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Chicago Wolfes 9-7-0, 18pts |
Player | # | POS | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | AGE | CONTRACT | |||
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Alex Formenton | 0 | LW | 100.00 | 69 | 38 | 79 | 76 | 82 | 85 | 87 | 69 | 58 | 64 | 71 | 83 | 72 | 63 | 64 | 72 | 84 | 0 | 24 | 1,000,000$/1yrs | |||
Fabian Zetterlund | 0 | RW | 100.00 | 72 | 45 | 89 | 74 | 87 | 84 | 76 | 78 | 50 | 76 | 66 | 67 | 73 | 58 | 50 | 1 | 84 | 0 | 24 | 1,450,000$/2yrs | |||
Sheldon Dries | 0 | C | 100.00 | 74 | 65 | 74 | 79 | 72 | 83 | 83 | 75 | 74 | 66 | 71 | 70 | 75 | 70 | 60 | 1 | 84 | 0 | 30 | 750,000$/1yrs | |||
Troy Stecher | 0 | D | 100.00 | 71 | 60 | 72 | 79 | 73 | 85 | 87 | 76 | 40 | 71 | 65 | 79 | 73 | 78 | 68 | 1 | 82 | 0 | 30 | 750,000$/1yrs | |||
Kyle Burroughs | 0 | D | 100.00 | 76 | 80 | 61 | 75 | 77 | 86 | 75 | 70 | 40 | 63 | 63 | 76 | 69 | 60 | 53 | 1 | 84 | 0 | 28 | 750,000$/3yrs | |||
Scratches |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
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Scratches |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Bill Peters | 71 | 77 | 76 | 75 | 84 | 78 | 63 | CAN | 57 | 3 | 500,000$ |
General Manager |
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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 |
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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 |
# | 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 |
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Player Name | POS | Age | Cap Hit | 2017-18 | 2018-19 | 2019-20 | 2020-21 | 2021-22 | 2022-23 | 2023-24 | 2024-25 |
---|---|---|---|---|---|---|---|---|---|---|---|
Alex Formenton | LW | 24 | 1,000,000$ | 1,000,000$ | RFA | ||||||
Fabian Zetterlund | RW | 24 | 1,450,000$ | 1,450,000$ | 1,450,000$ | RFA | |||||
Kyle Burroughs | D | 28 | 750,000$ | 750,000$ | 750,000$ | 750,000$ | UFA | ||||
Sheldon Dries | C | 30 | 750,000$ | 750,000$ | UFA | ||||||
Troy Stecher | D | 30 | 750,000$ | 750,000$ | UFA |
Forward Lines | |||||||
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Defensive Pairings | |||||||
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1st Power Play Unit | |||||||
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2nd Power Play Unit | |||||||
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Goalies | |||||||
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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 | Stars | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 10 | 21 | -11 | 2 | 0.200 | 10 | 20 | 30 | 0 | 0 | 7 | 20 | 26 | 2 | 80 | 57 | 117 | 133 | 3 | 118 | 36 | 18 | 46 | 8 | 1 | 12.50% | 9 | 2 | 77.78% | 0 | 100 | 195 | 51.28% | 80 | 170 | 47.06% | 149 | 314 | 47.45% | 345 | 212 | 366 | 137 | 254 | 126 | 32.1% | 12.5% | 82.2% | 94.7 | FUN |
2 | Wild | 7 | 4 | 3 | 0 | 0 | 0 | 0 | 0 | 28 | 27 | 1 | 8 | 0.571 | 28 | 55 | 83 | 0 | 0 | 7 | 20 | 26 | 2 | 143 | 57 | 117 | 133 | 3 | 133 | 38 | 36 | 108 | 21 | 8 | 38.10% | 18 | 11 | 38.89% | 1 | 100 | 195 | 51.28% | 80 | 170 | 47.06% | 149 | 314 | 47.45% | 345 | 212 | 366 | 137 | 254 | 126 | 55.6% | 19.6% | 79.7% | 99.3 | FUN |
3 | Barracuda | 4 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 17 | 12 | 5 | 8 | 1.000 | 17 | 28 | 45 | 0 | 0 | 7 | 20 | 26 | 2 | 87 | 57 | 117 | 133 | 3 | 99 | 35 | 6 | 59 | 10 | 4 | 40.00% | 3 | 2 | 33.33% | 1 | 100 | 195 | 51.28% | 80 | 170 | 47.06% | 149 | 314 | 47.45% | 345 | 212 | 366 | 137 | 254 | 126 | 56.5% | 19.5% | 87.9% | 107.4 | FUN |
_Vs Division | 4 | 8 | 3 | 0 | 0 | 0 | 0 | 0 | 17 | 12 | 5 | 16 | 2.000 | 17 | 28 | 45 | 0 | 0 | 7 | 20 | 26 | 2 | 87 | 57 | 117 | 133 | 3 | 99 | 35 | 6 | 59 | 10 | 4 | 40.00% | 3 | 2 | 33.33% | 1 | 100 | 195 | 51.28% | 80 | 170 | 47.06% | 149 | 314 | 47.45% | 345 | 212 | 366 | 137 | 254 | 126 | 56.5% | 19.5% | 87.9% | 107.4 | FUN | |
_Vs Conference | 16 | 9 | 7 | 0 | 0 | 0 | 0 | 0 | 55 | 60 | -5 | 18 | 0.563 | 55 | 103 | 158 | 0 | 0 | 7 | 20 | 26 | 2 | 310 | 57 | 117 | 133 | 3 | 350 | 109 | 60 | 213 | 39 | 13 | 33.33% | 30 | 15 | 50.00% | 2 | 100 | 195 | 51.28% | 80 | 170 | 47.06% | 149 | 314 | 47.45% | 345 | 212 | 366 | 137 | 254 | 126 | 48.3% | 17.7% | 82.9% | 100.6 | FUN | |
