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Full Scoreboard ยป |
Tampa Bay Lightning 28-21-3, 59pts · 5th 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 | 99.00 | 50 | 2 | 95 | 81 | 74 | 99 | 95 | 88 | 97 | 88 | 89 | 60 | 90 | 81 | 88 | 84 | 71 | 78 | 33 | 8,400,000$/4yrs | |||
![]() | 0 | LW/RW | 100.00 | 52 | 1 | 99 | 84 | 67 | 98 | 99 | 85 | 31 | 89 | 99 | 43 | 75 | 66 | 67 | 78 | 71 | 76 | 27 | 6,500,000$/4yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 55 | 6 | 88 | 93 | 71 | 97 | 91 | 78 | 59 | 80 | 91 | 60 | 75 | 76 | 77 | 68 | 71 | 76 | 27 | 4,250,000$/1yrs | |||
![]() | 0 | C/LW | 100.00 | 52 | 3 | 99 | 82 | 79 | 93 | 99 | 78 | 85 | 77 | 81 | 53 | 61 | 71 | 72 | 79 | 71 | 73 | 30 | 2,800,000$/4yrs | |||
![]() | 0 | RW | 100.00 | 71 | 41 | 65 | 79 | 75 | 83 | 95 | 89 | 71 | 80 | 83 | 61 | 80 | 48 | 48 | 87 | 71 | 73 | 21 | 2,800,000$/3yrs | |||
![]() | 0 | LW | 100.00 | 50 | 3 | 99 | 76 | 79 | 89 | 91 | 81 | 52 | 76 | 88 | 46 | 56 | 75 | 78 | 78 | 71 | 72 | 32 | 3,000,000$/4yrs | |||
![]() | 0 | RW | 100.00 | 91 | 28 | 74 | 81 | 83 | 93 | 91 | 68 | 31 | 68 | 83 | 67 | 25 | 69 | 70 | 72 | 71 | 72 | 27 | 2,800,000$/5yrs | |||
![]() | 0 | LW/RW | 100.00 | 41 | 1 | 99 | 80 | 72 | 92 | 99 | 81 | 38 | 92 | 83 | 30 | 60 | 83 | 86 | 79 | 59 | 72 | 34 | 4,300,000$/3yrs | |||
![]() | 0 | C | 100.00 | 61 | 32 | 83 | 80 | 71 | 93 | 95 | 86 | 69 | 75 | 82 | 57 | 80 | 52 | 52 | 82 | 71 | 72 | 24 | 1,350,000$/2yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 52 | 1 | 99 | 84 | 62 | 88 | 98 | 71 | 68 | 68 | 86 | 53 | 25 | 68 | 72 | 78 | 71 | 70 | 31 | 1,750,000$/3yrs | |||
![]() | 0 | LW/RW | 100.00 | 41 | 1 | 99 | 92 | 67 | 78 | 80 | 79 | 52 | 85 | 71 | 43 | 25 | 67 | 68 | 67 | 71 | 69 | 23 | 2,125,000$/5yrs | |||
![]() | 0 | LW/RW | 100.00 | 48 | 1 | 99 | 83 | 71 | 80 | 86 | 63 | 47 | 75 | 57 | 79 | 25 | 71 | 73 | 66 | 77 | 68 | 29 | 1,250,000$/1yrs | |||
![]() | 0 | D | 100.00 | 73 | 11 | 77 | 90 | 77 | 99 | 96 | 83 | 25 | 71 | 58 | 90 | 41 | 74 | 75 | 63 | 71 | 79 | 27 | 6,900,000$/4yrs | |||
![]() | 0 | D | 100.00 | 81 | 31 | 79 | 87 | 69 | 99 | 74 | 90 | 25 | 74 | 83 | 81 | 25 | 73 | 75 | 69 | 71 | 77 | 27 | 6,100,000$/4yrs | |||
![]() | 6 | D | 100.00 | 61 | 1 | 99 | 93 | 78 | 99 | 99 | 73 | 25 | 59 | 51 | 85 | 25 | 71 | 72 | 61 | 71 | 76 | 25 | 6,150,000$/4yrs | |||
![]() | 0 | D | 100.00 | 61 | 1 | 99 | 86 | 48 | 99 | 89 | 78 | 25 | 67 | 60 | 84 | 25 | 74 | 76 | 73 | 71 | 74 | 32 | 4,150,000$/4yrs | |||
![]() | 0 | D | 100.00 | 87 | 20 | 82 | 73 | 76 | 84 | 93 | 59 | 25 | 55 | 49 | 99 | 25 | 63 | 64 | 57 | 71 | 74 | 27 | 4,250,000$/4yrs | |||
![]() | 0 | D | 100.00 | 55 | 1 | 94 | 86 | 73 | 95 | 95 | 65 | 25 | 61 | 52 | 85 | 25 | 69 | 70 | 58 | 71 | 73 | 27 | 3,300,000$/4yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | D | 100.00 | 45 | 2 | 99 | 80 | 74 | 97 | 94 | 60 | 25 | 64 | 47 | 82 | 48 | 82 | 88 | 67 | 20 | 72 | 34 | 685,000$/1yrs | |||
![]() | 0 | D | 100.00 | 69 | 6 | 90 | 76 | 78 | 84 | 67 | 60 | 25 | 60 | 50 | 84 | 25 | 67 | 68 | 63 | 20 | 70 | 31 | 685,000$/1yrs | |||
