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Full Scoreboard ยป |
Anaheim Ducks 29-19-3, 61pts · 2nd 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/LW/RW | 100.00 | 53 | 3 | 99 | 86 | 79 | 94 | 94 | 99 | 95 | 99 | 99 | 72 | 79 | 72 | 72 | 83 | 77 | 84 | 26 | 8,500,000$/5yrs | |||
![]() | 0 | C | 100.00 | 60 | 8 | 90 | 89 | 79 | 99 | 88 | 94 | 84 | 93 | 96 | 57 | 69 | 74 | 76 | 79 | 77 | 80 | 28 | 9,225,000$/4yrs | |||
![]() | 0 | C/LW | 100.00 | 79 | 13 | 73 | 86 | 81 | 99 | 99 | 82 | 82 | 84 | 88 | 33 | 75 | 68 | 69 | 69 | 77 | 74 | 23 | 3,667,065$/3yrs | |||
![]() | 0 | RW | 100.00 | 61 | 3 | 95 | 85 | 60 | 98 | 81 | 84 | 36 | 88 | 75 | 65 | 89 | 68 | 71 | 80 | 77 | 74 | 34 | 4,850,000$/2yrs | |||
![]() | 0 | C | 100.00 | 67 | 28 | 70 | 80 | 74 | 80 | 79 | 93 | 76 | 86 | 85 | 63 | 80 | 48 | 48 | 87 | 78 | 74 | 22 | 1,500,000$/3yrs | |||
![]() | 0 | LW | 100.00 | 79 | 12 | 98 | 80 | 74 | 74 | 92 | 72 | 30 | 77 | 81 | 78 | 45 | 68 | 70 | 79 | 77 | 73 | 29 | 4,250,000$/2yrs | |||
![]() | 15 | C | 100.00 | 67 | 26 | 86 | 69 | 84 | 96 | 79 | 79 | 96 | 80 | 67 | 57 | 68 | 84 | 90 | 76 | 73 | 72 | 36 | 3,500,000$/3yrs | |||
![]() | 0 | LW/RW | 100.00 | 98 | 35 | 94 | 74 | 68 | 72 | 56 | 62 | 41 | 60 | 75 | 96 | 25 | 65 | 66 | 76 | 67 | 69 | 26 | 2,750,000$/4yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 75 | 15 | 99 | 75 | 68 | 88 | 91 | 58 | 97 | 63 | 64 | 74 | 25 | 68 | 69 | 73 | 77 | 67 | 32 | 1,650,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 35 | 1 | 99 | 82 | 68 | 79 | 83 | 79 | 18 | 75 | 59 | 34 | 25 | 64 | 64 | 58 | 77 | 64 | 26 | 1,200,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 49 | 24 | 86 | 69 | 80 | 83 | 68 | 67 | 25 | 56 | 66 | 32 | 63 | 85 | 91 | 67 | 77 | 61 | 36 | 685,000$/1yrs | |||
![]() | 0 | C/RW | 100.00 | 44 | 1 | 99 | 75 | 73 | 70 | 67 | 65 | 60 | 64 | 67 | 33 | 25 | 58 | 59 | 54 | 52 | 60 | 25 | 685,000$/1yrs | |||
![]() | 0 | D | 99.00 | 72 | 16 | 93 | 82 | 78 | 98 | 94 | 69 | 25 | 67 | 51 | 84 | 25 | 71 | 74 | 70 | 77 | 75 | 32 | 5,500,000$/3yrs | |||
![]() | 0 | D | 99.00 | 52 | 2 | 96 | 90 | 68 | 99 | 90 | 97 | 25 | 79 | 60 | 71 | 53 | 69 | 70 | 73 | 77 | 74 | 30 | 5,250,000$/5yrs | |||
![]() | 0 | D | 100.00 | 73 | 43 | 61 | 82 | 68 | 83 | 78 | 77 | 25 | 72 | 50 | 71 | 75 | 70 | 70 | 57 | 77 | 70 | 26 | 3,500,000$/5yrs | |||
![]() | 0 | D | 100.00 | 62 | 13 | 98 | 72 | 61 | 95 | 92 | 57 | 25 | 53 | 47 | 86 | 51 | 78 | 80 | 65 | 77 | 70 | 34 | 685,000$/1yrs | |||
![]() | 0 | D | 100.00 | 46 | 1 | 99 | 81 | 77 | 87 | 76 | 64 | 25 | 54 | 51 | 86 | 25 | 63 | 63 | 54 | 77 | 69 | 24 | 1,525,000$/3yrs | |||
![]() | 0 | D | 100.00 | 53 | 1 | 99 | 72 | 86 | 77 | 85 | 52 | 25 | 47 | 42 | 89 | 25 | 57 | 57 | 53 | 77 | 67 | 24 | 1,250,000$/3yrs | |||
Scratches | ||||||||||||||||||||||||||
