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Full Scoreboard >> |
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Full Scoreboard >> |
![]() | Stuttgart Bisons 8-3-1, 17pts · 1st in World Conference |
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/RW | 100.00 | 63 | 42 | 90 | 89 | 73 | 83 | 99 | 93 | 46 | 90 | 92 | 71 | 35 | 72 | 75 | 91 | 75 | 86 | 28 | 6,962,366$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 71 | 43 | 89 | 82 | 69 | 81 | 89 | 82 | 32 | 81 | 90 | 74 | 80 | 74 | 77 | 86 | 75 | 83 | 32 | 4,100,000$/1yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 59 | 41 | 96 | 83 | 72 | 76 | 96 | 80 | 55 | 77 | 87 | 72 | 80 | 65 | 66 | 83 | 75 | 80 | 26 | 3,100,000$/2yrs | |||
![]() | 0 | C/LW | 100.00 | 78 | 54 | 85 | 79 | 77 | 69 | 99 | 82 | 92 | 82 | 77 | 74 | 62 | 88 | 90 | 79 | 75 | 77 | 34 | 6,000,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 63 | 41 | 87 | 84 | 61 | 79 | 91 | 99 | 40 | 90 | 70 | 63 | 83 | 78 | 83 | 79 | 75 | 76 | 36 | 4,900,000$/1yrs | |||
![]() | 0 | C | 100.00 | 75 | 44 | 64 | 81 | 77 | 73 | 89 | 82 | 91 | 78 | 81 | 64 | 75 | 60 | 60 | 80 | 75 | 76 | 21 | 875,000$/1yrs | |||
![]() | 0 | LW/RW | 100.00 | 67 | 52 | 80 | 81 | 71 | 70 | 99 | 85 | 34 | 81 | 74 | 62 | 75 | 65 | 66 | 77 | 75 | 73 | 28 | 2,250,000$/5yrs | |||
![]() | 13 | C/LW | 100.00 | 76 | 54 | 83 | 77 | 74 | 66 | 92 | 69 | 38 | 71 | 75 | 73 | 25 | 69 | 72 | 73 | 75 | 72 | 28 | 2,750,000$/1yrs | |||
![]() | 37 | C/LW/RW | 100.00 | 85 | 57 | 78 | 81 | 61 | 76 | 98 | 68 | 84 | 73 | 66 | 82 | 75 | 70 | 75 | 69 | 75 | 72 | 32 | 2,600,000$/1yrs | |||
![]() | 0 | C | 100.00 | 71 | 43 | 83 | 82 | 69 | 70 | 93 | 71 | 92 | 73 | 70 | 71 | 77 | 63 | 65 | 71 | 75 | 71 | 22 | 925,000$/1yrs | |||
![]() | 0 | C | 100.00 | 71 | 42 | 91 | 80 | 64 | 70 | 90 | 75 | 68 | 67 | 72 | 75 | 75 | 65 | 65 | 70 | 75 | 71 | 28 | 2,000,000$/3yrs | |||
![]() | 0 | LW | 100.00 | 86 | 56 | 83 | 80 | 81 | 65 | 77 | 68 | 25 | 70 | 71 | 69 | 25 | 54 | 55 | 71 | 75 | 70 | 21 | 625,000$/1yrs | |||
![]() | 0 | D | 100.00 | 69 | 43 | 88 | 84 | 77 | 88 | 86 | 80 | 25 | 70 | 48 | 94 | 25 | 86 | 93 | 75 | 75 | 83 | 34 | 8,800,000$/2yrs | |||
![]() | 0 | D | 100.00 | 82 | 45 | 78 | 82 | 73 | 91 | 90 | 77 | 25 | 72 | 53 | 89 | 61 | 86 | 94 | 75 | 75 | 82 | 37 | 7,000,000$/1yrs | |||
![]() | 0 | D | 100.00 | 78 | 44 | 88 | 83 | 72 | 76 | 69 | 77 | 25 | 68 | 48 | 76 | 25 | 51 | 51 | 73 | 75 | 74 | 20 | 875,000$/2yrs | |||
![]() | 0 | D | 100.00 | 83 | 55 | 86 | 76 | 80 | 78 | 99 | 62 | 25 | 61 | 48 | 89 | 25 | 78 | 83 | 62 | 75 | 73 | 33 | 2,000,000$/4yrs | |||
![]() | 0 | D | 100.00 | 85 | 45 | 86 | 80 | 70 | 83 | 96 | 61 | 25 | 66 | 48 | 86 | 25 | 73 | 75 | 63 | 75 | 73 | 31 | 1,500,000$/1yrs | |||
![]() | 0 | D | 100.00 | 76 | 43 | 89 | 83 | 66 | 82 | 87 | 71 | 25 | 63 | 48 | 71 | 25 | 64 | 65 | 67 | 75 | 70 | 24 | 1,400,000$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 27 | LW | 100.00 | 87 | 79 | 76 | 83 | 86 | 70 | 99 | 76 | 39 | 66 | 76 | 61 | 25 | 79 | 80 | 72 | 75 | 70 | 33 | 3,500,000$/2yrs | |||
TEAM AVERAGE | 100.00 | 75 | 49 | 84 | 82 | 72 | 76 | 91 | 77 | 47 | 74 | 68 | 75 | 51 | 71 | 73 | 75 | 75 | 75 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 100.00 | 77 | 70 | 67 | 66 | 82 | 72 | 72 | 76 | 82 | 77 | 75 | 47 | 47 | 83 | 75 | 79 | 23 | 775,000$/2yrs |
![]() | 0 | 100.00 | 76 | 55 | 58 | 79 | 81 | 71 | 73 | 77 | 81 | 76 | 92 | 75 | 78 | 84 | 75 | 78 | 36 | 1,850,000$/2yrs |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 100.00 | 77 | 63 | 63 | 73 | 82 | 72 | 73 | 77 | 82 | 77 | 84 | 61 | 63 | 84 | 75 | 79 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
