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Full Scoreboard »» |
New York City Rangers Team Overall:77 17-11-5, 39pts · 5th in Conférence EST |
# | Player | Position | Height | Weight | Age | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | Overall | Condition | Contract | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | ![]() | C | 6' 3" | 207 | 26 | 59 | 45 | 78 | 86 | 85 | 88 | 90 | 84 | 89 | 83 | 83 | 76 | 84 | 74 | 80 | 0 | 40 | 82 | 100.00 | 6,125,000$/3yrs | |
0 | ![]() | RW | 5' 10" | 177 | 31 | 54 | 38 | 82 | 89 | 66 | 90 | 88 | 92 | 58 | 89 | 87 | 63 | 91 | 80 | 74 | 0 | 40 | 82 | 100.00 | 10,500,000$/3yrs | |
0 | ![]() | C | 6' 1" | 216 | 28 | 54 | 47 | 85 | 77 | 81 | 87 | 91 | 76 | 90 | 85 | 73 | 90 | 74 | 77 | 80 | 0 | 40 | 80 | 96.00 | 7,500,000$/3yrs | |
0 | ![]() | LW | 5' 11" | 170 | 28 | 54 | 41 | 86 | 83 | 66 | 88 | 87 | 82 | 53 | 91 | 81 | 59 | 83 | 77 | 73 | 0 | 40 | 79 | 100.00 | 11,642,857$/3yrs | |
0 | ![]() | C/LW | 6' 0" | 184 | 26 | 62 | 39 | 82 | 79 | 71 | 86 | 83 | 77 | 80 | 82 | 78 | 81 | 79 | 73 | 76 | 0 | 40 | 79 | 100.00 | 6,000,000$/1yrs | |
0 | ![]() | LW/RW | 6' 1" | 211 | 27 | 79 | 53 | 76 | 72 | 80 | 85 | 82 | 71 | 74 | 72 | 78 | 83 | 71 | 75 | 74 | 0 | 40 | 77 | 100.00 | 2,250,000$/1yrs | |
0 | ![]() | LW/RW | 5' 11" | 198 | 24 | 59 | 39 | 86 | 80 | 72 | 83 | 88 | 77 | 53 | 69 | 76 | 67 | 80 | 68 | 70 | 0 | 40 | 76 | 100.00 | 1,650,000$/3yrs | |
0 | ![]() | LW/RW | 5' 11" | 192 | 28 | 72 | 43 | 84 | 77 | 71 | 82 | 86 | 73 | 54 | 72 | 75 | 63 | 74 | 75 | 72 | 0 | 40 | 76 | 100.00 | 5,500,000$/3yrs | |
0 | ![]() | LW/RW | 6' 0" | 188 | 23 | 59 | 39 | 88 | 76 | 74 | 81 | 83 | 74 | 56 | 71 | 78 | 59 | 76 | 67 | 69 | 0 | 40 | 75 | 100.00 | 1,288,333$/3yrs | |
0 | ![]() | LW/RW | 5' 9" | 163 | 27 | 52 | 37 | 87 | 77 | 62 | 79 | 85 | 76 | 54 | 79 | 69 | 59 | 78 | 75 | 72 | 0 | 40 | 74 | 100.00 | 4,500,000$/1yrs | |
0 | ![]() | C | 6' 1" | 195 | 25 | 57 | 39 | 86 | 68 | 76 | 82 | 89 | 66 | 85 | 78 | 63 | 76 | 65 | 71 | 68 | 0 | 40 | 73 | 100.00 | 2,937,500$/3yrs | |
0 | ![]() | C/LW | 6' 0" | 187 | 24 | 81 | 45 | 87 | 68 | 72 | 79 | 88 | 67 | 76 | 65 | 66 | 78 | 68 | 69 | 67 | 0 | 40 | 73 | 100.00 | 1,475,000$/1yrs | |
0 | ![]() | D | 6' 1" | 201 | 29 | 62 | 43 | 77 | 80 | 78 | 92 | 89 | 78 | 30 | 86 | 76 | 84 | 63 | 78 | 86 | 0 | 40 | 81 | 100.00 | 4,000,000$/3yrs | |
0 | ![]() | D | 5' 10" | 180 | 29 | 69 | 39 | 86 | 77 | 66 | 90 | 84 | 76 | 30 | 83 | 69 | 90 | 58 | 77 | 79 | 0 | 40 | 79 | 99.38 | 6,250,000$/3yrs | |
0 | ![]() | D | 6' 0" | 197 | 27 | 79 | 43 | 82 | 76 | 74 | 87 | 89 | 74 | 30 | 81 | 73 | 57 | 61 | 75 | 68 | 0 | 40 | 77 | 100.00 | 1,200,000$/3yrs | |
0 | ![]() | D | 6' 3" | 207 | 25 | 64 | 42 | 89 | 69 | 85 | 89 | 91 | 67 | 30 | 78 | 66 | 90 | 53 | 71 | 74 | 0 | 40 | 76 | 100.00 | 5,300,000$/3yrs | |