TEAM AVERAGE | 99.89 | 63 | 14 | 91 | 79 | 74 | 87 | 83 | 75 | 49 | 72 | 68 | 66 | 51 | 68 | 70 | 70 | 75 | 71 |
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 | 89 | 89 | 99 | 86 | 91 | 92 | 72 | 96 | 92 | 84 | 82 | 72 | 73 | 77 | 77 | 84 | 28 | 8,500,000$/4yrs |
![]() | 0 | 100.00 | 76 | 91 | 99 | 81 | 79 | 80 | 80 | 80 | 81 | 76 | 87 | 65 | 67 | 66 | 77 | 77 | 32 | 2,000,000$/1yrs |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 100.00 | 83 | 90 | 99 | 84 | 85 | 86 | 76 | 88 | 87 | 80 | 85 | 69 | 70 | 72 | 77 | 81 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Jeremy Colliton | 59 | 51 | 94 | 99 | 70 | 57 | 63 | CAN | 38 | 1 | 2,500,000$ |
General Manager | Fred Morier |
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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 | Mark Scheifele | 0 | C | 51 | 31 | 26 | 57 | 11 | 10 | 0 | 64 | 221 | 64 | 126 | 14.03% | 22 | 21.32 | 7 | 2 | 9 | 101 | 0 | 0 | 0 | 49 | 4 | 1 | 52.48% | 1170 | 49 | 18 | 2 | 1 | 1.05 | 0 | 0 | |
2 | Leon Draisaitl | 0 | C/LW/RW | 51 | 17 | 38 | 55 | 12 | 2 | 0 | 29 | 215 | 50 | 101 | 7.91% | 23 | 21.62 | 2 | 7 | 9 | 101 | 0 | 1 | 1 | 56 | 4 | 2 | 55.05% | 198 | 44 | 18 | 0 | 0 | 1.00 | 0 | 5 | |
3 | Barrett Hayton | 0 | C | 51 | 17 | 28 | 45 | 2 | 16 | 0 | 90 | 164 | 46 | 85 | 10.37% | 26 | 18.92 | 2 | 4 | 6 | 101 | 0 | 0 | 0 | 50 | 1 | 0 | 49.39% | 733 | 22 | 14 | 0 | 1 | 0.93 | 2 | 5 | |
4 | Mats Zuccarello | 0 | RW | 51 | 15 | 24 | 39 | 0 | 2 | 0 | 23 | 145 | 34 | 83 | 10.34% | 22 | 17.40 | 3 | 2 | 5 | 101 | 0 | 0 | 0 | 0 | 3 | 0 | 30.43% | 46 | 18 | 17 | 0 | 0 | 0.88 | 2 | 5 | |
5 | Pierre-Luc Dubois | 0 | C/LW | 51 | 15 | 20 | 35 | 2 | 22 | 0 | 109 | 123 | 29 | 69 | 12.20% | 3 | 18.65 | 1 | 5 | 6 | 101 | 1 | 0 | 1 | 50 | 4 | 0 | 48.78% | 41 | 30 | 4 | 0 | 0 | 0.74 | 1 | 2 | |
6 | Tyson Barrie | 0 | D | 51 | 2 | 27 | 29 | -12 | 6 | 0 | 18 | 109 | 50 | 58 | 1.83% | 68 | 25.00 | 0 | 4 | 4 | 103 | 0 | 0 | 0 | 60 | 1 | 0 | 0.00% | 0 | 38 | 51 | 0 | 0 | 0.45 | 0 | 0 | |
7 | Tanner Pearson | 0 | LW | 51 | 13 | 14 | 27 | -5 | 4 | 0 | 95 | 134 | 36 | 70 | 9.70% | 38 | 16.26 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 35.71% | 42 | 36 | 22 | 0 | 1 | 0.65 | 0 | 0 | |
8 | Ryan Getzlaf | 15 | C | 51 | 11 | 11 | 22 | -7 | 19 | 5 | 79 | 79 | 21 | 43 | 13.92% | 17 | 15.05 | 1 | 4 | 5 | 101 | 0 | 0 | 0 | 0 | 0 | 2 | 56.60% | 659 | 8 | 8 | 0 | 0 | 0.57 | 0 | 0 | |
9 | Jake Muzzin | 0 | D | 51 | 4 | 17 | 21 | -11 | 8 | 0 | 74 | 72 | 26 | 27 | 5.56% | 90 | 25.21 | 0 | 2 | 2 | 103 | 0 | 0 | 0 | 60 | 0 | 3 | 0.00% | 0 | 13 | 75 | 0 | 0 | 0.33 | 0 | 0 | |
10 | Nikolay Goldobin | 0 | LW/RW | 51 | 11 | 9 | 20 | -2 | 0 | 0 | 4 | 130 | 29 | 79 | 8.46% | 1 | 13.28 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 38.24% | 34 | 29 | 0 | 0 | 0 | 0.59 | 0 | 0 | |
