | 0 | 0 | 0 | 31 | 1 | 0 | 0.00% | 0 | 34 | 61 | 0 | 0 | 0.38 | 0 | 0 | |
7 | Dylan Strome | 0 | C | 80 | 15 | 21 | 36 | -7 | 4 | 0 | 21 | 230 | 88 | 120 | 6.52% | 9 | 12.95 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 55.32% | 47 | 42 | 17 | 0 | 0 | 0.70 | 0 | 0 | |
8 | Alex Killorn | 0 | LW/RW | 80 | 12 | 22 | 34 | 8 | 16 | 0 | 143 | 95 | 38 | 64 | 12.63% | 27 | 19.51 | 3 | 9 | 12 | 209 | 1 | 0 | 1 | 28 | 1 | 0 | 28.70% | 108 | 15 | 26 | 0 | 0 | 0.44 | 0 | 0 | |
9 | Olli Maatta | 0 | D | 80 | 3 | 23 | 26 | -16 | 4 | 0 | 115 | 121 | 41 | 46 | 2.48% | 113 | 24.61 | 0 | 4 | 4 | 211 | 0 | 0 | 0 | 35 | 1 | 0 | 0.00% | 0 | 7 | 72 | 0 | 0 | 0.26 | 0 | 0 | |
10 | Christian Dvorak | 0 | C | 80 | 6 | 18 | 24 | -12 | 0 | 0 | 42 | 203 | 71 | 135 | 2.96% | 18 | 10.04 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 50.87% | 401 | 65 | 12 | 0 | 0 | 0.60 | 0 | 0 | |
11 | Shea Theodore | 0 | D | 80 | 6 | 18 | 24 | 11 | 2 | 0 | 30 | 117 | 57 | 49 | 5.13% | 105 | 21.68 | 1 | 5 | 6 | 210 | 0 | 0 | 0 | 33 | 1 | 1 | 0.00% | 0 | 27 | 66 | 0 | 0 | 0.28 | 1 | 5 | |
12 | Jonas Brodin | 0 | D | 80 | 6 | 14 | 20 | 11 | 2 | 0 | 83 | 86 | 34 | 35 | 6.98% | 114 | 21.73 | 3 | 5 | 8 | 210 | 0 | 0 | 0 | 31 | 2 | 0 | 0.00% | 0 | 12 | 53 | 0 | 0 | 0.23 | 0 | 0 | |
13 | Tyler Toffoli | 0 | RW | 80 | 8 | 7 | 15 | 12 | 2 | 0 | 37 | 79 | 30 | 42 | 10.13% | 43 | 13.98 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2 | 0 | 18.75% | 48 | 20 | 27 | 0 | 0 | 0.27 | 0 | 0 | |
14 | Josh Morrissey | 0 | D | 80 | 1 | 13 | 14 | 7 | 0 | 0 | 51 | 68 | 22 | 25 | 1.47% | 68 | 13.92 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 3 | 0 | 0 | 0.00% | 0 | 10 | 43 | 0 | 0 | 0.25 | 0 | 0 | |
15 | Matt Benning | 0 | D | 80 | 0 | 12 | 12 | 5 | 0 | 0 | 99 | 44 | 23 | 17 | 0.00% | 43 | 13.74 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 1 | 45 | 0 | 0 | 0.22 | 0 | 0 | |
16 | Seth Griffith | 0 | LW/RW | 80 | 6 | 5 | 11 | -6 | 6 | 0 | 84 | 55 | 10 | 32 | 10.91% | 22 | 13.40 | 1 | 0 | 1 | 12 | 0 | 0 | 0 | 7 | 1 | 1 | 53.85% | 39 | 5 | 14 | 0 | 0 | 0.21 | 0 | 1 | |
17 | Corey Perry | 0 | LW/RW | 35 | 5 | 2 | 7 | -5 | 0 | 0 | 25 | 47 | 18 | 24 | 10.64% | 3 | 10.31 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 40.00% | 10 | 13 | 3 | 0 | 0 | 0.39 | 1 | 1 | |
18 | Robby Fabbri | 0 | C/LW | 80 | 5 | 2 | 7 | -11 | 2 | 0 | 59 | 41 | 13 | 22 | 12.20% | 16 | 10.10 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 27.27% | 22 | 2 | 4 | 0 | 0 | 0.17 | 0 | 0 | |
Team Total or Average | 1392 | 236 | 387 | 623 | -4 | 82 | 0 | 1341 | 2844 | 955 | 1627 | 8.30% | 869 | 16.91 | 49 | 83 | 132 | 2106 | 1 | 1 | 2 | 272 | 41 | 16 | 52.24% | 4906 | 617 | 585 | 1 | 4 | 0.53 | 7 | 26 |