0 | ![]() | D | 6' 4" | 212 | 26 | 87 | 46 | 76 | 68 | 89 | 86 | 79 | 67 | 30 | 73 | 65 | 84 | 53 | 73 | 67 | 0 | 40 | 75 | 99.86 | 3,850,000$/2yrs | |
0 | ![]() | D | 6' 0" | 203 | 23 | 62 | 46 | 83 | 72 | 75 | 82 | 88 | 70 | 30 | 75 | 71 | 63 | 55 | 67 | 65 | 0 | 40 | 74 | 100.00 | 888,333$/3yrs | |
Scratches | ||||||||||||||||||||||||||
0 | ![]() | LW/RW | 6' 2" | 198 | 23 | 79 | 41 | 83 | 67 | 80 | 73 | 87 | 65 | 56 | 63 | 66 | 71 | 64 | 67 | 65 | 0 | 40 | 72 | 100.00 | 800,000$/3yrs | |
0 | ![]() | RW | 5' 11" | 187 | 23 | 73 | 46 | 85 | 66 | 70 | 78 | 73 | 65 | 52 | 62 | 64 | 63 | 66 | 67 | 65 | 0 | 40 | 70 | 65.30 | 700,000$/3yrs |
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 | Height | Weight | Age | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | Overall | Condition | Contract |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | ![]() | 6' 5" | 215 | 29 | 96 | 93 | 95 | 96 | 96 | 95 | 78 | 84 | 0 | 40 | 81 | 100.00 | 1,850,000$/3yrs | |||||||
0 | ![]() | 6' 6" | 206 | 29 | 93 | 93 | 95 | 93 | 93 | 92 | 78 | 84 | 0 | 40 | 79 | 100.00 | 3,666,667$/3yrs | |||||||
Scratches |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Alain Vigneault | 90 | 95 | 86 | 98 | 89 | 96 | 1 | CAN | 57 | 1 | 3,500,000$ |
General Manager | Martin Charron |
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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 | MP | 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 | 33 | 16 | 20 | 36 | 2 | 2 | 0 | 24 | 120 | 31 | 78 | 13.33% | 9 | 18.11 | 4 | 9 | 13 | 97 | 0 | 0 | 0 | 29 | 0 | 0 | 54.36% | 688 | 0 | 0 | 0 | 0 | 1.20 | 2 | 4 | ||
2 | Patrick Kane | 0 | RW | 33 | 16 | 17 | 33 | 9 | 12 | 0 | 26 | 142 | 36 | 106 | 11.27% | 2 | 20.24 | 5 | 5 | 10 | 117 | 0 | 0 | 0 | 0 | 3 | 0 | 47.83% | 46 | 0 | 0 | 0 | 0 | 0.99 | 1 | 4 | ||
3 | Ryan Ellis | 0 | D | 33 | 11 | 20 | 31 | 3 | 8 | 0 | 43 | 52 | 21 | 33 | 21.15% | 38 | 23.81 | 5 | 4 | 9 | 99 | 0 | 0 | 0 | 80 | 1 | 1 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.79 | 0 | 0 | ||
4 | Ryan O'Reilly | 0 | C | 33 | 4 | 20 | 24 | 9 | 0 | 0 | 14 | 82 | 29 | 66 | 4.88% | 9 | 21.74 | 0 | 9 | 9 | 100 | 0 | 0 | 0 | 110 | 1 | 0 | 52.23% | 919 | 0 | 0 | 0 | 0 | 0.67 | 0 | 1 | ||
5 | Artemi Panarin | 0 | LW | 33 | 8 | 15 | 23 | 5 | 4 | 0 | 15 | 100 | 20 | 63 | 8.00% | 3 | 20.08 | 2 | 6 | 8 | 117 | 0 | 0 | 0 | 29 | 1 | 0 | 34.62% | 78 | 0 | 0 | 0 | 1 | 0.69 | 0 | 3 | ||
6 | Ryan Nugent-Hopkins | 0 | C/LW | 33 | 8 | 11 | 19 | 2 | 10 | 0 | 42 | 88 | 26 | 79 | 9.09% | 6 | 20.65 | 2 | 3 | 5 | 97 | 0 | 0 | 0 | 53 | 1 | 0 | 43.68% | 87 | 0 | 0 | 0 | 0 | 0.56 | 1 | 2 | ||
7 | Roman Josi | 0 | D | 27 | 5 | 13 | 18 | 3 | 21 | 5 | 39 | 52 | 12 | 32 | 9.62% | 22 | 25.11 | 4 | 4 | 8 | 98 | 0 | 0 | 0 | 67 | 1 | 1 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.53 | 0 | 0 | ||
