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Full Scoreboard ยป |
Dallas Stars 44-31-5, 93pts · 5th in Western 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 | 66 | 25 | 83 | 90 | 84 | 99 | 94 | 87 | 88 | 89 | 88 | 68 | 83 | 71 | 72 | 83 | 83 | 80 | 27 | 5,350,000$/2yrs | |||
![]() | 0 | C/RW | 100.00 | 58 | 23 | 86 | 85 | 71 | 94 | 97 | 91 | 90 | 92 | 95 | 55 | 53 | 76 | 80 | 87 | 83 | 79 | 30 | 8,500,000$/3yrs | |||
![]() | 0 | LW | 100.00 | 73 | 39 | 44 | 85 | 79 | 93 | 94 | 74 | 49 | 77 | 88 | 55 | 38 | 75 | 76 | 81 | 83 | 73 | 29 | 7,000,000$/3yrs | |||
![]() | 0 | LW | 100.00 | 53 | 12 | 90 | 88 | 74 | 91 | 96 | 80 | 40 | 81 | 73 | 51 | 61 | 67 | 69 | 73 | 83 | 72 | 25 | 5,500,000$/3yrs | |||
![]() | 0 | C | 100.00 | 54 | 13 | 80 | 84 | 72 | 93 | 97 | 73 | 87 | 77 | 78 | 62 | 25 | 73 | 74 | 78 | 83 | 72 | 31 | 5,350,000$/3yrs | |||
![]() | 0 | LW/RW | 100.00 | 50 | 11 | 88 | 85 | 67 | 92 | 99 | 88 | 36 | 80 | 90 | 34 | 35 | 67 | 68 | 81 | 83 | 72 | 30 | 4,250,000$/4yrs | |||
![]() | 0 | C/RW | 100.00 | 63 | 14 | 92 | 77 | 73 | 91 | 62 | 65 | 86 | 58 | 68 | 84 | 63 | 77 | 79 | 72 | 67 | 69 | 31 | 4,375,000$/5yrs | |||
![]() | 0 | C/LW | 100.00 | 66 | 23 | 83 | 80 | 72 | 82 | 99 | 58 | 86 | 69 | 68 | 77 | 25 | 64 | 65 | 71 | 83 | 69 | 26 | 2,300,000$/1yrs | |||
![]() | 0 | C/LW | 100.00 | 61 | 15 | 91 | 71 | 80 | 80 | 60 | 66 | 77 | 59 | 59 | 72 | 45 | 76 | 79 | 5 | 78 | 65 | 32 | 685,000$/1yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 58 | 13 | 93 | 68 | 68 | 82 | 77 | 75 | 42 | 65 | 87 | 23 | 85 | 67 | 67 | 75 | 79 | 64 | 29 | 775,000$/5yrs | |||
![]() | 0 | C/RW | 100.00 | 67 | 46 | 86 | 71 | 83 | 79 | 81 | 70 | 73 | 62 | 56 | 41 | 57 | 84 | 88 | 66 | 25 | 64 | 36 | 685,000$/1yrs | |||
![]() | 0 | D | 99.00 | 72 | 40 | 69 | 87 | 85 | 99 | 99 | 75 | 25 | 71 | 55 | 86 | 63 | 66 | 66 | 70 | 83 | 77 | 25 | 5,600,000$/2yrs | |||
![]() | 0 | D | 99.00 | 51 | 12 | 82 | 87 | 72 | 99 | 99 | 91 | 25 | 81 | 50 | 76 | 25 | 81 | 84 | 69 | 82 | 76 | 33 | 6,350,000$/3yrs | |||
![]() | 0 | D | 100.00 | 75 | 27 | 79 | 84 | 85 | 90 | 99 | 63 | 25 | 61 | 47 | 84 | 25 | 72 | 74 | 65 | 83 | 75 | 29 | 900,000$/3yrs | |||
![]() | 0 | D | 100.00 | 54 | 11 | 94 | 92 | 78 | 99 | 97 | 80 | 25 | 72 | 56 | 82 | 25 | 63 | 64 | 67 | 83 | 75 | 23 | 5,000,000$/2yrs | |||
![]() | 0 | D | 100.00 | 66 | 14 | 92 | 70 | 68 | 95 | 60 | 71 | 25 | 50 | 47 | 95 | 75 | 69 | 70 | 5 | 49 | 71 | 33 | 685,000$/2yrs | |||
![]() | 0 | D | 100.00 | 69 | 14 | 89 | 73 | 77 | 85 | 70 | 61 | 25 | 50 | 50 | 85 | 25 | 55 | 55 | 61 | 22 | 68 | 25 | 1,416,667$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | C/RW | 100.00 | 67 | 30 | 80 | 84 | 71 | 81 | 93 | 84 | 84 | 89 | 77 | 79 | 53 | 69 | 70 | 79 | 83 | 76 | 27 | 7,110,000$/5yrs | |||
![]() | 0 | D | 100.00 | 61 | 15 | 86 | 70 | 84 | 85 | 90 | 60 | 25 | 59 | 46 | 80 | 80 | 84 | 91 | 63 | 36 | 71 | 35 | 1,700,000$/1yrs | |||
TEAM AVERAGE | 99.89 | 62 | 21 | 84 | 81 | 76 | 90 | 88 | 74 | 53 | 71 | 67 | 68 | 50 | 71 | 73 | 66 | 71 | 72 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 99.00 | 80 | 65 | 80 | 83 | 89 | 81 | 76 | 89 | 91 | 90 | 95 | 64 | 65 | 86 | 82 | 79 | 34 | 1,500,000$/4yrs |