11 | Anthony DeAngelo | 0 | D | 51 | 2 | 13 | 15 | 8 | 42 | 0 | 95 | 50 | 18 | 23 | 4.00% | 57 | 20.70 | 1 | 0 | 1 | 101 | 0 | 0 | 0 | 40 | 0 | 0 | 0.00% | 0 | 14 | 51 | 0 | 0 | 0.28 | 1 | 1 | |
12 | Tyler Motte | 0 | LW/RW | 51 | 7 | 8 | 15 | 7 | 20 | 0 | 146 | 51 | 16 | 36 | 13.73% | 44 | 18.06 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 34.43% | 61 | 3 | 26 | 0 | 0 | 0.33 | 0 | 0 | |
13 | Kris Russell | 0 | D | 51 | 2 | 12 | 14 | 9 | 0 | 0 | 27 | 50 | 32 | 12 | 4.00% | 87 | 21.26 | 1 | 0 | 1 | 101 | 0 | 1 | 1 | 62 | 0 | 0 | 0.00% | 0 | 2 | 42 | 0 | 0 | 0.26 | 0 | 0 | |
14 | Luke Glendening | 0 | C/LW/RW | 51 | 7 | 3 | 10 | -6 | 0 | 0 | 34 | 36 | 13 | 22 | 19.44% | 13 | 7.59 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 10 | 0 | 1 | 54.80% | 177 | 5 | 8 | 0 | 0 | 0.52 | 0 | 0 | |
15 | Jonas Siegenthaler | 0 | D | 51 | 1 | 7 | 8 | 3 | 0 | 0 | 14 | 38 | 11 | 12 | 2.63% | 56 | 14.13 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0.00% | 0 | 5 | 33 | 0 | 0 | 0.22 | 0 | 1 | |
16 | Corey Perry | 0 | LW/RW | 51 | 2 | 3 | 5 | -7 | 4 | 0 | 14 | 19 | 6 | 13 | 10.53% | 4 | 7.54 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 15 | 0 | 0 | 22.22% | 9 | 5 | 0 | 0 | 0 | 0.26 | 0 | 0 | |
17 | Jacob Larsson | 0 | D | 51 | 0 | 3 | 3 | 4 | 0 | 0 | 6 | 41 | 26 | 19 | 0.00% | 54 | 14.33 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 8 | 0 | 0 | 0.00% | 0 | 5 | 27 | 0 | 0 | 0.08 | 0 | 0 | |
18 | Michael Amadio | 0 | C/RW | 30 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0.01 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
Team Total or Average | 897 | 157 | 263 | 420 | 8 | 155 | 5 | 921 | 1677 | 507 | 878 | 9.36% | 625 | 16.85 | 18 | 30 | 48 | 1028 | 1 | 2 | 3 | 467 | 25 | 10 | 51.74% | 3170 | 326 | 414 | 2 | 3 | 0.56 | 6 | 19 |
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 | John Gibson | Ducks | 34 | 19 | 14 | 0 | 0.909 | 3.06 | 1981 | 2 | 0 | 101 | 1115 | 469 | 1 | 0 | 0.867 | 15 | 33 | 18 | 4 | 1 | 3 |
2 | Martin Jones | Ducks | 19 | 10 | 5 | 3 | 0.914 | 3.04 | 1107 | 0 | 0 | 56 | 654 | 327 | 2 | 0 | 0.667 | 3 | 18 | 33 | 3 | 1 | 1 |
Team Total or Average | 53 | 29 | 19 | 3 | 0.911 | 3.05 | 3089 | 2 | 0 | 157 | 1769 | 796 | 3 | 0 | 0.833 | 18 | 51 | 51 | 7 | 2 | 4 |
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 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 2 | 5 | 4 | 1.000 | 7 | 12 | 19 | 0 | 0 | 1 | 5 | 1 | 0 | 61 | 17 | 24 | 20 | 0 | 79 | 30 | 4 | 36 | 2 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 43 | 27 | 43 | 16 | 32 | 16 | 77.8% | 11.5% | 97.5% | 108.9 | LUCKY | |
2 | 3 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 12 | 13 | -1 | 3 | 0.500 | 12 | 21 | 33 | 0 | 0 | 4 | 3 | 4 | 1 | 104 | 35 | 36 | 32 | 1 | 109 | 35 | 4 | 60 | 8 | 3 | 37.50% | 2 | 1 | 50.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 64 | 38 | 67 | 25 | 51 | 26 | 42.9% | 11.5% | 88.1% | 99.6 | FUN | |