8 | Zach Hyman | 0 | LW/RW | 33 | 5 | 10 | 15 | 5 | 33 | 5 | 78 | 74 | 25 | 61 | 6.76% | 8 | 17.84 | 0 | 0 | 0 | 8 | 0 | 0 | 0 | 88 | 1 | 0 | 47.06% | 68 | 0 | 0 | 0 | 0 | 0.51 | 0 | 0 | ||
9 | Connor Murphy | 0 | D | 33 | 4 | 10 | 14 | 6 | 42 | 0 | 87 | 25 | 6 | 11 | 16.00% | 32 | 17.80 | 0 | 2 | 2 | 24 | 0 | 0 | 0 | 92 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.48 | 0 | 0 | ||
10 | Anthony Duclair | 0 | LW/RW | 33 | 3 | 8 | 11 | 0 | 4 | 0 | 15 | 48 | 19 | 38 | 6.25% | 0 | 10.59 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 8 | 1 | 0 | 34.48% | 29 | 0 | 0 | 0 | 0 | 0.63 | 1 | 2 | ||
11 | Chris Tierney | 0 | C | 33 | 4 | 7 | 11 | -11 | 8 | 0 | 11 | 49 | 10 | 24 | 8.16% | 8 | 12.40 | 0 | 0 | 0 | 13 | 0 | 0 | 0 | 31 | 0 | 0 | 50.21% | 486 | 0 | 0 | 0 | 0 | 0.54 | 0 | 0 | ||
12 | Erik Gustafsson | 0 | D | 33 | 2 | 9 | 11 | -10 | 30 | 0 | 67 | 22 | 10 | 14 | 9.09% | 17 | 21.02 | 0 | 4 | 4 | 110 | 0 | 0 | 0 | 17 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.32 | 0 | 0 | ||
13 | Jaccob Slavin | 0 | D | 21 | 1 | 9 | 10 | 8 | 10 | 0 | 20 | 23 | 11 | 13 | 4.35% | 35 | 21.92 | 1 | 1 | 2 | 29 | 0 | 0 | 0 | 47 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.43 | 0 | 0 | ||
14 | Jason Zucker | 0 | LW/RW | 33 | 6 | 4 | 10 | -11 | 12 | 0 | 54 | 45 | 14 | 34 | 13.33% | 4 | 12.23 | 0 | 0 | 0 | 36 | 0 | 0 | 0 | 2 | 1 | 0 | 32.00% | 50 | 0 | 0 | 0 | 0 | 0.50 | 0 | 0 | ||
15 | Nikita Gusev | 0 | LW/RW | 33 | 3 | 5 | 8 | 1 | 2 | 0 | 1 | 26 | 7 | 28 | 11.54% | 1 | 6.27 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 42.86% | 14 | 0 | 0 | 0 | 0 | 0.77 | 1 | 1 | ||
16 | Vince Dunn | 0 | D | 33 | 1 | 7 | 8 | 2 | 15 | 5 | 15 | 24 | 4 | 15 | 4.17% | 24 | 16.02 | 1 | 0 | 1 | 77 | 0 | 0 | 0 | 35 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.30 | 0 | 0 | ||
17 | Jake DeBrusk | 0 | LW/RW | 33 | 3 | 3 | 6 | -10 | 4 | 0 | 16 | 34 | 10 | 39 | 8.82% | 0 | 10.75 | 0 | 0 | 0 | 63 | 0 | 0 | 0 | 1 | 1 | 1 | 41.38% | 29 | 0 | 0 | 0 | 0 | 0.34 | 0 | 0 | ||
18 | Ivan Barbashev | 0 | C/LW | 30 | 2 | 2 | 4 | -2 | 13 | 5 | 30 | 21 | 5 | 16 | 9.52% | 3 | 7.59 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 32 | 1 | 0 | 46.27% | 201 | 0 | 0 | 0 | 0 | 0.35 | 0 | 0 | ||
19 | Warren Foegele | 0 | LW/RW | 16 | 1 | 1 | 2 | 2 | 2 | 0 | 10 | 8 | 4 | 13 | 12.50% | 1 | 6.56 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 0 | 25.93% | 27 | 0 | 0 | 0 | 0 | 0.38 | 0 | 0 | ||
20 | Nicolas Aube-Kubel | 0 | RW | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 2.78 | 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 | 590 | 103 | 191 | 294 | 13 | 232 | 20 | 607 | 1035 | 300 | 763 | 9.95% | 222 | 16.46 | 24 | 47 | 71 | 1102 | 0 | 0 | 0 | 731 | 15 | 3 | 50.00% | 2722 | 0 | 0 | 0 | 1 | 0.61 | 6 | 17 |
