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Full Scoreboard »» |
New York Rangers 11-6-3, 25pts · 5th in Conference Est |
Player | # | POS | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | RW | 100.00 | 69 | 42 | 89 | 90 | 65 | 87 | 93 | 91 | 25 | 93 | 87 | 75 | 48 | 72 | 74 | 86 | 50 | 0 | 25 | 10,903,000$/3yrs | |||
![]() | 0 | C/RW | 100.00 | 65 | 51 | 96 | 96 | 61 | 84 | 91 | 95 | 84 | 84 | 97 | 63 | 63 | 71 | 75 | 87 | 50 | 0 | 26 | 9,500,000$/8yrs | |||
![]() | 0 | LW/RW | 100.00 | 77 | 43 | 93 | 80 | 69 | 57 | 88 | 65 | 35 | 67 | 62 | 71 | 25 | 69 | 70 | 69 | 50 | 0 | 27 | 1,000,000$/1yrs | |||
![]() | 0 | C/LW | 100.00 | 77 | 79 | 71 | 67 | 79 | 64 | 63 | 68 | 80 | 66 | 66 | 67 | 63 | 47 | 47 | 67 | 50 | 0 | 28 | 762,500$/2yrs | |||
![]() | 0 | C/RW | 100.00 | 63 | 41 | 88 | 94 | 68 | 79 | 83 | 91 | 57 | 87 | 75 | 62 | 41 | 68 | 71 | 77 | 50 | 0 | 25 | 7,000,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 73 | 67 | 58 | 82 | 76 | 85 | 98 | 99 | 39 | 94 | 94 | 64 | 35 | 70 | 71 | 86 | 50 | 0 | 24 | 9,500,000$/8yrs | |||
![]() | 0 | LW/RW | 100.00 | 97 | 89 | 74 | 72 | 72 | 66 | 88 | 69 | 56 | 65 | 73 | 66 | 25 | 58 | 59 | 72 | 50 | 0 | 27 | 750,000$/1yrs | |||
![]() | 0 | C/LW | 100.00 | 86 | 86 | 82 | 78 | 82 | 67 | 59 | 68 | 69 | 63 | 62 | 83 | 25 | 65 | 66 | 69 | 50 | 0 | 28 | 975,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 67 | 42 | 95 | 78 | 70 | 67 | 74 | 62 | 26 | 80 | 66 | 73 | 45 | 64 | 64 | 71 | 50 | 0 | 26 | 1,600,000$/1yrs | |||
![]() | 0 | C | 100.00 | 67 | 52 | 83 | 96 | 73 | 81 | 93 | 91 | 96 | 86 | 88 | 79 | 40 | 73 | 73 | 86 | 50 | 0 | 26 | 6,100,000$/1yrs | |||
![]() | 0 | C/RW | 100.00 | 87 | 46 | 86 | 78 | 83 | 74 | 85 | 67 | 85 | 62 | 73 | 82 | 71 | 72 | 73 | 75 | 50 | 0 | 30 | 900,000$/1yrs | |||
![]() | 0 | RW | 100.00 | 69 | 42 | 94 | 86 | 71 | 83 | 97 | 96 | 71 | 81 | 87 | 74 | 69 | 72 | 73 | 84 | 50 | 0 | 26 | 6,500,000$/2yrs | |||
![]() | 0 | D | 100.00 | 90 | 47 | 75 | 80 | 83 | 66 | 64 | 55 | 25 | 48 | 47 | 74 | 75 | 79 | 82 | 61 | 50 | 0 | 32 | 850,000$/2yrs | |||
![]() | 0 | D | 100.00 | 77 | 44 | 90 | 89 | 74 | 88 | 98 | 65 | 25 | 60 | 49 | 88 | 25 | 72 | 72 | 68 | 50 | 0 | 25 | 6,750,000$/3yrs | |||
![]() | 0 | D | 100.00 | 81 | 55 | 81 | 86 | 80 | 89 | 96 | 80 | 25 | 78 | 54 | 86 | 25 | 69 | 74 | 73 | 50 | 0 | 24 | 4,800,000$/1yrs | |||
![]() | 0 | D | 100.00 | 79 | 44 | 82 | 86 | 68 | 74 | 90 | 64 | 25 | 49 | 48 | 85 | 25 | 64 | 65 | 64 | 50 | 0 | 24 | 2,400,000$/1yrs | |||
![]() | 0 | D | 100.00 | 81 | 44 | 84 | 86 | 67 | 84 | 88 | 78 | 25 | 71 | 56 | 80 | 25 | 66 | 66 | 72 | 50 | 0 | 24 | 4,400,000$/2yrs | |||
![]() | 0 | D | 100.00 | 79 | 44 | 91 | 77 | 73 | 62 | 43 | 55 | 25 | 51 | 48 | 78 | 75 | 58 | 58 | 61 | 50 | 0 | 25 | 1,137,500$/2yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | C | 100.00 | 80 | 85 | 87 | 76 | 77 | 53 | 81 | 54 | 64 | 56 | 55 | 62 | 25 | 64 | 65 | 61 | 50 | 0 | 29 | 1,300,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 67 | 69 | 63 | 62 | 69 | 61 | 62 | 59 | 50 | 46 | 65 | 63 | 62 | 59 | 59 | 61 | 50 | 0 | 25 | 1,133,333$/1yrs | |||
![]() | 0 | D | 100.00 | 65 | 42 | 95 | 65 | 77 | 72 | 72 | 66 | 25 | 63 | 56 | 67 | 25 | 45 | 45 | 64 | 50 | 0 | 25 | 762,500$/2yrs | |||
![]() | 0 | D | 100.00 | 71 | 53 | 88 | 77 | 67 | 68 | 66 | 57 | 25 | 52 | 48 | 69 | 25 | 66 | 66 | 60 | 50 | 0 | 30 | 1,350,000$/1yrs | |||
TEAM AVERAGE | 100.00 | 76 | 55 | 84 | 81 | 73 | 73 | 81 | 73 | 47 | 68 | 66 | 73 | 43 | 66 | 67 | 72 | 50 | 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 | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 100.00 | 60 | 54 | 54 | 97 | 66 | 54 | 82 | 60 | 65 | 60 | 61 | 53 | 53 | 63 | 50 | 0 | 28 | 950,000$/1yrs |