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 | Jacob Markstrom | Panthers | 50 | 26 | 16 | 7 | 0.925 | 2.58 | 2932 | 0 | 0 | 126 | 1672 | 847 | 3 | 1 | 0.571 | 14 | 49 | 31 | 6 | 7 | 5 |
2 | Ilya Sorokin | Panthers | 33 | 17 | 11 | 3 | 0.927 | 2.39 | 1905 | 4 | 0 | 76 | 1044 | 495 | 1 | 1 | 0.692 | 13 | 31 | 49 | 4 | 4 | 1 |
Team Total or Average | 83 | 43 | 27 | 10 | 0.926 | 2.51 | 4837 | 4 | 0 | 202 | 2716 | 1342 | 4 | 2 | 0.630 | 27 | 80 | 80 | 10 | 11 | 6 |
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 | 2 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 5 | 5 | 0 | 2 | 0.500 | 5 | 6 | 11 | 0 | 0 | 3 | 0 | 1 | 1 | 76 | 23 | 33 | 19 | 1 | 72 | 22 | 2 | 36 | 2 | 0 | 0.00% | 1 | 1 | 0.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 50 | 34 | 39 | 14 | 30 | 16 | 55.6% | 6.6% | 93.1% | 99.6 | DULL | |
2 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 6 | 6 | 0 | 2 | 0.500 | 6 | 9 | 15 | 0 | 0 | 3 | 1 | 2 | 0 | 80 | 31 | 24 | 25 | 0 | 71 | 26 | 2 | 25 | 0 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 47 | 32 | 40 | 15 | 31 | 15 | 50.0% | 7.5% | 91.5% | 99.0 | DULL | |
3 | 3 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 7 | 8 | -1 | 2 | 0.333 | 7 | 12 | 19 | 0 | 0 | 1 | 2 | 4 | 0 | 106 | 36 | 34 | 36 | 0 | 101 | 24 | 10 | 48 | 14 | 1 | 7.14% | 5 | 1 | 80.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 70 | 44 | 59 | 25 | 49 | 26 | 46.2% | 6.6% | 92.1% | 98.7 | DULL | |
4 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 5 | 3 | 2 | 2 | 0.500 | 5 | 10 | 15 | 0 | 0 | 1 | 1 | 3 | 0 | 72 | 18 | 25 | 29 | 0 | 64 | 18 | 2 | 29 | 6 | 2 | 33.33% | 1 | 0 | 100.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 46 | 28 | 41 | 16 | 32 | 16 | 50.0% | 6.9% | 95.3% | 102.3 | DULL | |
5 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 6 | 8 | -2 | 2 | 0.500 | 6 | 8 | 14 | 0 | 0 | 0 | 2 | 4 | 0 | 72 | 26 | 24 | 22 | 0 | 62 | 19 | 4 | 46 | 8 | 2 | 25.00% | 2 | 1 | 50.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 49 | 31 | 37 | 15 | 33 | 17 | 36.4% | 8.3% | 87.1% | 95.4 | Unlucky | |
6 | 2 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 8 | 5 | 3 | 4 | 1.000 | 8 | 12 | 20 | 0 | 0 | 2 | 3 | 2 | 1 | 73 | 23 | 32 | 17 | 1 | 61 | 25 | 0 | 40 | 7 | 3 | 42.86% | 0 | 0 | 0.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 48 | 31 | 40 | 15 | 31 | 17 | 50.0% | 11.0% | 91.8% | 102.8 | LUCKY | |
7 | 2 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 5 | 6 | -1 | 2 | 0.500 | 5 | 8 | 13 | 0 | 0 | 0 | 2 | 2 | 1 | 75 | 37 | 12 | 24 | 8 | 68 | 21 | 2 | 35 | 4 | 1 | 25.00% | 1 | 0 | 100.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 50 | 33 | 42 | 14 | 32 | 17 | 40.0% | 6.7% | 91.2% | 97.8 | DULL | |