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 | Darcy Kuemper | 29 | 14 | 10 | 5 | 0.891 | 2.69 | 1693 | 0 | 2 | 76 | 698 | 0 | 1 | 1 | 0.818 | 11 | 28 | 5 | 1 | 4 | 0 | |
2 | Jacob Markstrom | 6 | 3 | 1 | 0 | 0.882 | 3.32 | 307 | 0 | 1 | 17 | 144 | 0 | 0 | 1 | 0.500 | 6 | 5 | 28 | 0 | 0 | 1 | |
Team Total or Average | 35 | 17 | 11 | 5 | 0.890 | 2.79 | 2001 | 0 | 3 | 93 | 842 | 0 | 1 | 2 | 0.706 | 17 | 33 | 33 | 1 | 4 | 1 |
Projected Total Cap Hit | 89,173,690$ |
Projected Cap Space | 2,326,310$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 0$ |
Players In Salary Cap | 21 |
LTIR Players | 1 |
Player Name | Pos | Age | Cap Hit | 2019-2020 | 2020-2021 | 2021-2022 | 2022-2023 | 2023-2024 | 2024-2025 | 2025-2026 | 2026-2027 |
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Anthony Duclair ![]() | LW/RW | 24 | 1,650,000$ | 1,650,000$ | 1,650,000$ | 1,650,000$ | |||||
Artemi Panarin ![]() | LW | 28 | 11,642,857$ | 11,642,857$ | 11,642,857$ | 11,642,857$ | |||||
Chris Tierney ![]() | C | 25 | 2,937,500$ | 2,937,500$ | 2,937,500$ | 2,937,500$ | |||||
Connor Murphy ![]() | D | 26 | 3,850,000$ | 3,850,000$ | 3,850,000$ | ||||||
Darcy Kuemper ![]() | LW/RW | 29 | 1,850,000$ | 1,850,000$ | 1,850,000$ | 1,850,000$ | |||||
Erik Gustafsson ![]() | D | 27 | 1,200,000$ | 1,200,000$ | 1,200,000$ | 1,200,000$ | |||||
Ivan Barbashev ![]() | C/LW | 24 | 1,475,000$ | 1,475,000$ | |||||||
Jaccob Slavin ![]() | D | 25 | 5,300,000$ | 5,300,000$ | 5,300,000$ | 5,300,000$ | |||||
Jacob Markstrom ![]() | D | 29 | 3,666,667$ | 3,666,667$ | 3,666,667$ | 3,666,667$ | |||||
Jake DeBrusk ![]() | LW/RW | 23 | 1,288,333$ | 1,288,333$ | 1,288,333$ | 1,288,333$ | |||||
Jason Zucker ![]() | LW/RW | 28 | 5,500,000$ | 5,500,000$ | 5,500,000$ | 5,500,000$ | |||||
Mark Scheifele ![]() | C | 26 | 6,125,000$ | 6,125,000$ | 6,125,000$ | 6,125,000$ | |||||
Nicolas Aube-Kubel ![]() | RW | 23 | 700,000$ | 700,000$ | 700,000$ | 700,000$ | |||||
Nikita Gusev ![]() | LW/RW | 27 | 4,500,000$ | 4,500,000$ | |||||||
Patrick Kane ![]() | RW | 31 | 10,500,000$ | 10,500,000$ | 10,500,000$ | 10,500,000$ | |||||
Roman Josi ![]() | D | 29 | 4,000,000$ | 4,000,000$ | 4,000,000$ | 4,000,000$ | |||||
Ryan Ellis ![]() | D | 29 | 6,250,000$ | 6,250,000$ | 6,250,000$ | 6,250,000$ | |||||
Ryan Nugent-Hopkins ![]() | C/LW | 26 | 6,000,000$ | 6,000,000$ | |||||||
Ryan O'Reilly ![]() | C | 28 | 7,500,000$ | 7,500,000$ | 7,500,000$ | 7,500,000$ | |||||
Vince Dunn ![]() | D | 23 | 888,333$ | 888,333$ | 888,333$ | 888,333$ | |||||
Warren Foegele ![]() | LW/RW | 23 | 800,000$ | 800,000$ | 800,000$ | 800,000$ | |||||
Zach Hyman ![]() | LW/RW | 27 | 2,250,000$ | 2,250,000$ |
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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 |