![]() | 0 | 100.00 | 91 | 85 | 86 | 68 | 81 | 85 | 84 | 86 | 90 | 85 | 95 | 48 | 48 | 73 | 82 | 77 | 22 | 730,833$/5yrs |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 99.50 | 86 | 75 | 83 | 76 | 85 | 83 | 80 | 88 | 91 | 88 | 95 | 56 | 57 | 80 | 82 | 78 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Jim Montgomery | 79 | 93 | 63 | 89 | 69 | 63 | 71 | CAN | 51 | 4 | 2,500,000$ |
General Manager | Jeff Shirley |
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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 | Steven Stamkos | 0 | C/RW | 80 | 32 | 53 | 85 | -2 | 12 | 0 | 79 | 313 | 101 | 192 | 10.22% | 23 | 19.77 | 10 | 14 | 24 | 201 | 0 | 0 | 0 | 0 | 3 | 1 | 44.03% | 134 | 84 | 20 | 0 | 0 | 1.07 | 0 | 11 | |
2 | Mika Zibanejad | 0 | C | 80 | 32 | 52 | 84 | -8 | 18 | 0 | 122 | 307 | 91 | 215 | 10.42% | 36 | 20.04 | 6 | 15 | 21 | 200 | 0 | 0 | 0 | 18 | 9 | 5 | 53.18% | 2106 | 57 | 22 | 0 | 1 | 1.05 | 2 | 11 | |
3 | Mike Hoffman | 0 | LW/RW | 80 | 25 | 35 | 60 | -14 | 12 | 0 | 45 | 301 | 91 | 166 | 8.31% | 5 | 18.54 | 7 | 9 | 16 | 200 | 0 | 0 | 0 | 0 | 5 | 0 | 27.47% | 91 | 85 | 2 | 0 | 0 | 0.81 | 0 | 6 | |
4 | Ryan Strome | 0 | C/RW | 80 | 31 | 28 | 59 | -6 | 8 | 0 | 123 | 247 | 75 | 190 | 12.55% | 37 | 19.58 | 7 | 4 | 11 | 177 | 0 | 0 | 0 | 88 | 4 | 4 | 50.37% | 1745 | 42 | 41 | 1 | 0 | 0.75 | 3 | 11 | |
5 | Keith Yandle | 0 | D | 80 | 10 | 35 | 45 | -7 | 22 | 0 | 63 | 213 | 88 | 76 | 4.69% | 133 | 26.00 | 2 | 7 | 9 | 203 | 0 | 1 | 1 | 82 | 1 | 1 | 100.00% | 1 | 38 | 80 | 0 | 0 | 0.43 | 0 | 0 | |
6 | Evander Kane | 0 | LW | 80 | 20 | 19 | 39 | -2 | 64 | 0 | 195 | 159 | 38 | 93 | 12.58% | 13 | 18.88 | 6 | 3 | 9 | 194 | 1 | 0 | 1 | 74 | 4 | 2 | 34.07% | 91 | 38 | 20 | 0 | 1 | 0.52 | 2 | 8 | |
7 | Darnell Nurse | 0 | D | 80 | 7 | 32 | 39 | -20 | 40 | 0 | 152 | 172 | 64 | 70 | 4.07% | 157 | 24.64 | 4 | 5 | 9 | 204 | 0 | 0 | 0 | 86 | 1 | 0 | 0.00% | 0 | 27 | 91 | 0 | 0 | 0.40 | 0 | 1 | |
8 | Mikael Backlund | 0 | C | 80 | 18 | 15 | 33 | -3 | 8 | 0 | 49 | 165 | 46 | 98 | 10.91% | 23 | 11.76 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 0 | 3 | 2 | 54.03% | 509 | 38 | 13 | 0 | 0 | 0.70 | 0 | 0 | |
9 | Zach Werenski | 0 | D | 80 | 5 | 24 | 29 | -4 | 4 | 0 | 36 | 151 | 66 | 54 | 3.31% | 143 | 22.27 | 1 | 6 | 7 | 195 | 0 | 0 | 0 | 103 | 0 | 1 | 0.00% | 0 | 31 | 83 | 0 | 0 | 0.33 | 0 | 0 | |
10 | Jonathan Drouin | 0 | LW | 80 | 15 | 8 | 23 | -6 | 6 | 0 | 34 | 127 | 42 | 62 | 11.81% | 23 | 16.40 | 0 | 0 | 0 | 2 | 0 | 1 | 1 | 33 | 5 | 0 | 30.38% | 79 | 31 | 5 | 0 | 0 | 0.35 | 0 | 0 | |
11 | Brenden Dillon | 0 | D | 80 | 4 | 15 | 19 | -9 | 18 | 0 | 124 | 109 | 48 | 42 | 3.67% | 111 | 20.36 | 3 | 3 | 6 | 195 | 0 | 0 | 0 | 81 | 0 | 0 | 0.00% | 0 | 10 | 70 | 0 | 0 | 0.23 | 0 | 0 | |
12 | Scott Laughton | 0 | C/LW | 80 | 7 | 8 | 15 | -9 | 2 | 0 | 70 | 99 | 36 | 66 | 7.07% | 22 | 9.82 | 0 | 2 | 2 | 17 | 0 | 0 | 0 | 92 | 2 | 0 | 41.94% | 124 | 22 | 15 | 1 | 0 | 0.38 | 0 | 0 | |
13 | Brandon Sutter | 0 | C/RW | 65 | 6 | 4 | 10 | -9 | 2 | 0 | 37 | 84 | 27 | 41 | 7.14% | 21 | 8.33 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 17 | 0 | 0 | 50.36% | 139 | 13 | 17 | 0 | 0 | 0.37 | 1 | 1 | |
14 | David Schlemko | 0 | D | 68 | 1 | 7 | 8 | 0 | 4 | 0 | 51 | 57 | 29 | 33 | 1.75% | 81 | 13.95 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 35 | 0 | 0 | 0.00% | 0 | 2 | 60 | 0 | 0 | 0.17 | 0 | 1 | |
