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Full Scoreboard »» |
Pittsburgh Penguins 10-10-1, 21pts · 11th 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 | C | 100.00 | 73 | 44 | 92 | 84 | 76 | 73 | 62 | 77 | 87 | 64 | 75 | 68 | 25 | 56 | 56 | 73 | 50 | 0 | 21 | 925,000$/1yrs | |||
![]() | 0 | LW | 100.00 | 76 | 43 | 72 | 86 | 64 | 79 | 89 | 91 | 39 | 87 | 80 | 73 | 50 | 85 | 92 | 81 | 50 | 0 | 34 | 6,125,000$/3yrs | |||
![]() | 0 | C/LW | 100.00 | 87 | 58 | 85 | 85 | 69 | 75 | 99 | 75 | 43 | 77 | 72 | 73 | 25 | 70 | 73 | 76 | 50 | 0 | 26 | 2,250,000$/1yrs | |||
![]() | 0 | C | 100.00 | 82 | 57 | 89 | 77 | 75 | 68 | 65 | 74 | 76 | 80 | 64 | 69 | 25 | 48 | 48 | 71 | 50 | 0 | 21 | 925,000$/2yrs | |||
![]() | 0 | LW | 99.00 | 67 | 43 | 88 | 90 | 75 | 72 | 88 | 77 | 38 | 76 | 77 | 62 | 55 | 78 | 80 | 76 | 50 | 0 | 30 | 6,000,000$/3yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 84 | 45 | 87 | 66 | 74 | 62 | 59 | 63 | 68 | 63 | 59 | 77 | 25 | 62 | 63 | 66 | 50 | 0 | 29 | 800,000$/1yrs | |||
![]() | 0 | C/RW | 100.00 | 73 | 43 | 96 | 76 | 67 | 61 | 73 | 62 | 47 | 62 | 56 | 80 | 59 | 65 | 66 | 66 | 50 | 0 | 29 | 1,200,000$/2yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 71 | 44 | 93 | 82 | 79 | 73 | 93 | 71 | 54 | 81 | 77 | 72 | 63 | 69 | 69 | 78 | 50 | 0 | 25 | 3,500,000$/1yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 65 | 62 | 73 | 70 | 62 | 74 | 75 | 71 | 80 | 68 | 68 | 65 | 65 | 60 | 60 | 68 | 50 | 0 | 27 | 762,500$/2yrs | |||
![]() | 0 | C | 99.00 | 61 | 42 | 90 | 81 | 78 | 78 | 83 | 77 | 97 | 71 | 81 | 82 | 70 | 83 | 87 | 78 | 50 | 0 | 31 | 7,500,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 80 | 44 | 92 | 78 | 68 | 68 | 85 | 79 | 32 | 66 | 81 | 65 | 25 | 61 | 62 | 76 | 50 | 0 | 23 | 1,450,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 67 | 42 | 90 | 83 | 70 | 64 | 85 | 65 | 25 | 77 | 70 | 60 | 25 | 63 | 63 | 71 | 50 | 0 | 26 | 750,000$/1yrs | |||
![]() | 0 | D | 100.00 | 77 | 59 | 73 | 81 | 89 | 81 | 97 | 58 | 25 | 55 | 47 | 87 | 53 | 81 | 81 | 65 | 50 | 0 | 32 | 6,000,000$/2yrs | |||
![]() | 0 | D | 100.00 | 85 | 99 | 57 | 71 | 78 | 64 | 62 | 55 | 25 | 50 | 50 | 77 | 75 | 47 | 47 | 61 | 50 | 0 | 26 | 912,500$/1yrs | |||
![]() | 0 | D | 100.00 | 80 | 45 | 87 | 87 | 78 | 91 | 92 | 91 | 25 | 66 | 60 | 85 | 25 | 76 | 76 | 74 | 50 | 0 | 27 | 9,500,000$/8yrs | |||
![]() | 0 | D | 100.00 | 67 | 42 | 87 | 90 | 71 | 93 | 92 | 86 | 25 | 80 | 56 | 79 | 63 | 67 | 68 | 73 | 50 | 0 | 23 | 8,450,000$/7yrs | |||
![]() | 0 | D | 100.00 | 86 | 58 | 84 | 85 | 69 | 85 | 96 | 72 | 25 | 62 | 53 | 82 | 75 | 67 | 68 | 69 | 50 | 0 | 27 | 5,875,000$/3yrs | |||
![]() | 0 | D | 100.00 | 75 | 44 | 84 | 80 | 79 | 85 | 93 | 63 | 25 | 53 | 49 | 94 | 25 | 65 | 65 | 66 | 50 | 0 | 26 | 2,800,000$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | LW/RW | 100.00 | 64 | 59 | 76 | 73 | 59 | 84 | 88 | 69 | 50 | 71 | 64 | 61 | 61 | 46 | 46 | 67 | 50 | 0 | 25 | 758,333$/2yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 73 | 43 | 96 | 74 | 72 | 56 | 78 | 55 | 71 | 60 | 56 | 73 | 25 | 64 | 64 | 63 | 50 | 0 | 32 | 750,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 90 | 46 | 90 | 80 | 73 | 58 | 73 | 58 | 38 | 61 | 72 | 65 | 25 | 62 | 63 | 71 | 50 | 0 | 24 | 1,300,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 57 | 63 | 43 | 67 | 63 | 67 | 72 | 49 | 50 | 46 | 46 | 52 | 44 | 44 | 44 | 51 | 50 | 0 | 21 | 848,333$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 78 | 71 | 94 | 73 | 71 | 79 | 83 | 66 | 50 | 61 | 68 | 67 | 65 | 44 | 44 | 69 | 50 | 0 | 24 | 750,000$/1yrs | |||
TEAM AVERAGE | 99.91 | 75 | 52 | 83 | 79 | 72 | 73 | 82 | 70 | 48 | 67 | 64 | 73 | 46 | 64 | 65 | 70 | 50 | 0 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 100.00 | 76 | 81 | 82 | 73 | 77 | 74 | 83 | 77 | 78 | 76 | 90 | 85 | 92 | 78 | 50 | 0 | 37 | 3,500,000$/2yrs |
![]() | 0 | 99.00 | 62 | 74 | 72 | 73 | 65 | 58 | 83 | 65 | 65 | 62 | 95 | 60 | 61 | 67 | 50 | 0 | 28 | 5,400,000$/5yrs |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 99.50 | 69 | 78 | 77 | 73 | 71 | 66 | 83 | 71 | 72 | 69 | 93 | 73 | 77 | 73 | 50 | 0 |