8 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 3 | 6 | 4 | 1.000 | 9 | 15 | 24 | 0 | 0 | 4 | 1 | 4 | 0 | 84 | 27 | 28 | 29 | 0 | 73 | 25 | 0 | 35 | 3 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 43 | 28 | 44 | 15 | 32 | 15 | 75.0% | 10.7% | 95.9% | 106.6 | LUCKY | |
9 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 4 | 5 | 4 | 1.000 | 9 | 16 | 25 | 0 | 0 | 2 | 4 | 3 | 0 | 67 | 24 | 25 | 18 | 0 | 57 | 21 | 4 | 30 | 13 | 6 | 46.15% | 2 | 1 | 50.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 45 | 26 | 41 | 17 | 33 | 18 | 50.0% | 13.4% | 93.0% | 106.4 | LUCKY | |
10 | 4 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 8 | 9 | -1 | 4 | 0.500 | 8 | 12 | 20 | 0 | 0 | 1 | 3 | 4 | 0 | 138 | 41 | 48 | 49 | 0 | 124 | 54 | 2 | 73 | 18 | 1 | 5.56% | 1 | 1 | 0.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 91 | 54 | 80 | 32 | 68 | 37 | 46.7% | 5.8% | 92.7% | 98.5 | DULL | |
11 | 2 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 3 | 5 | -2 | 1 | 0.250 | 3 | 4 | 7 | 0 | 0 | 2 | 1 | 0 | 0 | 69 | 29 | 25 | 14 | 1 | 62 | 23 | 0 | 42 | 9 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 47 | 29 | 40 | 17 | 34 | 18 | 37.5% | 4.3% | 91.9% | 96.3 | DULL | |
12 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 6 | 10 | -4 | 0 | 0.000 | 6 | 9 | 15 | 1 | 0 | 1 | 4 | 1 | 0 | 88 | 28 | 30 | 30 | 0 | 72 | 22 | 4 | 29 | 1 | 0 | 0.00% | 2 | 1 | 50.00% | 1 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 48 | 31 | 39 | 15 | 32 | 16 | 40.0% | 6.8% | 86.1% | 92.9 | Unlucky | |
13 | 4 | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 12 | 8 | 4 | 6 | 0.750 | 12 | 19 | 31 | 0 | 0 | 2 | 6 | 4 | 0 | 139 | 43 | 46 | 50 | 0 | 123 | 34 | 2 | 80 | 17 | 4 | 23.53% | 1 | 0 | 100.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 93 | 59 | 79 | 32 | 66 | 35 | 50.0% | 8.6% | 93.5% | 102.1 | DULL | |
14 | 2 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 4 | 7 | -3 | 1 | 0.250 | 4 | 7 | 11 | 0 | 0 | 0 | 0 | 4 | 0 | 70 | 24 | 14 | 31 | 1 | 78 | 23 | 2 | 34 | 5 | 0 | 0.00% | 1 | 1 | 0.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 45 | 28 | 40 | 16 | 34 | 18 | 40.0% | 5.7% | 91.0% | 96.7 | Unlucky | |
15 | 3 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 7 | 8 | -1 | 3 | 0.500 | 7 | 10 | 17 | 0 | 0 | 2 | 3 | 2 | 1 | 104 | 40 | 24 | 38 | 5 | 112 | 22 | 6 | 50 | 6 | 2 | 33.33% | 3 | 0 | 100.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 69 | 42 | 63 | 25 | 51 | 26 | 38.5% | 6.7% | 92.9% | 99.6 | DULL | |
16 | 4 | 2 | 1 | 0 | 1 | 0 | 0 | 0 | 17 | 14 | 3 | 6 | 0.750 | 17 | 31 | 48 | 0 | 0 | 4 | 4 | 8 | 1 | 147 | 43 | 41 | 61 | 2 | 145 | 46 | 8 | 66 | 8 | 2 | 25.00% | 4 | 3 | 25.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 90 | 56 | 82 | 31 | 67 | 35 | 57.7% | 11.6% | 90.3% | 101.9 | FUN | |