15 | Steven Santini | 0 | D | 50 | 2 | 6 | 8 | -4 | 19 | 5 | 42 | 47 | 25 | 22 | 4.26% | 54 | 13.22 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0.00% | 1 | 5 | 31 | 0 | 0 | 0.24 | 0 | 0 | |
16 | Patrik Berglund | 0 | C/LW | 80 | 2 | 4 | 6 | -10 | 4 | 0 | 32 | 34 | 17 | 33 | 5.88% | 18 | 8.88 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 69 | 0 | 0 | 48.21% | 112 | 9 | 6 | 0 | 0 | 0.17 | 0 | 0 | |
17 | Braydon Coburn | 0 | D | 42 | 0 | 5 | 5 | -5 | 2 | 0 | 27 | 34 | 17 | 13 | 0.00% | 44 | 14.26 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 9 | 0 | 0 | 0.00% | 0 | 2 | 32 | 0 | 0 | 0.17 | 1 | 1 | |
18 | Brandon Pirri | 0 | C/LW/RW | 76 | 1 | 2 | 3 | -1 | 0 | 0 | 36 | 61 | 12 | 42 | 1.64% | 4 | 12.08 | 0 | 0 | 0 | 29 | 0 | 0 | 0 | 7 | 0 | 0 | 31.82% | 22 | 15 | 2 | 0 | 0 | 0.07 | 1 | 4 | |
19 | David Backes | 0 | C/RW | 25 | 0 | 0 | 0 | -4 | 2 | 0 | 23 | 23 | 6 | 12 | 0.00% | 0 | 8.27 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 57.14% | 7 | 3 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
Team Total or Average | 1366 | 218 | 352 | 570 | -123 | 247 | 5 | 1340 | 2703 | 919 | 1520 | 8.07% | 948 | 16.71 | 46 | 68 | 114 | 1850 | 1 | 2 | 3 | 804 | 37 | 17 | 50.40% | 5161 | 552 | 610 | 2 | 2 | 0.50 | 10 | 55 |
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 | Carter Hart | Stars | 61 | 34 | 22 | 5 | 0.923 | 2.89 | 3701 | 4 | 0 | 178 | 2300 | 1079 | 5 | 1 | 0.877 | 57 | 61 | 19 | 10 | 3 | 7 |
2 | Thomas Greiss | Stars | 20 | 10 | 9 | 0 | 0.919 | 2.85 | 1158 | 4 | 0 | 55 | 676 | 316 | 2 | 1 | 0.000 | 0 | 19 | 61 | 1 | 3 | 1 |
Team Total or Average | 81 | 44 | 31 | 5 | 0.922 | 2.88 | 4860 | 8 | 0 | 233 | 2976 | 1395 | 7 | 2 | 0.877 | 57 | 80 | 80 | 11 | 6 | 8 |
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 | 2 | 2 | 0 | 1 | 0 | 0 | 0 | 14 | 17 | -3 | 6 | 0.600 | 14 | 24 | 38 | 0 | 0 | 3 | 6 | 4 | 1 | 193 | 79 | 53 | 55 | 6 | 188 | 54 | 27 | 89 | 11 | 0 | 0.00% | 8 | 3 | 62.50% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 106 | 66 | 115 | 44 | 81 | 39 | 50.0% | 7.3% | 91.0% | 98.2 | Unlucky | |
2 | 5 | 2 | 1 | 0 | 0 | 0 | 1 | 1 | 14 | 13 | 1 | 7 | 0.700 | 14 | 23 | 37 | 1 | 0 | 5 | 2 | 6 | 2 | 175 | 51 | 52 | 66 | 18 | 194 | 73 | 20 | 77 | 2 | 0 | 0.00% | 10 | 1 | 90.00% | 1 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 97 | 58 | 127 | 42 | 85 | 40 | 53.8% | 8.0% | 93.3% | 101.3 | DULL | |
3 | 4 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 13 | 13 | 0 | 5 | 0.625 | 13 | 20 | 33 | 0 | 0 | 6 | 3 | 3 | 1 | 148 | 66 | 40 | 40 | 5 | 149 | 59 | 14 | 64 | 9 | 1 | 11.11% | 7 | 3 | 57.14% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 84 | 52 | 97 | 34 | 66 | 32 | 54.5% | 8.8% | 91.3% | 100.1 | DULL | |
4 | 4 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 16 | 9 | 7 | 8 | 1.000 | 16 | 28 | 44 | 0 | 0 | 2 | 9 | 5 | 0 | 175 | 53 | 63 | 59 | 0 | 139 | 39 | 14 | 61 | 13 | 7 | 53.85% | 7 | 2 | 71.43% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 88 | 55 | 89 | 31 | 62 | 31 | 56.3% | 9.1% | 93.5% | 102.7 | LUCKY | |
5 | 4 | 2 | 1 | 0 | 0 | 0 | 1 | 0 | 13 | 10 | 3 | 6 | 0.750 | 13 | 19 | 32 | 0 | 0 | 7 | 4 | 1 | 2 | 142 | 60 | 50 | 29 | 7 | 143 | 51 | 14 | 82 | 13 | 1 | 7.69% | 6 | 4 | 33.33% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 87 | 54 | 88 | 33 | 68 | 33 | 66.7% | 9.2% | 93.0% | 102.2 | LUCKY | |