Player | # | POS | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | C/LW | 100.00 | 79 | 44 | 95 | 70 | 75 | 57 | 90 | 61 | 25 | 50 | 57 | 66 | 25 | 45 | 45 | 62 | 57 | 0 | 21 | 789,167$/2yrs | |||
![]() | 0 | LW | 100.00 | 79 | 71 | 97 | 67 | 71 | 71 | 73 | 64 | 50 | 60 | 64 | 67 | 61 | 44 | 44 | 67 | 60 | 0 | 22 | 925,000$/2yrs | |||
![]() | 0 | C | 100.00 | 70 | 62 | 87 | 60 | 62 | 69 | 74 | 53 | 66 | 55 | 46 | 59 | 44 | 44 | 44 | 56 | 60 | 0 | 22 | 850,000$/1yrs | |||
![]() | 0 | RW | 100.00 | 83 | 46 | 96 | 77 | 84 | 52 | 72 | 57 | 36 | 59 | 70 | 62 | 25 | 61 | 61 | 68 | 57 | 0 | 24 | 800,000$/1yrs | |||
![]() | 0 | D | 100.00 | 77 | 73 | 87 | 77 | 73 | 67 | 71 | 55 | 25 | 53 | 39 | 67 | 37 | 58 | 58 | 56 | 60 | 0 | 24 | 762,500$/2yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | LW/RW | 100.00 | 78 | 75 | 84 | 60 | 75 | 67 | 68 | 66 | 50 | 54 | 74 | 67 | 70 | 44 | 44 | 69 | 22 | 0 | 26 | 762,500$/2yrs | |||
![]() | 0 | LW | 100.00 | 80 | 77 | 86 | 72 | 67 | 57 | 84 | 59 | 64 | 62 | 56 | 72 | 25 | 56 | 57 | 65 | 22 | 0 | 28 | 750,000$/1yrs | |||
![]() | 0 | D | 100.00 | 74 | 74 | 73 | 81 | 74 | 72 | 75 | 62 | 25 | 53 | 53 | 69 | 50 | 65 | 66 | 63 | 22 | 0 | 29 | 3,000,000$/2yrs |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 100.00 | 61 | 58 | 56 | 73 | 70 | 52 | 69 | 62 | 65 | 61 | 75 | 45 | 45 | 62 | 57 | 0 | 23 | 883,750$/1yrs | ||||||
Scratches |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
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General Manager | Jean-Francois Chagnon |
---|
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 | Brad Marchand | 0 | LW | 21 | 10 | 12 | 22 | -1 | 26 | 0 | 37 | 108 | 24 | 48 | 9.26% | 8 | 20.42 | 6 | 4 | 10 | 53 | 0 | 0 | 0 | 36 | 1 | 1 | 46.88% | 32 | 20 | 4 | 0 | 0 | 1.03 | 0 | 1 | ||
2 | Taylor Hall | 0 | LW | 21 | 8 | 9 | 17 | 1 | 6 | 0 | 28 | 82 | 29 | 45 | 9.76% | 10 | 21.47 | 1 | 4 | 5 | 52 | 1 | 0 | 1 | 58 | 1 | 0 | 43.18% | 44 | 22 | 13 | 0 | 0 | 0.75 | 0 | 1 | ||
3 | Ryan O'Reilly | 0 | C | 21 | 4 | 13 | 17 | 1 | 2 | 0 | 16 | 39 | 10 | 19 | 10.26% | 7 | 21.62 | 1 | 6 | 7 | 52 | 0 | 1 | 1 | 61 | 0 | 1 | 56.74% | 608 | 8 | 13 | 0 | 0 | 0.75 | 0 | 1 | ||
4 | Ivan Barbashev | 0 | C/LW | 21 | 5 | 8 | 13 | -2 | 7 | 5 | 29 | 46 | 23 | 36 | 10.87% | 4 | 16.09 | 1 | 1 | 2 | 38 | 0 | 0 | 0 | 8 | 2 | 0 | 4.55% | 22 | 19 | 5 | 0 | 0 | 0.77 | 0 | 1 | ||
5 | Pavel Zacha | 0 | C/LW/RW | 21 | 5 | 8 | 13 | -3 | 2 | 0 | 19 | 45 | 10 | 38 | 11.11% | 5 | 16.73 | 0 | 2 | 2 | 39 | 0 | 0 | 0 | 23 | 2 | 0 | 40.67% | 300 | 11 | 7 | 0 | 0 | 0.74 | 0 | 0 | ||
6 | Shane Pinto | 0 | C | 21 | 4 | 5 | 9 | 1 | 4 | 0 | 18 | 38 | 12 | 14 | 10.53% | 7 | 12.54 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 0 | 0 | 51.16% | 129 | 13 | 4 | 0 | 0 | 0.68 | 0 | 0 | ||
7 | Seth Jones | 0 | D | 21 | 3 | 5 | 8 | -12 | 8 | 0 | 27 | 43 | 15 | 18 | 6.98% | 47 | 27.82 | 1 | 1 | 2 | 57 | 0 | 0 | 0 | 63 | 1 | 0 | 0.00% | 0 | 8 | 15 | 1 | 0 | 0.27 | 0 | 0 | ||
8 | Miro Heiskanen | 0 | D | 21 | 2 | 6 | 8 | -10 | 11 | 5 | 20 | 42 | 16 | 14 | 4.76% | 26 | 24.24 | 1 | 3 | 4 | 57 | 0 | 0 | 0 | 47 | 0 | 0 | 0.00% | 0 | 6 | 22 | 0 | 0 | 0.31 | 0 | 0 | ||
9 | Eeli Tolvanen | 0 | LW/RW | 21 | 4 | 4 | 8 | -3 | 2 | 0 | 20 | 37 | 13 | 22 | 10.81% | 4 | 16.96 | 1 | 1 | 2 | 39 | 0 | 0 | 0 | 25 | 0 | 0 | 38.10% | 21 | 10 | 6 | 0 | 0 | 0.45 | 0 | 0 | ||
10 | Juuso Parssinen | 0 | C | 21 | 3 | 3 | 6 | 1 | 6 | 0 | 23 | 43 | 15 | 14 | 6.98% | 4 | 12.02 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 50.00% | 4 | 6 | 6 | 0 | 0 | 0.48 | 0 | 0 | ||
11 | Nicolas Petan | 0 | C/LW/RW | 21 | 2 | 4 | 6 | 4 | 6 | 0 | 13 | 27 | 22 | 24 | 7.41% | 1 | 8.32 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 66.67% | 3 | 6 | 0 | 0 | 0 | 0.69 | 0 | 0 | ||
12 | Colin Blackwell | 0 | C/RW | 21 | 4 | 1 | 5 | 4 | 0 | 0 | 11 | 24 | 6 | 11 | 16.67% | 5 | 8.32 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2 | 0 | 38.78% | 49 | 1 | 4 | 0 | 0 | 0.57 | 0 | 0 | ||
13 | Vladislav Gavrikov | 0 | D | 21 | 2 | 2 | 4 | 17 | 4 | 0 | 17 | 15 | 7 | 5 | 13.33% | 23 | 15.56 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 62 | 0 | 2 | 0.00% | 0 | 1 | 4 | 0 | 0 | 0.24 | 0 | 0 | ||