![]() | 0 | 100.00 | 82 | 79 | 75 | 84 | 85 | 79 | 71 | 81 | 84 | 82 | 75 | 51 | 51 | 80 | 50 | 0 | 23 | 750,000$/1yrs |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 100.00 | 71 | 67 | 65 | 91 | 76 | 67 | 77 | 71 | 75 | 71 | 68 | 52 | 52 | 72 | 50 | 0 |
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 | 67 | 42 | 94 | 70 | 70 | 54 | 71 | 60 | 69 | 50 | 59 | 67 | 25 | 48 | 48 | 61 | 56 | 0 | 23 | 1,031,250$/1yrs | |||
![]() | 0 | C | 100.00 | 70 | 62 | 87 | 63 | 62 | 79 | 86 | 54 | 68 | 48 | 56 | 60 | 53 | 44 | 44 | 60 | 56 | 0 | 22 | 850,833$/2yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 82 | 85 | 75 | 68 | 85 | 72 | 75 | 61 | 76 | 60 | 58 | 68 | 55 | 47 | 47 | 63 | 56 | 0 | 26 | 750,000$/1yrs | |||
![]() | 0 | D | 100.00 | 79 | 90 | 54 | 63 | 90 | 78 | 86 | 48 | 25 | 40 | 39 | 66 | 37 | 56 | 56 | 53 | 56 | 0 | 30 | 750,000$/1yrs | |||
Scratches |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 100.00 | 60 | 56 | 70 | 85 | 62 | 62 | 56 | 64 | 61 | 60 | 30 | 44 | 44 | 60 | 56 | 0 | 22 | 880,833$/2yrs | ||||||
Scratches |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
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General Manager | Samuel Bourque |
---|
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 | MP | AMG | PPG | PPA | PPP | PPM | PKG | PKA | PKP | PKM | GW | GT | FO% | FOT | GA | TA | EG | HT | P/20 | PSG | PSS |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Brayden Point | 0 | C/RW | 20 | 10 | 8 | 18 | -2 | 12 | 10 | 16 | 57 | 16 | 41 | 17.54% | 5 | 20.29 | 2 | 3 | 5 | 40 | 0 | 0 | 0 | 6 | 2 | 1 | 51.72% | 553 | 16 | 4 | 0 | 0 | 0.89 | 1 | 3 | ||
2 | Dylan Larkin | 0 | C | 20 | 6 | 11 | 17 | 4 | 5 | 5 | 26 | 52 | 19 | 43 | 11.54% | 4 | 17.67 | 2 | 3 | 5 | 34 | 0 | 0 | 0 | 24 | 1 | 0 | 59.07% | 237 | 16 | 6 | 0 | 0 | 0.96 | 0 | 0 | ||
3 | Matthew Tkachuk | 0 | LW/RW | 20 | 6 | 10 | 16 | -5 | 46 | 10 | 42 | 51 | 17 | 42 | 11.76% | 6 | 19.65 | 0 | 5 | 5 | 41 | 0 | 0 | 0 | 0 | 1 | 1 | 26.67% | 30 | 9 | 10 | 0 | 1 | 0.81 | 0 | 3 | ||
4 | Mitchell Marner | 0 | RW | 20 | 6 | 8 | 14 | -1 | 2 | 0 | 24 | 43 | 19 | 50 | 13.95% | 14 | 20.94 | 1 | 3 | 4 | 41 | 0 | 0 | 0 | 21 | 0 | 2 | 27.27% | 33 | 16 | 7 | 0 | 0 | 0.67 | 0 | 3 | ||
5 | Mathew Barzal | 0 | C/RW | 20 | 8 | 6 | 14 | 3 | 2 | 0 | 26 | 46 | 13 | 31 | 17.39% | 5 | 16.08 | 3 | 1 | 4 | 34 | 0 | 0 | 0 | 0 | 4 | 0 | 27.78% | 18 | 12 | 6 | 0 | 0 | 0.87 | 0 | 0 | ||
6 | Sam Reinhart | 0 | RW | 20 | 4 | 10 | 14 | 3 | 2 | 0 | 27 | 29 | 9 | 21 | 13.79% | 8 | 15.84 | 0 | 4 | 4 | 34 | 0 | 0 | 0 | 0 | 0 | 0 | 64.29% | 14 | 9 | 8 | 0 | 0 | 0.88 | 0 | 0 | ||
7 | Danton Heinen | 0 | LW/RW | 20 | 4 | 5 | 9 | 0 | 0 | 0 | 18 | 38 | 9 | 18 | 10.53% | 3 | 13.22 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 17 | 0 | 1 | 50.00% | 4 | 8 | 3 | 0 | 0 | 0.68 | 0 | 0 | ||
8 | Mikhail Sergachev | 0 | D | 20 | 1 | 7 | 8 | -2 | 26 | 10 | 35 | 44 | 14 | 18 | 2.27% | 26 | 25.02 | 0 | 0 | 0 | 45 | 0 | 0 | 0 | 49 | 0 | 1 | 0.00% | 0 | 14 | 22 | 0 | 0 | 0.32 | 0 | 0 | ||
9 | Filip Hronek | 0 | D | 20 | 2 | 6 | 8 | 4 | 17 | 5 | 27 | 27 | 11 | 11 | 7.41% | 13 | 21.31 | 1 | 1 | 2 | 30 | 1 | 0 | 1 | 40 | 0 | 0 | 0.00% | 0 | 6 | 16 | 0 | 0 | 0.38 | 0 | 0 | ||
10 | Ivan Provorov | 0 | D | 20 | 3 | 4 | 7 | -3 | 6 | 0 | 31 | 29 | 12 | 7 | 10.34% | 35 | 25.72 | 2 | 0 | 2 | 45 | 0 | 0 | 0 | 56 | 0 | 0 | 0.00% | 0 | 2 | 23 | 0 | 0 | 0.27 | 0 | 0 | ||
11 | Dante Fabbro | 0 | D | 20 | 1 | 6 | 7 | 5 | 14 | 0 | 28 | 27 | 13 | 9 | 3.70% | 37 | 21.07 | 1 | 1 | 2 | 31 | 0 | 0 | 0 | 35 | 0 | 0 | 0.00% | 0 | 1 | 17 | 0 | 0 | 0.33 | 0 | 0 | ||
12 | Anders Bjork | 0 | LW/RW | 20 | 1 | 6 | 7 | -2 | 4 | 0 | 16 | 27 | 10 | 25 | 3.70% | 5 | 12.50 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 22 | 0 | 0 | 83.33% | 6 | 10 | 3 | 0 | 0 | 0.56 | 0 | 0 | ||
13 | Nick Bjugstad | 0 | C/RW | 20 | 2 | 5 | 7 | -3 | 11 | 5 | 27 | 39 | 15 | 32 | 5.13% | 14 | 14.01 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 49 | 0 | 0 | 51.83% | 191 | 6 | 5 | 0 | 0 | 0.50 | 0 | 0 | ||