# | 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 |
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1 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 8 | 9 | -1 | 2 | 0.500 | 8 | 13 | 21 | 0 | 0 | 4 | 2 | 2 | 0 | 64 | 24 | 15 | 25 | 0 | 56 | 15 | 10 | 44 | 10 | 1 | 10.00% | 5 | 1 | 80.00% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 45 | 32 | 46 | 15 | 27 | 13 | 46.7% | 12.5% | 83.9% | 96.4 | FUN | |
2 | 3 | 0 | 2 | 0 | 0 | 0 | 1 | 0 | 6 | 11 | -5 | 2 | 0.333 | 6 | 6 | 12 | 0 | 0 | 2 | 2 | 1 | 1 | 93 | 30 | 27 | 32 | 7 | 102 | 17 | 24 | 66 | 12 | 2 | 16.67% | 6 | 1 | 83.33% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 76 | 53 | 70 | 22 | 38 | 19 | 28.6% | 6.5% | 89.2% | 95.7 | Unlucky | |
3 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 1 | 1 | 0 | 1 | 34 | 9 | 11 | 13 | 1 | 24 | 6 | 4 | 24 | 2 | 1 | 50.00% | 2 | 0 | 100.00% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 22 | 15 | 24 | 6 | 13 | 6 | 50.0% | 8.8% | 91.7% | 100.5 | DULL | |
4 | 3 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 9 | 10 | -1 | 3 | 0.500 | 9 | 15 | 24 | 0 | 0 | 4 | 3 | 1 | 4 | 81 | 26 | 33 | 18 | 13 | 81 | 16 | 20 | 41 | 14 | 2 | 14.29% | 7 | 3 | 57.14% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 77 | 55 | 73 | 22 | 39 | 19 | 50.0% | 11.1% | 87.7% | 98.8 | FUN | |
5 | 3 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 6 | 8 | -2 | 2 | 0.333 | 6 | 10 | 16 | 0 | 0 | 3 | 1 | 2 | 0 | 71 | 29 | 14 | 28 | 0 | 83 | 17 | 34 | 56 | 7 | 2 | 28.57% | 15 | 2 | 86.67% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 69 | 46 | 72 | 21 | 37 | 18 | 40.0% | 8.5% | 90.4% | 98.8 | Unlucky | |
6 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 1 | 5 | 4 | 1.000 | 6 | 11 | 17 | 0 | 1 | 1 | 3 | 2 | 0 | 53 | 15 | 19 | 19 | 0 | 40 | 14 | 14 | 44 | 12 | 1 | 8.33% | 7 | 1 | 85.71% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 51 | 37 | 43 | 15 | 24 | 12 | 100.0% | 11.3% | 97.5% | 108.8 | LUCKY | |
7 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 2 | 3 | 2 | 1.000 | 5 | 9 | 14 | 0 | 0 | 2 | 1 | 2 | 0 | 28 | 7 | 10 | 11 | 0 | 20 | 3 | 20 | 14 | 2 | 1 | 50.00% | 3 | 1 | 66.67% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 26 | 19 | 20 | 7 | 12 | 6 | 80.0% | 17.9% | 90.0% | 107.9 | FUN | |
8 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | -1 | 0 | 0.000 | 2 | 3 | 5 | 0 | 0 | 0 | 1 | 1 | 0 | 27 | 14 | 7 | 6 | 0 | 21 | 12 | 6 | 15 | 3 | 0 | 0.00% | 3 | 1 | 66.67% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 25 | 18 | 22 | 6 | 12 | 6 | 50.0% | 7.4% | 85.7% | 93.1 | Unlucky | |
9 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 2 | 4 | 4 | 1.000 | 6 | 10 | 16 | 0 | 0 | 3 | 2 | 1 | 0 | 68 | 26 | 23 | 19 | 0 | 44 | 13 | 10 | 42 | 7 | 1 | 14.29% | 5 | 0 | 100.00% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 51 | 37 | 45 | 14 | 23 | 11 | 71.4% | 8.8% | 95.5% | 104.3 | DULL | |