14 | Sonny Milano | 0 | LW/RW | 21 | 0 | 4 | 4 | 1 | 0 | 0 | 15 | 32 | 9 | 14 | 0.00% | 8 | 11.93 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 20.00% | 5 | 7 | 4 | 0 | 0 | 0.32 | 0 | 0 | ||
15 | Tyler Myers | 0 | D | 21 | 0 | 3 | 3 | -2 | 22 | 0 | 34 | 22 | 10 | 8 | 0.00% | 32 | 20.89 | 0 | 0 | 0 | 35 | 0 | 0 | 0 | 8 | 0 | 0 | 0.00% | 0 | 2 | 16 | 0 | 0 | 0.14 | 0 | 0 | ||
16 | Lukas Sedlak | 0 | C/LW/RW | 21 | 1 | 2 | 3 | 4 | 0 | 0 | 13 | 23 | 9 | 6 | 4.35% | 4 | 8.45 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 2 | 3 | 4 | 0 | 0 | 0.34 | 0 | 0 | ||
17 | Connor Mackey | 0 | D | 21 | 0 | 3 | 3 | 16 | 45 | 5 | 18 | 13 | 4 | 6 | 0.00% | 14 | 12.27 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0.00% | 0 | 1 | 7 | 0 | 0 | 0.23 | 0 | 0 | ||
18 | Neal Pionk | 0 | D | 21 | 1 | 1 | 2 | -3 | 15 | 5 | 26 | 25 | 11 | 5 | 4.00% | 23 | 19.61 | 0 | 0 | 0 | 34 | 0 | 0 | 0 | 40 | 0 | 1 | 0.00% | 0 | 1 | 15 | 0 | 0 | 0.10 | 0 | 0 | ||
Team Total or Average | 378 | 58 | 93 | 151 | 14 | 166 | 20 | 384 | 704 | 245 | 347 | 8.24% | 232 | 16.40 | 12 | 22 | 34 | 463 | 1 | 1 | 2 | 449 | 10 | 5 | 49.22% | 1219 | 145 | 149 | 1 | 0 | 0.49 | 0 | 4 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | 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 | Marc-Andre Fleury | 19 | 10 | 8 | 1 | 0.916 | 2.68 | 1143 | 2 | 0 | 51 | 606 | 312 | 1 | 0 | 0.750 | 4 | 19 | 2 | 4 | 0 | 3 | |
2 | Elvis Merzlikins | 2 | 0 | 2 | 0 | 0.900 | 3.03 | 119 | 0 | 0 | 6 | 60 | 28 | 0 | 0 | 0.000 | 0 | 2 | 19 | 0 | 0 | 0 | |
Team Total or Average | 21 | 10 | 10 | 1 | 0.914 | 2.71 | 1263 | 2 | 0 | 57 | 666 | 340 | 1 | 0 | 0.750 | 4 | 21 | 21 | 4 | 0 | 3 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | VS Team | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | P | PCT | G | A | TP | SO | EG | GP1 | GP2 | GP3 | GP4 | SHF | SH1 | SP2 | SP3 | SP4 | SHA | SHB | Pim | Hit | PPA | PPG | PP% | PKA | PK GA | PK% | PK GF | W OF FO | T OF FO | OF FO% | W DF FO | T DF FO | DF FO% | W NT FO | T NT FO | NT FO% | PZ DF | PZ OF | PZ NT | PC DF | PC OF | PC NT | GF% | SH% | SV% | PDO | PDOBRK |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 7 | 6 | 1 | 2 | 0.500 | 7 | 8 | 15 | 0 | 0 | 0 | 1 | 6 | 0 | 67 | 16 | 30 | 21 | 0 | 79 | 24 | 18 | 35 | 5 | 1 | 20.00% | 9 | 1 | 88.89% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 42 | 24 | 42 | 17 | 34 | 17 | 54.5% | 10.4% | 92.4% | 102.9 | LUCKY | |
2 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 8 | -5 | 0 | 0.000 | 3 | 5 | 8 | 0 | 0 | 0 | 2 | 1 | 0 | 33 | 12 | 12 | 9 | 0 | 43 | 14 | 28 | 20 | 4 | 2 | 50.00% | 4 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 19 | 11 | 23 | 9 | 17 | 8 | 11.1% | 9.1% | 81.4% | 90.5 | FUN | |
3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 0 | 1 | 2 | 0 | 37 | 11 | 15 | 11 | 0 | 32 | 8 | 8 | 21 | 3 | 0 | 0.00% | 4 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 21 | 11 | 20 | 8 | 18 | 9 | 75.0% | 8.1% | 96.9% | 105.0 | DULL | |
4 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | -3 | 0 | 0.000 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 36 | 11 | 14 | 11 | 0 | 30 | 9 | 4 | 14 | 0 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 21 | 12 | 19 | 8 | 18 | 9 | 0.0% | 0.0% | 90.0% | 90.0 | Unlucky | |
5 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 28 | 4 | 14 | 10 | 0 | 36 | 10 | 6 | 21 | 4 | 0 | 0.00% | 3 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 18 | 9 | 23 | 9 | 17 | 8 | 60.0% | 10.7% | 94.4% | 105.2 | LUCKY | |
6 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | -1 | 0 | 0.000 | 2 | 2 | 4 | 0 | 0 | 0 | 1 | 1 | 0 | 29 | 7 | 10 | 12 | 0 | 31 | 8 | 8 | 18 | 3 | 0 | 0.00% | 4 | 1 | 75.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 20 | 12 | 21 | 9 | 17 | 8 | 50.0% | 6.9% | 90.3% | 97.2 | Unlucky | |
7 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 5 | -2 | 0 | 0.000 | 3 | 5 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 34 | 15 | 6 | 13 | 0 | 32 | 21 | 13 | 14 | 4 | 1 | 25.00% | 5 | 2 | 60.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 23 | 13 | 19 | 8 | 17 | 8 | 40.0% | 8.8% | 84.4% | 93.2 | Unlucky | |