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General Manager | John Goegel |
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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 | PPG | PPA | PPP | PKG | PKA | PKP | PKM | GW | GT | FO% | FOT | GA | TA | EG | HT | P/20 | PSG | PSS |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Jamie Benn | ![]() | 0 | C/LW | 12 | 6 | 11 | 17 | 9 | 4 | 0 | 15 | 31 | 10 | 30 | 19.35% | 2 | 17.92 | 3 | 5 | 8 | 0 | 0 | 0 | 2 | 1 | 0 | 56.79% | 280 | 0 | 0 | 0 | 0 | 1.58 | 0 | 0 |
2 | Bryan Rust | ![]() | 0 | LW/RW | 12 | 9 | 6 | 15 | 10 | 4 | 0 | 19 | 41 | 12 | 29 | 21.95% | 4 | 21.88 | 1 | 3 | 4 | 1 | 0 | 1 | 44 | 2 | 0 | 29.63% | 27 | 0 | 0 | 1 | 0 | 1.14 | 0 | 0 |
3 | Mats Zuccarello | ![]() | 0 | LW/RW | 12 | 5 | 9 | 14 | 6 | 2 | 0 | 7 | 27 | 7 | 22 | 18.52% | 0 | 18.11 | 3 | 4 | 7 | 0 | 0 | 0 | 4 | 1 | 0 | 16.67% | 18 | 0 | 0 | 0 | 0 | 1.29 | 0 | 0 |
4 | Kris Letang | ![]() | 0 | D | 12 | 2 | 10 | 12 | 5 | 12 | 0 | 29 | 12 | 7 | 15 | 16.67% | 20 | 24.11 | 1 | 4 | 5 | 0 | 0 | 0 | 36 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.83 | 0 | 0 |
5 | William Nylander | ![]() | 0 | C/RW | 12 | 5 | 7 | 12 | -2 | 2 | 0 | 2 | 45 | 13 | 35 | 11.11% | 1 | 20.30 | 3 | 4 | 7 | 0 | 1 | 1 | 44 | 0 | 1 | 38.39% | 112 | 0 | 0 | 0 | 0 | 0.99 | 0 | 0 |
6 | Brayden McNabb | ![]() | 0 | D | 12 | 2 | 7 | 9 | 4 | 14 | 0 | 48 | 15 | 7 | 11 | 13.33% | 19 | 20.42 | 1 | 3 | 4 | 0 | 1 | 1 | 33 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.73 | 0 | 0 |
7 | Alex Pietrangelo | ![]() | 0 | D | 12 | 2 | 5 | 7 | 4 | 4 | 0 | 12 | 18 | 4 | 17 | 11.11% | 22 | 24.48 | 2 | 1 | 3 | 0 | 0 | 0 | 40 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.48 | 0 | 0 |
8 | Mason McTavish | ![]() | 0 | C | 12 | 2 | 3 | 5 | -5 | 16 | 0 | 39 | 19 | 3 | 18 | 10.53% | 0 | 15.82 | 1 | 3 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 48.02% | 252 | 0 | 0 | 0 | 0 | 0.53 | 0 | 0 |
9 | Michael Bunting | ![]() | 0 | LW/RW | 12 | 1 | 4 | 5 | -5 | 6 | 0 | 13 | 23 | 3 | 14 | 4.35% | 0 | 18.05 | 1 | 2 | 3 | 0 | 0 | 0 | 25 | 0 | 0 | 45.00% | 20 | 0 | 0 | 0 | 0 | 0.46 | 0 | 0 |
10 | Pavel Mintyukov | ![]() | 0 | D | 12 | 2 | 3 | 5 | 3 | 6 | 0 | 11 | 12 | 2 | 5 | 16.67% | 7 | 20.16 | 1 | 1 | 2 | 0 | 0 | 0 | 30 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.41 | 0 | 0 |
11 | Rasmus Sandin | ![]() | 0 | D | 12 | 1 | 4 | 5 | -3 | 2 | 0 | 7 | 4 | 1 | 3 | 25.00% | 8 | 15.14 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.55 | 0 | 0 |
12 | Yegor Sharangovich | ![]() | 0 | C/LW/RW | 12 | 3 | 1 | 4 | 1 | 0 | 0 | 4 | 31 | 6 | 18 | 9.68% | 0 | 12.57 | 0 | 0 | 0 | 0 | 0 | 0 | 25 | 2 | 0 | 37.50% | 32 | 0 | 0 | 0 | 0 | 0.53 | 0 | 0 |
13 | Pius Suter | ![]() | 0 | C | 12 | 3 | 1 | 4 | 0 | 0 | 0 | 3 | 11 | 2 | 14 | 27.27% | 1 | 9.28 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 50.00% | 4 | 0 | 0 | 0 | 0 | 0.72 | 0 | 0 |
14 | Yanni Gourde | ![]() | 37 | C/LW/RW | 12 | 1 | 2 | 3 | 0 | 7 | 5 | 5 | 8 | 3 | 11 | 12.50% | 0 | 9.26 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 48.62% | 109 | 0 | 0 | 0 | 0 | 0.54 | 0 | 0 |
15 | Warren Foegele | ![]() | 13 | C/LW | 12 | 0 | 2 | 2 | 0 | 5 | 5 | 14 | 17 | 5 | 12 | 0.00% | 0 | 10.83 | 0 | 1 | 1 | 0 | 0 | 0 | 4 | 0 | 0 | 22.22% | 9 | 0 | 0 | 0 | 0 | 0.31 | 0 | 0 |