17 | 8 | 4 | 3 | 0 | 1 | 0 | 0 | 0 | 23 | 16 | 7 | 10 | 0.625 | 23 | 42 | 65 | 0 | 0 | 6 | 7 | 9 | 1 | 275 | 82 | 107 | 84 | 2 | 272 | 84 | 8 | 148 | 27 | 8 | 29.63% | 4 | 0 | 100.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 183 | 114 | 163 | 62 | 133 | 71 | 48.4% | 8.4% | 94.1% | 102.5 | DULL | |
18 | 4 | 2 | 1 | 0 | 0 | 0 | 1 | 0 | 8 | 9 | -1 | 6 | 0.750 | 8 | 10 | 18 | 0 | 0 | 2 | 2 | 3 | 2 | 148 | 42 | 42 | 62 | 4 | 146 | 48 | 6 | 63 | 7 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 96 | 63 | 82 | 31 | 66 | 33 | 47.1% | 5.4% | 93.8% | 99.2 | DULL | |
19 | 4 | 2 | 0 | 0 | 0 | 2 | 0 | 0 | 15 | 14 | 1 | 6 | 0.750 | 15 | 24 | 39 | 0 | 0 | 3 | 4 | 8 | 0 | 134 | 37 | 49 | 48 | 0 | 141 | 40 | 4 | 57 | 15 | 5 | 33.33% | 2 | 1 | 50.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 87 | 55 | 86 | 33 | 67 | 35 | 43.5% | 11.2% | 90.1% | 101.3 | FUN | |
20 | 6 | 4 | 2 | 0 | 0 | 0 | 0 | 0 | 17 | 13 | 4 | 8 | 0.667 | 17 | 29 | 46 | 0 | 0 | 6 | 2 | 9 | 0 | 211 | 80 | 54 | 77 | 0 | 206 | 56 | 2 | 113 | 21 | 5 | 23.81% | 1 | 0 | 100.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 141 | 90 | 121 | 47 | 97 | 51 | 48.0% | 8.1% | 93.7% | 101.7 | DULL | |
21 | 6 | 1 | 2 | 0 | 1 | 1 | 0 | 1 | 19 | 19 | 0 | 6 | 0.500 | 19 | 33 | 52 | 1 | 0 | 4 | 6 | 8 | 3 | 211 | 58 | 73 | 79 | 4 | 216 | 71 | 4 | 100 | 15 | 3 | 20.00% | 2 | 1 | 50.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 136 | 85 | 129 | 49 | 100 | 52 | 47.1% | 9.0% | 91.2% | 100.2 | LUCKY | |
22 | 6 | 2 | 2 | 0 | 0 | 0 | 0 | 2 | 21 | 18 | 3 | 6 | 0.500 | 21 | 32 | 53 | 0 | 0 | 5 | 8 | 8 | 1 | 207 | 63 | 86 | 56 | 10 | 196 | 83 | 8 | 100 | 32 | 2 | 6.25% | 4 | 2 | 50.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 140 | 84 | 124 | 52 | 105 | 57 | 54.3% | 10.1% | 90.8% | 101.0 | FUN | |
23 | 6 | 3 | 1 | 0 | 1 | 0 | 0 | 1 | 20 | 11 | 9 | 9 | 0.750 | 20 | 30 | 50 | 0 | 0 | 4 | 8 | 7 | 1 | 219 | 67 | 65 | 81 | 10 | 196 | 74 | 8 | 92 | 20 | 3 | 15.00% | 4 | 0 | 100.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 143 | 91 | 123 | 48 | 98 | 52 | 60.7% | 9.1% | 94.4% | 103.5 | LUCKY | |
_Vs Division | 32 | 14 | 10 | 0 | 3 | 1 | 0 | 4 | 100 | 77 | 23 | 39 | 0.609 | 100 | 166 | 266 | 1 | 0 | 25 | 31 | 41 | 6 | 1123 | 350 | 385 | 377 | 26 | 1086 | 368 | 30 | 553 | 115 | 21 | 18.26% | 15 | 3 | 80.00% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 745 | 465 | 662 | 260 | 535 | 285 | 51.6% | 8.9% | 92.9% | 101.8 | Unlucky | |