8 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | -2 | 0 | 0.000 | 1 | 1 | 2 | 0 | 0 | 0 | 0 | 1 | 0 | 30 | 5 | 17 | 8 | 0 | 29 | 11 | 12 | 26 | 2 | 0 | 0.00% | 6 | 3 | 50.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 22 | 13 | 20 | 8 | 17 | 8 | 100.0% | 3.3% | 89.7% | 93.0 | Unlucky | |
9 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 11 | 3 | 8 | 4 | 1.000 | 11 | 18 | 29 | 0 | 0 | 3 | 5 | 3 | 0 | 68 | 26 | 24 | 18 | 0 | 61 | 26 | 15 | 40 | 6 | 2 | 33.33% | 5 | 0 | 100.00% | 1 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 41 | 25 | 43 | 18 | 35 | 16 | 75.0% | 16.2% | 95.1% | 111.3 | LUCKY | |
10 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 2 | 1.000 | 3 | 6 | 9 | 0 | 0 | 2 | 0 | 1 | 0 | 34 | 15 | 12 | 7 | 0 | 33 | 5 | 2 | 18 | 5 | 2 | 40.00% | 1 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 22 | 13 | 20 | 8 | 17 | 8 | 50.0% | 8.8% | 97.0% | 105.8 | DULL | |
11 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 1 | 0 | 2 | 0 | 39 | 12 | 10 | 17 | 0 | 27 | 15 | 4 | 15 | 5 | 0 | 0.00% | 2 | 1 | 50.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 21 | 12 | 21 | 8 | 16 | 8 | 75.0% | 7.7% | 92.6% | 100.3 | DULL | |
12 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | 4 | -1 | 1 | 0.500 | 3 | 5 | 8 | 0 | 0 | 2 | 0 | 1 | 0 | 36 | 11 | 12 | 12 | 5 | 32 | 13 | 6 | 28 | 3 | 0 | 0.00% | 3 | 1 | 66.67% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 25 | 15 | 20 | 9 | 18 | 9 | 50.0% | 8.3% | 87.5% | 95.8 | Unlucky | |
13 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 2 | 2 | 2 | 1.000 | 4 | 7 | 11 | 0 | 0 | 0 | 4 | 0 | 0 | 30 | 12 | 15 | 3 | 0 | 24 | 6 | 2 | 13 | 2 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 20 | 11 | 20 | 9 | 19 | 10 | 66.7% | 13.3% | 91.7% | 105.0 | LUCKY | |
14 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 3 | 2 | 2 | 1.000 | 5 | 9 | 14 | 0 | 0 | 0 | 2 | 3 | 0 | 40 | 9 | 12 | 19 | 0 | 30 | 8 | 8 | 15 | 5 | 3 | 60.00% | 4 | 1 | 75.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 20 | 11 | 22 | 9 | 17 | 8 | 50.0% | 12.5% | 90.0% | 102.5 | FUN | |
15 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 0 | 1 | 0 | 30 | 10 | 8 | 12 | 0 | 36 | 7 | 6 | 11 | 2 | 0 | 0.00% | 3 | 2 | 33.33% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 20 | 11 | 23 | 8 | 16 | 8 | 33.3% | 3.3% | 88.9% | 92.2 | Unlucky | |
16 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 2 | -1 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 1 | 0 | 0 | 31 | 12 | 9 | 10 | 0 | 34 | 15 | 12 | 15 | 3 | 0 | 0.00% | 6 | 1 | 83.33% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 21 | 12 | 22 | 8 | 16 | 8 | 50.0% | 3.2% | 94.1% | 97.3 | DULL | |
17 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 2 | -1 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 1 | 0 | 0 | 39 | 4 | 17 | 18 | 0 | 22 | 7 | 4 | 21 | 1 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 23 | 14 | 18 | 9 | 18 | 9 | 33.3% | 2.6% | 90.9% | 93.5 | Unlucky | |
18 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 2 | 0 | 1 | 0 | 37 | 15 | 5 | 17 | 0 | 25 | 12 | 2 | 20 | 1 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 22 | 13 | 20 | 8 | 16 | 8 | 75.0% | 8.1% | 96.0% | 104.1 | DULL | |
19 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | -2 | 0 | 0.000 | 1 | 1 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 26 | 6 | 11 | 9 | 0 | 30 | 13 | 10 | 19 | 2 | 1 | 50.00% | 5 | 1 | 80.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 20 | 11 | 21 | 9 | 18 | 8 | 0.0% | 3.8% | 90.0% | 93.8 | Unlucky | |
_Vs Division | 5 | 2 | 2 | 0 | 0 | 0 | 0 | 1 | 11 | 14 | -3 | 5 | 0.500 | 11 | 19 | 30 | 0 | 0 | 4 | 2 | 5 | 0 | 172 | 41 | 61 | 69 | 5 | 153 | 52 | 26 | 96 | 15 | 0 | 0.00% | 13 | 4 | 69.23% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 109 | 63 | 107 | 45 | 88 | 44 | 52.4% | 6.4% | 90.8% | 97.2 | Unlucky | |
_Vs Conference | 10 | 5 | 4 | 0 | 0 | 0 | 0 | 1 | 31 | 30 | 1 | 11 | 0.550 | 31 | 51 | 82 | 0 | 0 | 7 | 14 | 10 | 0 | 332 | 98 | 122 | 111 | 5 | 312 | 106 | 79 | 187 | 30 | 4 | 13.33% | 27 | 5 | 81.48% | 1 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 211 | 123 | 216 | 91 | 177 | 87 | 51.9% | 9.3% | 90.4% | 99.7 | FUN | |