10 | 3 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 12 | 8 | 4 | 4 | 0.667 | 12 | 23 | 35 | 0 | 2 | 7 | 2 | 3 | 0 | 98 | 40 | 23 | 35 | 0 | 81 | 37 | 14 | 70 | 17 | 2 | 11.76% | 7 | 0 | 100.00% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 75 | 52 | 66 | 22 | 37 | 19 | 55.6% | 12.2% | 90.1% | 102.4 | FUN | |
11 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 10 | 9 | 1 | 2 | 0.500 | 10 | 19 | 29 | 1 | 0 | 3 | 3 | 4 | 0 | 74 | 20 | 23 | 31 | 0 | 41 | 8 | 10 | 40 | 8 | 3 | 37.50% | 4 | 1 | 75.00% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 54 | 41 | 41 | 13 | 23 | 12 | 46.7% | 13.5% | 78.0% | 91.6 | FUN | |
12 | 3 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 12 | 8 | 4 | 4 | 0.667 | 12 | 20 | 32 | 1 | 0 | 4 | 2 | 6 | 0 | 97 | 28 | 33 | 36 | 0 | 64 | 21 | 14 | 51 | 9 | 4 | 44.44% | 7 | 1 | 85.71% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 73 | 53 | 70 | 19 | 36 | 18 | 53.3% | 12.4% | 87.5% | 99.9 | FUN | |
13 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | 4 | -1 | 1 | 0.500 | 3 | 6 | 9 | 0 | 0 | 1 | 0 | 2 | 0 | 32 | 8 | 9 | 10 | 10 | 19 | 4 | 6 | 22 | 8 | 1 | 12.50% | 3 | 0 | 100.00% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 29 | 21 | 22 | 7 | 13 | 7 | 33.3% | 9.4% | 78.9% | 88.3 | FUN | |
14 | 2 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 6 | 8 | -2 | 2 | 0.500 | 6 | 10 | 16 | 0 | 0 | 2 | 1 | 3 | 0 | 52 | 10 | 23 | 16 | 3 | 61 | 25 | 16 | 49 | 6 | 1 | 16.67% | 8 | 0 | 100.00% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 44 | 30 | 56 | 14 | 27 | 13 | 38.5% | 11.5% | 86.9% | 98.4 | FUN | |
15 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 5 | 4 | 4 | 1.000 | 9 | 17 | 26 | 0 | 0 | 5 | 3 | 1 | 0 | 66 | 29 | 23 | 14 | 0 | 66 | 14 | 25 | 42 | 7 | 2 | 28.57% | 10 | 2 | 80.00% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 50 | 36 | 47 | 12 | 22 | 11 | 70.0% | 13.6% | 92.4% | 106.1 | LUCKY | |
16 | 2 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 3 | 7 | -4 | 1 | 0.250 | 3 | 6 | 9 | 0 | 0 | 1 | 0 | 2 | 0 | 77 | 27 | 20 | 29 | 1 | 41 | 12 | 12 | 38 | 8 | 1 | 12.50% | 6 | 0 | 100.00% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 48 | 34 | 47 | 14 | 25 | 13 | 22.2% | 3.9% | 82.9% | 86.8 | Unlucky | |
_Vs Division | 9 | 4 | 3 | 0 | 0 | 2 | 0 | 0 | 29 | 26 | 3 | 10 | 0.556 | 29 | 49 | 78 | 1 | 0 | 11 | 5 | 13 | 0 | 248 | 74 | 80 | 91 | 3 | 228 | 66 | 84 | 170 | 24 | 8 | 33.33% | 33 | 4 | 87.88% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 213 | 149 | 220 | 63 | 114 | 57 | 48.8% | 11.7% | 88.6% | 100.3 | FUN | |
_Vs Conference | 16 | 8 | 4 | 0 | 1 | 2 | 0 | 1 | 56 | 45 | 11 | 21 | 0.656 | 56 | 100 | 156 | 1 | 2 | 25 | 11 | 19 | 1 | 478 | 160 | 146 | 163 | 14 | 418 | 127 | 133 | 328 | 58 | 14 | 24.14% | 55 | 6 | 89.09% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 391 | 275 | 380 | 112 | 201 | 101 | 51.9% | 11.7% | 89.2% | 100.9 | FUN | |