16 | Matthew Knies | ![]() | 0 | LW | 7 | 0 | 2 | 2 | 2 | 2 | 0 | 6 | 9 | 1 | 5 | 0.00% | 1 | 9.49 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 60.00% | 5 | 0 | 0 | 0 | 0 | 0.60 | 0 | 0 |
17 | Anton Lundell | ![]() | 0 | C | 12 | 0 | 1 | 1 | 0 | 6 | 0 | 12 | 15 | 6 | 13 | 0.00% | 1 | 10.19 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 59.46% | 148 | 0 | 0 | 0 | 0 | 0.16 | 0 | 0 |
18 | Anders Lee | ![]() | 27 | LW | 5 | 0 | 0 | 0 | -2 | 2 | 0 | 5 | 6 | 1 | 2 | 0.00% | 0 | 9.14 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 83.33% | 6 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 |
19 | Dylan DeMelo | ![]() | 0 | D | 12 | 0 | 0 | 0 | -3 | 12 | 0 | 19 | 6 | 2 | 2 | 0.00% | 23 | 16.02 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 |
Team Total or Average | 216 | 44 | 78 | 122 | 24 | 106 | 10 | 270 | 350 | 95 | 276 | 12.57% | 109 | 16.33 | 18 | 32 | 50 | 367 | 1 | 2 | 3 | 305 | 8 | 1 | 49.71% | 1022 | 0 | 0 | 1 | 0 | 0.69 | 0 | 0 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | Goalie Name | Team Name | GP | W | L | OTL | PCT | GAA | MP | PIM | SO | GA | SA | SAR | A | EG | PS % | PSA | ST | BG | S1 | S2 | S3 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Semyon Varlamov | ![]() | 9 | 7 | 1 | 1 | 0.931 | 2.10 | 543 | 0 | 0 | 19 | 276 | 0 | 1 | 0 | 0.000 | 0 | 9 | 3 | 1 | 1 | 0 |
2 | Joel Hofer | ![]() | 3 | 1 | 2 | 0 | 0.862 | 4.00 | 180 | 0 | 0 | 12 | 87 | 0 | 0 | 0 | 0.000 | 0 | 3 | 9 | 0 | 0 | 0 |
Team Total or Average | 12 | 8 | 3 | 1 | 0.915 | 2.57 | 723 | 0 | 0 | 31 | 363 | 0 | 1 | 0 | 0.000 | 0 | 12 | 12 | 1 | 1 | 0 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | VS Team | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | P | PCT | G | A | TP | SO | EG | GP1 | GP2 | GP3 | GP4 | SHF | SH1 | SP2 | SP3 | SP4 | SHA | SHB | Pim | Hit | PPA | PPG | PP% | PKA | PK GA | PK% | PK GF | W OF FO | T OF FO | OF FO% | W DF FO | T DF FO | DF FO% | W NT FO | T NT FO | NT FO% | PZ DF | PZ OF | PZ NT | PC DF | PC OF | PC NT | GF% | SH% | SV% | PDO | PDOBRK |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | ![]() | 2 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 4.00 | 3.50 | 0.50 | 3 | 0.750 | 4.0 | 6.5 | 10.5 | 0 | 0 | 3 | 3 | 2 | 0 | 30.0 | 20 | 24 | 16 | 0 | 38.5 | 12.0 | 9.00 | 21.5 | 3.50 | 2.00 | 57.14% | 4.50 | 1.00 | 77.78% | 1 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 22.50 | 16.00 | 26.00 | 7.50 | 11.50 | 5.50 | 44.4% | 13.3% | 90.9% | 104.2 | FUN |
2 | ![]() | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 3.50 | 4.00 | -0.50 | 2 | 0.500 | 3.5 | 5.5 | 9.0 | 0 | 0 | 3 | 2 | 2 | 0 | 29.5 | 19 | 12 | 28 | 0 | 38.5 | 8.5 | 6.00 | 27.0 | 2.50 | 0.50 | 20.00% | 2.50 | 1.00 | 60.00% | 0 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 25.00 | 17.50 | 22.00 | 6.00 | 12.50 | 6.00 | 50.0% | 11.9% | 89.6% | 101.5 | FUN |
3 | ![]() | 2 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 2.00 | 3.00 | -1.00 | 2 | 0.500 | 2.0 | 3.5 | 5.5 | 0 | 0 | 2 | 1 | 0 | 1 | 34.0 | 22 | 25 | 19 | 2 | 36.0 | 11.5 | 9.00 | 27.0 | 5.50 | 1.00 | 18.18% | 4.00 | 1.00 | 75.00% | 0 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 23.50 | 16.00 | 24.50 | 7.50 | 12.50 | 6.00 | 33.3% | 5.9% | 91.7% | 97.5 | DULL |
4 | ![]() | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 5.00 | 1.50 | 3.50 | 4 | 1.000 | 5.0 | 9.0 | 14.0 | 0 | 0 | 3 | 5 | 2 | 0 | 31.0 | 20 | 23 | 19 | 0 | 21.0 | 6.0 | 13.00 | 20.5 | 7.00 | 3.00 | 42.86% | 3.50 | 0.50 | 85.71% | 0 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 24.50 | 17.50 | 22.00 | 7.50 | 12.50 | 6.50 | 66.7% | 16.1% | 92.9% | 109.0 | LUCKY |