_Since Last GM Reset | 21 | 10 | 10 | 0 | 0 | 0 | 0 | 1 | 58 | 58 | 0 | 21 | 0.500 | 58 | 93 | 151 | 0 | 0 | 12 | 21 | 25 | 0 | 704 | 213 | 253 | 237 | 5 | 666 | 232 | 168 | 384 | 60 | 12 | 20.00% | 70 | 14 | 80.00% | 1 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 449 | 261 | 445 | 187 | 369 | 183 | 51.1% | 8.2% | 91.3% | 99.5 | DULL | |
Total | 21 | 10 | 10 | 0 | 0 | 0 | 0 | 1 | 58 | 58 | 0 | 21 | 0.500 | 58 | 93 | 151 | 0 | 0 | 12 | 21 | 25 | 0 | 704 | 213 | 253 | 237 | 5 | 666 | 232 | 168 | 384 | 60 | 12 | 20.00% | 70 | 14 | 80.00% | 1 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 449 | 261 | 445 | 187 | 369 | 183 | 51.1% | 8.2% | 91.3% | 99.5 | DULL |
Puck Time | |
---|---|
Offensive Zone | 21 |
Neutral Zone | 17 |
Defensive Zone | 21 |
Puck Time | |
---|---|
Offensive Zone Start | 451 |
Neutral Zone Start | 307 |
Defensive Zone Start | 460 |
Puck Time | |
---|---|
With Puck | 30 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 600 |
Faceoffs Lost | 618 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 10.1 | 9.57 |
2nd Period | 22.2 | 20.31 |
3rd Period | 33.5 | 30.68 |
Overtime | 33.7 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.6 | 0.64 |
2nd Period | 1.6 | 1.65 |
3rd Period | 2.8 | 2.67 |
Overtime | 2.8 | 2.83 |
Even Strenght Goal | 45 |
---|---|
PP Goal | 12 |
PK Goal | 1 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 5 | 5 |
Lost | 6 | 4 |
Overtime Lost | 0 | 1 |
PP Attempt | 60 |
---|---|
PP Goal | 12 |
PK Attempt | 70 |
PK Goal Against | 14 |
Home | |
---|---|
Shots For | 33.5 |
Shots Against | 31.7 |
Goals For | 2.8 |
Goals Against | 2.8 |
Hits | 18.3 |
Shots Blocked | 11.0 |
Pim | 8.0 |
Projected Total Cap Hit | 79,031,666$ |
Projected Cap Space | 3,468,334$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 20,581,150$ |
Players In Salary Cap | 25 |
LTIR Players | 0 |
Penguins Roster | Pos | Age | Cap Hit | 2023-24 | 2024-25 | 2025-26 | 2026-27 | 2027-28 | 2028-29 | 2029-30 | 2030-31 |
---|---|---|---|---|---|---|---|---|---|---|---|
Adam Raska ![]() | LW/RW | 21 | 848,333$ | 848,333$ | 848,333$ | ||||||
Alex Barre-Boulet ![]() | LW/RW | 25 | 758,333$ | 758,333$ | 758,333$ | ||||||
Alexander Nylander ![]() | LW/RW | 24 | 750,000$ | 750,000$ | |||||||
Brad Marchand ![]() | LW | 34 | 6,125,000$ | 6,125,000$ | 6,125,000$ | 6,125,000$ | |||||
Carl Grundstrom ![]() | LW/RW | 24 | 1,300,000$ | 1,300,000$ | 1,300,000$ | ||||||
Colin Blackwell ![]() | C/RW | 29 | 1,200,000$ | 1,200,000$ | 1,200,000$ | ||||||
Connor Mackey ![]() | D | 26 | 912,500$ | 912,500$ | |||||||
Eeli Tolvanen ![]() | LW/RW | 23 | 1,450,000$ | 1,450,000$ | 1,450,000$ | ||||||
Elvis Merzlikins ![]() | G | 28 | 5,400,000$ | 5,400,000$ | 5,400,000$ | 5,400,000$ | 5,400,000$ | 5,400,000$ | |||
Ivan Barbashev ![]() | C/LW | 26 | 2,250,000$ | 2,250,000$ | |||||||
Jayson Megna ![]() | C/LW/RW | 32 | 750,000$ | 750,000$ | |||||||
Juuso Parssinen ![]() | C | 21 | 925,000$ | 925,000$ | 925,000$ | ||||||
Lukas Sedlak ![]() | C/LW/RW | 29 | 800,000$ | 800,000$ | |||||||
Marc-Andre Fleury ![]() | G | 37 | 3,500,000$ | 3,500,000$ | 3,500,000$ | ||||||
Miro Heiskanen ![]() | D | 23 | 8,450,000$ | 8,450,000$ | 8,450,000$ | 8,450,000$ | 8,450,000$ | 8,450,000$ | 8,450,000$ | 8,450,000$ | |
Neal Pionk ![]() | D | 27 | 5,875,000$ | 5,875,000$ | 5,875,000$ | 5,875,000$ | |||||
Nicolas Petan ![]() | C/LW/RW | 27 | 762,500$ | 762,500$ | 762,500$ | ||||||
Pavel Zacha ![]() | C/LW/RW | 25 | 3,500,000$ | 3,500,000$ | |||||||
Ryan O'Reilly ![]() | C | 31 | 7,500,000$ | 7,500,000$ | |||||||
Seth Jones ![]() | D | 27 | 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$ |
Shane Pinto ![]() | C | 21 | 925,000$ | 925,000$ | |||||||
Sonny Milano ![]() | LW/RW | 26 | 750,000$ | 750,000$ | |||||||
Taylor Hall ![]() | LW | 30 | 6,000,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | |||||
Tyler Myers ![]() | D | 32 | 6,000,000$ | 6,000,000$ | 6,000,000$ | ||||||
Vladislav Gavrikov ![]() | D | 26 | 2,800,000$ | 2,800,000$ |