TEAM AVERAGE | 99.95 | 60 | 10 | 91 | 83 | 72 | 92 | 91 | 76 | 45 | 73 | 72 | 67 | 46 | 70 | 72 | 71 | 66 | 73 |
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 | 84 | 93 | 99 | 92 | 87 | 85 | 64 | 84 | 86 | 86 | 71 | 66 | 68 | 83 | 71 | 80 | 32 | 2,500,000$/2yrs |
![]() | 0 | 97.00 | 75 | 63 | 56 | 75 | 69 | 77 | 91 | 92 | 84 | 77 | 77 | 45 | 45 | 90 | 70 | 72 | 21 | 925,000$/5yrs |
Scratches | ||||||||||||||||||||
![]() | 0 | 100.00 | 76 | 66 | 81 | 67 | 78 | 80 | 78 | 80 | 78 | 78 | 74 | 66 | 67 | 64 | 18 | 73 | 33 | 750,000$/1yrs |
TEAM AVERAGE | 99.00 | 78 | 74 | 79 | 78 | 78 | 81 | 78 | 85 | 83 | 80 | 74 | 59 | 60 | 79 | 53 | 75 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Peter Laviolette | 55 | 97 | 68 | 78 | 99 | 95 | 74 | USA | 54 | 1 | 2,500,000$ |
General Manager | Jordan Banck |
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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 | Jonathan Toews | 0 | C | 52 | 20 | 38 | 58 | 2 | 14 | 0 | 58 | 213 | 70 | 117 | 9.39% | 35 | 24.13 | 3 | 7 | 10 | 91 | 0 | 0 | 0 | 72 | 2 | 1 | 57.21% | 1540 | 34 | 31 | 0 | 0 | 0.92 | 4 | 5 | |
2 | Brock Nelson | 0 | C/LW | 52 | 15 | 29 | 44 | 5 | 0 | 0 | 31 | 122 | 39 | 62 | 12.30% | 22 | 20.07 | 2 | 8 | 10 | 94 | 1 | 1 | 2 | 80 | 4 | 0 | 53.23% | 866 | 21 | 20 | 0 | 1 | 0.84 | 0 | 0 | |
3 | Andreas Athanasiou | 0 | C/LW/RW | 52 | 18 | 25 | 43 | 14 | 10 | 0 | 35 | 180 | 58 | 125 | 10.00% | 19 | 18.70 | 2 | 9 | 11 | 94 | 0 | 0 | 0 | 6 | 4 | 0 | 47.27% | 55 | 44 | 14 | 0 | 0 | 0.88 | 0 | 2 | |
4 | Jake Guentzel | 0 | LW/RW | 52 | 23 | 17 | 40 | 7 | 0 | 0 | 37 | 181 | 40 | 87 | 12.71% | 14 | 17.65 | 4 | 4 | 8 | 92 | 0 | 0 | 0 | 0 | 3 | 2 | 32.26% | 62 | 45 | 8 | 1 | 1 | 0.87 | 0 | 1 | |
5 | James van Riemsdyk | 0 | LW | 52 | 14 | 14 | 28 | 5 | 0 | 0 | 24 | 112 | 43 | 79 | 12.50% | 12 | 14.75 | 0 | 0 | 0 | 5 | 0 | 0 | 0 | 1 | 1 | 3 | 50.00% | 40 | 26 | 10 | 0 | 0 | 0.73 | 0 | 0 | |
6 | Noah Gregor | 0 | C | 52 | 17 | 9 | 26 | 2 | 16 | 0 | 59 | 136 | 33 | 75 | 12.50% | 19 | 15.07 | 2 | 0 | 2 | 77 | 0 | 0 | 0 | 0 | 5 | 1 | 42.17% | 313 | 21 | 9 | 0 | 0 | 0.66 | 0 | 0 | |
7 | Phil Kessel | 0 | LW/RW | 51 | 8 | 15 | 23 | 3 | 2 | 0 | 14 | 84 | 28 | 56 | 9.52% | 5 | 15.50 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 35.19% | 54 | 28 | 4 | 0 | 0 | 0.58 | 0 | 0 | |
8 | Damon Severson | 0 | D | 52 | 4 | 18 | 22 | 7 | 28 | 0 | 128 | 69 | 35 | 25 | 5.80% | 72 | 23.01 | 2 | 2 | 4 | 91 | 0 | 1 | 1 | 68 | 0 | 1 | 0.00% | 0 | 15 | 55 | 0 | 0 | 0.37 | 0 | 0 | |
9 | Stelio Mattheos | 0 | RW | 52 | 6 | 15 | 21 | 1 | 50 | 0 | 106 | 130 | 37 | 93 | 4.62% | 18 | 16.78 | 0 | 0 | 0 | 13 | 0 | 0 | 0 | 0 | 2 | 0 | 55.81% | 43 | 37 | 13 | 0 | 0 | 0.48 | 2 | 4 | |
10 | Tyler Johnson | 0 | C/LW/RW | 52 | 8 | 12 | 20 | -1 | 4 | 0 | 33 | 87 | 28 | 63 | 9.20% | 10 | 14.59 | 4 | 1 | 5 | 86 | 0 | 0 | 0 | 0 | 1 | 2 | 48.65% | 37 | 18 | 12 | 0 | 0 | 0.53 | 0 | 0 | |
11 | Mathew Dumba | 0 | D | 52 | 2 | 16 | 18 | -1 | 26 | 0 | 111 | 99 | 41 | 39 | 2.02% | 65 | 22.21 | 1 | 3 | 4 | 95 | 0 | 0 | 0 | 12 | 0 | 0 | 0.00% | 0 | 32 | 49 | 0 | 0 | 0.31 | 0 | 0 | |