5 | ![]() | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2.00 | 1.50 | 0.50 | 2 | 0.500 | 2.0 | 3.5 | 5.5 | 0 | 0 | 0 | 2 | 2 | 0 | 23.5 | 8 | 20 | 19 | 0 | 23.0 | 9.0 | 9.00 | 19.0 | 3.00 | 0.50 | 16.67% | 4.50 | 1.00 | 77.78% | 0 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 23.00 | 15.50 | 24.50 | 7.00 | 11.50 | 6.00 | 75.0% | 8.5% | 93.5% | 102.0 | DULL |
6 | ![]() | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 5.50 | 2.00 | 3.50 | 4 | 1.000 | 5.5 | 11.0 | 16.5 | 0 | 0 | 5 | 1 | 5 | 0 | 27.0 | 22 | 15 | 17 | 0 | 24.5 | 7.5 | 7.00 | 20.0 | 3.00 | 2.00 | 66.67% | 3.50 | 0.50 | 85.71% | 0 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 22.50 | 15.00 | 24.50 | 7.00 | 12.50 | 6.00 | 70.0% | 20.4% | 91.8% | 112.2 | LUCKY |
_Vs Division | 12 | 7 | 3 | 0 | 1 | 1 | 0 | 0 | 3.67 | 2.58 | 1.08 | 17 | 0.708 | 3.7 | 6.5 | 10.2 | 0 | 0 | 16 | 14 | 13 | 1 | 29.2 | 111 | 119 | 118 | 2 | 30.3 | 9.1 | 8.83 | 22.5 | 4.08 | 1.50 | 36.73% | 3.75 | 0.83 | 77.78% | 1 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 23.75 | 16.50 | 24.08 | 7.33 | 12.33 | 6.25 | 55.3% | 12.6% | 91.5% | 104.0 | LUCKY | |
_Vs Conference | 12 | 7 | 3 | 0 | 1 | 1 | 0 | 0 | 3.67 | 2.58 | 1.08 | 17 | 0.708 | 3.7 | 6.5 | 10.2 | 0 | 0 | 16 | 14 | 13 | 1 | 29.2 | 111 | 119 | 118 | 2 | 30.3 | 9.1 | 8.83 | 22.5 | 4.08 | 1.50 | 36.73% | 3.75 | 0.83 | 77.78% | 1 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 23.75 | 16.50 | 24.08 | 7.33 | 12.33 | 6.25 | 55.3% | 12.6% | 91.5% | 104.0 | LUCKY | |
_Since Last GM Reset | 12 | 7 | 3 | 0 | 1 | 1 | 0 | 0 | 3.67 | 2.58 | 1.08 | 17 | 0.708 | 3.7 | 6.5 | 10.2 | 0 | 0 | 16 | 14 | 13 | 1 | 29.2 | 111 | 119 | 118 | 2 | 30.3 | 9.1 | 8.83 | 22.5 | 4.08 | 1.50 | 36.73% | 3.75 | 0.83 | 77.78% | 1 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 23.75 | 16.50 | 24.08 | 7.33 | 12.33 | 6.25 | 55.3% | 12.6% | 91.5% | 104.0 | LUCKY | |
Total | 12 | 7 | 3 | 0 | 1 | 1 | 0 | 0 | 3.67 | 2.58 | 1.08 | 17 | 0.708 | 3.7 | 6.5 | 10.2 | 0 | 0 | 16 | 14 | 13 | 1 | 29.2 | 111 | 119 | 118 | 2 | 30.3 | 9.1 | 8.83 | 22.5 | 4.08 | 1.50 | 36.73% | 3.75 | 0.83 | 77.78% | 1 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 23.75 | 16.50 | 24.08 | 7.33 | 12.33 | 6.25 | 55.3% | 12.6% | 91.5% | 104.0 | LUCKY |
Puck Time | |
---|---|
Offensive Zone | 23 |
Neutral Zone | 12 |
Defensive Zone | 24 |
Puck Time | |
---|---|
Offensive Zone Start | 395 |
Neutral Zone Start | 198 |
Defensive Zone Start | 424 |
Puck Time | |
---|---|
With Puck | 30 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 508 |
Faceoffs Lost | 509 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 9.3 | 9.57 |
2nd Period | 19.2 | 20.31 |
3rd Period | 29.0 | 30.68 |
Overtime | 29.2 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 1.3 | 0.64 |
2nd Period | 2.5 | 1.65 |
3rd Period | 3.6 | 2.67 |
Overtime | 3.7 | 2.83 |
Even Strenght Goal | 25 |
---|---|
PP Goal | 18 |
PK Goal | 1 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 3 | 5 |
Lost | 2 | 1 |
Overtime Lost | 1 | 0 |
PP Attempt | 49 |
---|---|
PP Goal | 18 |
PK Attempt | 45 |
PK Goal Against | 10 |
Home | |
---|---|
Shots For | 29.2 |
Shots Against | 30.3 |
Goals For | 3.7 |
Goals Against | 2.6 |
Hits | 22.5 |
Shots Blocked | 9.1 |
Pim | 8.8 |
![]() | |
Total Salaries | 74,837,366$ |
Projected Total Cap Hit | 0$ |
Projected Cap Space | 83,500,000$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 0$ |
Players Signed (45 – 60) | 58 |
Goalies Signed (min. 6) | 7 |
Defensemen Signed (min. 16) | 19 |
