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Cleveland Monsters 5-1-0, 10pts · 1st 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 | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Adam Beckman | 0 | LW | 99.00 | 60 | 40 | 72 | 71 | 59 | 61 | 61 | 65 | 43 | 57 | 62 | 60 | 66 | 50 | 50 | 1 | 89 | 0 | 22 | 894,167$/1yrs | |||
Michael Carcone | 58 | C/LW | 100.00 | 54 | 61 | 52 | 72 | 54 | 66 | 67 | 70 | 45 | 68 | 65 | 62 | 69 | 55 | 50 | 1 | 36 | 0 | 27 | 750,000$/2yrs | |||
Robby Fabbri | 0 | C/LW | 100.00 | 67 | 45 | 71 | 75 | 74 | 86 | 78 | 71 | 50 | 69 | 67 | 65 | 71 | 80 | 70 | 1 | 89 | 0 | 28 | 2,455,000$/2yrs | |||
Ross Johnston | 0 | LW | 100.00 | 71 | 65 | 55 | 65 | 90 | 75 | 73 | 66 | 40 | 62 | 60 | 64 | 64 | 80 | 70 | 1 | 57 | 0 | 30 | 750,000$/3yrs | |||
Aleksi Heponiemi | 0 | C/LW | 100.00 | 54 | 40 | 74 | 71 | 52 | 63 | 64 | 64 | 60 | 65 | 56 | 60 | 64 | 52 | 50 | 1 | 37 | 0 | 25 | 750,000$/1yrs | |||
Tyler Pitlick | 0 | RW | 100.00 | 82 | 45 | 89 | 73 | 80 | 80 | 88 | 73 | 40 | 69 | 67 | 70 | 71 | 85 | 75 | 1 | 82 | 0 | 32 | 787,500$/1yrs | |||
Cole Smith | 0 | LW/RW | 100.00 | 85 | 78 | 65 | 75 | 80 | 83 | 78 | 73 | 40 | 73 | 64 | 75 | 71 | 60 | 53 | 1 | 28 | 0 | 28 | 750,000$/1yrs | |||
Emilio Pettersen | 64 | LW | 100.00 | 57 | 37 | 91 | 58 | 66 | 76 | 86 | 57 | 61 | 58 | 59 | 54 | 58 | 62 | 64 | 52 | 88 | 0 | 24 | 750,000$/1yrs | |||
Pavel Mintyukov (R) | 0 | D | 100.00 | 69 | 40 | 85 | 84 | 74 | 80 | 80 | 84 | 1 | 77 | 55 | 65 | 60 | 50 | 50 | 88 | 48 | 0 | 20 | 950,000$/2yrs | |||
Calle Rosen | 0 | D | 99.00 | 61 | 40 | 87 | 77 | 76 | 85 | 81 | 76 | 40 | 70 | 72 | 74 | 75 | 75 | 65 | 1 | 88 | 0 | 30 | 750,000$/1yrs | |||
Gianni Fairbrother | 0 | D | 100.00 | 50 | 48 | 50 | 51 | 53 | 50 | 50 | 50 | 40 | 50 | 50 | 50 | 50 | 50 | 50 | 1 | 42 | 0 | 23 | 848,333$/1yrs | |||
Christian Wolanin | 0 | D | 100.00 | 61 | 40 | 71 | 70 | 63 | 67 | 67 | 66 | 40 | 67 | 56 | 70 | 64 | 58 | 50 | 1 | 73 | 0 | 29 | 750,000$/2yrs | |||
Henri Jokiharju | 0 | D | 100.00 | 68 | 50 | 73 | 75 | 81 | 91 | 83 | 76 | 40 | 70 | 65 | 76 | 72 | 70 | 60 | 1 | 84 | 0 | 24 | 2,500,000$/1yrs | |||
Louie Belpedio | 0 | D | 100.00 | 58 | 57 | 59 | 70 | 62 | 68 | 69 | 65 | 40 | 61 | 58 | 67 | 64 | 55 | 50 | 1 | 84 | 0 | 27 | 750,000$/2yrs | |||
Scratches | ||||||||||||||||||||||||||
Jan Jenik | 70 | C | 100.00 | 57 | 51 | 62 | 70 | 57 | 59 | 58 | 61 | 42 | 60 | 53 | 58 | 61 | 50 | 50 | 1 | 73 | 0 | 23 | 750,000$/1yrs |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Dustin Wolf | 0 | 100.00 | 75 | 64 | 71 | 54 | 69 | 73 | 75 | 75 | 75 | 72 | 59 | 50 | 50 | 1 | 83 | 0 | 23 | 813,333$/1yrs |
Scratches | ||||||||||||||||||||