6 | 5 | 3 | 1 | 0 | 0 | 0 | 1 | 0 | 19 | 15 | 4 | 8 | 0.800 | 19 | 30 | 49 | 0 | 0 | 3 | 5 | 10 | 1 | 171 | 64 | 38 | 69 | 3 | 183 | 49 | 14 | 85 | 21 | 4 | 19.05% | 7 | 1 | 85.71% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 109 | 66 | 108 | 43 | 87 | 44 | 51.7% | 11.1% | 91.8% | 102.9 | LUCKY | |
7 | 6 | 2 | 3 | 0 | 0 | 0 | 0 | 1 | 22 | 21 | 1 | 5 | 0.417 | 22 | 36 | 58 | 0 | 0 | 8 | 11 | 3 | 0 | 228 | 72 | 79 | 75 | 5 | 235 | 58 | 14 | 114 | 16 | 5 | 31.25% | 7 | 0 | 100.00% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 131 | 80 | 134 | 49 | 99 | 49 | 44.7% | 9.6% | 91.1% | 100.7 | Unlucky | |
8 | 6 | 2 | 3 | 0 | 1 | 0 | 0 | 0 | 20 | 17 | 3 | 6 | 0.500 | 20 | 32 | 52 | 0 | 0 | 6 | 5 | 8 | 1 | 216 | 85 | 62 | 68 | 1 | 204 | 66 | 18 | 112 | 24 | 6 | 25.00% | 9 | 1 | 88.89% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 126 | 75 | 135 | 49 | 98 | 50 | 46.7% | 9.3% | 91.7% | 100.9 | LUCKY | |
9 | 3 | 0 | 2 | 0 | 0 | 0 | 1 | 0 | 5 | 11 | -6 | 2 | 0.333 | 5 | 6 | 11 | 0 | 0 | 2 | 2 | 0 | 2 | 113 | 42 | 39 | 30 | 12 | 122 | 42 | 6 | 46 | 8 | 1 | 12.50% | 3 | 2 | 33.33% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 64 | 41 | 72 | 24 | 47 | 23 | 30.8% | 4.4% | 91.0% | 95.4 | Unlucky | |
10 | 6 | 1 | 5 | 0 | 0 | 0 | 0 | 0 | 9 | 24 | -15 | 2 | 0.167 | 9 | 13 | 22 | 0 | 0 | 1 | 5 | 3 | 0 | 221 | 83 | 67 | 71 | 0 | 227 | 71 | 14 | 89 | 24 | 2 | 8.33% | 7 | 0 | 100.00% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 129 | 78 | 134 | 49 | 95 | 48 | 22.6% | 4.1% | 89.4% | 93.5 | Unlucky | |
11 | 4 | 1 | 2 | 0 | 1 | 0 | 0 | 0 | 10 | 12 | -2 | 4 | 0.500 | 10 | 17 | 27 | 0 | 0 | 3 | 2 | 4 | 1 | 154 | 46 | 55 | 51 | 2 | 136 | 45 | 10 | 65 | 7 | 1 | 14.29% | 5 | 2 | 60.00% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 87 | 55 | 88 | 34 | 64 | 31 | 47.4% | 6.5% | 91.2% | 97.7 | DULL | |
12 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 3 | 4 | 4 | 1.000 | 7 | 10 | 17 | 0 | 0 | 2 | 2 | 3 | 0 | 64 | 27 | 13 | 24 | 0 | 65 | 31 | 4 | 30 | 13 | 2 | 15.38% | 2 | 0 | 100.00% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 42 | 24 | 44 | 17 | 33 | 18 | 62.5% | 10.9% | 95.4% | 106.3 | LUCKY | |
13 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 8 | 6 | 2 | 3 | 0.750 | 8 | 13 | 21 | 0 | 0 | 1 | 5 | 2 | 0 | 74 | 24 | 29 | 19 | 7 | 72 | 31 | 6 | 41 | 8 | 2 | 25.00% | 3 | 2 | 33.33% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 43 | 25 | 45 | 18 | 36 | 19 | 60.0% | 10.8% | 91.7% | 102.5 | LUCKY | |
14 | 6 | 1 | 3 | 0 | 1 | 0 | 1 | 0 | 15 | 18 | -3 | 6 | 0.500 | 15 | 22 | 37 | 0 | 0 | 4 | 5 | 4 | 2 | 204 | 84 | 63 | 52 | 9 | 229 | 80 | 24 | 111 | 20 | 3 | 15.00% | 12 | 1 | 91.67% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 132 | 80 | 132 | 50 | 101 | 51 | 41.4% | 7.4% | 92.1% | 99.5 | DULL | |
15 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 7 | 8 | -1 | 2 | 0.500 | 7 | 12 | 19 | 1 | 0 | 2 | 2 | 3 | 0 | 77 | 28 | 24 | 25 | 0 | 70 | 14 | 2 | 38 | 8 | 1 | 12.50% | 1 | 0 | 100.00% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 47 | 31 | 40 | 15 | 32 | 16 | 42.9% | 9.1% | 88.6% | 97.7 | FUN | |