14 | Jujhar Khaira | 0 | C/LW | 20 | 4 | 0 | 4 | 0 | 7 | 5 | 18 | 38 | 8 | 12 | 10.53% | 7 | 10.32 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 53 | 2 | 0 | 33.33% | 12 | 3 | 0 | 0 | 0 | 0.39 | 0 | 0 | ||
15 | Brendan Gaunce | 0 | C/LW | 20 | 2 | 1 | 3 | 0 | 11 | 5 | 10 | 24 | 6 | 17 | 8.33% | 0 | 8.16 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 2 | 0 | 0 | 41.82% | 55 | 5 | 3 | 0 | 0 | 0.37 | 0 | 0 | ||
16 | Kiefer Sherwood | 0 | LW/RW | 20 | 0 | 3 | 3 | 1 | 7 | 5 | 18 | 21 | 10 | 20 | 0.00% | 5 | 7.57 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 1 | 4 | 0 | 0 | 0.40 | 0 | 0 | ||
17 | Zach Bogosian | 0 | D | 20 | 0 | 2 | 2 | -1 | 6 | 0 | 23 | 10 | 5 | 5 | 0.00% | 13 | 14.46 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 16 | 0 | 0 | 0.00% | 0 | 1 | 14 | 0 | 0 | 0.14 | 0 | 0 | ||
18 | Jakub Zboril | 0 | D | 20 | 1 | 1 | 2 | -1 | 2 | 0 | 9 | 2 | 6 | 0 | 50.00% | 15 | 13.22 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 11 | 0 | 0 | 0.15 | 0 | 0 | ||
Team Total or Average | 360 | 61 | 99 | 160 | 0 | 180 | 60 | 421 | 604 | 212 | 402 | 10.10% | 215 | 16.50 | 12 | 22 | 34 | 385 | 1 | 1 | 2 | 397 | 10 | 6 | 51.17% | 1153 | 135 | 162 | 0 | 1 | 0.54 | 1 | 9 |
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 | Stuart Skinner | 17 | 9 | 6 | 2 | 0.913 | 2.73 | 1013 | 0 | 0 | 46 | 530 | 250 | 3 | 0 | 0.750 | 8 | 17 | 3 | 1 | 1 | 1 | |
2 | Anthony Stolarz | 4 | 2 | 0 | 1 | 0.893 | 3.58 | 201 | 0 | 0 | 12 | 112 | 72 | 0 | 0 | 0.000 | 0 | 3 | 17 | 0 | 0 | 0 | |
Team Total or Average | 21 | 11 | 6 | 3 | 0.910 | 2.87 | 1214 | 0 | 0 | 58 | 642 | 322 | 3 | 0 | 0.750 | 8 | 20 | 20 | 1 | 1 | 1 |
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 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 4 | 7 | 0 | 0 | 1 | 0 | 2 | 0 | 36 | 8 | 13 | 15 | 0 | 32 | 14 | 4 | 18 | 1 | 1 | 100.00% | 2 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 20 | 12 | 21 | 8 | 17 | 8 | 50.0% | 8.3% | 93.8% | 102.1 | DULL | |
2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 3 | 2 | 1.000 | 4 | 8 | 12 | 0 | 0 | 0 | 2 | 2 | 0 | 38 | 7 | 20 | 11 | 0 | 19 | 13 | 4 | 11 | 4 | 1 | 25.00% | 2 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 25 | 16 | 18 | 8 | 16 | 8 | 75.0% | 10.5% | 94.7% | 105.3 | LUCKY | |
3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 4 | 1 | 2 | 1.000 | 5 | 8 | 13 | 0 | 0 | 1 | 0 | 4 | 0 | 27 | 5 | 9 | 13 | 0 | 36 | 8 | 26 | 15 | 2 | 0 | 0.00% | 8 | 3 | 62.50% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 18 | 9 | 24 | 8 | 17 | 8 | 83.3% | 18.5% | 88.9% | 107.4 | FUN | |
4 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 | 1 | 1 | 2 | 1.000 | 2 | 1 | 3 | 0 | 0 | 0 | 1 | 0 | 1 | 30 | 18 | 9 | 3 | 3 | 30 | 8 | 11 | 24 | 0 | 0 | 0.00% | 3 | 1 | 66.67% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 22 | 12 | 22 | 9 | 20 | 9 | 100.0% | 6.7% | 96.7% | 103.3 | DULL | |
5 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 6 | 9 | 0 | 0 | 0 | 1 | 2 | 0 | 33 | 7 | 12 | 14 | 0 | 33 | 12 | 9 | 20 | 2 | 1 | 50.00% | 2 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 22 | 13 | 19 | 8 | 18 | 9 | 50.0% | 9.1% | 93.9% | 103.0 | LUCKY | |
6 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 8 | -7 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 1 | 0 | 0 | 19 | 8 | 10 | 1 | 0 | 37 | 4 | 28 | 22 | 2 | 0 | 0.00% | 4 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 20 | 10 | 21 | 9 | 18 | 8 | 11.1% | 5.3% | 78.4% | 83.6 | Unlucky | |
7 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | -1 | 0 | 0.000 | 2 | 2 | 4 | 0 | 0 | 1 | 1 | 0 | 0 | 27 | 12 | 6 | 9 | 0 | 39 | 11 | 10 | 17 | 2 | 1 | 50.00% | 5 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 21 | 12 | 21 | 9 | 16 | 8 | 25.0% | 7.4% | 92.3% | 99.7 | DULL | |