_Vs Conference | 54 | 25 | 16 | 0 | 4 | 4 | 1 | 4 | 164 | 138 | 26 | 68 | 0.630 | 164 | 269 | 433 | 1 | 0 | 37 | 50 | 72 | 9 | 1899 | 580 | 625 | 678 | 33 | 1843 | 613 | 54 | 926 | 185 | 33 | 17.84% | 26 | 9 | 65.38% | 0 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 1250 | 783 | 1114 | 438 | 906 | 480 | 50.4% | 8.6% | 92.5% | 101.1 | DULL | |
_Since Last GM Reset | 80 | 35 | 27 | 0 | 6 | 5 | 2 | 5 | 240 | 209 | 31 | 96 | 0.600 | 240 | 388 | 628 | 2 | 0 | 58 | 74 | 100 | 13 | 2865 | 922 | 941 | 979 | 49 | 2718 | 881 | 90 | 1371 | 258 | 50 | 19.38% | 44 | 14 | 68.18% | 1 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 1868 | 1177 | 1644 | 648 | 1332 | 702 | 49.4% | 8.4% | 92.3% | 100.7 | DULL | |
Total | 80 | 35 | 27 | 0 | 6 | 5 | 2 | 5 | 240 | 209 | 31 | 96 | 0.600 | 240 | 388 | 628 | 2 | 0 | 58 | 74 | 100 | 13 | 2865 | 922 | 941 | 979 | 49 | 2718 | 881 | 90 | 1371 | 258 | 50 | 19.38% | 44 | 14 | 68.18% | 1 | 1072 | 2044 | 52.45% | 929 | 1750 | 53.09% | 589 | 1160 | 50.78% | 1868 | 1177 | 1644 | 648 | 1332 | 702 | 49.4% | 8.4% | 92.3% | 100.7 | DULL |
Puck Time | |
---|---|
Offensive Zone | 23 |
Neutral Zone | 16 |
Defensive Zone | 20 |
Puck Time | |
---|---|
Offensive Zone Start | 2044 |
Neutral Zone Start | 1160 |
Defensive Zone Start | 1750 |
Puck Time | |
---|---|
With Puck | 31 |
Without Puck | 28 |
Faceoffs | |
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Faceoffs Won | 2590 |
Faceoffs Lost | 2364 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 11.5 | 9.57 |
2nd Period | 23.3 | 20.31 |
3rd Period | 35.5 | 30.68 |
Overtime | 36.1 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.7 | 0.64 |
2nd Period | 1.7 | 1.65 |
3rd Period | 2.9 | 2.67 |
Overtime | 3.1 | 2.83 |
Even Strenght Goal | 187 |
---|---|
PP Goal | 50 |
PK Goal | 1 |
Empty Net Goal | 2 |
Home | Away | |
---|---|---|
Win | 24 | 19 |
Lost | 10 | 17 |
Overtime Lost | 5 | 5 |
PP Attempt | 258 |
---|---|
PP Goal | 50 |
PK Attempt | 44 |
PK Goal Against | 14 |
Home | |
---|---|
Shots For | 35.8 |
Shots Against | 34.0 |
Goals For | 3.0 |
Goals Against | 2.6 |
Hits | 17.1 |
Shots Blocked | 11.0 |
Pim | 1.1 |
Projected Total Cap Hit | 80,952,857$ |
Projected Cap Space | 547,143$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 76,596,357$ |
Players In Salary Cap | 20 |
LTIR Players | 0 |
Player Name | Pos | Age | Cap Hit | 2012-2013 | 2013-2014 | 2014-2015 | 2015-2016 | 2016-2017 | 2017-2018 | 2018-2019 | 2019-2020 |
---|---|---|---|---|---|---|---|---|---|---|---|
Aleksander Barkov | C | 24 | 5,900,000$ | 5,900,000$ | 5,900,000$ | ||||||
Alex Killorn | LW/RW | 30 | 4,450,000$ | 4,450,000$ | 4,450,000$ | 4,450,000$ | |||||
Christian Dvorak ![]() | C | 24 | 800,000$ | 800,000$ | 800,000$ | 800,000$ | 800,000$ | ||||
Corey Perry ![]() | LW/RW | 35 | 685,000$ | 685,000$ | 685,000$ | 685,000$ | |||||