LTIR Players | 0 |
Bisons Roster | Pos | Age | Base Salary |
Cap Hit Remaining |
Season 43 |
Season 44 |
Season 45 |
Season 46 |
Season 47 |
Season 48 |
Season 49 |
Season 50 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Alex Pietrangelo | D | 34 | 8,800,000$ | 8,800,000$ | 8,800,000$ | 8,800,000$ | UFA | |||||
Anders Lee | LW | 33 | 3,500,000$ | 3,500,000$ | 3,500,000$ | 3,500,000$ | UFA | |||||
Anton Lundell | C | 22 | 925,000$ | 925,000$ | 925,000$ | RFA | ||||||
Brayden McNabb | D | 33 | 2,000,000$ | 2,000,000$ | 2,000,000$ | 2,000,000$ | 2,000,000$ | 2,000,000$ | UFA | |||
Bryan Rust | LW/RW | 32 | 4,100,000$ | 4,100,000$ | 4,100,000$ | UFA | ||||||
Dylan DeMelo | D | 31 | 1,500,000$ | 1,500,000$ | 1,500,000$ | UFA | ||||||
Jamie Benn | C/LW | 34 | 6,000,000$ | 6,000,000$ | 6,000,000$ | UFA | ||||||
Joel Hofer | G | 23 | 775,000$ | 775,000$ | 775,000$ | 775,000$ | RFA | |||||
Kris Letang | D | 37 | 7,000,000$ | 7,000,000$ | 7,000,000$ | UFA | ||||||
Mason McTavish | C | 21 | 875,000$ | 875,000$ | 875,000$ | RFA | ||||||
Mats Zuccarello | LW/RW | 36 | 4,900,000$ | 4,900,000$ | 4,900,000$ | UFA | ||||||
Matthew Knies | LW | 21 | 625,000$ | 625,000$ | 625,000$ | RFA | ||||||
Michael Bunting | LW/RW | 28 | 2,250,000$ | 2,250,000$ | 2,250,000$ | 2,250,000$ | 2,250,000$ | 2,250,000$ | 2,250,000$ | UFA | ||
Pavel Mintyukov | D | 20 | 875,000$ | 875,000$ | 875,000$ | 875,000$ | RFA | |||||
Pius Suter | C | 28 | 2,000,000$ | 2,000,000$ | 2,000,000$ | 2,000,000$ | 2,000,000$ | UFA | ||||
Rasmus Sandin | D | 24 | 1,400,000$ | 1,400,000$ | 1,400,000$ | RFA | ||||||
Semyon Varlamov | G | 36 | 1,850,000$ | 1,850,000$ | 1,850,000$ | 1,850,000$ | UFA | |||||
Warren Foegele | C/LW | 28 | 2,750,000$ | 2,750,000$ | 2,750,000$ | UFA | ||||||
William Nylander | C/RW | 28 | 6,962,366$ | 6,962,366$ | 6,962,366$ | UFA | ||||||
Yanni Gourde | C/LW/RW | 32 | 2,600,000$ | 2,600,000$ | 2,600,000$ | UFA | ||||||
Yegor Sharangovich | C/LW/RW | 26 | 3,100,000$ | 3,100,000$ | 3,100,000$ | 3,100,000$ | UFA |
Farm Roster | Pos | Age | Base Salary |
Cap Hit Remaining |
Season 43 |
Season 44 |
Season 45 |
Season 46 |
Season 47 |
Season 48 |
Season 49 |
Season 50 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Adam Engstrom | D | 20 | 625,000$ | 62,500$ | 62,500$ | 62,500$ | RFA | |||||
Andre Gasseau | C | 20 | 700,000$ | 70,000$ | 70,000$ | RFA | ||||||
Angus Crookshank | LW | 24 | 838,333$ | 83,833$ | 83,833$ | RFA | ||||||
Anthony Beauvillier | C/LW/RW | 27 | 4,150,000$ | 4,150,000$ | 4,150,000$ | UFA | ||||||
Anthony DeAngelo | D | 28 | 5,000,000$ | 5,000,000$ | 5,000,000$ | UFA | ||||||
Arber Xhekaj | D | 23 | 828,333$ | 82,833$ | 82,833$ | RFA | ||||||
Arttu Hyry | C/RW | 23 | 450,000$ | 45,000$ | 45,000$ | RFA | ||||||
Artyom Duda | D | 20 | 725,000$ | 72,500$ | 72,500$ | 72,500$ | RFA | |||||
Avery Hayes | C/RW | 21 | 450,000$ | 45,000$ | 45,000$ | RFA | ||||||
Brayden Pachal | D | 24 | 850,000$ | 85,000$ | 85,000$ | 85,000$ | 85,000$ | RFA | ||||
Elmer Soderblom | LW/RW | 22 | 450,000$ | 45,000$ | 45,000$ | RFA | ||||||
Emil Lilleberg | D | 23 | 870,000$ | 87,000$ | 87,000$ | 87,000$ | RFA | |||||
Georgii Merkulov | C/LW/RW | 23 | 925,000$ | 92,500$ | 92,500$ | 92,500$ | RFA | |||||
Haydn Fleury | D | 27 | 762,500$ | 76,250$ | 76,250$ | UFA | ||||||
Ilya Solovyov | D | 23 | 828,333$ | 82,833$ | 82,833$ | RFA | ||||||
Isaiah Saville | G | 23 | 849,667$ | 84,967$ | 84,967$ | RFA | ||||||
Isak Posch | G | 22 | 450,000$ | 450,000$ | 450,000$ | RFA | ||||||