8 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 1 | 2 | 0 | 0 | 38 | 18 | 8 | 12 | 0 | 35 | 8 | 4 | 23 | 2 | 0 | 0.00% | 2 | 1 | 50.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 23 | 14 | 20 | 7 | 15 | 8 | 75.0% | 7.9% | 94.3% | 102.2 | DULL | |
9 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 1 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 24 | 9 | 5 | 10 | 0 | 38 | 10 | 11 | 22 | 2 | 0 | 0.00% | 3 | 1 | 66.67% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 20 | 11 | 22 | 8 | 17 | 8 | 25.0% | 4.2% | 89.5% | 93.6 | Unlucky | |
10 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 2 | 2 | 2 | 1.000 | 4 | 8 | 12 | 0 | 0 | 1 | 0 | 3 | 0 | 32 | 5 | 11 | 16 | 0 | 33 | 15 | 11 | 26 | 2 | 1 | 50.00% | 3 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 23 | 13 | 17 | 8 | 18 | 9 | 60.0% | 12.5% | 93.9% | 106.4 | LUCKY | |
11 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 5 | 3 | 4 | 1.000 | 8 | 13 | 21 | 0 | 0 | 2 | 3 | 3 | 0 | 57 | 20 | 17 | 20 | 0 | 64 | 18 | 8 | 42 | 7 | 3 | 42.86% | 4 | 0 | 100.00% | 1 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 43 | 25 | 42 | 17 | 34 | 17 | 50.0% | 14.0% | 92.2% | 106.2 | LUCKY | |
12 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 4 | 7 | -3 | 0 | 0.000 | 4 | 7 | 11 | 0 | 0 | 0 | 2 | 2 | 0 | 53 | 23 | 15 | 15 | 0 | 56 | 23 | 9 | 43 | 6 | 1 | 16.67% | 2 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 43 | 24 | 41 | 17 | 34 | 18 | 30.0% | 7.5% | 87.5% | 95.0 | Unlucky | |
13 | 2 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 6 | 4 | 2 | 3 | 0.750 | 6 | 10 | 16 | 0 | 0 | 3 | 3 | 0 | 0 | 59 | 17 | 33 | 9 | 0 | 58 | 30 | 15 | 47 | 9 | 2 | 22.22% | 5 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 48 | 30 | 39 | 16 | 33 | 16 | 50.0% | 10.2% | 93.1% | 103.3 | LUCKY | |
14 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | 5 | -1 | 1 | 0.500 | 4 | 7 | 11 | 0 | 0 | 0 | 2 | 2 | 0 | 30 | 8 | 12 | 9 | 4 | 39 | 6 | 6 | 26 | 2 | 0 | 0.00% | 3 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 24 | 14 | 23 | 9 | 17 | 8 | 44.4% | 13.3% | 87.2% | 100.5 | FUN | |
15 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | -1 | 0 | 0.000 | 2 | 4 | 6 | 0 | 0 | 0 | 0 | 2 | 0 | 27 | 6 | 9 | 12 | 0 | 34 | 11 | 12 | 21 | 5 | 0 | 0.00% | 6 | 2 | 66.67% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 24 | 14 | 19 | 8 | 16 | 8 | 66.7% | 7.4% | 91.2% | 98.6 | DULL | |
16 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 4 | 2 | 1.000 | 5 | 6 | 11 | 0 | 0 | 1 | 3 | 1 | 0 | 40 | 6 | 18 | 16 | 0 | 33 | 11 | 6 | 26 | 0 | 0 | 0.00% | 3 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 20 | 12 | 22 | 9 | 16 | 7 | 83.3% | 12.5% | 97.0% | 109.5 | LUCKY | |
17 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 5 | 6 | -1 | 1 | 0.500 | 5 | 7 | 12 | 0 | 0 | 3 | 1 | 1 | 0 | 34 | 12 | 13 | 9 | 3 | 26 | 13 | 6 | 18 | 1 | 1 | 100.00% | 3 | 1 | 66.67% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 24 | 14 | 21 | 8 | 18 | 9 | 44.4% | 14.7% | 76.9% | 91.6 | FUN | |
_Vs Division | 6 | 0 | 4 | 0 | 0 | 0 | 1 | 1 | 14 | 19 | -5 | 3 | 0.250 | 14 | 21 | 35 | 0 | 0 | 1 | 6 | 6 | 1 | 167 | 67 | 51 | 48 | 7 | 198 | 59 | 48 | 131 | 15 | 2 | 13.33% | 19 | 3 | 84.21% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 135 | 79 | 128 | 53 | 105 | 52 | 42.9% | 8.4% | 90.4% | 98.8 | Unlucky | |
_Vs Conference | 10 | 4 | 4 | 0 | 0 | 0 | 1 | 1 | 30 | 30 | 0 | 11 | 0.550 | 30 | 46 | 76 | 0 | 0 | 5 | 9 | 15 | 1 | 287 | 100 | 90 | 96 | 7 | 330 | 99 | 86 | 206 | 25 | 6 | 24.00% | 33 | 6 | 81.82% | 1 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 218 | 126 | 217 | 89 | 174 | 86 | 50.0% | 10.5% | 90.9% | 101.4 | FUN | |