12 | Jared Spurgeon | 0 | D | 52 | 2 | 16 | 18 | -7 | 2 | 0 | 30 | 55 | 18 | 21 | 3.64% | 70 | 19.06 | 1 | 3 | 4 | 95 | 0 | 0 | 0 | 3 | 0 | 0 | 100.00% | 1 | 7 | 46 | 0 | 0 | 0.36 | 0 | 0 | |
13 | Ivan Provorov | 6 | D | 52 | 5 | 11 | 16 | 0 | 2 | 0 | 38 | 68 | 20 | 22 | 7.35% | 59 | 21.41 | 2 | 2 | 4 | 83 | 1 | 0 | 1 | 78 | 0 | 0 | 0.00% | 0 | 11 | 50 | 0 | 0 | 0.29 | 0 | 0 | |
14 | Jesper Bratt | 0 | LW/RW | 52 | 7 | 6 | 13 | -14 | 0 | 0 | 6 | 65 | 32 | 45 | 10.77% | 7 | 8.80 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 5 | 2 | 0 | 34.78% | 23 | 13 | 5 | 1 | 0 | 0.57 | 0 | 0 | |
15 | Mike Matheson | 0 | D | 52 | 1 | 8 | 9 | 9 | 2 | 0 | 20 | 46 | 26 | 22 | 2.17% | 53 | 17.25 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 86 | 1 | 0 | 0.00% | 2 | 5 | 37 | 0 | 0 | 0.20 | 0 | 0 | |
16 | Robert Hagg | 0 | D | 52 | 2 | 7 | 9 | 4 | 30 | 0 | 86 | 34 | 19 | 19 | 5.88% | 69 | 17.50 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 70 | 1 | 0 | 0.00% | 1 | 4 | 37 | 0 | 0 | 0.20 | 0 | 0 | |
17 | Josh Anderson | 0 | RW | 52 | 3 | 2 | 5 | -13 | 12 | 0 | 65 | 33 | 10 | 17 | 9.09% | 11 | 9.47 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 72 | 0 | 0 | 31.82% | 22 | 8 | 10 | 0 | 0 | 0.20 | 0 | 0 | |
18 | Matthew Nieto | 0 | LW/RW | 51 | 0 | 1 | 1 | 2 | 2 | 0 | 3 | 2 | 3 | 4 | 0.00% | 3 | 2.15 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 79 | 0 | 0 | 26.67% | 15 | 1 | 3 | 0 | 0 | 0.18 | 0 | 0 | |
Team Total or Average | 934 | 155 | 259 | 414 | 25 | 200 | 0 | 884 | 1716 | 580 | 971 | 9.03% | 563 | 16.58 | 23 | 39 | 62 | 936 | 2 | 2 | 4 | 639 | 26 | 10 | 52.73% | 3074 | 370 | 413 | 2 | 2 | 0.53 | 6 | 12 |
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 | Justus Annunen | Lightning | 33 | 20 | 9 | 2 | 0.925 | 2.60 | 1871 | 2 | 0 | 81 | 1073 | 556 | 2 | 0 | 0.571 | 7 | 31 | 16 | 3 | 6 | 2 |
2 | Frederik Andersen | Lightning | 22 | 8 | 12 | 1 | 0.903 | 3.27 | 1268 | 4 | 0 | 69 | 713 | 326 | 0 | 0 | 1.000 | 4 | 21 | 31 | 1 | 3 | 1 |
Team Total or Average | 55 | 28 | 21 | 3 | 0.916 | 2.87 | 3140 | 6 | 0 | 150 | 1786 | 882 | 2 | 0 | 0.727 | 11 | 52 | 47 | 4 | 9 | 3 |
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 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 6 | -3 | 0 | 0.000 | 3 | 4 | 7 | 0 | 0 | 0 | 1 | 2 | 0 | 22 | 7 | 10 | 5 | 0 | 31 | 7 | 0 | 17 | 3 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 19 | 9 | 21 | 8 | 19 | 10 | 33.3% | 13.6% | 80.6% | 94.3 | FUN | |
2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 3 | 2 | 1.000 | 4 | 8 | 12 | 0 | 0 | 0 | 1 | 3 | 0 | 33 | 5 | 11 | 17 | 0 | 34 | 9 | 8 | 15 | 1 | 0 | 0.00% | 4 | 0 | 100.00% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 21 | 13 | 22 | 8 | 16 | 7 | 80.0% | 12.1% | 97.1% | 109.2 | LUCKY | |
3 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 5 | 5 | 4 | 1.000 | 10 | 17 | 27 | 0 | 0 | 4 | 3 | 3 | 0 | 69 | 27 | 28 | 14 | 0 | 65 | 20 | 14 | 29 | 5 | 1 | 20.00% | 7 | 1 | 85.71% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 39 | 21 | 43 | 18 | 36 | 18 | 69.2% | 14.5% | 92.3% | 106.8 | LUCKY | |