_Since Last GM Reset | 33 | 14 | 11 | 0 | 1 | 3 | 2 | 2 | 106 | 97 | 9 | 39 | 0.591 | 106 | 183 | 289 | 2 | 3 | 43 | 27 | 33 | 6 | 1015 | 342 | 313 | 342 | 35 | 844 | 234 | 239 | 658 | 132 | 25 | 18.94% | 98 | 14 | 85.71% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 824 | 587 | 770 | 237 | 415 | 210 | 49.4% | 10.4% | 88.5% | 99.0 | FUN | |
Total | 33 | 14 | 11 | 0 | 1 | 3 | 2 | 2 | 106 | 97 | 9 | 39 | 0.591 | 106 | 183 | 289 | 2 | 3 | 43 | 27 | 33 | 6 | 1015 | 342 | 313 | 342 | 35 | 844 | 234 | 239 | 658 | 132 | 25 | 18.94% | 98 | 14 | 85.71% | 0 | 590 | 1149 | 51.35% | 494 | 1011 | 48.86% | 263 | 500 | 52.60% | 824 | 587 | 770 | 237 | 415 | 210 | 49.4% | 10.4% | 88.5% | 99.0 | FUN |
Puck Time | |
---|---|
Offensive Zone | 24 |
Neutral Zone | 12 |
Defensive Zone | 23 |
Puck Time | |
---|---|
Offensive Zone Start | 1149 |
Neutral Zone Start | 500 |
Defensive Zone Start | 1011 |
Puck Time | |
---|---|
With Puck | 31 |
Without Puck | 29 |
Faceoffs | |
---|---|
Faceoffs Won | 1347 |
Faceoffs Lost | 1313 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 10.4 | 9.57 |
2nd Period | 19.8 | 20.31 |
3rd Period | 30.2 | 30.68 |
Overtime | 31.3 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 1.3 | 0.64 |
2nd Period | 2.1 | 1.65 |
3rd Period | 3.1 | 2.67 |
Overtime | 3.3 | 2.83 |
Even Strenght Goal | 79 |
---|---|
PP Goal | 25 |
PK Goal | 0 |
Empty Net Goal | 2 |
Home | Away | |
---|---|---|
Win | 6 | 11 |
Lost | 8 | 3 |
Overtime Lost | 3 | 2 |
PP Attempt | 132 |
---|---|
PP Goal | 25 |
PK Attempt | 98 |
PK Goal Against | 14 |
Home | |
---|---|
Shots For | 30.8 |
Shots Against | 25.6 |
Goals For | 3.2 |
Goals Against | 2.9 |
Hits | 19.9 |
Shots Blocked | 7.1 |
Pim | 7.2 |
Date | Matchup | Result | Detail | ||
---|---|---|---|---|---|
2020-11-22 | @ | Rangers2,Kings3 | RECAP | ||
2020-11-23 | @ | Rangers5,Hurricanes3 | RECAP | ||
2020-11-25 | @ | Penguins4,Rangers3 (OT) | RECAP | ||
2020-11-27 | @ | Oilers1,Rangers3 | RECAP | ||
2020-11-29 | @ | Panthers3,Rangers5 | RECAP | ||
2020-12-02 | @ | Rangers5,Maple Leafs2 | RECAP | ||
2020-12-03 | @ | Rangers4,Bruins0 | RECAP | ||
2020-12-06 | @ | Islanders4,Rangers2 | RECAP | ||
2020-12-08 | @ | Bruins8,Rangers3 | RECAP | ||
2020-12-09 | @ | Rangers3,Canadiens4 (SO) | RECAP | ||
2020-12-11 | @ | Rangers3,Penguins4 (OT) | RECAP | ||
2020-12-13 | @ | Flames5,Rangers3 | RECAP | ||
2020-12-15 | @ | Capitals8,Rangers4 | RECAP | ||
2020-12-17 | @ | Rangers5,Bruins0 | RECAP | ||
2020-12-19 | @ | Blackhawks5,Rangers3 | RECAP | ||
2020-12-20 | @ | Rangers2,Predators3 | RECAP | ||
2020-12-22 | @ | Rangers3,Oilers1 | RECAP | ||
2020-12-24 | @ | Avalanche0,Rangers3 | RECAP | ||
2020-12-27 | @ | Islanders2,Rangers6 | RECAP | ||
2020-12-29 | @ | Kings4,Rangers3 (SO) | RECAP | ||