_Since Last GM Reset | 20 | 10 | 6 | 0 | 0 | 1 | 1 | 2 | 62 | 60 | 2 | 25 | 0.625 | 62 | 99 | 161 | 0 | 0 | 14 | 23 | 24 | 1 | 604 | 189 | 220 | 194 | 10 | 642 | 215 | 180 | 421 | 49 | 12 | 24.49% | 60 | 9 | 85.00% | 1 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 447 | 264 | 420 | 175 | 348 | 173 | 49.5% | 10.3% | 90.7% | 100.9 | FUN | |
Total | 20 | 10 | 6 | 0 | 0 | 1 | 1 | 2 | 62 | 60 | 2 | 25 | 0.625 | 62 | 99 | 161 | 0 | 0 | 14 | 23 | 24 | 1 | 604 | 189 | 220 | 194 | 10 | 642 | 215 | 180 | 421 | 49 | 12 | 24.49% | 60 | 9 | 85.00% | 1 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 447 | 264 | 420 | 175 | 348 | 173 | 49.5% | 10.3% | 90.7% | 100.9 | FUN |
Puck Time | |
---|---|
Offensive Zone | 22 |
Neutral Zone | 17 |
Defensive Zone | 21 |
Puck Time | |
---|---|
Offensive Zone Start | 411 |
Neutral Zone Start | 292 |
Defensive Zone Start | 439 |
Puck Time | |
---|---|
With Puck | 30 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 590 |
Faceoffs Lost | 552 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 9.5 | 9.57 |
2nd Period | 20.5 | 20.31 |
3rd Period | 30.2 | 30.68 |
Overtime | 30.7 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.7 | 0.64 |
2nd Period | 1.9 | 1.65 |
3rd Period | 3.1 | 2.67 |
Overtime | 3.1 | 2.83 |
Even Strenght Goal | 49 |
---|---|
PP Goal | 12 |
PK Goal | 1 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 5 | 6 |
Lost | 2 | 4 |
Overtime Lost | 1 | 2 |
PP Attempt | 49 |
---|---|
PP Goal | 12 |
PK Attempt | 60 |
PK Goal Against | 9 |
Home | |
---|---|
Shots For | 30.2 |
Shots Against | 32.1 |
Goals For | 3.1 |
Goals Against | 3.0 |
Hits | 21.1 |
Shots Blocked | 10.8 |
Pim | 9.0 |
Projected Total Cap Hit | 82,073,833$ |
Projected Cap Space | 426,167$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 21,373,400$ |
Players In Salary Cap | 24 |
LTIR Players | 0 |
Rangers Roster | Pos | Age | Cap Hit | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 | 2030-31 |
---|---|---|---|---|---|---|---|---|---|---|---|
Anders Bjork ![]() | LW/RW | 26 | 1,600,000$ | 1,600,000$ | |||||||
Anthony Stolarz ![]() | G | 28 | 950,000$ | 950,000$ | |||||||
Austin Wagner ![]() | LW/RW | 25 | 1,133,333$ | 1,133,333$ | |||||||
Brayden Point ![]() | C/RW | 26 | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ |
Brendan Gaunce ![]() | C/LW | 28 | 762,500$ | 762,500$ | 762,500$ | ||||||
Daniil Miromanov ![]() | D | 25 | 762,500$ | 762,500$ | 762,500$ | ||||||
Dante Fabbro ![]() | D | 24 | 2,400,000$ | 2,400,000$ | |||||||
Danton Heinen ![]() | LW/RW | 27 | 1,000,000$ | 1,000,000$ | |||||||
Dylan Larkin ![]() | C | 26 | 6,100,000$ | 6,100,000$ | |||||||
Filip Hronek ![]() | D | 24 | 4,400,000$ | 4,400,000$ | 4,400,000$ | ||||||
Ivan Provorov ![]() | D | 25 | 6,750,000$ | 6,750,000$ | 6,750,000$ | 6,750,000$ | |||||
Jakub Zboril ![]() | D | 25 | 1,137,500$ | 1,137,500$ | 1,137,500$ | ||||||
Jordan Oesterle ![]() | D | 30 | 1,350,000$ | 1,350,000$ | |||||||
Jujhar Khaira ![]() | C/LW | 28 | 975,000$ | 975,000$ | |||||||
Kevin Rooney ![]() | C | 29 | 1,300,000$ | 1,300,000$ | 1,300,000$ | ||||||
Kiefer Sherwood ![]() | LW/RW | 27 | 750,000$ | 750,000$ | |||||||
Mathew Barzal ![]() | C/RW | 25 | 7,000,000$ | 7,000,000$ | |||||||
Matthew Tkachuk ![]() | LW/RW | 24 | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ | 9,500,000$ |
Mikhail Sergachev ![]() | D | 24 | 4,800,000$ | 4,800,000$ | |||||||
Mitchell Marner ![]() | RW | 25 | 10,903,000$ | 10,903,000$ | 10,903,000$ | 10,903,000$ | |||||
Nick Bjugstad ![]() | C/RW | 30 | 900,000$ | 900,000$ | |||||||
Sam Reinhart ![]() | RW | 26 | 6,500,000$ | 6,500,000$ | 6,500,000$ | ||||||
Stuart Skinner ![]() | G | 23 | 750,000$ | 750,000$ | |||||||
Zach Bogosian ![]() | D | 32 | 850,000$ | 850,000$ | 850,000$ |