Dylan Strome ![]() | C | 23 | 2,800,000$ | 2,800,000$ | 2,800,000$ | 2,800,000$ | 2,800,000$ | ||||
Ilya Sorokin ![]() | D | 25 | 925,000$ | 925,000$ | 925,000$ | ||||||
Jacob Markstrom ![]() | D | 30 | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | 5,000,000$ | ||||
Jeff Skinner | LW | 28 | 9,000,000$ | 9,000,000$ | 9,000,000$ | 9,000,000$ | |||||
Jonas Brodin ![]() | D | 27 | 4,166,667$ | 4,166,667$ | 4,500,000$ | 4,500,000$ | 4,500,000$ | 4,500,000$ | |||
Josh Morrissey ![]() | D | 25 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | |||||
Kyle Connor ![]() | LW | 23 | 7,142,857$ | 7,142,857$ | 7,142,857$ | 7,142,857$ | 7,142,857$ | ||||
Matt Benning ![]() | D | 26 | 2,200,000$ | 2,200,000$ | 2,200,000$ | 2,200,000$ | 2,200,000$ | ||||
Nicklas Backstrom | C | 32 | 9,200,000$ | 9,200,000$ | 9,200,000$ | 9,200,000$ | |||||
Oliver Ekman-Larsson | D | 29 | 8,250,000$ | 8,250,000$ | 8,250,000$ | 8,250,000$ | |||||
Olli Maatta ![]() | D | 25 | 4,083,333$ | 4,083,333$ | 4,083,333$ | ||||||
Robby Fabbri ![]() | C/LW | 24 | 950,000$ | 950,000$ | 950,000$ | 950,000$ | 950,000$ | ||||
Ryan Nugent-Hopkins | C/LW | 27 | 6,000,000$ | 6,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ | |||
Seth Griffith ![]() | LW/RW | 27 | 700,000$ | 700,000$ | 700,000$ | ||||||
Shea Theodore | D | 25 | 5,200,000$ | 5,200,000$ | 5,200,000$ | 5,200,000$ | |||||
Tyler Toffoli ![]() | RW | 28 | 2,500,000$ | 2,500,000$ | 2,500,000$ | 2,500,000$ | 2,500,000$ |
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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 |
Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
---|---|---|---|---|---|
Alex Formenton | 1 | ||||
Dmitri Samaroukov | 1 | ||||
Ian Mitchell | 1 | ||||
Igor Chibrikov | 2 | 72 | |||
Joni Jurmo | 2 | 48 | |||
Martin Fehervary | 1 | ||||
Tyler Kleven | 2 | 24 | |||
Ville Ottavainen | 2 | 96 |
Date | Matchup | Result | Detail | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2020-08-18 | @ | Rangers1,Panthers4 | RECAP | |||||||||||
2020-08-19 | @ | Panthers3,Rangers2 (OT) | RECAP | |||||||||||
2020-08-21 | @ | Panthers1,Flyers4 | RECAP | |||||||||||
2020-08-23 | @ | Panthers3,Rangers1 | RECAP | |||||||||||
2020-08-25 | @ | Devils2,Panthers1 (SO) | RECAP | |||||||||||
2020-08-27 | @ | Flyers1,Panthers4 | RECAP | |||||||||||
2020-08-29 | @ | Panthers8,Devils2 | RECAP | |||||||||||
2020-08-31 | @ | Devils3,Panthers2 (SO) | RECAP | |||||||||||
2020-09-03 | @ | Blue Jackets1,Panthers4 | RECAP | |||||||||||
2020-09-05 | @ | Panthers2,Stars4 | RECAP | |||||||||||
2020-09-07 | @ | Panthers1,Lightning3 | RECAP | |||||||||||
2020-09-08 | @ | Panthers1,Sabres6 | RECAP | |||||||||||
2020-09-10 | @ | Lightning4,Panthers5 (OT) | RECAP | |||||||||||