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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 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 7 | 6 | 1 | 2 | 0.500 | 7 | 8 | 15 | 0 | 0 | 0 | 1 | 6 | 0 | 67 | 16 | 30 | 21 | 0 | 79 | 24 | 18 | 35 | 5 | 1 | 20.00% | 9 | 1 | 88.89% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 42 | 24 | 42 | 17 | 34 | 17 | 54.5% | 10.4% | 92.4% | 102.9 | LUCKY | |
2 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 8 | -5 | 0 | 0.000 | 3 | 5 | 8 | 0 | 0 | 0 | 2 | 1 | 0 | 33 | 12 | 12 | 9 | 0 | 43 | 14 | 28 | 20 | 4 | 2 | 50.00% | 4 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 19 | 11 | 23 | 9 | 17 | 8 | 11.1% | 9.1% | 81.4% | 90.5 | FUN | |
3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 0 | 1 | 2 | 0 | 37 | 11 | 15 | 11 | 0 | 32 | 8 | 8 | 21 | 3 | 0 | 0.00% | 4 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 21 | 11 | 20 | 8 | 18 | 9 | 75.0% | 8.1% | 96.9% | 105.0 | DULL | |
4 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | -3 | 0 | 0.000 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 36 | 11 | 14 | 11 | 0 | 30 | 9 | 4 | 14 | 0 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 21 | 12 | 19 | 8 | 18 | 9 | 0.0% | 0.0% | 90.0% | 90.0 | Unlucky | |
5 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 28 | 4 | 14 | 10 | 0 | 36 | 10 | 6 | 21 | 4 | 0 | 0.00% | 3 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 18 | 9 | 23 | 9 | 17 | 8 | 60.0% | 10.7% | 94.4% | 105.2 | LUCKY | |
6 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 3 | -1 | 0 | 0.000 | 2 | 2 | 4 | 0 | 0 | 0 | 1 | 1 | 0 | 29 | 7 | 10 | 12 | 0 | 31 | 8 | 8 | 18 | 3 | 0 | 0.00% | 4 | 1 | 75.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 20 | 12 | 21 | 9 | 17 | 8 | 50.0% | 6.9% | 90.3% | 97.2 | Unlucky | |
7 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 5 | -2 | 0 | 0.000 | 3 | 5 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 34 | 15 | 6 | 13 | 0 | 32 | 21 | 13 | 14 | 4 | 1 | 25.00% | 5 | 2 | 60.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 23 | 13 | 19 | 8 | 17 | 8 | 40.0% | 8.8% | 84.4% | 93.2 | Unlucky | |
8 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | -2 | 0 | 0.000 | 1 | 1 | 2 | 0 | 0 | 0 | 0 | 1 | 0 | 30 | 5 | 17 | 8 | 0 | 29 | 11 | 12 | 26 | 2 | 0 | 0.00% | 6 | 3 | 50.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 22 | 13 | 20 | 8 | 17 | 8 | 100.0% | 3.3% | 89.7% | 93.0 | Unlucky | |
9 | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 11 | 3 | 8 | 4 | 1.000 | 11 | 18 | 29 | 0 | 0 | 3 | 5 | 3 | 0 | 68 | 26 | 24 | 18 | 0 | 61 | 26 | 15 | 40 | 6 | 2 | 33.33% | 5 | 0 | 100.00% | 1 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 41 | 25 | 43 | 18 | 35 | 16 | 75.0% | 16.2% | 95.1% | 111.3 | LUCKY | |
10 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 2 | 1.000 | 3 | 6 | 9 | 0 | 0 | 2 | 0 | 1 | 0 | 34 | 15 | 12 | 7 | 0 | 33 | 5 | 2 | 18 | 5 | 2 | 40.00% | 1 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 22 | 13 | 20 | 8 | 17 | 8 | 50.0% | 8.8% | 97.0% | 105.8 | DULL | |
11 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 2 | 1 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 1 | 0 | 2 | 0 | 39 | 12 | 10 | 17 | 0 | 27 | 15 | 4 | 15 | 5 | 0 | 0.00% | 2 | 1 | 50.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 21 | 12 | 21 | 8 | 16 | 8 | 75.0% | 7.7% | 92.6% | 100.3 | DULL | |
12 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | 4 | -1 | 1 | 0.500 | 3 | 5 | 8 | 0 | 0 | 2 | 0 | 1 | 0 | 36 | 11 | 12 | 12 | 5 | 32 | 13 | 6 | 28 | 3 | 0 | 0.00% | 3 | 1 | 66.67% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 25 | 15 | 20 | 9 | 18 | 9 | 50.0% | 8.3% | 87.5% | 95.8 | Unlucky | |
13 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 2 | 2 | 2 | 1.000 | 4 | 7 | 11 | 0 | 0 | 0 | 4 | 0 | 0 | 30 | 12 | 15 | 3 | 0 | 24 | 6 | 2 | 13 | 2 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 20 | 11 | 20 | 9 | 19 | 10 | 66.7% | 13.3% | 91.7% | 105.0 | LUCKY | |
14 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 3 | 2 | 2 | 1.000 | 5 | 9 | 14 | 0 | 0 | 0 | 2 | 3 | 0 | 40 | 9 | 12 | 19 | 0 | 30 | 8 | 8 | 15 | 5 | 3 | 60.00% | 4 | 1 | 75.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 20 | 11 | 22 | 9 | 17 | 8 | 50.0% | 12.5% | 90.0% | 102.5 | FUN | |