16 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 3 | 4 | 4 | 1.000 | 7 | 10 | 17 | 0 | 0 | 1 | 3 | 3 | 0 | 58 | 14 | 15 | 29 | 0 | 83 | 26 | 6 | 48 | 10 | 1 | 10.00% | 3 | 1 | 66.67% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 39 | 22 | 47 | 18 | 33 | 16 | 75.0% | 12.1% | 96.4% | 108.5 | LUCKY | |
17 | 3 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 7 | 9 | -2 | 2 | 0.333 | 7 | 11 | 18 | 0 | 0 | 3 | 3 | 1 | 0 | 112 | 31 | 34 | 47 | 0 | 117 | 30 | 12 | 47 | 3 | 0 | 0.00% | 6 | 0 | 100.00% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 64 | 39 | 66 | 23 | 48 | 25 | 43.8% | 6.3% | 92.3% | 98.6 | DULL | |
18 | 2 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 3 | 7 | -4 | 2 | 0.500 | 3 | 3 | 6 | 0 | 0 | 0 | 0 | 2 | 1 | 59 | 23 | 12 | 22 | 10 | 87 | 22 | 12 | 45 | 5 | 0 | 0.00% | 6 | 0 | 100.00% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 37 | 21 | 54 | 19 | 33 | 15 | 30.0% | 5.1% | 92.0% | 97.0 | DULL | |
19 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 1 | 5 | 2 | 1.000 | 6 | 9 | 15 | 0 | 0 | 2 | 3 | 1 | 0 | 40 | 17 | 13 | 10 | 0 | 28 | 16 | 2 | 17 | 9 | 4 | 44.44% | 1 | 0 | 100.00% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 23 | 14 | 21 | 9 | 15 | 8 | 66.7% | 15.0% | 96.4% | 111.4 | LUCKY | |
20 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 7 | 6 | 1 | 2 | 0.500 | 7 | 13 | 20 | 0 | 0 | 1 | 6 | 0 | 0 | 72 | 20 | 32 | 20 | 0 | 84 | 28 | 4 | 33 | 6 | 0 | 0.00% | 2 | 1 | 50.00% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 42 | 26 | 46 | 15 | 31 | 15 | 58.3% | 9.7% | 92.9% | 102.6 | LUCKY | |
21 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 6 | 5 | 1 | 3 | 0.750 | 6 | 9 | 15 | 0 | 0 | 2 | 2 | 2 | 0 | 68 | 32 | 20 | 15 | 7 | 75 | 27 | 8 | 39 | 1 | 0 | 0.00% | 4 | 1 | 75.00% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 42 | 27 | 50 | 16 | 32 | 15 | 60.0% | 8.8% | 93.3% | 102.2 | DULL | |
22 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 3 | 5 | 4 | 1.000 | 8 | 11 | 19 | 0 | 0 | 0 | 4 | 4 | 0 | 82 | 25 | 33 | 24 | 0 | 67 | 20 | 6 | 24 | 8 | 3 | 37.50% | 3 | 0 | 100.00% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 42 | 26 | 43 | 16 | 33 | 16 | 62.5% | 9.8% | 95.5% | 105.3 | LUCKY | |
23 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 6 | 8 | -2 | 0 | 0.000 | 6 | 9 | 15 | 0 | 0 | 2 | 1 | 3 | 0 | 64 | 22 | 16 | 26 | 0 | 81 | 36 | 4 | 24 | 8 | 4 | 50.00% | 2 | 0 | 100.00% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 41 | 25 | 46 | 16 | 31 | 15 | 20.0% | 9.4% | 90.1% | 99.5 | FUN | |
_Vs Division | 29 | 9 | 15 | 0 | 2 | 0 | 2 | 1 | 85 | 95 | -10 | 27 | 0.466 | 85 | 133 | 218 | 0 | 0 | 22 | 31 | 28 | 4 | 1040 | 388 | 309 | 335 | 18 | 1078 | 324 | 84 | 511 | 105 | 20 | 19.05% | 42 | 3 | 92.86% | 0 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 629 | 381 | 645 | 241 | 482 | 244 | 41.4% | 8.2% | 91.2% | 99.4 | DULL | |
_Vs Conference | 55 | 21 | 22 | 0 | 4 | 1 | 5 | 2 | 165 | 169 | -4 | 63 | 0.573 | 165 | 264 | 429 | 1 | 0 | 48 | 57 | 51 | 11 | 2027 | 743 | 622 | 635 | 56 | 2027 | 645 | 183 | 949 | 160 | 30 | 18.75% | 85 | 18 | 78.82% | 1 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 1181 | 724 | 1253 | 462 | 910 | 453 | 47.2% | 8.1% | 91.7% | 99.8 | DULL | |