4 | 2 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 4 | 4 | 0 | 2 | 0.500 | 4 | 6 | 10 | 0 | 0 | 0 | 2 | 1 | 2 | 77 | 20 | 22 | 28 | 9 | 64 | 31 | 10 | 35 | 3 | 0 | 0.00% | 5 | 0 | 100.00% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 47 | 30 | 44 | 17 | 33 | 16 | 50.0% | 5.2% | 93.8% | 98.9 | DULL | |
5 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 2 | 3 | 2 | 1.000 | 5 | 9 | 14 | 0 | 0 | 3 | 1 | 1 | 0 | 40 | 14 | 5 | 21 | 0 | 38 | 12 | 2 | 21 | 3 | 1 | 33.33% | 1 | 0 | 100.00% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 24 | 15 | 20 | 6 | 14 | 8 | 66.7% | 12.5% | 94.7% | 107.2 | LUCKY | |
6 | 2 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 4 | 6 | -2 | 2 | 0.500 | 4 | 6 | 10 | 0 | 0 | 1 | 2 | 0 | 1 | 65 | 21 | 20 | 20 | 4 | 80 | 15 | 6 | 35 | 7 | 1 | 14.29% | 3 | 0 | 100.00% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 45 | 27 | 44 | 16 | 32 | 17 | 33.3% | 6.2% | 92.5% | 98.7 | DULL | |
7 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 3 | 2 | 1.000 | 4 | 6 | 10 | 0 | 0 | 1 | 0 | 3 | 0 | 29 | 10 | 10 | 9 | 0 | 38 | 15 | 4 | 11 | 3 | 1 | 33.33% | 2 | 1 | 50.00% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 19 | 11 | 23 | 9 | 17 | 8 | 100.0% | 13.8% | 97.4% | 111.2 | LUCKY | |
8 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 6 | 3 | 3 | 3 | 0.750 | 6 | 11 | 17 | 0 | 0 | 2 | 2 | 2 | 1 | 62 | 27 | 22 | 11 | 6 | 75 | 19 | 10 | 39 | 4 | 0 | 0.00% | 5 | 1 | 80.00% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 45 | 26 | 43 | 16 | 35 | 19 | 75.0% | 9.7% | 96.0% | 105.7 | LUCKY | |
9 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 5 | 4 | 1 | 2 | 0.500 | 5 | 7 | 12 | 0 | 0 | 2 | 2 | 1 | 0 | 62 | 24 | 21 | 17 | 0 | 63 | 22 | 4 | 34 | 1 | 1 | 100.00% | 2 | 0 | 100.00% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 41 | 24 | 43 | 16 | 35 | 18 | 50.0% | 8.1% | 93.7% | 101.7 | DULL | |
10 | 2 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 5 | 7 | -2 | 1 | 0.250 | 5 | 9 | 14 | 0 | 0 | 2 | 2 | 1 | 0 | 76 | 22 | 33 | 21 | 0 | 66 | 16 | 6 | 40 | 8 | 1 | 12.50% | 3 | 2 | 33.33% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 46 | 29 | 42 | 17 | 32 | 17 | 44.4% | 6.6% | 89.4% | 96.0 | Unlucky | |
11 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | -1 | 0 | 0.000 | 2 | 4 | 6 | 0 | 0 | 0 | 1 | 1 | 0 | 27 | 10 | 8 | 9 | 0 | 26 | 2 | 4 | 18 | 0 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 16 | 7 | 24 | 10 | 19 | 8 | 40.0% | 7.4% | 88.5% | 95.9 | Unlucky | |
12 | 4 | 2 | 1 | 0 | 1 | 0 | 0 | 0 | 15 | 11 | 4 | 6 | 0.750 | 15 | 23 | 38 | 0 | 0 | 4 | 2 | 8 | 1 | 133 | 46 | 38 | 48 | 1 | 147 | 49 | 10 | 64 | 13 | 2 | 15.38% | 5 | 0 | 100.00% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 87 | 52 | 84 | 33 | 68 | 35 | 54.2% | 11.3% | 92.5% | 103.8 | LUCKY | |
13 | 4 | 3 | 0 | 0 | 0 | 0 | 1 | 0 | 14 | 9 | 5 | 8 | 1.000 | 14 | 21 | 35 | 0 | 0 | 5 | 3 | 5 | 2 | 136 | 47 | 45 | 42 | 4 | 133 | 43 | 10 | 58 | 6 | 2 | 33.33% | 5 | 0 | 100.00% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 84 | 51 | 89 | 35 | 70 | 34 | 57.1% | 10.3% | 93.2% | 103.5 | LUCKY | |