2020-12-31 | @ | Rangers1,Hurricanes4 | RECAP | ||
2021-01-03 | @ | Avalanche1,Rangers3 | RECAP | ||
2021-01-05 | @ | Rangers4,Kings3 (SO) | RECAP | ||
2021-01-07 | @ | Golden Knights4,Rangers3 (OT) | RECAP | ||
2021-01-09 | @ | Rangers2,Capitals1 (SO) | RECAP | ||
2021-01-10 | @ | Blackhawks4,Rangers7 | RECAP | ||
2021-01-11 | @ | Rangers4,Panthers2 | RECAP | ||
2021-01-14 | @ | Rangers4,Islanders2 | RECAP | ||
2021-01-15 | @ | Capitals2,Rangers0 | RECAP | ||
2021-01-18 | @ | Rangers5,Flames4 | RECAP | ||
2021-01-19 | @ | Hurricanes1,Rangers0 | RECAP | ||
2021-01-21 | @ | Golden Knights3,Rangers0 | RECAP | ||
2021-01-23 | @ | Rangers3,Senators2 (OT) | RECAP | ||
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2021-04-30 | @ |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
89,173,690$ | 0$ | 89,173,690$ | 2,326,310$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | Madison Square Garden | |
City | New York City | ||
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 | 0 | 0 | 0 | 0 | 0 |
Attendance PCT | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
Income | |||||
---|---|---|---|---|---|
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
24 | 0 - 0.00% | 0$ | 0$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
89,173,690$ | 89,173,690$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
0$ | 89,173,690$ | 0$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 99 | 545,139$ | 53,968,761$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
69,501,762$ | 89,173,690$ | 10,000,000$ | -59,501,762$ |
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DEFENSE | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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GOALIE | ||||||||||||||||||||||||||||||
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Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
---|---|---|---|---|---|---|---|
2021 | |||||||
2022 | |||||||
2023 | |||||||
2024 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
---|---|---|---|---|---|
Axel Andersson | |||||
Connor McMichael | |||||
David Farrance | |||||
Dmitri Voronkov | |||||
Ian Scott | |||||
Jack Drury | |||||
Karl Henriksson | |||||
Max Gildon | |||||
Nikita Alexandrov | |||||
Peter Diliberatore | |||||
Raphael Lavoie | |||||
Yegor Spiridonov |
Year | Ronde 1 | Ronde 2 | Ronde 3 | Ronde 4 | Ronde 5 | Ronde 6 | Ronde 7 |
---|---|---|---|---|---|---|---|
2021 | |||||||
2022 | |||||||
2023 | |||||||
2024 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
---|---|---|---|---|---|
Axel Andersson | |||||
Connor McMichael | |||||
David Farrance | |||||
Dmitri Voronkov | |||||
Ian Scott | |||||
Jack Drury | |||||
Karl Henriksson | |||||
Max Gildon | |||||
Nikita Alexandrov | |||||
Peter Diliberatore | |||||
Raphael Lavoie | |||||
Yegor Spiridonov |
|