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Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | 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 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 4 | 7 | 0 | 0 | 1 | 0 | 2 | 0 | 36 | 8 | 13 | 15 | 0 | 32 | 14 | 4 | 18 | 1 | 1 | 100.00% | 2 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 20 | 12 | 21 | 8 | 17 | 8 | 50.0% | 8.3% | 93.8% | 102.1 | DULL | |
2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 3 | 2 | 1.000 | 4 | 8 | 12 | 0 | 0 | 0 | 2 | 2 | 0 | 38 | 7 | 20 | 11 | 0 | 19 | 13 | 4 | 11 | 4 | 1 | 25.00% | 2 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 25 | 16 | 18 | 8 | 16 | 8 | 75.0% | 10.5% | 94.7% | 105.3 | LUCKY | |
3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 4 | 1 | 2 | 1.000 | 5 | 8 | 13 | 0 | 0 | 1 | 0 | 4 | 0 | 27 | 5 | 9 | 13 | 0 | 36 | 8 | 26 | 15 | 2 | 0 | 0.00% | 8 | 3 | 62.50% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 18 | 9 | 24 | 8 | 17 | 8 | 83.3% | 18.5% | 88.9% | 107.4 | FUN | |
4 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 | 1 | 1 | 2 | 1.000 | 2 | 1 | 3 | 0 | 0 | 0 | 1 | 0 | 1 | 30 | 18 | 9 | 3 | 3 | 30 | 8 | 11 | 24 | 0 | 0 | 0.00% | 3 | 1 | 66.67% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 22 | 12 | 22 | 9 | 20 | 9 | 100.0% | 6.7% | 96.7% | 103.3 | DULL | |
5 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 6 | 9 | 0 | 0 | 0 | 1 | 2 | 0 | 33 | 7 | 12 | 14 | 0 | 33 | 12 | 9 | 20 | 2 | 1 | 50.00% | 2 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 22 | 13 | 19 | 8 | 18 | 9 | 50.0% | 9.1% | 93.9% | 103.0 | LUCKY | |
6 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 8 | -7 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 1 | 0 | 0 | 19 | 8 | 10 | 1 | 0 | 37 | 4 | 28 | 22 | 2 | 0 | 0.00% | 4 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 20 | 10 | 21 | 9 | 18 | 8 | 11.1% | 5.3% | 78.4% | 83.6 | Unlucky | |
7 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | -1 | 0 | 0.000 | 2 | 2 | 4 | 0 | 0 | 1 | 1 | 0 | 0 | 27 | 12 | 6 | 9 | 0 | 39 | 11 | 10 | 17 | 2 | 1 | 50.00% | 5 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 21 | 12 | 21 | 9 | 16 | 8 | 25.0% | 7.4% | 92.3% | 99.7 | DULL | |
8 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 1 | 2 | 0 | 0 | 38 | 18 | 8 | 12 | 0 | 35 | 8 | 4 | 23 | 2 | 0 | 0.00% | 2 | 1 | 50.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 23 | 14 | 20 | 7 | 15 | 8 | 75.0% | 7.9% | 94.3% | 102.2 | DULL | |
9 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 1 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 24 | 9 | 5 | 10 | 0 | 38 | 10 | 11 | 22 | 2 | 0 | 0.00% | 3 | 1 | 66.67% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 20 | 11 | 22 | 8 | 17 | 8 | 25.0% | 4.2% | 89.5% | 93.6 | Unlucky | |
10 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 2 | 2 | 2 | 1.000 | 4 | 8 | 12 | 0 | 0 | 1 | 0 | 3 | 0 | 32 | 5 | 11 | 16 | 0 | 33 | 15 | 11 | 26 | 2 | 1 | 50.00% | 3 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 23 | 13 | 17 | 8 | 18 | 9 | 60.0% | 12.5% | 93.9% | 106.4 | LUCKY | |
11 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 5 | 3 | 4 | 1.000 | 8 | 13 | 21 | 0 | 0 | 2 | 3 | 3 | 0 | 57 | 20 | 17 | 20 | 0 | 64 | 18 | 8 | 42 | 7 | 3 | 42.86% | 4 | 0 | 100.00% | 1 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 43 | 25 | 42 | 17 | 34 | 17 | 50.0% | 14.0% | 92.2% | 106.2 | LUCKY | |
12 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 4 | 7 | -3 | 0 | 0.000 | 4 | 7 | 11 | 0 | 0 | 0 | 2 | 2 | 0 | 53 | 23 | 15 | 15 | 0 | 56 | 23 | 9 | 43 | 6 | 1 | 16.67% | 2 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 43 | 24 | 41 | 17 | 34 | 18 | 30.0% | 7.5% | 87.5% | 95.0 | Unlucky | |
13 | 2 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 6 | 4 | 2 | 3 | 0.750 | 6 | 10 | 16 | 0 | 0 | 3 | 3 | 0 | 0 | 59 | 17 | 33 | 9 | 0 | 58 | 30 | 15 | 47 | 9 | 2 | 22.22% | 5 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 48 | 30 | 39 | 16 | 33 | 16 | 50.0% | 10.2% | 93.1% | 103.3 | LUCKY | |