14 | 3 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 8 | 11 | -3 | 2 | 0.333 | 8 | 13 | 21 | 0 | 0 | 1 | 3 | 4 | 0 | 123 | 31 | 56 | 36 | 0 | 111 | 31 | 10 | 53 | 6 | 2 | 33.33% | 5 | 3 | 40.00% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 64 | 41 | 67 | 24 | 48 | 24 | 42.9% | 6.5% | 90.1% | 96.6 | Unlucky | |
15 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | -2 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 0 | 1 | 0 | 24 | 15 | 6 | 3 | 0 | 21 | 10 | 10 | 24 | 2 | 1 | 50.00% | 5 | 2 | 60.00% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 21 | 12 | 20 | 9 | 17 | 8 | 0.0% | 4.2% | 85.7% | 89.9 | Unlucky | |
16 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 3 | 1 | 2 | 1.000 | 4 | 6 | 10 | 0 | 0 | 1 | 0 | 3 | 0 | 36 | 13 | 8 | 15 | 0 | 35 | 15 | 4 | 20 | 2 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 22 | 13 | 21 | 7 | 16 | 8 | 57.1% | 11.1% | 91.4% | 102.5 | LUCKY | |
17 | 6 | 2 | 2 | 0 | 2 | 0 | 0 | 0 | 16 | 14 | 2 | 8 | 0.667 | 16 | 24 | 40 | 0 | 0 | 2 | 6 | 6 | 2 | 189 | 60 | 58 | 67 | 4 | 207 | 63 | 10 | 93 | 21 | 6 | 28.57% | 5 | 1 | 80.00% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 124 | 73 | 134 | 50 | 103 | 54 | 43.5% | 8.5% | 93.2% | 101.7 | DULL | |
18 | 4 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 17 | 7 | 10 | 8 | 1.000 | 17 | 29 | 46 | 0 | 0 | 4 | 6 | 7 | 0 | 129 | 32 | 56 | 41 | 0 | 135 | 52 | 18 | 70 | 1 | 1 | 100.00% | 9 | 1 | 88.89% | 1 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 83 | 49 | 91 | 34 | 65 | 31 | 72.7% | 13.2% | 94.8% | 108.0 | LUCKY | |
19 | 6 | 1 | 5 | 0 | 0 | 0 | 0 | 0 | 14 | 27 | -13 | 2 | 0.167 | 14 | 25 | 39 | 0 | 0 | 2 | 6 | 6 | 0 | 182 | 62 | 67 | 53 | 0 | 238 | 82 | 38 | 96 | 10 | 3 | 30.00% | 18 | 7 | 61.11% | 0 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 117 | 66 | 143 | 50 | 99 | 48 | 35.5% | 7.7% | 88.7% | 96.3 | Unlucky | |
20 | 6 | 1 | 4 | 0 | 0 | 0 | 0 | 1 | 17 | 25 | -8 | 3 | 0.250 | 17 | 30 | 47 | 0 | 0 | 7 | 7 | 3 | 0 | 214 | 68 | 90 | 56 | 3 | 179 | 50 | 28 | 118 | 19 | 0 | 0.00% | 14 | 5 | 64.29% | 1 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 135 | 79 | 122 | 53 | 107 | 53 | 45.9% | 7.9% | 86.0% | 94.0 | Unlucky | |
_Vs Division | 25 | 9 | 13 | 0 | 2 | 0 | 0 | 1 | 72 | 84 | -12 | 23 | 0.460 | 72 | 121 | 193 | 0 | 0 | 16 | 28 | 26 | 2 | 837 | 253 | 327 | 253 | 7 | 870 | 278 | 104 | 430 | 57 | 12 | 21.05% | 51 | 17 | 66.67% | 2 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 525 | 310 | 558 | 214 | 423 | 212 | 47.2% | 8.6% | 90.3% | 98.9 | Unlucky | |
_Vs Conference | 35 | 15 | 15 | 0 | 3 | 0 | 1 | 1 | 106 | 110 | -4 | 39 | 0.557 | 106 | 173 | 279 | 0 | 0 | 26 | 33 | 43 | 5 | 1166 | 374 | 424 | 361 | 12 | 1206 | 395 | 138 | 596 | 80 | 17 | 21.25% | 68 | 19 | 72.06% | 2 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 741 | 440 | 775 | 300 | 596 | 299 | 49.4% | 9.1% | 90.9% | 100.0 | FUN | |
