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Full Scoreboard ยป |
Columbus Blue Jackets 1-1-0, 2pts · 7th 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/LW | 100.00 | 59 | 12 | 86 | 95 | 67 | 97 | 97 | 87 | 87 | 96 | 90 | 53 | 53 | 65 | 65 | 78 | 50 | 78 | 23 | 8,454,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 71 | 29 | 72 | 87 | 82 | 88 | 97 | 78 | 32 | 86 | 90 | 52 | 25 | 60 | 61 | 78 | 50 | 74 | 23 | 6,000,000$/2yrs | |||
![]() | 0 | C/LW | 100.00 | 79 | 20 | 76 | 86 | 78 | 89 | 93 | 73 | 97 | 74 | 72 | 60 | 75 | 75 | 76 | 72 | 50 | 73 | 27 | 3,750,000$/1yrs | |||
![]() | 0 | C | 100.00 | 47 | 13 | 87 | 75 | 78 | 93 | 99 | 81 | 91 | 75 | 75 | 46 | 53 | 90 | 93 | 76 | 50 | 72 | 35 | 1,995,000$/4yrs | |||
![]() | 0 | LW/RW | 100.00 | 68 | 31 | 77 | 81 | 71 | 92 | 86 | 75 | 34 | 79 | 81 | 49 | 25 | 59 | 59 | 71 | 50 | 70 | 25 | 2,000,000$/3yrs | |||
![]() | 0 | C/LW | 100.00 | 66 | 32 | 78 | 83 | 82 | 84 | 97 | 65 | 90 | 64 | 70 | 77 | 25 | 66 | 67 | 71 | 50 | 70 | 26 | 2,350,000$/3yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 53 | 13 | 92 | 74 | 76 | 88 | 88 | 68 | 37 | 68 | 65 | 69 | 77 | 85 | 88 | 73 | 50 | 69 | 36 | 1,335,000$/4yrs | |||
![]() | 0 | RW | 100.00 | 61 | 24 | 84 | 81 | 78 | 82 | 94 | 73 | 47 | 65 | 71 | 53 | 75 | 77 | 79 | 72 | 50 | 69 | 32 | 2,195,000$/4yrs | |||
![]() | 0 | LW | 100.00 | 58 | 31 | 71 | 77 | 72 | 80 | 92 | 81 | 71 | 74 | 73 | 57 | 75 | 42 | 42 | 93 | 50 | 68 | 18 | 925,000$/2yrs | |||
![]() | 0 | RW | 100.00 | 56 | 41 | 76 | 74 | 71 | 83 | 95 | 79 | 70 | 69 | 74 | 58 | 78 | 40 | 40 | 95 | 50 | 67 | 18 | 925,000$/3yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 46 | 9 | 97 | 84 | 69 | 81 | 82 | 71 | 56 | 58 | 67 | 73 | 72 | 67 | 68 | 70 | 50 | 67 | 27 | 1,500,000$/2yrs | |||
![]() | 0 | C/LW | 100.00 | 43 | 9 | 93 | 84 | 74 | 86 | 98 | 68 | 34 | 72 | 62 | 61 | 25 | 67 | 68 | 62 | 50 | 67 | 27 | 1,450,000$/4yrs | |||
![]() | 0 | D | 100.00 | 62 | 14 | 87 | 86 | 78 | 99 | 90 | 63 | 25 | 72 | 51 | 88 | 25 | 73 | 79 | 71 | 50 | 75 | 31 | 6,750,000$/2yrs | |||
![]() | 44 | D | 100.00 | 78 | 44 | 65 | 77 | 86 | 87 | 81 | 59 | 25 | 50 | 48 | 96 | 75 | 74 | 75 | 60 | 50 | 74 | 28 | 4,150,000$/4yrs | |||
![]() | 0 | D | 100.00 | 65 | 14 | 92 | 81 | 77 | 99 | 95 | 60 | 25 | 60 | 49 | 81 | 25 | 76 | 77 | 62 | 50 | 73 | 26 | 4,500,000$/3yrs | |||
![]() | 0 | D | 100.00 | 69 | 26 | 81 | 84 | 78 | 91 | 73 | 59 | 25 | 52 | 48 | 83 | 25 | 67 | 67 | 63 | 50 | 71 | 26 | 2,650,000$/4yrs | |||
![]() | 0 | D | 100.00 | 67 | 15 | 92 | 80 | 73 | 96 | 88 | 59 | 25 | 52 | 48 | 84 | 25 | 60 | 61 | 66 | 50 | 71 | 28 | 1,995,000$/4yrs | |||
![]() | 0 | D | 100.00 | 55 | 11 | 99 | 83 | 72 | 89 | 89 | 61 | 25 | 57 | 50 | 76 | 25 | 64 | 65 | 58 | 50 | 69 | 26 | 2,700,000$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