3 | 6 | 4 | 1 | 0 | 1 | 0 | 0 | 0 | 16 | 11 | 5 | 10 | 0.833 | 16 | 28 | 44 | 0 | 0 | 6 | 4 | 5 | 1 | 207 | 82 | 75 | 45 | 5 | 174 | 75 | 10 | 107 | 26 | 1 | 3.85% | 5 | 1 | 80.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 134 | 79 | 124 | 50 | 102 | 54 | 60.0% | 7.7% | 93.7% | 101.4 | DULL | |
4 | 6 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 24 | 14 | 10 | 10 | 0.833 | 24 | 42 | 66 | 0 | 0 | 7 | 9 | 8 | 0 | 219 | 78 | 82 | 59 | 0 | 195 | 59 | 26 | 125 | 14 | 2 | 14.29% | 13 | 4 | 69.23% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 130 | 78 | 127 | 50 | 101 | 50 | 68.8% | 11.0% | 92.8% | 103.8 | LUCKY | |
5 | 4 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 12 | 12 | 0 | 5 | 0.625 | 12 | 19 | 31 | 0 | 0 | 5 | 5 | 1 | 1 | 129 | 37 | 58 | 32 | 6 | 154 | 64 | 12 | 85 | 12 | 3 | 25.00% | 6 | 0 | 100.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 88 | 52 | 89 | 34 | 68 | 34 | 42.9% | 9.3% | 92.2% | 101.5 | LUCKY | |
6 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 5 | 11 | -6 | 0 | 0.000 | 5 | 9 | 14 | 0 | 0 | 3 | 2 | 0 | 0 | 52 | 21 | 20 | 11 | 0 | 85 | 30 | 8 | 37 | 3 | 1 | 33.33% | 4 | 2 | 50.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 38 | 22 | 45 | 16 | 35 | 17 | 30.8% | 9.6% | 87.1% | 96.7 | FUN | |
7 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 6 | -4 | 0 | 0.000 | 2 | 4 | 6 | 0 | 0 | 1 | 0 | 1 | 0 | 45 | 13 | 13 | 19 | 0 | 33 | 19 | 2 | 18 | 0 | 0 | 0.00% | 1 | 1 | 0.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 20 | 12 | 23 | 7 | 15 | 7 | 28.6% | 4.4% | 81.8% | 86.3 | Unlucky | |
8 | 4 | 2 | 1 | 0 | 0 | 0 | 0 | 1 | 17 | 12 | 5 | 5 | 0.625 | 17 | 30 | 47 | 0 | 0 | 6 | 4 | 7 | 0 | 141 | 36 | 50 | 53 | 5 | 149 | 41 | 29 | 59 | 10 | 1 | 10.00% | 9 | 3 | 66.67% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 85 | 52 | 92 | 35 | 67 | 33 | 64.0% | 12.1% | 91.9% | 104.0 | LUCKY | |
9 | 4 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 14 | 12 | 2 | 6 | 0.750 | 14 | 23 | 37 | 0 | 0 | 5 | 4 | 3 | 3 | 127 | 40 | 44 | 39 | 7 | 134 | 49 | 10 | 75 | 2 | 0 | 0.00% | 5 | 1 | 80.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 79 | 46 | 97 | 33 | 68 | 34 | 56.0% | 11.0% | 91.0% | 102.1 | FUN | |
10 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | -1 | 0 | 0.000 | 2 | 3 | 5 | 0 | 0 | 0 | 2 | 0 | 0 | 39 | 14 | 14 | 11 | 0 | 44 | 15 | 2 | 17 | 2 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 21 | 13 | 22 | 8 | 15 | 7 | 40.0% | 5.1% | 93.2% | 98.3 | DULL | |
11 | 4 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 13 | 15 | -2 | 6 | 0.750 | 13 | 20 | 33 | 0 | 0 | 4 | 1 | 6 | 2 | 123 | 43 | 33 | 43 | 9 | 131 | 46 | 6 | 73 | 16 | 2 | 12.50% | 3 | 1 | 66.67% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 83 | 47 | 92 | 37 | 70 | 36 | 44.0% | 10.6% | 88.5% | 99.1 | FUN | |