_Since Last GM Reset | 80 | 33 | 31 | 0 | 4 | 1 | 7 | 4 | 242 | 239 | 3 | 93 | 0.581 | 242 | 380 | 622 | 2 | 0 | 66 | 90 | 75 | 14 | 2910 | 1048 | 902 | 926 | 92 | 2978 | 968 | 255 | 1381 | 247 | 48 | 19.43% | 121 | 25 | 79.34% | 1 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 1713 | 1052 | 1831 | 675 | 1320 | 657 | 47.5% | 8.3% | 92.0% | 100.3 | DULL | |
Total | 80 | 33 | 31 | 0 | 4 | 1 | 7 | 4 | 242 | 239 | 3 | 93 | 0.581 | 242 | 380 | 622 | 2 | 0 | 66 | 90 | 75 | 14 | 2910 | 1048 | 902 | 926 | 92 | 2978 | 968 | 255 | 1381 | 247 | 48 | 19.43% | 121 | 25 | 79.34% | 1 | 1043 | 2027 | 51.46% | 990 | 1954 | 50.67% | 587 | 1160 | 50.60% | 1713 | 1052 | 1831 | 675 | 1320 | 657 | 47.5% | 8.3% | 92.0% | 100.3 | DULL |
Puck Time | |
---|---|
Offensive Zone | 21 |
Neutral Zone | 16 |
Defensive Zone | 22 |
Puck Time | |
---|---|
Offensive Zone Start | 2027 |
Neutral Zone Start | 1160 |
Defensive Zone Start | 1954 |
Puck Time | |
---|---|
With Puck | 29 |
Without Puck | 31 |
Faceoffs | |
---|---|
Faceoffs Won | 2620 |
Faceoffs Lost | 2521 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 13.1 | 9.57 |
2nd Period | 24.4 | 20.31 |
3rd Period | 36.0 | 30.68 |
Overtime | 37.1 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.8 | 0.64 |
2nd Period | 2.0 | 1.65 |
3rd Period | 2.9 | 2.67 |
Overtime | 3.1 | 2.83 |
Even Strenght Goal | 191 |
---|---|
PP Goal | 48 |
PK Goal | 1 |
Empty Net Goal | 2 |
Home | Away | |
---|---|---|
Win | 23 | 21 |
Lost | 16 | 15 |
Overtime Lost | 1 | 4 |
PP Attempt | 247 |
---|---|
PP Goal | 48 |
PK Attempt | 121 |
PK Goal Against | 25 |
Home | |
---|---|
Shots For | 36.4 |
Shots Against | 37.2 |
Goals For | 3.0 |
Goals Against | 3.0 |
Hits | 17.3 |
Shots Blocked | 12.1 |
Pim | 3.2 |
Projected Total Cap Hit | 78,512,500$ |
Projected Cap Space | 2,987,500$ |
Retains And Buyout Cap Hit | 2,750,000$ |
Salary Cap To Date | 71,657,977$ |
Players In Salary Cap | 21 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|
Brandon Pirri ![]() | C/LW/RW | 29 | 775,000$ | 775,000$ | 1,250,000$ | 1,250,000$ | 1,250,000$ | 1,250,000$ | |||
Brandon Sutter | C/RW | 31 | 4,375,000$ | 4,375,000$ | 2,250,000$ | 2,250,000$ | 2,250,000$ | 2,250,000$ | |||
Braydon Coburn ![]() | D | 35 | 1,700,000$ | 1,700,000$ | |||||||
Brenden Dillon ![]() | D | 29 | 900,000$ | 900,000$ | 900,000$ | 900,000$ | |||||
Carter Hart ![]() | C | 22 | 730,833$ | 730,833$ | 2,500,000$ | 2,500,000$ | 2,500,000$ | 2,500,000$ | |||
Darnell Nurse | D | 25 | 5,600,000$ | 5,600,000$ | 5,600,000$ | ||||||
David Backes ![]() | C/RW | 36 | 685,000$ | 685,000$ | |||||||
David Schlemko ![]() | D | 33 | 685,000$ | 685,000$ | 685,000$ | ||||||
Evander Kane | LW | 29 | 7,000,000$ | 7,000,000$ | 7,000,000$ | 7,000,000$ | |||||
Jonathan Drouin | LW | 25 | 5,500,000$ | 5,500,000$ | 5,500,000$ | 5,500,000$ | |||||
Keith Yandle | D | 33 | 6,350,000$ | 6,350,000$ | 6,350,000$ | 6,350,000$ | |||||
Mika Zibanejad | C | 27 | 5,350,000$ | 5,350,000$ | 5,350,000$ | ||||||
Mikael Backlund | C | 31 | 5,350,000$ | 5,350,000$ | 5,350,000$ | 5,350,000$ | |||||
Mike Hoffman | LW/RW | 30 | 4,250,000$ | 4,250,000$ | 4,250,000$ | 4,250,000$ | 4,250,000$ | ||||
Patrik Berglund ![]() | C/LW | 32 | 685,000$ | 685,000$ | |||||||
Ryan Strome | C/RW | 27 | 7,110,000$ | 7,110,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | |||
Scott Laughton ![]() | C/LW | 26 | 2,300,000$ | 2,300,000$ | |||||||
Steven Santini ![]() | D | 25 | 1,416,667$ | 1,416,667$ | |||||||