_Since Last GM Reset | 16 | 9 | 7 | 0 | 0 | 0 | 0 | 0 | 55 | 60 | -5 | 18 | 0.563 | 55 | 103 | 158 | 0 | 0 | 7 | 20 | 26 | 2 | 310 | 57 | 117 | 133 | 3 | 350 | 109 | 60 | 213 | 39 | 13 | 33.33% | 30 | 15 | 50.00% | 2 | 100 | 195 | 51.28% | 80 | 170 | 47.06% | 149 | 314 | 47.45% | 345 | 212 | 366 | 137 | 254 | 126 | 48.3% | 17.7% | 82.9% | 100.6 | FUN | |
Total | 16 | 9 | 7 | 0 | 0 | 0 | 0 | 0 | 55 | 60 | -5 | 18 | 0.563 | 55 | 103 | 158 | 0 | 0 | 7 | 20 | 26 | 2 | 310 | 57 | 117 | 133 | 3 | 350 | 109 | 60 | 213 | 39 | 13 | 33.33% | 30 | 15 | 50.00% | 2 | 100 | 195 | 51.28% | 80 | 170 | 47.06% | 149 | 314 | 47.45% | 345 | 212 | 366 | 137 | 254 | 126 | 48.3% | 17.7% | 82.9% | 100.6 | FUN |
Puck Time | |
---|---|
Offensive Zone | 21 |
Neutral Zone | 15 |
Defensive Zone | 22 |
Puck Time | |
---|---|
Offensive Zone Start | 195 |
Neutral Zone Start | 314 |
Defensive Zone Start | 170 |
Puck Time | |
---|---|
With Puck | 29 |
Without Puck | 30 |
Faceoffs | |
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Faceoffs Won | 329 |
Faceoffs Lost | 350 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 3.6 | 9.57 |
2nd Period | 10.9 | 20.31 |
3rd Period | 19.2 | 30.68 |
Overtime | 19.4 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.4 | 0.64 |
2nd Period | 1.7 | 1.65 |
3rd Period | 3.3 | 2.67 |
Overtime | 3.4 | 2.83 |
Even Strenght Goal | 40 |
---|---|
PP Goal | 13 |
PK Goal | 2 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 5 | 4 |
Lost | 4 | 3 |
Overtime Lost | 0 | 0 |
PP Attempt | 39 |
---|---|
PP Goal | 13 |
PK Attempt | 30 |
PK Goal Against | 15 |
Home | |
---|---|
Shots For | 19.4 |
Shots Against | 21.9 |
Goals For | 3.4 |
Goals Against | 3.8 |
Hits | 13.3 |
Shots Blocked | 6.8 |
Pim | 3.8 |
Date | Matchup | Result | Detail | ||
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2024-04-19 | IOW | VS | WFS | IOW6,WFS4 | RECAP |
2024-04-21 | IOW | VS | WFS | IOW1,WFS2 | RECAP |
2024-04-23 | WFS | VS | IOW | WFS5,IOW3 | RECAP |
2024-04-25 | WFS | VS | IOW | WFS4,IOW5 | RECAP |
2024-04-27 | IOW | VS | WFS | IOW5,WFS4 | RECAP |
2024-04-29 | WFS | VS | IOW | WFS4,IOW3 (OT) | RECAP |
2024-05-01 | IOW | VS | WFS | IOW4,WFS5 | RECAP |
2024-05-03 | WFS | VS | SJB | WFS4,SJB3 (OT) | RECAP |
2024-05-05 | WFS | VS | SJB | WFS5,SJB4 | RECAP |
2024-05-07 | SJB | VS | WFS | SJB2,WFS3 | RECAP |
2024-05-09 | SJB | VS | WFS | SJB3,WFS5 | RECAP |
2024-05-17 | TEX | VS | WFS | TEX6,WFS1 | RECAP |
2024-05-19 | TEX | VS | WFS | TEX2,WFS4 | RECAP |
2024-05-21 | WFS | VS | TEX | WFS4,TEX5 | RECAP |
2024-05-23 | WFS | VS | TEX | WFS1,TEX4 | RECAP |
2024-05-25 | TEX | VS | WFS | TEX4,WFS0 | RECAP |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
470,000$ | 0$ | 0$ | 75,000,000$ |
Arena | About us | |
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Name | ||
City | Chicago | |
Capacity | 11000 | |
Season Ticket Holders | 20% |
Arena Capacity - Ticket Price Attendance - % | |||||
---|---|---|---|---|---|
Arena Capacity | 6000 | 5000 | |||
Ticket Price | 35$ | 15$ | $ | $ | $ |
Attendance | 51684 | 42848 | |||
Attendance PCT | 95.71% | 95.22% | 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 |
32 | 10504 - 95.49% | 245,166$ | 2,206,495$ | 11000 | 100 |
Expenses | |||
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Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
470,000$ | 470,000$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
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0$ | 0$ | 0$ | 0$ |
Estimate | |||
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Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 0 | 0$ | 0$ |
Team Total Estimate | |||
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Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
0$ | 0$ | 0$ | 0$ |
Sponsors | |||
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TV Rights | Primary Sponsor | Secondary Sponsor | Secondary Sponsor |
Left Wing | Center | Right Wing |
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Defense #1 | Defense #2 | Goalie |
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