12 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 9 | 7 | 2 | 2 | 0.500 | 9 | 14 | 23 | 0 | 0 | 1 | 7 | 1 | 0 | 72 | 23 | 27 | 22 | 0 | 74 | 33 | 10 | 39 | 4 | 2 | 50.00% | 5 | 1 | 80.00% | 1 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 40 | 23 | 46 | 18 | 33 | 15 | 53.8% | 12.5% | 90.5% | 103.0 | FUN | |
13 | 3 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 8 | 16 | -8 | 2 | 0.333 | 8 | 11 | 19 | 0 | 0 | 2 | 5 | 1 | 0 | 108 | 42 | 29 | 37 | 0 | 120 | 30 | 14 | 57 | 4 | 2 | 50.00% | 7 | 3 | 57.14% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 62 | 36 | 65 | 24 | 51 | 25 | 31.6% | 7.4% | 86.7% | 94.1 | Unlucky | |
14 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 1 | 2 | 0 | 0 | 1 | 0 | 0 | 0 | 33 | 15 | 12 | 6 | 0 | 36 | 20 | 4 | 12 | 0 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 20 | 13 | 23 | 8 | 16 | 7 | 20.0% | 3.0% | 88.9% | 91.9 | Unlucky | |
15 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | -1 | 0 | 0.000 | 2 | 3 | 5 | 0 | 0 | 1 | 0 | 1 | 0 | 32 | 10 | 10 | 12 | 0 | 33 | 5 | 4 | 12 | 1 | 0 | 0.00% | 2 | 1 | 50.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 22 | 13 | 22 | 8 | 15 | 7 | 50.0% | 6.3% | 90.9% | 97.2 | Unlucky | |
16 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 1 | 2 | 0 | 0 | 35 | 12 | 16 | 7 | 0 | 31 | 11 | 0 | 17 | 6 | 1 | 16.67% | 0 | 0 | 0.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 24 | 15 | 19 | 7 | 16 | 9 | 66.7% | 8.6% | 96.8% | 105.3 | DULL | |
17 | 2 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 5 | 5 | 0 | 2 | 0.500 | 5 | 9 | 14 | 0 | 0 | 0 | 2 | 2 | 1 | 72 | 14 | 27 | 27 | 4 | 56 | 19 | 4 | 30 | 5 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 38 | 21 | 47 | 17 | 34 | 17 | 50.0% | 6.9% | 91.1% | 98.0 | Unlucky | |
18 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 4 | 7 | 0 | 0 | 2 | 1 | 0 | 0 | 26 | 14 | 9 | 3 | 0 | 27 | 7 | 0 | 20 | 2 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 24 | 14 | 16 | 8 | 19 | 10 | 60.0% | 11.5% | 92.6% | 104.1 | LUCKY | |
19 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 2 | 5 | -3 | 0 | 0.000 | 2 | 3 | 5 | 0 | 0 | 1 | 1 | 0 | 0 | 60 | 24 | 18 | 18 | 0 | 72 | 33 | 10 | 26 | 1 | 0 | 0.00% | 5 | 0 | 100.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 37 | 22 | 50 | 17 | 32 | 14 | 28.6% | 3.3% | 93.1% | 96.4 | DULL | |
20 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 5 | 4 | 1 | 2 | 1.000 | 5 | 5 | 10 | 0 | 0 | 2 | 0 | 2 | 2 | 29 | 9 | 8 | 10 | 5 | 33 | 7 | 0 | 24 | 2 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 25 | 14 | 19 | 9 | 20 | 10 | 55.6% | 17.2% | 87.9% | 105.1 | FUN | |
_Vs Division | 21 | 12 | 4 | 0 | 2 | 2 | 1 | 0 | 71 | 52 | 19 | 32 | 0.762 | 71 | 122 | 193 | 0 | 0 | 23 | 26 | 19 | 3 | 720 | 249 | 275 | 188 | 12 | 711 | 263 | 56 | 413 | 62 | 9 | 14.52% | 28 | 6 | 78.57% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 462 | 276 | 453 | 177 | 356 | 182 | 57.4% | 9.9% | 92.7% | 102.5 | LUCKY | |