TEAM AVERAGE | 100.00 | 61 | 22 | 84 | 82 | 76 | 89 | 91 | 70 | 50 | 68 | 66 | 68 | 48 | 67 | 68 | 72 | 50 | 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 | 78 | 87 | 99 | 89 | 84 | 81 | 69 | 79 | 77 | 86 | 89 | 75 | 78 | 85 | 50 | 79 | 37 | 3,500,000$/4yrs |
![]() | 0 | 100.00 | 78 | 92 | 99 | 71 | 84 | 86 | 85 | 83 | 82 | 81 | 85 | 71 | 72 | 80 | 50 | 79 | 31 | 10,000,000$/2yrs |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 100.00 | 78 | 90 | 99 | 80 | 84 | 84 | 77 | 81 | 80 | 84 | 87 | 73 | 75 | 83 | 50 | 79 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
John Tortorella | 72 | 87 | 84 | 99 | 99 | 96 | 80 | USA | 62 | 3 | 2,500,000$ |
General Manager | Danielle Cook |
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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 | Boone Jenner | 0 | C/LW | 2 | 3 | 0 | 3 | 1 | 0 | 0 | 1 | 10 | 1 | 6 | 30.00% | 1 | 18.07 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 2 | 1 | 0 | 62.07% | 29 | 2 | 0 | 0 | 0 | 1.66 | 0 | 0 | |
2 | Radek Faksa | 0 | C/LW | 2 | 0 | 3 | 3 | 1 | 0 | 0 | 2 | 4 | 3 | 1 | 0.00% | 1 | 15.94 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 2 | 0 | 0 | 0 | 1.88 | 0 | 0 | |
3 | Alexis Lafreniere | 0 | LW | 2 | 1 | 1 | 2 | 3 | 0 | 0 | 1 | 4 | 2 | 5 | 25.00% | 0 | 8.38 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 1 | 0 | 0 | 0 | 2.39 | 0 | 0 | |
4 | Markus Granlund | 0 | C/LW/RW | 2 | 2 | 0 | 2 | 3 | 0 | 0 | 1 | 5 | 1 | 0 | 40.00% | 0 | 7.83 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 33.33% | 6 | 2 | 0 | 0 | 0 | 2.56 | 0 | 0 | |
5 | Mattias Janmark | 0 | C/LW | 2 | 0 | 2 | 2 | 3 | 0 | 0 | 0 | 3 | 2 | 0 | 0.00% | 0 | 8.25 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 100.00% | 1 | 0 | 0 | 0 | 0 | 2.42 | 0 | 0 | |
6 | Nikita Zaitsev | 0 | D | 2 | 0 | 2 | 2 | -1 | 0 | 0 | 0 | 2 | 1 | 0 | 0.00% | 0 | 19.02 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0.00% | 0 | 0 | 1 | 0 | 0 | 1.05 | 0 | 0 | |
7 | Sebastian Aho | 0 | C/LW | 2 | 0 | 1 | 1 | -5 | 0 | 0 | 1 | 11 | 2 | 4 | 0.00% | 2 | 20.75 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 49.25% | 67 | 3 | 1 | 0 | 0 | 0.48 | 0 | 0 | |
8 | Cody Ceci | 0 | D | 2 | 0 | 1 | 1 | -1 | 0 | 0 | 2 | 2 | 1 | 2 | 0.00% | 2 | 19.57 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 2 | 0 | 0 | 0.00% | 0 | 0 | 1 | 0 | 0 | 0.51 | 0 | 0 | |
9 | Eric Staal | 0 | C | 2 | 0 | 1 | 1 | -1 | 0 | 0 | 1 | 5 | 1 | 5 | 0.00% | 0 | 15.14 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 52.17% | 23 | 1 | 0 | 0 | 0 | 0.66 | 0 | 0 | |
10 | Alex Steen | 0 | C/LW/RW | 2 | 1 | 0 | 1 | -1 | 0 | 0 | 0 | 3 | 1 | 1 | 33.33% | 0 | 13.32 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 66.67% | 3 | 1 | 1 | 0 | 0 | 0.75 | 0 | 0 | |
11 | Kyle Okposo | 0 | RW | 2 | 0 | 1 | 1 | 1 | 0 | 0 | 2 | 2 | 2 | 3 | 0.00% | 3 | 15.94 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 50.00% | 2 | 1 | 0 | 0 | 0 | 0.63 | 0 | 0 | |
12 | Ryan McDonagh | 0 | D | 2 | 0 | 1 | 1 | -2 | 0 | 0 | 2 | 5 | 0 | 0 | 0.00% | 7 | 27.02 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 2 | 0 | 0 | 0.00% | 0 | 0 | 3 | 0 | 0 | 0.37 | 0 | 0 | |