Ivan Ivan | C | 21 | 500,000$ | 50,000$ | 50,000$ | 50,000$ | 50,000$ | 50,000$ | 50,000$ | RFA | ||
Jack Musa | C/LW/RW | 20 | 450,000$ | 45,000$ | 45,000$ | RFA | ||||||
Jack Rathbone | D | 25 | 850,000$ | 85,000$ | 85,000$ | RFA | ||||||
Jakub Skarek | G | 24 | 450,000$ | 45,000$ | 45,000$ | RFA | ||||||
Logan Mailloux | D | 21 | 725,000$ | 72,500$ | 72,500$ | RFA | ||||||
Mason Lohrei | D | 23 | 450,000$ | 45,000$ | 45,000$ | 45,000$ | 45,000$ | RFA | ||||
Matej Blumel | LW/RW | 24 | 450,000$ | 45,000$ | 45,000$ | RFA | ||||||
Matt Villalta | G | 25 | 775,000$ | 77,500$ | 77,500$ | RFA | ||||||
Maxim Tsyplakov | RW | 25 | 600,000$ | 60,000$ | 60,000$ | RFA | ||||||
Michael Buchinger | D | 20 | 550,000$ | 55,000$ | 55,000$ | RFA | ||||||
Mikael Pyyhtia | C/LW | 22 | 897,500$ | 89,750$ | 89,750$ | 89,750$ | RFA | |||||
Nico Sturm | C/LW | 29 | 1,000,000$ | 100,000$ | 100,000$ | 100,000$ | UFA | |||||
Nikita Grebyonkin | LW/RW | 21 | 500,000$ | 50,000$ | 50,000$ | 50,000$ | RFA | |||||
Nikita Tolopilo | G | 24 | 450,000$ | 45,000$ | 45,000$ | RFA | ||||||
Nikolas Matinpalo | D | 25 | 450,000$ | 450,000$ | 450,000$ | 450,000$ | RFA | |||||
Nils Aman | C | 24 | 883,750$ | 88,375$ | 88,375$ | RFA | ||||||
Sammy Walker | C/RW | 25 | 855,000$ | 85,500$ | 85,500$ | RFA | ||||||
Samuel Poulin | LW/RW | 23 | 863,333$ | 86,333$ | 86,333$ | RFA | ||||||
Taylor Raddysh | RW | 26 | 758,333$ | 75,833$ | 75,833$ | RFA | ||||||
Viljami Marjala | C/LW | 21 | 450,000$ | 45,000$ | 45,000$ | 45,000$ | RFA |
Forward Lines | |||||||
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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 | 0 | 0 | 0 | 1 | 0 | 0 | 4.00 | 3.50 | 0.50 | 3 | 0.750 | 4.0 | 6.5 | 10.5 | 0 | 0 | 3 | 3 | 2 | 0 | 30.0 | 20 | 24 | 16 | 0 | 38.5 | 12.0 | 9.00 | 21.5 | 3.50 | 2.00 | 57.14% | 4.50 | 1.00 | 77.78% | 1 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 22.50 | 16.00 | 26.00 | 7.50 | 11.50 | 5.50 | 44.4% | 13.3% | 90.9% | 104.2 | FUN |
2 | ![]() | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 3.50 | 4.00 | -0.50 | 2 | 0.500 | 3.5 | 5.5 | 9.0 | 0 | 0 | 3 | 2 | 2 | 0 | 29.5 | 19 | 12 | 28 | 0 | 38.5 | 8.5 | 6.00 | 27.0 | 2.50 | 0.50 | 20.00% | 2.50 | 1.00 | 60.00% | 0 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 25.00 | 17.50 | 22.00 | 6.00 | 12.50 | 6.00 | 50.0% | 11.9% | 89.6% | 101.5 | FUN |
3 | ![]() | 2 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 2.00 | 3.00 | -1.00 | 2 | 0.500 | 2.0 | 3.5 | 5.5 | 0 | 0 | 2 | 1 | 0 | 1 | 34.0 | 22 | 25 | 19 | 2 | 36.0 | 11.5 | 9.00 | 27.0 | 5.50 | 1.00 | 18.18% | 4.00 | 1.00 | 75.00% | 0 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 23.50 | 16.00 | 24.50 | 7.50 | 12.50 | 6.00 | 33.3% | 5.9% | 91.7% | 97.5 | DULL |
4 | ![]() | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 5.00 | 1.50 | 3.50 | 4 | 1.000 | 5.0 | 9.0 | 14.0 | 0 | 0 | 3 | 5 | 2 | 0 | 31.0 | 20 | 23 | 19 | 0 | 21.0 | 6.0 | 13.00 | 20.5 | 7.00 | 3.00 | 42.86% | 3.50 | 0.50 | 85.71% | 0 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 24.50 | 17.50 | 22.00 | 7.50 | 12.50 | 6.50 | 66.7% | 16.1% | 92.9% | 109.0 | LUCKY |
5 | ![]() | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2.00 | 1.50 | 0.50 | 2 | 0.500 | 2.0 | 3.5 | 5.5 | 0 | 0 | 0 | 2 | 2 | 0 | 23.5 | 8 | 20 | 19 | 0 | 23.0 | 9.0 | 9.00 | 19.0 | 3.00 | 0.50 | 16.67% | 4.50 | 1.00 | 77.78% | 0 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 23.00 | 15.50 | 24.50 | 7.00 | 11.50 | 6.00 | 75.0% | 8.5% | 93.5% | 102.0 | DULL |