2020-09-12 | @ | Red Wings3,Panthers2 (OT) | RECAP | |||||||||||
2020-09-15 | @ | Canadiens1,Panthers3 | RECAP | |||||||||||
2020-09-16 | @ | Panthers1,Senators3 | RECAP | |||||||||||
2020-09-19 | @ | Bruins1,Panthers3 | RECAP | |||||||||||
2020-09-20 | @ | Panthers2,Devils3 | RECAP | |||||||||||
2020-09-22 | @ | Lightning4,Panthers3 | RECAP | |||||||||||
2020-09-24 | @ | Panthers4,Avalanche3 (OT) | RECAP | |||||||||||
2020-09-26 | @ | Lightning4,Panthers3 (OT) | RECAP | |||||||||||
2020-09-28 | @ | Panthers4,Devils6 | RECAP | |||||||||||
2020-09-29 | @ | Sabres1,Panthers2 (SO) | RECAP | |||||||||||
2020-10-01 | @ | Panthers3,Senators4 (OT) | RECAP | |||||||||||
2020-10-03 | @ | Panthers3,Flames4 | RECAP | |||||||||||
2020-10-05 | @ | Panthers5,Wild2 | RECAP | |||||||||||
2020-10-07 | @ | Rangers3,Panthers1 | RECAP | |||||||||||
2020-10-10 | @ | Panthers5,Blues1 | RECAP | |||||||||||
2020-10-11 | @ | Coyotes2,Panthers1 | RECAP | |||||||||||
2020-10-13 | @ | Panthers4,Oilers2 | RECAP | |||||||||||
2020-10-15 | @ | Canucks1,Panthers4 | RECAP | |||||||||||
2020-10-17 | @ | Panthers4,Red Wings2 | RECAP | |||||||||||
2020-10-19 | @ | Blue Jackets2,Panthers3 (OT) | RECAP | |||||||||||
2020-10-21 | @ | Red Wings4,Panthers5 | RECAP | |||||||||||
2020-10-23 | @ | Panthers2,Blue Jackets3 (SO) | RECAP | |||||||||||
2020-10-25 | @ | Ducks6,Panthers4 | RECAP | |||||||||||
2020-10-28 | @ | Sabres1,Panthers2 | RECAP | |||||||||||
2020-10-30 | @ | Panthers2,Kings5 | RECAP | |||||||||||
2020-10-31 | @ | Panthers5,Lightning1 | RECAP | |||||||||||
2020-11-04 | @ | Jets1,Panthers5 | RECAP | |||||||||||
2020-11-06 | @ | Panthers1,Bruins4 | RECAP | |||||||||||
2020-11-07 | @ | Golden Knights5,Panthers2 | RECAP | |||||||||||
2020-11-10 | @ | Panthers4,Canadiens3 | RECAP | |||||||||||
2020-11-13 | @ | Bruins2,Panthers1 | RECAP | |||||||||||
2020-11-14 | @ | Avalanche2,Panthers4 | RECAP | |||||||||||
2020-11-17 | @ | Panthers4,Red Wings5 (OT) | RECAP | |||||||||||
2020-11-18 | @ | Panthers2,Lightning3 (SO) | RECAP | |||||||||||
2020-11-20 | @ | Rangers2,Panthers1 | RECAP | |||||||||||
2020-11-22 | @ | Panthers3,Bruins2 | RECAP | |||||||||||
2020-11-23 | @ | Panthers1,Rangers2 | RECAP | |||||||||||
2020-11-24 | @ | Oilers3,Panthers2 | RECAP | |||||||||||
2020-11-26 | @ | Flames1,Panthers2 (OT) | RECAP | |||||||||||
2020-11-27 | @ | Panthers1,Oilers3 | RECAP | |||||||||||
2020-11-29 | @ | Panthers6,Rangers3 | RECAP | |||||||||||
2020-12-03 | @ | Canadiens1,Panthers4 | RECAP | |||||||||||
2020-12-04 | @ | Panthers1,Blue Jackets3 | RECAP | |||||||||||
2020-12-06 | @ | Panthers2,Coyotes3 (OT) | RECAP | |||||||||||
2020-12-07 | @ | Wild3,Panthers2 (SO) | RECAP | |||||||||||