_Vs Conference | 36 | 16 | 10 | 0 | 4 | 2 | 3 | 1 | 122 | 108 | 14 | 49 | 0.681 | 122 | 208 | 330 | 0 | 0 | 42 | 37 | 36 | 8 | 1208 | 402 | 435 | 353 | 33 | 1243 | 448 | 111 | 675 | 93 | 13 | 13.98% | 50 | 14 | 72.00% | 0 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 769 | 458 | 804 | 307 | 612 | 311 | 53.7% | 10.1% | 91.3% | 101.4 | LUCKY | |
_Since Last GM Reset | 51 | 20 | 19 | 0 | 5 | 2 | 4 | 1 | 162 | 158 | 4 | 61 | 0.598 | 162 | 266 | 428 | 0 | 0 | 53 | 57 | 43 | 11 | 1714 | 579 | 605 | 506 | 42 | 1769 | 628 | 159 | 929 | 120 | 18 | 15.00% | 74 | 19 | 74.32% | 1 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 1086 | 648 | 1139 | 434 | 868 | 437 | 50.9% | 9.5% | 91.1% | 100.5 | Unlucky | |
Total | 51 | 20 | 19 | 0 | 5 | 2 | 4 | 1 | 162 | 158 | 4 | 61 | 0.598 | 162 | 266 | 428 | 0 | 0 | 53 | 57 | 43 | 11 | 1714 | 579 | 605 | 506 | 42 | 1769 | 628 | 159 | 929 | 120 | 18 | 15.00% | 74 | 19 | 74.32% | 1 | 630 | 1188 | 53.03% | 648 | 1208 | 53.64% | 363 | 736 | 49.32% | 1086 | 648 | 1139 | 434 | 868 | 437 | 50.9% | 9.5% | 91.1% | 100.5 | Unlucky |
Puck Time | |
---|---|
Offensive Zone | 21 |
Neutral Zone | 17 |
Defensive Zone | 22 |
Puck Time | |
---|---|
Offensive Zone Start | 1188 |
Neutral Zone Start | 736 |
Defensive Zone Start | 1208 |
Puck Time | |
---|---|
With Puck | 29 |
Without Puck | 30 |
Faceoffs | |
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Faceoffs Won | 1641 |
Faceoffs Lost | 1491 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 11.4 | 9.57 |
2nd Period | 23.2 | 20.31 |
3rd Period | 33.1 | 30.68 |
Overtime | 34.0 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 1.0 | 0.64 |
2nd Period | 2.2 | 1.65 |
3rd Period | 3.0 | 2.67 |
Overtime | 3.2 | 2.83 |
Even Strenght Goal | 143 |
---|---|
PP Goal | 18 |
PK Goal | 1 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 16 | 13 |
Lost | 9 | 10 |
Overtime Lost | 1 | 2 |
PP Attempt | 120 |
---|---|
PP Goal | 18 |
PK Attempt | 74 |
PK Goal Against | 19 |
Home | |
---|---|
Shots For | 33.6 |
Shots Against | 34.7 |
Goals For | 3.2 |
Goals Against | 3.1 |
Hits | 18.2 |
Shots Blocked | 12.3 |
Pim | 3.1 |
Projected Total Cap Hit | 73,769,987$ |
Projected Cap Space | 12,730,013$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 45,834,882$ |
Players In Salary Cap | 21 |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|
Anthony DeAngelo ![]() | D | 26 | 3,500,000$ | 3,500,000$ | 2,000,000$ | 2,000,000$ | 2,000,000$ | 2,000,000$ | |||
Barrett Hayton ![]() | C | 22 | 1,500,000$ | 1,500,000$ | 1,500,000$ | 1,500,000$ | |||||
Corey Perry ![]() | LW/RW | 36 | 685,000$ | 685,000$ | |||||||
Jacob Larsson ![]() | D | 24 | 1,525,000$ | 1,525,000$ | 1,525,000$ | 1,525,000$ | |||||
Jake Muzzin | D | 32 | 5,500,000$ | 5,500,000$ | 5,000,000$ | 5,000,000$ | |||||