15 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 4 | -3 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 0 | 1 | 0 | 30 | 10 | 8 | 12 | 0 | 36 | 7 | 6 | 11 | 2 | 0 | 0.00% | 3 | 2 | 33.33% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 20 | 11 | 23 | 8 | 16 | 8 | 33.3% | 3.3% | 88.9% | 92.2 | Unlucky | |
16 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 2 | -1 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 1 | 0 | 0 | 31 | 12 | 9 | 10 | 0 | 34 | 15 | 12 | 15 | 3 | 0 | 0.00% | 6 | 1 | 83.33% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 21 | 12 | 22 | 8 | 16 | 8 | 50.0% | 3.2% | 94.1% | 97.3 | DULL | |
17 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 2 | -1 | 0 | 0.000 | 1 | 2 | 3 | 0 | 0 | 0 | 1 | 0 | 0 | 39 | 4 | 17 | 18 | 0 | 22 | 7 | 4 | 21 | 1 | 0 | 0.00% | 2 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 23 | 14 | 18 | 9 | 18 | 9 | 33.3% | 2.6% | 90.9% | 93.5 | Unlucky | |
18 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 2 | 1.000 | 3 | 5 | 8 | 0 | 0 | 2 | 0 | 1 | 0 | 37 | 15 | 5 | 17 | 0 | 25 | 12 | 2 | 20 | 1 | 0 | 0.00% | 1 | 0 | 100.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 22 | 13 | 20 | 8 | 16 | 8 | 75.0% | 8.1% | 96.0% | 104.1 | DULL | |
19 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 3 | -2 | 0 | 0.000 | 1 | 1 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 26 | 6 | 11 | 9 | 0 | 30 | 13 | 10 | 19 | 2 | 1 | 50.00% | 5 | 1 | 80.00% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 20 | 11 | 21 | 9 | 18 | 8 | 0.0% | 3.8% | 90.0% | 93.8 | Unlucky | |
_Vs Division | 5 | 2 | 2 | 0 | 0 | 0 | 0 | 1 | 11 | 14 | -3 | 5 | 0.500 | 11 | 19 | 30 | 0 | 0 | 4 | 2 | 5 | 0 | 172 | 41 | 61 | 69 | 5 | 153 | 52 | 26 | 96 | 15 | 0 | 0.00% | 13 | 4 | 69.23% | 0 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 109 | 63 | 107 | 45 | 88 | 44 | 52.4% | 6.4% | 90.8% | 97.2 | Unlucky | |
_Vs Conference | 10 | 5 | 4 | 0 | 0 | 0 | 0 | 1 | 31 | 30 | 1 | 11 | 0.550 | 31 | 51 | 82 | 0 | 0 | 7 | 14 | 10 | 0 | 332 | 98 | 122 | 111 | 5 | 312 | 106 | 79 | 187 | 30 | 4 | 13.33% | 27 | 5 | 81.48% | 1 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 211 | 123 | 216 | 91 | 177 | 87 | 51.9% | 9.3% | 90.4% | 99.7 | FUN | |
_Since Last GM Reset | 21 | 10 | 10 | 0 | 0 | 0 | 0 | 1 | 58 | 58 | 0 | 21 | 0.500 | 58 | 93 | 151 | 0 | 0 | 12 | 21 | 25 | 0 | 704 | 213 | 253 | 237 | 5 | 666 | 232 | 168 | 384 | 60 | 12 | 20.00% | 70 | 14 | 80.00% | 1 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 449 | 261 | 445 | 187 | 369 | 183 | 51.1% | 8.2% | 91.3% | 99.5 | DULL | |
Total | 21 | 10 | 10 | 0 | 0 | 0 | 0 | 1 | 58 | 58 | 0 | 21 | 0.500 | 58 | 93 | 151 | 0 | 0 | 12 | 21 | 25 | 0 | 704 | 213 | 253 | 237 | 5 | 666 | 232 | 168 | 384 | 60 | 12 | 20.00% | 70 | 14 | 80.00% | 1 | 222 | 451 | 49.22% | 232 | 460 | 50.43% | 146 | 307 | 47.56% | 449 | 261 | 445 | 187 | 369 | 183 | 51.1% | 8.2% | 91.3% | 99.5 | DULL |
Puck Time | |
---|---|
Offensive Zone | 21 |
Neutral Zone | 17 |
Defensive Zone | 21 |
Puck Time | |
---|---|
Offensive Zone Start | 451 |
Neutral Zone Start | 307 |
Defensive Zone Start | 460 |
Puck Time | |
---|---|
With Puck | 30 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 600 |
Faceoffs Lost | 618 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 10.1 | 9.57 |
2nd Period | 22.2 | 20.31 |
3rd Period | 33.5 | 30.68 |
Overtime | 33.7 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.6 | 0.64 |
2nd Period | 1.6 | 1.65 |
3rd Period | 2.8 | 2.67 |
Overtime | 2.8 | 2.83 |
Even Strenght Goal | 45 |
---|---|
PP Goal | 12 |
PK Goal | 1 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 5 | 5 |
Lost | 6 | 4 |
Overtime Lost | 0 | 1 |
PP Attempt | 60 |
---|---|
PP Goal | 12 |
PK Attempt | 70 |
PK Goal Against | 14 |
Home | |
---|---|
Shots For | 33.5 |
Shots Against | 31.7 |
Goals For | 2.8 |
Goals Against | 2.8 |
Hits | 18.3 |
Shots Blocked | 11.0 |
Pim | 8.0 |
Date | Matchup | Result | Detail | ||
---|---|---|---|---|---|
2023-10-06 | @ | Blackhawks2,Penguins1 | RECAP | ||