13 | Markus Nutivaara | 0 | D | 2 | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0.00% | 2 | 14.31 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.70 | 0 | 0 | |
14 | Timo Meier | 0 | LW/RW | 2 | 1 | 0 | 1 | -5 | 2 | 0 | 3 | 8 | 2 | 3 | 12.50% | 0 | 20.41 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 20.00% | 5 | 4 | 0 | 0 | 0 | 0.49 | 0 | 0 | |
15 | Tyler Bertuzzi | 0 | LW/RW | 2 | 0 | 0 | 0 | -5 | 0 | 0 | 3 | 4 | 2 | 0 | 0.00% | 1 | 19.37 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 2 | 0 | 1 | 0 | 0 | 0.00 | 0 | 0 | |
16 | Erik Gudbranson | 44 | D | 2 | 0 | 0 | 0 | -2 | 2 | 0 | 2 | 1 | 0 | 0 | 0.00% | 5 | 26.29 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 0.00% | 0 | 0 | 4 | 0 | 0 | 0.00 | 0 | 0 | |
17 | Jake McCabe | 0 | D | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0.00% | 4 | 13.95 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 4 | 0 | 0 | 0.00 | 0 | 0 | |
18 | Tyson Foerster | 0 | RW | 2 | 0 | 0 | 0 | -1 | 2 | 0 | 2 | 2 | 1 | 3 | 0.00% | 0 | 13.42 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 100.00% | 2 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |
Team Total or Average | 36 | 8 | 14 | 22 | -10 | 6 | 0 | 25 | 71 | 22 | 33 | 11.27% | 28 | 16.50 | 1 | 2 | 3 | 23 | 0 | 0 | 0 | 15 | 1 | 0 | 51.43% | 140 | 17 | 16 | 0 | 0 | 0.74 | 0 | 0 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | Goalie Name | Team Name | GP | W | L | OTL | PCT | GAA | MP | PIM | SO | GA | SA | SAR | A | EG | PS % | PSA | ST | BG | S1 | S2 | S3 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Sergei Bobrovsky | Blue Jackets | 2 | 1 | 1 | 0 | 0.883 | 4.50 | 120 | 0 | 0 | 9 | 77 | 36 | 0 | 0 | 0.000 | 0 | 2 | 0 | 0 | 0 | 0 |
Team Total or Average | 2 | 1 | 1 | 0 | 0.883 | 4.50 | 120 | 0 | 0 | 9 | 77 | 36 | 0 | 0 | 0.000 | 0 | 2 | 0 | 0 | 0 | 0 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | 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 | 2 | 5 | -3 | 0 | 0.000 | 2 | 3 | 5 | 0 | 0 | 0 | 1 | 1 | 0 | 36 | 11 | 13 | 12 | 0 | 38 | 12 | 2 | 15 | 3 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 28 | 49 | 57.14% | 28 | 56 | 50.00% | 16 | 35 | 45.71% | 21 | 13 | 20 | 8 | 17 | 8 | 28.6% | 5.6% | 86.8% | 92.4 | Unlucky | |
2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 4 | 2 | 2 | 1.000 | 6 | 11 | 17 | 0 | 0 | 1 | 4 | 1 | 0 | 35 | 16 | 9 | 10 | 0 | 39 | 16 | 4 | 10 | 1 | 1 | 100.00% | 2 | 0 | 100.00% | 0 | 28 | 49 | 57.14% | 28 | 56 | 50.00% | 16 | 35 | 45.71% | 18 | 11 | 26 | 9 | 15 | 6 | 55.6% | 17.1% | 89.7% | 106.9 | FUN | |
_Vs Division | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 4 | 2 | 2 | 1.000 | 6 | 11 | 17 | 0 | 0 | 1 | 4 | 1 | 0 | 35 | 16 | 9 | 10 | 0 | 39 | 16 | 4 | 10 | 1 | 1 | 100.00% | 2 | 0 | 100.00% | 0 | 28 | 49 | 57.14% | 28 | 56 | 50.00% | 16 | 35 | 45.71% | 18 | 11 | 26 | 9 | 15 | 6 | 55.6% | 17.1% | 89.7% | 106.9 | FUN | |