_Since Last GM Reset | 52 | 22 | 21 | 0 | 4 | 1 | 2 | 2 | 158 | 152 | 6 | 59 | 0.567 | 158 | 260 | 418 | 0 | 0 | 41 | 50 | 61 | 9 | 1728 | 561 | 614 | 533 | 31 | 1786 | 563 | 206 | 890 | 118 | 23 | 19.49% | 102 | 24 | 76.47% | 2 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 1107 | 657 | 1150 | 446 | 889 | 449 | 51.3% | 9.1% | 91.5% | 100.6 | LUCKY | |
Total | 52 | 22 | 21 | 0 | 4 | 1 | 2 | 2 | 158 | 152 | 6 | 59 | 0.567 | 158 | 260 | 418 | 0 | 0 | 41 | 50 | 61 | 9 | 1728 | 561 | 614 | 533 | 31 | 1786 | 563 | 206 | 890 | 118 | 23 | 19.49% | 102 | 24 | 76.47% | 2 | 626 | 1207 | 51.86% | 627 | 1164 | 53.87% | 391 | 728 | 53.71% | 1107 | 657 | 1150 | 446 | 889 | 449 | 51.3% | 9.1% | 91.5% | 100.6 | LUCKY |
Puck Time | |
---|---|
Offensive Zone | 21 |
Neutral Zone | 17 |
Defensive Zone | 22 |
Puck Time | |
---|---|
Offensive Zone Start | 1207 |
Neutral Zone Start | 728 |
Defensive Zone Start | 1164 |
Puck Time | |
---|---|
With Puck | 29 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 1644 |
Faceoffs Lost | 1455 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 10.8 | 9.57 |
2nd Period | 22.6 | 20.31 |
3rd Period | 32.8 | 30.68 |
Overtime | 33.4 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.8 | 0.64 |
2nd Period | 1.8 | 1.65 |
3rd Period | 2.9 | 2.67 |
Overtime | 3.1 | 2.83 |
Even Strenght Goal | 133 |
---|---|
PP Goal | 23 |
PK Goal | 2 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 14 | 14 |
Lost | 10 | 11 |
Overtime Lost | 2 | 1 |
PP Attempt | 118 |
---|---|
PP Goal | 23 |
PK Attempt | 102 |
PK Goal Against | 24 |
Home | |
---|---|
Shots For | 33.2 |
Shots Against | 34.3 |
Goals For | 3.0 |
Goals Against | 2.9 |
Hits | 17.1 |
Shots Blocked | 10.8 |
Pim | 4.0 |
Projected Total Cap Hit | 80,197,241$ |
Projected Cap Space | 6,302,759$ |
Retains And Buyout Cap Hit | 2,500,000$ |
Salary Cap To Date | 48,217,241$ |
Players In Salary Cap | 23 |
LTIR Players | 0 |
Player Name | Pos | Age | Cap Hit | 2015-2016 | 2016-2017 | 2017-2018 | 2018-2019 | 2019-2020 | 2020-2021 | 2021-2022 | 2022-2023 |
---|---|---|---|---|---|---|---|---|---|---|---|
Andreas Athanasiou | C/LW/RW | 27 | 4,250,000$ | 4,250,000$ | |||||||
Brock Nelson | C/LW | 30 | 2,800,000$ | 2,800,000$ | 2,800,000$ | 2,800,000$ | 2,800,000$ | ||||
Damon Severson ![]() | D | 27 | 6,900,000$ | 6,900,000$ | 6,900,000$ | 6,900,000$ | 6,900,000$ | ||||
Frederik Andersen | D | 32 | 2,500,000$ | 2,500,000$ | 2,500,000$ | ||||||
Ivan Provorov | D | 25 | 6,150,000$ | 6,150,000$ | 6,150,000$ | 6,150,000$ | 6,150,000$ | ||||
Jake Guentzel | LW/RW | 27 | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | 6,500,000$ | ||||
James van Riemsdyk | LW | 32 | 3,000,000$ | 3,000,000$ | 3,000,000$ | 3,000,000$ | 3,000,000$ | ||||
Jared Spurgeon | D | 32 | 4,150,000$ | 4,150,000$ | 4,150,000$ | 4,150,000$ | 4,150,000$ | ||||
Jesper Bratt ![]() | LW/RW | 23 | 2,125,000$ | 2,125,000$ | 1,300,000$ | 1,300,000$ | 1,300,000$ | 1,300,000$ | |||
Jonathan Bernier ![]() | D | 33 | 750,000$ | 750,000$ | |||||||
Jonathan Toews | C | 33 | 8,400,000$ | 8,400,000$ | 8,400,000$ | 8,400,000$ | 8,400,000$ | ||||