2020-12-08 | @ | Panthers4,Maple Leafs3 (OT) | RECAP | |||||||||||
2020-12-09 | @ | Blues2,Panthers4 | RECAP | |||||||||||
2020-12-10 | @ | Panthers1,Canucks2 | RECAP | |||||||||||
2020-12-12 | @ | Kings1,Panthers4 | RECAP | |||||||||||
2020-12-13 | @ | Panthers1,Canadiens3 | RECAP | |||||||||||
2020-12-15 | @ | Flyers1,Panthers4 | RECAP | |||||||||||
2020-12-18 | @ | Panthers3,Blue Jackets1 | RECAP | |||||||||||
2020-12-19 | @ | Devils2,Panthers4 | RECAP | |||||||||||
2020-12-22 | @ | Panthers2,Ducks4 | RECAP | |||||||||||
2020-12-23 | @ | Blue Jackets1,Panthers7 | RECAP | |||||||||||
2020-12-25 | @ | Panthers4,Jets3 | RECAP | |||||||||||
2020-12-26 | @ | Wild3,Panthers0 | RECAP | |||||||||||
Trade Deadline --- Trades cant be done after this day is simulated! | ||||||||||||||
2020-12-29 | @ | Stars2,Panthers3 (SO) | RECAP | |||||||||||
2021-01-01 | @ | Panthers3,Sabres1 | RECAP | |||||||||||
2021-01-02 | @ | Maple Leafs3,Panthers5 | RECAP | |||||||||||
2021-01-04 | @ | Panthers3,Maple Leafs2 | RECAP | |||||||||||
2021-01-07 | @ | Rangers2,Panthers4 | RECAP | |||||||||||
2021-01-09 | @ | Panthers1,Flyers4 | RECAP | |||||||||||
2021-01-11 | @ | Flyers1,Panthers3 | RECAP | |||||||||||
2021-01-15 | @ | Panthers4,Golden Knights3 | RECAP | |||||||||||
2021-01-17 | @ | Maple Leafs6,Panthers5 | RECAP | |||||||||||
2021-01-21 | @ | Panthers4,Flyers2 | RECAP | |||||||||||
2021-01-22 | @ | |||||||||||||
2021-01-27 | @ |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
80,952,857$ | 0$ | 80,952,857$ | 547,143$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | BBT Center | |
City | Florida | ||
Capacity | 18000 | ||
Season Ticket Holders | 50% |
Arena Capacity - Ticket Price Attendance - % | |||||
---|---|---|---|---|---|
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Arena Capacity | 6000 | 5000 | 2000 | 4000 | 1000 |
Ticket Price | 300$ | 150$ | 100$ | 75$ | 400$ |
Attendance | 179828 | 154465 | 60911 | 122343 | 36805 |
Attendance PCT | 76.85% | 79.21% | 78.09% | 78.43% | 94.37% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
2 | 14214 - 78.97% | 4,092,036$ | 159,589,390$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
80,952,857$ | 80,952,857$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
78,967,308$ | 80,952,857$ | 76,596,357$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
8,184,071$ | 9 | 499,718$ | 4,497,462$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
4,497,462$ | 80,952,857$ | 264,451,250$ | 268,137,859$ |
Left Wing | Center | Right Wing | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Year | Round 1 | Round 2 | Round 3 | Round 4 |
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