_Vs Conference | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 8 | 9 | -1 | 2 | 0.500 | 8 | 14 | 22 | 0 | 0 | 1 | 5 | 2 | 0 | 71 | 27 | 22 | 22 | 0 | 77 | 28 | 6 | 25 | 4 | 1 | 25.00% | 3 | 0 | 100.00% | 0 | 28 | 49 | 57.14% | 28 | 56 | 50.00% | 16 | 35 | 45.71% | 40 | 25 | 46 | 17 | 33 | 15 | 43.8% | 11.3% | 88.3% | 99.6 | FUN | |
_Since Last GM Reset | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 8 | 9 | -1 | 2 | 0.500 | 8 | 14 | 22 | 0 | 0 | 1 | 5 | 2 | 0 | 71 | 27 | 22 | 22 | 0 | 77 | 28 | 6 | 25 | 4 | 1 | 25.00% | 3 | 0 | 100.00% | 0 | 28 | 49 | 57.14% | 28 | 56 | 50.00% | 16 | 35 | 45.71% | 40 | 25 | 46 | 17 | 33 | 15 | 43.8% | 11.3% | 88.3% | 99.6 | FUN | |
Total | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 8 | 9 | -1 | 2 | 0.500 | 8 | 14 | 22 | 0 | 0 | 1 | 5 | 2 | 0 | 71 | 27 | 22 | 22 | 0 | 77 | 28 | 6 | 25 | 4 | 1 | 25.00% | 3 | 0 | 100.00% | 0 | 28 | 49 | 57.14% | 28 | 56 | 50.00% | 16 | 35 | 45.71% | 40 | 25 | 46 | 17 | 33 | 15 | 43.8% | 11.3% | 88.3% | 99.6 | FUN |
Puck Time | |
---|---|
Offensive Zone | 20 |
Neutral Zone | 16 |
Defensive Zone | 23 |
Puck Time | |
---|---|
Offensive Zone Start | 49 |
Neutral Zone Start | 35 |
Defensive Zone Start | 56 |
Puck Time | |
---|---|
With Puck | 29 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 72 |
Faceoffs Lost | 68 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 13.5 | 9.57 |
2nd Period | 24.5 | 20.31 |
3rd Period | 35.5 | 30.68 |
Overtime | 35.5 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.5 | 0.64 |
2nd Period | 3.0 | 1.65 |
3rd Period | 4.0 | 2.67 |
Overtime | 4.0 | 2.83 |
Even Strenght Goal | 7 |
---|---|
PP Goal | 1 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 1 | 0 |
Lost | 1 | 0 |
Overtime Lost | 0 | 0 |
PP Attempt | 4 |
---|---|
PP Goal | 1 |
PK Attempt | 3 |
PK Goal Against | 0 |
Home | |
---|---|
Shots For | 35.5 |
Shots Against | 38.5 |
Goals For | 4.0 |
Goals Against | 4.5 |
Hits | 12.5 |
Shots Blocked | 14.0 |
Pim | 3.0 |
Projected Total Cap Hit | 69,124,000$ |
Projected Cap Space | 17,376,000$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 1,906,868$ |
Players In Salary Cap | 20 |
LTIR Players | 0 |
Player Name | Pos | Age | Cap Hit | 2013-2014 | 2014-2015 | 2015-2016 | 2016-2017 | 2017-2018 | 2018-2019 | 2019-2020 | 2020-2021 |
---|---|---|---|---|---|---|---|---|---|---|---|
Alex Steen ![]() | C/LW/RW | 36 | 1,335,000$ | 1,335,000$ | 1,335,000$ | 1,335,000$ | 1,335,000$ | ||||
Alexis Lafreniere ![]() | LW | 18 | 925,000$ | 925,000$ | 925,000$ | ||||||
Boone Jenner ![]() | C/LW | 27 | 3,750,000$ | 3,750,000$ | |||||||
Cody Ceci | D | 26 | 4,500,000$ | 4,500,000$ | 4,500,000$ | 4,500,000$ | |||||
Eric Staal ![]() | C | 35 | 1,995,000$ | 1,995,000$ | 1,995,000$ | 1,995,000$ | 1,995,000$ | ||||
Erik Gudbranson | D | 28 | 4,150,000$ | 4,150,000$ | 4,150,000$ | 4,150,000$ | 4,150,000$ | ||||
Jake McCabe ![]() | D | 26 | 2,650,000$ | 2,650,000$ | 2,650,000$ | 2,650,000$ | 2,650,000$ | ||||