6 | ![]() | 2 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 5.50 | 2.00 | 3.50 | 4 | 1.000 | 5.5 | 11.0 | 16.5 | 0 | 0 | 5 | 1 | 5 | 0 | 27.0 | 22 | 15 | 17 | 0 | 24.5 | 7.5 | 7.00 | 20.0 | 3.00 | 2.00 | 66.67% | 3.50 | 0.50 | 85.71% | 0 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 22.50 | 15.00 | 24.50 | 7.00 | 12.50 | 6.00 | 70.0% | 20.4% | 91.8% | 112.2 | LUCKY |
_Vs Division | 12 | 7 | 3 | 0 | 1 | 1 | 0 | 0 | 3.67 | 2.58 | 1.08 | 17 | 0.708 | 3.7 | 6.5 | 10.2 | 0 | 0 | 16 | 14 | 13 | 1 | 29.2 | 111 | 119 | 118 | 2 | 30.3 | 9.1 | 8.83 | 22.5 | 4.08 | 1.50 | 36.73% | 3.75 | 0.83 | 77.78% | 1 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 23.75 | 16.50 | 24.08 | 7.33 | 12.33 | 6.25 | 55.3% | 12.6% | 91.5% | 104.0 | LUCKY | |
_Vs Conference | 12 | 7 | 3 | 0 | 1 | 1 | 0 | 0 | 3.67 | 2.58 | 1.08 | 17 | 0.708 | 3.7 | 6.5 | 10.2 | 0 | 0 | 16 | 14 | 13 | 1 | 29.2 | 111 | 119 | 118 | 2 | 30.3 | 9.1 | 8.83 | 22.5 | 4.08 | 1.50 | 36.73% | 3.75 | 0.83 | 77.78% | 1 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 23.75 | 16.50 | 24.08 | 7.33 | 12.33 | 6.25 | 55.3% | 12.6% | 91.5% | 104.0 | LUCKY | |
_Since Last GM Reset | 12 | 7 | 3 | 0 | 1 | 1 | 0 | 0 | 3.67 | 2.58 | 1.08 | 17 | 0.708 | 3.7 | 6.5 | 10.2 | 0 | 0 | 16 | 14 | 13 | 1 | 29.2 | 111 | 119 | 118 | 2 | 30.3 | 9.1 | 8.83 | 22.5 | 4.08 | 1.50 | 36.73% | 3.75 | 0.83 | 77.78% | 1 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 23.75 | 16.50 | 24.08 | 7.33 | 12.33 | 6.25 | 55.3% | 12.6% | 91.5% | 104.0 | LUCKY | |
Total | 12 | 7 | 3 | 0 | 1 | 1 | 0 | 0 | 3.67 | 2.58 | 1.08 | 17 | 0.708 | 3.7 | 6.5 | 10.2 | 0 | 0 | 16 | 14 | 13 | 1 | 29.2 | 111 | 119 | 118 | 2 | 30.3 | 9.1 | 8.83 | 22.5 | 4.08 | 1.50 | 36.73% | 3.75 | 0.83 | 77.78% | 1 | 207 | 395 | 52.41% | 194 | 424 | 45.75% | 107 | 198 | 54.04% | 23.75 | 16.50 | 24.08 | 7.33 | 12.33 | 6.25 | 55.3% | 12.6% | 91.5% | 104.0 | LUCKY |
Puck Time | |
---|---|
Offensive Zone | 23 |
Neutral Zone | 12 |
Defensive Zone | 24 |
Puck Time | |
---|---|
Offensive Zone Start | 395 |
Neutral Zone Start | 198 |
Defensive Zone Start | 424 |
Puck Time | |
---|---|
With Puck | 30 |
Without Puck | 30 |
Faceoffs | |
---|---|
Faceoffs Won | 508 |
Faceoffs Lost | 509 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 9.3 | 9.57 |
2nd Period | 19.2 | 20.31 |
3rd Period | 29.0 | 30.68 |
Overtime | 29.2 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 1.3 | 0.64 |
2nd Period | 2.5 | 1.65 |
3rd Period | 3.6 | 2.67 |
Overtime | 3.7 | 2.83 |
Even Strenght Goal | 25 |
---|---|
PP Goal | 18 |
PK Goal | 1 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 3 | 5 |
Lost | 2 | 1 |
Overtime Lost | 1 | 0 |
PP Attempt | 49 |
---|---|
PP Goal | 18 |
PK Attempt | 45 |
PK Goal Against | 10 |
Home | |
---|---|
Shots For | 29.2 |
Shots Against | 30.3 |
Goals For | 3.7 |
Goals Against | 2.6 |
Hits | 22.5 |
Shots Blocked | 9.1 |
Pim | 8.8 |
Date | Matchup | Result | Detail | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2 | ![]() | @ | ![]() | BIS2,MUS5 | RECAP | |||||||||
5 | ![]() | @ | ![]() | HEL6,BIS3 | RECAP | |||||||||
7 | ![]() | @ | ![]() | BIS5,BFT1 | RECAP | |||||||||
8 | ![]() | @ | ![]() | BIS4,HEL2 | RECAP | |||||||||
10 | ![]() | @ | ![]() | BFT3,BIS6 | RECAP | |||||||||
15 | ![]() | @ | ![]() | BIS5,REV3 | RECAP | |||||||||
16 | ![]() | @ | ![]() | MUS1,BIS2 (OT) | RECAP | |||||||||
19 | ![]() | @ | ![]() | REV4,BIS3 (OT) | RECAP | |||||||||
23 | ![]() | @ | ![]() | BIS5,TRA1 | RECAP | |||||||||