14 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | 5 | -1 | 1 | 0.500 | 4 | 7 | 11 | 0 | 0 | 0 | 2 | 2 | 0 | 30 | 8 | 12 | 9 | 4 | 39 | 6 | 6 | 26 | 2 | 0 | 0.00% | 3 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 24 | 14 | 23 | 9 | 17 | 8 | 44.4% | 13.3% | 87.2% | 100.5 | FUN | |
15 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | -1 | 0 | 0.000 | 2 | 4 | 6 | 0 | 0 | 0 | 0 | 2 | 0 | 27 | 6 | 9 | 12 | 0 | 34 | 11 | 12 | 21 | 5 | 0 | 0.00% | 6 | 2 | 66.67% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 24 | 14 | 19 | 8 | 16 | 8 | 66.7% | 7.4% | 91.2% | 98.6 | DULL | |
16 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 4 | 2 | 1.000 | 5 | 6 | 11 | 0 | 0 | 1 | 3 | 1 | 0 | 40 | 6 | 18 | 16 | 0 | 33 | 11 | 6 | 26 | 0 | 0 | 0.00% | 3 | 0 | 100.00% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 20 | 12 | 22 | 9 | 16 | 7 | 83.3% | 12.5% | 97.0% | 109.5 | LUCKY | |
17 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 5 | 6 | -1 | 1 | 0.500 | 5 | 7 | 12 | 0 | 0 | 3 | 1 | 1 | 0 | 34 | 12 | 13 | 9 | 3 | 26 | 13 | 6 | 18 | 1 | 1 | 100.00% | 3 | 1 | 66.67% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 24 | 14 | 21 | 8 | 18 | 9 | 44.4% | 14.7% | 76.9% | 91.6 | FUN | |
_Vs Division | 6 | 0 | 4 | 0 | 0 | 0 | 1 | 1 | 14 | 19 | -5 | 3 | 0.250 | 14 | 21 | 35 | 0 | 0 | 1 | 6 | 6 | 1 | 167 | 67 | 51 | 48 | 7 | 198 | 59 | 48 | 131 | 15 | 2 | 13.33% | 19 | 3 | 84.21% | 0 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 135 | 79 | 128 | 53 | 105 | 52 | 42.9% | 8.4% | 90.4% | 98.8 | Unlucky | |
_Vs Conference | 10 | 4 | 4 | 0 | 0 | 0 | 1 | 1 | 30 | 30 | 0 | 11 | 0.550 | 30 | 46 | 76 | 0 | 0 | 5 | 9 | 15 | 1 | 287 | 100 | 90 | 96 | 7 | 330 | 99 | 86 | 206 | 25 | 6 | 24.00% | 33 | 6 | 81.82% | 1 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 218 | 126 | 217 | 89 | 174 | 86 | 50.0% | 10.5% | 90.9% | 101.4 | FUN | |
_Since Last GM Reset | 20 | 10 | 6 | 0 | 0 | 1 | 1 | 2 | 62 | 60 | 2 | 25 | 0.625 | 62 | 99 | 161 | 0 | 0 | 14 | 23 | 24 | 1 | 604 | 189 | 220 | 194 | 10 | 642 | 215 | 180 | 421 | 49 | 12 | 24.49% | 60 | 9 | 85.00% | 1 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 447 | 264 | 420 | 175 | 348 | 173 | 49.5% | 10.3% | 90.7% | 100.9 | FUN | |
Total | 20 | 10 | 6 | 0 | 0 | 1 | 1 | 2 | 62 | 60 | 2 | 25 | 0.625 | 62 | 99 | 161 | 0 | 0 | 14 | 23 | 24 | 1 | 604 | 189 | 220 | 194 | 10 | 642 | 215 | 180 | 421 | 49 | 12 | 24.49% | 60 | 9 | 85.00% | 1 | 214 | 411 | 52.07% | 222 | 439 | 50.57% | 154 | 292 | 52.74% | 447 | 264 | 420 | 175 | 348 | 173 | 49.5% | 10.3% | 90.7% | 100.9 | FUN |
Puck Time | |
---|---|
Offensive Zone | 22 |
Neutral Zone | 17 |
Defensive Zone | 21 |
Puck Time | |
---|---|
Offensive Zone Start | 411 |
Neutral Zone Start | 292 |
Defensive Zone Start | 439 |
Puck Time | |
---|---|
With Puck | 30 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 590 |
Faceoffs Lost | 552 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 9.5 | 9.57 |
2nd Period | 20.5 | 20.31 |
3rd Period | 30.2 | 30.68 |
Overtime | 30.7 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.7 | 0.64 |
2nd Period | 1.9 | 1.65 |
3rd Period | 3.1 | 2.67 |
Overtime | 3.1 | 2.83 |
Even Strenght Goal | 49 |
---|---|
PP Goal | 12 |
PK Goal | 1 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 5 | 6 |
Lost | 2 | 4 |
Overtime Lost | 1 | 2 |
PP Attempt | 49 |
---|---|
PP Goal | 12 |
PK Attempt | 60 |
PK Goal Against | 9 |
Home | |
---|---|
Shots For | 30.2 |
Shots Against | 32.1 |
Goals For | 3.1 |
Goals Against | 3.0 |
Hits | 21.1 |
Shots Blocked | 10.8 |
Pim | 9.0 |
Date | Matchup | Result | Detail | ||
---|---|---|---|---|---|
2023-10-08 | @ | Rangers4,Sabres3 | RECAP | ||
2023-10-10 | @ | Rangers3,Blue Jackets4 | RECAP | ||
2023-10-12 | @ | Coyotes1,Rangers4 | RECAP | ||