Kyle Okposo ![]() | RW | 32 | 2,195,000$ | 2,195,000$ | 2,195,000$ | 2,195,000$ | 2,195,000$ | ||||
Markus Granlund ![]() | C/LW/RW | 27 | 1,500,000$ | 1,500,000$ | 1,500,000$ | ||||||
Markus Nutivaara ![]() | D | 26 | 2,700,000$ | 2,700,000$ | |||||||
Mattias Janmark ![]() | C/LW | 27 | 1,450,000$ | 1,450,000$ | 1,450,000$ | 1,450,000$ | 1,450,000$ | ||||
Nikita Zaitsev ![]() | D | 28 | 1,995,000$ | 1,995,000$ | 1,995,000$ | 1,995,000$ | 1,995,000$ | ||||
Pekka Rinne | LW/RW | 37 | 3,500,000$ | 3,500,000$ | 3,500,000$ | 3,500,000$ | 3,500,000$ | ||||
Radek Faksa ![]() | C/LW | 26 | 2,350,000$ | 2,350,000$ | 2,350,000$ | 2,350,000$ | |||||
Ryan McDonagh | D | 31 | 6,750,000$ | 6,750,000$ | 6,750,000$ | ||||||
Sebastian Aho | C/LW | 23 | 8,454,000$ | 8,454,000$ | 8,454,000$ | ||||||
Sergei Bobrovsky | C/RW | 31 | 10,000,000$ | 10,000,000$ | 10,000,000$ | ||||||
Timo Meier | LW/RW | 23 | 6,000,000$ | 6,000,000$ | 6,000,000$ | ||||||
Tyler Bertuzzi ![]() | LW/RW | 25 | 2,000,000$ | 2,000,000$ | 2,000,000$ | 2,000,000$ | |||||
Tyson Foerster ![]() | RW | 18 | 925,000$ | 925,000$ | 925,000$ | 925,000$ |
Forward Lines | |||||||
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1st Power Play Unit | |||||||
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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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Cole Fraser | 1 | ||||
Luke Reid | 3 | 80 | |||
Maxim Groshev | 3 | 56 | |||
Mithcell Gibson | 1 | ||||
Ryder Rolston | 2 | 73 | |||
Vasily Ponomaryov | 3 | 32 | |||
Wyatt Kaiser | 2 | 49 |
Salary Cap | |||
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Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
69,124,000$ | 0$ | 69,124,000$ | 17,376,000$ |
Arena | Goal Horn | About us | |
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![]() | Name | Nationwide Arena | |
City | Columbus | ||
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 | 9130 | 7504 | 3052 | 6439 | 1841 |
Attendance PCT | 76.08% | 75.04% | 76.30% | 80.49% | 92.05% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
39 | 13983 - 77.68% | 4,014,898$ | 8,029,796$ | 18000 | 100 |
Expenses | |||
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Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
69,124,000$ | 69,124,000$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
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1,975,836$ | 69,124,000$ | 1,906,868$ | 0$ |
Estimate | |||
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Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
156,581,022$ | 141 | 493,959$ | 69,648,219$ |
Team Total Estimate | |||
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Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
75,127,431$ | 69,124,000$ | 202,501,213$ | 298,166,404$ |
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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