John Gibson ![]() ![]() | LW | 28 | 8,500,000$ | 8,500,000$ | 8,500,000$ | 8,500,000$ | 8,500,000$ | ||||
Jonas Siegenthaler ![]() | D | 24 | 1,250,000$ | 1,250,000$ | 1,250,000$ | 1,250,000$ | |||||
Kris Russell ![]() | D | 34 | 685,000$ | 685,000$ | |||||||
Leon Draisaitl | C/LW/RW | 26 | 8,500,000$ | 8,500,000$ | 11,000,000$ | 11,000,000$ | 11,000,000$ | 11,000,000$ | |||
Luke Glendening ![]() | C/LW/RW | 32 | 1,650,000$ | 1,650,000$ | 1,650,000$ | ||||||
Mark Scheifele ![]() | C | 28 | 9,225,000$ | 9,225,000$ | 9,225,000$ | 9,225,000$ | 9,225,000$ | ||||
Martin Jones ![]() | D | 32 | 2,000,000$ | 2,000,000$ | |||||||
Mats Zuccarello | RW | 34 | 4,850,000$ | 4,850,000$ | 4,850,000$ | ||||||
Michael Amadio ![]() | C/RW | 25 | 685,000$ | 685,000$ | |||||||
Nikolay Goldobin ![]() | LW/RW | 26 | 1,200,000$ | 1,200,000$ | |||||||
Pierre-Luc Dubois ![]() | C/LW | 23 | 3,667,065$ | 3,667,065$ | 3,000,000$ | 3,000,000$ | |||||
Ryan Getzlaf ![]() | C | 36 | 3,500,000$ | 3,500,000$ | 2,000,000$ | 2,000,000$ | |||||
Tanner Pearson | LW | 29 | 4,250,000$ | 4,250,000$ | 4,250,000$ | ||||||
Tyler Motte ![]() | LW/RW | 26 | 2,750,000$ | 2,750,000$ | 2,750,000$ | 2,750,000$ | 2,750,000$ | ||||
Tyson Barrie | D | 30 | 5,250,000$ | 5,250,000$ | 3,700,000$ | 3,700,000$ | 3,700,000$ | 3,700,000$ |
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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 |
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Brent Johnson | 5 | 49 | |||
Dmitri Zlodeyev | 3 | 74 | |||
Guillaume Richard | 4 | 62 | |||
Isak Rosen | 5 | 19 | |||
Kasper Simontaival | 3 | 35 | |||
Oliver Kapanen | 5 | 42 | |||
Robbie Fromm-Delorme | 2 | 83 |
Date | Matchup | Result | Detail | |||||||||||
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2022-02-18 | @ | Ducks4,Kings3 (OT) | RECAP | |||||||||||
2022-02-19 | @ | Kings5,Ducks4 (OT) | RECAP | |||||||||||
2022-02-21 | @ | Ducks3,Canucks1 | RECAP | |||||||||||
2022-02-22 | @ | Canucks2,Ducks4 | RECAP | |||||||||||
2022-02-24 | @ | Ducks3,Coyotes2 | RECAP | |||||||||||
2022-02-26 | @ | Flames1,Ducks4 | RECAP | |||||||||||
2022-03-01 | @ | Oilers1,Ducks3 | RECAP | |||||||||||
2022-03-02 | @ | Ducks2,Golden Knights3 (OT) | RECAP | |||||||||||
2022-03-04 | @ | Canucks4,Ducks2 | RECAP | |||||||||||
2022-03-06 | @ | Ducks3,Flames1 | RECAP | |||||||||||
2022-03-08 | @ | Golden Knights2,Ducks4 | RECAP | |||||||||||
2022-03-10 | @ | Jets2,Ducks4 | RECAP | |||||||||||
2022-03-12 | @ | Ducks3,Blues4 (SO) | RECAP | |||||||||||
2022-03-13 | @ | Maple Leafs8,Ducks2 | RECAP | |||||||||||
2022-03-14 | @ | Ducks4,Kings5 | RECAP | |||||||||||
2022-03-16 | @ | Ducks1,Oilers5 | RECAP | |||||||||||
2022-03-18 | @ | Bruins3,Ducks2 | RECAP | |||||||||||
2022-03-21 | @ | Blues2,Ducks7 | RECAP | |||||||||||