2023-10-15 | @ | Predators2,Rangers3 | RECAP | ||
2023-10-17 | @ | Rangers5,Kraken6 (SO) | RECAP | ||
2023-10-20 | @ | Rangers5,Flames1 | RECAP | ||
2023-10-22 | @ | Rangers4,Oilers2 | RECAP | ||
2023-10-24 | @ | Rangers3,Canucks2 | RECAP | ||
2023-10-26 | @ | Rangers1,Jets4 | RECAP | ||
2023-10-29 | @ | Hurricanes3,Rangers2 | RECAP | ||
2023-10-31 | @ | Rangers5,Wild2 | RECAP | ||
2023-11-03 | @ | Red Wings4,Rangers5 | RECAP | ||
2023-11-05 | @ | Wild2,Rangers1 (OT) | RECAP | ||
2023-11-08 | @ | Blue Jackets3,Rangers1 | RECAP | ||
2023-11-14 | @ | Rangers4,Devils5 (SO) | RECAP | ||
2023-11-16 | @ | Rangers1,Stars8 | RECAP | ||
2023-11-18 | @ | Rangers2,Penguins3 | RECAP | ||
2023-11-20 | @ | Rangers2,Flyers1 (SO) | RECAP | ||
2023-11-21 | @ | Bruins2,Rangers3 | RECAP | ||
2023-11-23 | @ | Sabres2,Rangers4 | RECAP | ||
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Salary Cap | |||
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Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
82,073,833$ | 0$ | 82,073,833$ | 426,167$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | Madison Square Garden | |
City | New York | ||
Capacity | 18000 | ||
Season Ticket Holders | 40% |
Arena Capacity - Ticket Price Attendance - % | |||||
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Arena Capacity | 6000 | 5000 | 2000 | 4000 | 1000 |
Ticket Price | 100$ | 60$ | 35$ | 25$ | 200$ |
Attendance | 45856 | 36678 | 15460 | 29289 | 7379 |
Attendance PCT | 95.53% | 91.70% | 96.63% | 91.53% | 92.24% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
33 | 16833 - 93.52% | 607,882$ | 4,863,057$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
82,073,833$ | 82,073,833$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
21,373,400$ | 82,073,833$ | 21,373,400$ | 0$ |
Estimate | |||
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Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
20,060,110$ | 142 | 427,468$ | 60,700,456$ |
Team Total Estimate | |||
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Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
63,311,090$ | 82,073,833$ | -430,466,926$ | -473,717,906$ |
Left Wing | Center | Right Wing | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Defense #1 | Defense #2 | Goalie | ||||||||||||||||||||||||||||||||||||
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Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
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2024 | |||||||
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Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
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1 ballo ny 2023 | |||||
Axel Landen | 2023 | 139 | |||
Brandon Baddock | |||||
Bryce Brodzinski | 2019 | 203 | |||
Christian Kyrou | 2022 | 34 | |||
Cole Jordan | 2021 | 148 | |||
Eli Barnett | 2022 | 194 | |||
Elias Pettersson | 2022 | 98 | |||
Elias Salomonsson | 2022 | 66 | |||
Gavin Hain | |||||
Hank Kempf | 2021 | 212 | |||
Hardy Haman Aktell | |||||
Jack Sparkes | 2022 | 130 | |||
John Fusco | 2020 | 191 | |||
Justin Bailey | Link | ||||
Keean Washkurak | 2019 | 161 | |||
Kody Clark | |||||
Kole Sherwood | Link | ||||
Kyle Olson | |||||
Kyle Turris | Link | ||||
Leo Loof | 2020 | 98 | |||
Lucas Ciona | 2021 | 180 | |||
Lukas Dragicevic | 2023 | 43 | |||
Luke Coughlin | 2023 | 203 | |||
Marcus Kallionkieli | 2019 | 102 | |||
Matej Tomek | |||||
Matt Villata | |||||
Matthew Strome | |||||
Michael Dal Colle | Link | ||||
Michael Dipietro | Link | ||||
Miguel Tourigny | 2022 | 162 | |||
Mikko Koskinen | Link | ||||
Niklas Nordgren | |||||
Patrick Shea | |||||
Reece Newkirk | 2019 | 134 | |||
Riley Suter | |||||
Ryan Shea | |||||
Samu Bau | 2023 | 171 | |||
William Villeneuve | 2020 | 129 |
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