Steven Stamkos | C/RW | 30 | 8,500,000$ | 8,500,000$ | 8,500,000$ | 8,500,000$ | |||||
Thomas Greiss ![]() | D | 34 | 1,500,000$ | 1,500,000$ | 1,500,000$ | 1,500,000$ | 1,500,000$ | ||||
Zach Werenski ![]() | D | 23 | 5,000,000$ | 5,000,000$ | 5,000,000$ |
Forward Lines | |||||||
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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 |
---|---|---|---|---|---|
Jackson van de Leest | 2 | 95 | |||
Jacob-Bernard Docker | 1 | ||||
Marat Khusnutdinov | 2 | 23 | |||
Nicklas Nordgren | 1 | ||||
Petrus Palmu | 1 | ||||
Sam Hentges | 1 | ||||
Stephen Halliday | 2 | 71 | |||
Thimo Nickl | 2 | 47 |
Date | Matchup | Result | Detail | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2020-08-17 | @ | Stars1,Kings2 (SO) | RECAP | |||||||||||
2020-08-18 | @ | Stars2,Wild3 | RECAP | |||||||||||
2020-08-20 | @ | Canucks2,Stars3 | RECAP | |||||||||||
2020-08-22 | @ | Kings2,Stars3 (SO) | RECAP | |||||||||||
2020-08-24 | @ | Stars3,Avalanche1 | RECAP | |||||||||||
2020-08-26 | @ | Stars1,Wild5 | RECAP | |||||||||||
2020-08-28 | @ | Golden Knights4,Stars0 | RECAP | |||||||||||
2020-08-30 | @ | Stars4,Kings6 | RECAP | |||||||||||
2020-09-01 | @ | Bruins4,Stars1 | RECAP | |||||||||||
2020-09-03 | @ | Stars1,Coyotes4 | RECAP | |||||||||||
2020-09-05 | @ | Panthers2,Stars4 | RECAP | |||||||||||
2020-09-07 | @ | Stars1,Jets2 | RECAP | |||||||||||
2020-09-09 | @ | Flames3,Stars5 | RECAP | |||||||||||
2020-09-11 | @ | Stars2,Kings1 | RECAP | |||||||||||
2020-09-13 | @ | Stars6,Canucks2 | RECAP | |||||||||||
2020-09-15 | @ | Blues5,Stars3 | RECAP | |||||||||||
2020-09-17 | @ | Canucks3,Stars4 | RECAP | |||||||||||
2020-09-20 | @ | Stars4,Golden Knights2 | RECAP | |||||||||||
2020-09-21 | @ | Golden Knights1,Stars5 | RECAP | |||||||||||
2020-09-23 | @ | Stars4,Golden Knights3 (SO) | RECAP | |||||||||||
2020-09-25 | @ | Bruins2,Stars3 (SO) | RECAP | |||||||||||
2020-09-27 | @ | Stars1,Bruins5 | RECAP | |||||||||||
2020-09-28 | @ | Oilers4,Stars6 | RECAP | |||||||||||
2020-10-01 | @ | Coyotes5,Stars1 | RECAP | |||||||||||
2020-10-02 | @ | Stars4,Canadiens1 | RECAP | |||||||||||
2020-10-04 | @ | Avalanche4,Stars5 (SO) | RECAP | |||||||||||
2020-10-07 | @ | Stars4,Blues5 (SO) | RECAP | |||||||||||
2020-10-10 | @ | Stars4,Oilers3 (SO) | RECAP | |||||||||||
2020-10-11 | @ | Jets1,Stars5 | RECAP | |||||||||||
2020-10-13 | @ | Stars1,Coyotes3 | RECAP | |||||||||||
2020-10-15 | @ | Blues4,Stars2 | RECAP | |||||||||||
2020-10-17 | @ | Stars3,Lightning4 | RECAP | |||||||||||
2020-10-19 | @ | Oilers4,Stars2 | RECAP | |||||||||||
2020-10-21 | @ | Stars1,Coyotes5 | RECAP | |||||||||||
2020-10-23 | @ | Red Wings6,Stars1 | RECAP | |||||||||||
2020-10-25 | @ | Stars3,Blue Jackets4 | RECAP | |||||||||||
2020-10-28 | @ | Jets5,Stars4 | RECAP | |||||||||||
2020-10-29 | @ | Stars3,Maple Leafs2 | RECAP | |||||||||||
2020-10-31 | @ | Avalanche4,Stars5 | RECAP | |||||||||||
2020-11-04 | @ | Coyotes3,Stars4 | RECAP | |||||||||||
2020-11-07 | @ | Flames5,Stars1 | RECAP | |||||||||||
2020-11-08 | @ | Stars4,Flames3 (OT) | RECAP | |||||||||||
2020-11-10 | @ | Stars1,Ducks2 | RECAP | |||||||||||
2020-11-12 | @ | Ducks1,Stars3 | RECAP | |||||||||||
2020-11-14 | @ | Wild4,Stars2 | RECAP | |||||||||||