2022-03-22 | @ | Ducks4,Canucks3 | RECAP | |||||||||||
2022-03-25 | @ | Ducks4,Jets3 (SO) | RECAP | |||||||||||
2022-03-26 | @ | Canucks2,Ducks3 | RECAP | |||||||||||
2022-03-29 | @ | Avalanche5,Ducks1 | RECAP | |||||||||||
2022-03-30 | @ | Ducks3,Oilers1 | RECAP | |||||||||||
2022-04-01 | @ | Lightning2,Ducks3 | RECAP | |||||||||||
2022-04-02 | @ | Ducks1,Devils3 | RECAP | |||||||||||
2022-04-04 | @ | Avalanche6,Ducks4 | RECAP | |||||||||||
2022-04-06 | @ | Ducks4,Maple Leafs1 | RECAP | |||||||||||
2022-04-07 | @ | Ducks3,Oilers1 | RECAP | |||||||||||
2022-04-09 | @ | Canadiens2,Ducks6 | RECAP | |||||||||||
2022-04-11 | @ | Ducks3,Jets5 | RECAP | |||||||||||
2022-04-12 | @ | Coyotes7,Ducks2 | RECAP | |||||||||||
2022-04-15 | @ | Flyers3,Ducks4 (OT) | RECAP | |||||||||||
2022-04-17 | @ | Ducks2,Golden Knights4 | RECAP | |||||||||||
2022-04-18 | @ | Ducks2,Blues4 | RECAP | |||||||||||
2022-04-19 | @ | Oilers1,Ducks3 | RECAP | |||||||||||
2022-04-22 | @ | Ducks4,Coyotes3 (SO) | RECAP | |||||||||||
2022-04-23 | @ | Blues2,Ducks5 | RECAP | |||||||||||
2022-04-25 | @ | Ducks4,Golden Knights3 (SO) | RECAP | |||||||||||
2022-04-26 | @ | Ducks1,Rangers4 | RECAP | |||||||||||
2022-04-27 | @ | Maple Leafs7,Ducks2 | RECAP | |||||||||||
2022-04-30 | @ | Oilers2,Ducks3 (OT) | RECAP | |||||||||||
2022-05-02 | @ | Ducks4,Coyotes3 (OT) | RECAP | |||||||||||
2022-05-04 | @ | Blue Jackets4,Ducks5 (SO) | RECAP | |||||||||||
2022-05-06 | @ | Ducks3,Red Wings1 | RECAP | |||||||||||
2022-05-07 | @ | Canucks2,Ducks8 | RECAP | |||||||||||
2022-05-09 | @ | Ducks1,Flyers2 | RECAP | |||||||||||
2022-05-10 | @ | Devils2,Ducks1 | RECAP | |||||||||||
2022-05-12 | @ | Jets2,Ducks3 (OT) | RECAP | |||||||||||
2022-05-13 | @ | Ducks2,Stars6 | RECAP | |||||||||||
2022-05-15 | @ | Ducks3,Canadiens5 | RECAP | |||||||||||
2022-05-17 | @ | Sabres3,Ducks2 | 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 |
74,672,065$ | 0$ | 73,769,987$ | 12,730,013$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | Honda Center | |
City | Anaheim | ||
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 | 122280 | 101646 | 40429 | 82139 | 24799 |
Attendance PCT | 78.38% | 78.19% | 77.75% | 78.98% | 95.38% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
15 | 14281 - 79.34% | 4,129,238$ | 107,360,199$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
74,672,065$ | 74,672,065$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
48,022,820$ | 507,911$ | 45,834,882$ | 0$ |
Estimate | |||
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Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
61,938,576$ | 55 | 532,221$ | 29,272,155$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
30,445,671$ | 73,769,987$ | 506,980,357$ | 544,384,704$ |
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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