2023-10-09 | @ | Penguins3,Capitals2 | RECAP | ||
2023-10-10 | @ | Flames1,Penguins3 | RECAP | ||
2023-10-14 | @ | Penguins3,Red Wings8 | RECAP | ||
2023-10-17 | @ | Penguins3,Blues1 | RECAP | ||
2023-10-20 | @ | Stars5,Penguins3 | RECAP | ||
2023-10-22 | @ | Avalanche3,Penguins0 | RECAP | ||
2023-10-24 | @ | Senators2,Penguins4 | RECAP | ||
2023-10-26 | @ | Ducks1,Penguins6 | RECAP | ||
2023-10-31 | @ | Penguins3,Sharks1 | RECAP | ||
2023-11-03 | @ | Penguins1,Ducks5 | RECAP | ||
2023-11-05 | @ | Penguins5,Kings3 | RECAP | ||
2023-11-07 | @ | Sabres2,Penguins5 | RECAP | ||
2023-11-10 | @ | Penguins3,Blue Jackets4 (SO) | RECAP | ||
2023-11-12 | @ | Devils4,Penguins1 | RECAP | ||
2023-11-14 | @ | Penguins1,Hurricanes2 | RECAP | ||
2023-11-15 | @ | Golden Knights3,Penguins1 | RECAP | ||
2023-11-18 | @ | Rangers2,Penguins3 | RECAP | ||
2023-11-20 | @ | Penguins6,Sabres1 | RECAP | ||
2023-11-21 | @ | Maple Leafs3,Penguins2 | RECAP | ||
2023-11-24 | @ | Penguins1,Predators3 | RECAP | ||
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Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
79,031,666$ | 0$ | 79,031,666$ | 3,468,334$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | PPG Paints Arena | |
City | Pittsburgh | ||
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 | 63338 | 52267 | 20981 | 40874 | 10262 |
Attendance PCT | 95.97% | 95.03% | 95.37% | 92.90% | 93.29% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
30 | 17066 - 94.81% | 615,635$ | 6,771,986$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
79,031,666$ | 79,031,666$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
20,581,150$ | 79,031,666$ | 20,581,150$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
18,469,053$ | 142 | 411,623$ | 58,450,466$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
64,282,325$ | 79,031,666$ | -473,689,804$ | -519,503,076$ |
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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2027 | |||||||
2028 |
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 ) |
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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. |
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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 |
---|---|---|---|---|---|
1 ballo pit 2023 | |||||
Aarne Talvitie | |||||
Aaron Pionk | 2023 | 158 | |||
Aidan Mcdonough | 2019 | 192 | |||
Albin Sundsvik | 2020 | 160 | |||
Alex Laferriere | 2020 | 46 | |||
Alexander Gordin | 2020 | 170 | |||
Alexander Yelesin | |||||
Andre Lee | 2019 | 171 | |||
Andrew Gibson | 2023 | 55 | |||
Bear Hughes | 2020 | 149 | |||
Benjamin Roger | 2021 | 58 | |||
Brad Gardiner | 2023 | 98 | |||
Brandon Coe | 2020 | 111 | |||
Brandon Lisowsky | 2022 | 220 | |||
Brett Murray | 2016 | 99 | Link | ||
Bryce Montgomery | 2021 | 175 | |||
C.J. Suess | Link | ||||
Cameron Whitehead | 2022 | 129 | |||
Chase Priskie | Link | ||||
Chris Romaine | 2022 | 188 | |||
Cole Reinhardt | 2020 | 183 | |||
David Gucciardi | 2022 | 211 | |||
Dmytro Timashov | Link | ||||
Ethan Haider | 2019 | 94 | |||
Ethan Hay | 2023 | 214 | |||
Ethan Keppen | 2019 | 91 | |||
Filip Eriksson | 2023 | 162 | |||
Garlin Bjorklund | 2020 | 180 | |||
Greg Meireles | 2019 | 156 | |||
Ian Scott | |||||
Jack Harvey | 2023 | 190 | |||
Jakov Novak | 2018 | 191 | |||
Jakub Demek | 2021 | 133 | |||
Jakub Stancl | 2023 | 118 | |||
Jayson Shaugabay | 2023 | 126 | |||
Jeremy Hanzel | 2023 | 194 | |||
Jesse Nurmi | 2023 | 121 | |||
Jett Woo | 2018 | 50 | |||
Joshua Bloom | 2021 | 101 | |||
Kristian Kostadinski | 2023 | 222 | |||
Layton Ahac | 2019 | 87 | |||
Marc-Andre Gaudet | 2022 | 156 | |||
Mathias Laferriere | 2018 | 160 | |||
Matthew Andonovski | 2023 | 150 | |||
Matthew Morden | 2022 | 124 | |||
Michael Krutil | 2020 | 118 | |||
Nicholas Moldenhauer | 2022 | 113 | |||
Nolan Patrick | Link | ||||
Oliver Bonk | 2023 | 23 | |||
Oskar Magnusson | 2020 | 211 | |||
Quinn Finley | 2022 | 92 | |||
Sami Niku | Link | ||||
Ty Mueller | 2023 | 120 | |||
Wyatt Kaiser | 2020 | 87 | |||
Zachary Schultz | 2023 | 182 |
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