Josh Anderson ![]() | RW | 27 | 2,800,000$ | 2,800,000$ | 2,900,000$ | 2,900,000$ | 2,900,000$ | 2,900,000$ | |||
Justus Annunen ![]() | C | 21 | 925,000$ | 925,000$ | 1,200,000$ | 1,200,000$ | 1,200,000$ | 1,200,000$ | |||
Marc-Edouard Vlasic | D | 34 | 685,000$ | 685,000$ | |||||||
Mathew Dumba ![]() | D | 27 | 6,100,000$ | 6,100,000$ | 6,100,000$ | 6,100,000$ | 6,100,000$ | ||||
Matthew Nieto ![]() | LW/RW | 29 | 1,250,000$ | 1,250,000$ | |||||||
Michael Stone | D | 31 | 685,000$ | 685,000$ | |||||||
Mike Matheson | D | 27 | 3,300,000$ | 3,300,000$ | 3,300,000$ | 3,300,000$ | 3,300,000$ | ||||
Noah Gregor ![]() | C | 24 | 1,350,000$ | 1,350,000$ | 1,350,000$ | ||||||
Phil Kessel | LW/RW | 34 | 4,300,000$ | 4,300,000$ | 3,500,000$ | 3,500,000$ | |||||
Robert Hagg | D | 27 | 4,250,000$ | 4,250,000$ | 4,250,000$ | 4,250,000$ | 4,250,000$ | ||||
Stelio Mattheos ![]() | RW | 21 | 2,800,000$ | 2,800,000$ | 2,800,000$ | 2,800,000$ | |||||
Tyler Johnson | C/LW/RW | 31 | 1,750,000$ | 1,750,000$ | 1,750,000$ | 1,750,000$ |
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Priority | Type | Description |
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1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
---|---|---|---|---|---|
Aidan Hreschuk | 5 | 56 | |||
Brock Faber | 3 | 65 | |||
EvanVierling | 2 | 66 | |||
Jack Bar | 5 | 80 | |||
Jack Works | 2 | 94 | |||
Joaquim Lemay | 4 | 83 | |||
Kyle Aucoin | 3 | 84 | |||
Lukas Reichel | 3 | 12 | |||
Luke Hughes | 5 | 8 | |||
Ryan Ufko | 4 | 51 | |||
Stiven Sardarian | 5 | 55 | |||
Ty Smilanic | 2 | 18 | |||
William Eklund | 4 | 11 | |||
Zion Nybeck | 3 | 42 |
Date | Matchup | Result | Detail | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2022-02-17 | @ | Lightning2,Devils4 | RECAP | |||||||||||
2022-02-18 | @ | Lightning1,Flyers4 | RECAP | |||||||||||
2022-02-20 | @ | Blue Jackets4,Lightning1 | RECAP | |||||||||||
2022-02-22 | @ | Rangers6,Lightning1 | RECAP | |||||||||||
2022-02-24 | @ | Lightning2,Rangers3 | RECAP | |||||||||||
2022-02-25 | @ | Blue Jackets6,Lightning2 | RECAP | |||||||||||
2022-02-27 | @ | Lightning5,Panthers3 | RECAP | |||||||||||
2022-03-01 | @ | Devils2,Lightning1 | RECAP | |||||||||||
2022-03-03 | @ | Flyers1,Lightning4 | RECAP | |||||||||||
2022-03-05 | @ | Lightning2,Devils7 | RECAP | |||||||||||
2022-03-07 | @ | Lightning2,Blue Jackets3 | RECAP | |||||||||||
2022-03-08 | @ | Panthers1,Lightning4 | RECAP | |||||||||||
2022-03-10 | @ | Lightning6,Panthers2 | RECAP | |||||||||||
2022-03-11 | @ | Lightning4,Maple Leafs2 | RECAP | |||||||||||
2022-03-13 | @ | Lightning2,Flyers4 | RECAP | |||||||||||
2022-03-14 | @ | Red Wings3,Lightning4 | RECAP | |||||||||||
2022-03-16 | @ | Maple Leafs1,Lightning2 (SO) | RECAP | |||||||||||
2022-03-19 | @ | Lightning2,Canucks1 (SO) | RECAP | |||||||||||
2022-03-20 | @ | Canadiens3,Lightning5 | RECAP | |||||||||||
2022-03-23 | @ | Lightning4,Oilers2 | RECAP | |||||||||||
2022-03-24 | @ | Golden Knights2,Lightning5 | RECAP | |||||||||||
2022-03-27 | @ | Canadiens3,Lightning1 | RECAP | |||||||||||