2020-11-16 | @ | Stars3,Rangers1 | RECAP | |||||||||||
2020-11-17 | @ | Stars1,Oilers2 (OT) | RECAP | |||||||||||
2020-11-19 | @ | Stars4,Jets2 | RECAP | |||||||||||
2020-11-21 | @ | Stars5,Senators2 | RECAP | |||||||||||
2020-11-22 | @ | Rangers2,Stars4 | RECAP | |||||||||||
2020-11-23 | @ | Stars3,Flames2 | RECAP | |||||||||||
2020-11-25 | @ | Sabres3,Stars2 | RECAP | |||||||||||
2020-11-26 | @ | Blues3,Stars2 | RECAP | |||||||||||
2020-11-28 | @ | Stars2,Ducks6 | RECAP | |||||||||||
2020-12-03 | @ | Ducks3,Stars4 (OT) | RECAP | |||||||||||
2020-12-04 | @ | Stars4,Wild3 (SO) | RECAP | |||||||||||
2020-12-06 | @ | Stars3,Canucks2 | RECAP | |||||||||||
2020-12-07 | @ | Kings2,Stars4 | RECAP | |||||||||||
2020-12-08 | @ | Senators4,Stars3 (SO) | RECAP | |||||||||||
2020-12-10 | @ | Stars2,Red Wings1 (SO) | RECAP | |||||||||||
2020-12-11 | @ | Stars6,Flyers1 | RECAP | |||||||||||
2020-12-12 | @ | Flames4,Stars1 | RECAP | |||||||||||
2020-12-14 | @ | Stars2,Jets4 | RECAP | |||||||||||
2020-12-15 | @ | Coyotes4,Stars1 | RECAP | |||||||||||
2020-12-17 | @ | Stars4,Devils1 | RECAP | |||||||||||
2020-12-18 | @ | Lightning2,Stars4 | RECAP | |||||||||||
2020-12-22 | @ | Devils2,Stars4 | RECAP | |||||||||||
2020-12-23 | @ | Stars2,Avalanche4 | RECAP | |||||||||||
2020-12-25 | @ | Maple Leafs6,Stars4 | RECAP | |||||||||||
2020-12-27 | @ | Jets3,Stars4 (OT) | RECAP | |||||||||||
Trade Deadline --- Trades cant be done after this day is simulated! | ||||||||||||||
2020-12-29 | @ | Stars2,Panthers3 (SO) | RECAP | |||||||||||
2021-01-01 | @ | Stars6,Blues2 | RECAP | |||||||||||
2021-01-02 | @ | Blue Jackets4,Stars3 | RECAP | |||||||||||
2021-01-03 | @ | Stars3,Sabres2 | RECAP | |||||||||||
2021-01-06 | @ | Wild1,Stars2 (OT) | RECAP | |||||||||||
2021-01-10 | @ | Avalanche2,Stars4 | RECAP | |||||||||||
2021-01-14 | @ | Stars5,Blues2 | RECAP | |||||||||||
2021-01-16 | @ | Wild2,Stars4 | RECAP | |||||||||||
2021-01-17 | @ | Stars2,Sabres4 | RECAP | |||||||||||
2021-01-21 | @ | Canadiens2,Stars3 | RECAP | |||||||||||
2021-01-26 | @ | |||||||||||||
2021-01-27 | @ |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
75,762,500$ | 2,750,000$ | 78,512,500$ | 2,987,500$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | American Airlines Center | |
City | Dallas | ||
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 | 189241 | 156390 | 62493 | 126720 | 37614 |
Attendance PCT | 78.85% | 78.20% | 78.12% | 79.20% | 94.04% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
1 | 14311 - 79.51% | 4,135,856$ | 165,434,254$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
75,762,500$ | 75,762,500$ | 0$ | 2,750,000$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
74,066,119$ | 75,762,500$ | 71,657,977$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
4,135,856$ | 9 | 468,638$ | 4,217,742$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
4,217,742$ | 78,512,500$ | 277,899,631$ | 277,817,745$ |
Left Wing | Center | Right Wing | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Defense #1 | Defense #2 | Goalie | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Year | Round 1 | Round 2 | Round 3 | Round 4 |
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6 | ||||
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