25 | ![]() | @ | ![]() | TRA2,BIS5 | RECAP | |||||||||
Trade Deadline --- Trades can�t be done after this day is simulated! | ||||||||||||||
27 | ![]() | @ | ![]() | BIS3,DRA1 | RECAP | |||||||||
29 | ![]() | @ | ![]() | DRA2,BIS1 | RECAP |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
74,837,366$ | 0$ | 0$ | 83,500,000$ |
Arena | Goal Horn | About us | |
---|---|---|---|
![]() | Name | ||
City | Stuttgart | ||
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$ | 20$ | 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 |
0 | 0 - 0.00% | 0$ | 0$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
74,837,366$ | 74,837,366$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
0$ | 0$ | 0$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 4 | 0$ | 0$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
0$ | 0$ | 166,527,077$ | 166,527,077$ |
Left Wing | Center | Right Wing | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Defense #1 | Defense #2 | Goalie | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Year | Round 1 | Round 2 | Round 3 | Round 4 | Round 5 | Round 6 | Round 7 |
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2025 | ![]() | ![]() | ![]() | ![]() | |||
2026 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2027 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2028 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2029 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
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 |
---|---|---|---|---|---|
Albin Boija | ![]() | 2024 | 166 | 0 | |
Emmitt Finnie | ![]() | 2024 | 82 | 0 | |
Ethan Procyszyn | ![]() | 2024 | 50 | 0 | |
Felix Unger Sorum | ![]() | 2023 | 69 | - | Link |
Francesco Dell'Elce | ![]() | 2024 | 168 | 0 | |
Hunter St. Martin | ![]() | 2024 | 110 | 0 | |
Jack Pridham | ![]() | 2024 | 78 | 0 | |
Jeremy Hanzel | ![]() | 2023 | 125 | - | Link |
Jeremy Wilmer | ![]() | 2023 | 177 | - | Link |
Marcel Marcel | ![]() | 2023 | 96 | - | Link |
Nikita Prishchepov | ![]() | 2024 | 140 | 0 | |
Ryan Conmy | ![]() | 2023 | 153 | - | Link |
Ryan Walsh | ![]() | 2024 | 196 | 0 | |
Tanner Molendyk | ![]() | 2023 | 23 | - | Link |
Trevor Hoskin | ![]() | 2024 | 129 | 0 | |
Vasili Atanasov | ![]() | 2023 | 169 | - | Link |
Year | Round 1 | Round 2 | Round 3 | Round 4 | Round 5 | Round 6 | Round 7 |
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2025 | ![]() | ![]() | ![]() | ![]() | |||
2026 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2027 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2028 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
2029 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
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 |
---|---|---|---|---|---|
Albin Boija | ![]() | 2024 | 166 | 0 | |
Emmitt Finnie | ![]() | 2024 | 82 | 0 | |
Ethan Procyszyn | ![]() | 2024 | 50 | 0 | |
Felix Unger Sorum | ![]() | 2023 | 69 | - | Link |
Francesco Dell'Elce | ![]() | 2024 | 168 | 0 | |
Hunter St. Martin | ![]() | 2024 | 110 | 0 | |
Jack Pridham | ![]() | 2024 | 78 | 0 | |
Jeremy Hanzel | ![]() | 2023 | 125 | - | Link |
Jeremy Wilmer | ![]() | 2023 | 177 | - | Link |
Marcel Marcel | ![]() | 2023 | 96 | - | Link |
Nikita Prishchepov | ![]() | 2024 | 140 | 0 | |
Ryan Conmy | ![]() | 2023 | 153 | - | Link |
Ryan Walsh | ![]() | 2024 | 196 | 0 | |
Tanner Molendyk | ![]() | 2023 | 23 | - | Link |
Trevor Hoskin | ![]() | 2024 | 129 | 0 | |
Vasili Atanasov | ![]() | 2023 | 169 | - | Link |
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