2022-03-28 | @ | Lightning2,Coyotes3 (OT) | RECAP | |||||||||||
2022-03-30 | @ | Sabres3,Lightning1 | RECAP | |||||||||||
2022-04-01 | @ | Lightning2,Ducks3 | RECAP | |||||||||||
2022-04-02 | @ | Lightning4,Stars1 | RECAP | |||||||||||
2022-04-04 | @ | Jets1,Lightning4 | RECAP | |||||||||||
2022-04-05 | @ | Lightning1,Avalanche4 | RECAP | |||||||||||
2022-04-07 | @ | Blue Jackets5,Lightning4 | RECAP | |||||||||||
2022-04-09 | @ | Devils4,Lightning6 | RECAP | |||||||||||
2022-04-11 | @ | Lightning2,Flyers1 (OT) | RECAP | |||||||||||
2022-04-13 | @ | Blues2,Lightning1 (SO) | RECAP | |||||||||||
2022-04-15 | @ | Lightning2,Panthers1 | RECAP | |||||||||||
2022-04-16 | @ | Blue Jackets5,Lightning4 (SO) | RECAP | |||||||||||
2022-04-18 | @ | Lightning4,Canadiens3 (OT) | RECAP | |||||||||||
2022-04-19 | @ | Canucks3,Lightning2 | RECAP | |||||||||||
2022-04-21 | @ | Lightning3,Flames6 | RECAP | |||||||||||
2022-04-23 | @ | Avalanche2,Lightning3 (OT) | RECAP | |||||||||||
2022-04-25 | @ | Lightning1,Devils6 | RECAP | |||||||||||
2022-04-26 | @ | Lightning4,Maple Leafs3 | RECAP | |||||||||||
2022-04-28 | @ | Rangers2,Lightning5 | RECAP | |||||||||||
2022-04-30 | @ | Lightning4,Blue Jackets2 | RECAP | |||||||||||
2022-05-02 | @ | Maple Leafs3,Lightning4 | RECAP | |||||||||||
2022-05-04 | @ | Coyotes4,Lightning3 | RECAP | |||||||||||
2022-05-05 | @ | Lightning1,Jets3 | RECAP | |||||||||||
2022-05-07 | @ | Oilers3,Lightning6 | RECAP | |||||||||||
2022-05-09 | @ | Devils4,Lightning2 | RECAP | |||||||||||
2022-05-10 | @ | Lightning5,Blues1 | RECAP | |||||||||||
2022-05-12 | @ | Lightning4,Flyers3 (OT) | RECAP | |||||||||||
2022-05-14 | @ | Lightning5,Canadiens2 | RECAP | |||||||||||
2022-05-15 | @ | Flyers1,Lightning3 | RECAP | |||||||||||
2022-05-17 | @ | Kings1,Lightning4 | RECAP | |||||||||||
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Trade Deadline --- Trades cant be done after this day is simulated! | ||||||||||||||
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Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
77,720,000$ | 2,500,000$ | 80,197,241$ | 6,302,759$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | Amalie Arena | |
City | Tampa Bay | ||
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 | 122281 | 101928 | 39934 | 81603 | 24404 |
Attendance PCT | 78.39% | 78.41% | 76.80% | 78.46% | 93.86% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
15 | 14237 - 79.09% | 4,117,485$ | 107,054,598$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
77,720,000$ | 77,720,000$ | 0$ | 2,500,000$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
49,768,931$ | 536,000$ | 48,217,241$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
61,762,268$ | 55 | 553,241$ | 30,428,255$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
31,491,476$ | 80,197,241$ | 533,783,960$ | 570,237,856$ |
Left Wing | Center | Right Wing | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Year | Round 1 | Round 2 | Round 3 | Round 4 |
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