Eric Comrie | 0 | 100.00 | 83 | 81 | 80 | 76 | 81 | 78 | 77 | 76 | 77 | 81 | 78 | 78 | 71 | 1 | 23 | 0 | 28 | 850,000$/1yrs |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Paul McFarland | 60 | 60 | 60 | 60 | 55 | 55 | 1 | CAN | 37 | 2 | 1,000,000$ |
General Manager |
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Priority | Type | Description |
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1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | 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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1 | Calle Rosen | Monsters (CBJ) | D | 6 | 3 | 7 | 10 | 0 | 2 | 0 | 3 | 42 | 17 | 29 | 7.14% | 10 | 23.60 | 1 | 2 | 3 | 11 | 0 | 0 | 0 | 7 | 2 | 0 | 0.00% | 0 | 10 | 13 | 0 | 0 | 1.41 | 0 | 0 | ||
2 | Robby Fabbri | Monsters (CBJ) | C/LW | 6 | 4 | 2 | 6 | 3 | 0 | 0 | 6 | 25 | 9 | 19 | 16.00% | 2 | 16.42 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 100.00% | 5 | 7 | 11 | 0 | 0 | 1.22 | 0 | 0 | ||
3 | Emilio Pettersen | Monsters (CBJ) | LW | 6 | 1 | 2 | 3 | 0 | 0 | 0 | 4 | 26 | 12 | 23 | 3.85% | 1 | 18.63 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 83.33% | 6 | 8 | 4 | 0 | 0 | 0.54 | 0 | 0 | ||
4 | Adam Beckman | Monsters (CBJ) | LW | 6 | 0 | 2 | 2 | 3 | 0 | 0 | 2 | 12 | 2 | 5 | 0.00% | 1 | 16.42 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 3 | 4 | 3 | 0 | 0 | 0.41 | 0 | 0 | ||
Team Total or Average | 24 | 8 | 13 | 21 | 6 | 2 | 0 | 15 | 105 | 40 | 76 | 7.62% | 14 | 18.77 | 1 | 2 | 3 | 11 | 0 | 0 | 0 | 7 | 3 | 1 | 71.43% | 14 | 29 | 31 | 0 | 0 | 0.93 | 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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Team Total or Average | 0.000 | 0.00 | 0 | 0.000 |
Player Name | POS | Age | Cap Hit | 2017-18 | 2018-19 | 2019-20 | 2020-21 | 2021-22 | 2022-23 | 2023-24 | 2024-25 |
---|---|---|---|---|---|---|---|---|---|---|---|
Adam Beckman | LW | 22 | 894,167$ | 894,167$ | RFA | ||||||
Aleksi Heponiemi | C/LW | 25 | 750,000$ | 750,000$ | RFA | ||||||
Calle Rosen | D | 30 | 750,000$ | 750,000$ | UFA | ||||||
Christian Wolanin | D | 29 | 750,000$ | 750,000$ | 750,000$ | UFA | |||||
Cole Smith | LW/RW | 28 | 750,000$ | 750,000$ | UFA | ||||||
Dustin Wolf | G | 23 | 813,333$ | 813,333$ | RFA | ||||||
Emilio Pettersen | LW | 24 | 750,000$ | 750,000$ | RFA | ||||||
Eric Comrie | G | 28 | 850,000$ | 850,000$ | UFA | ||||||
Gianni Fairbrother | D | 23 | 848,333$ | 848,333$ | RFA | ||||||
Henri Jokiharju | D | 24 | 2,500,000$ | 2,500,000$ | RFA | ||||||
Jan Jenik | C | 23 | 750,000$ | 750,000$ | RFA | ||||||
Louie Belpedio | D | 27 | 750,000$ | 750,000$ | 750,000$ | UFA | |||||
Michael Carcone | C/LW | 27 | 750,000$ | 750,000$ | 750,000$ | UFA | |||||
Pavel Mintyukov | D | 20 | 950,000$ | 950,000$ | 950,000$ | RFA | |||||
Robby Fabbri | C/LW | 28 | 2,455,000$ | 2,455,000$ | 2,455,000$ | UFA | |||||
Ross Johnston | LW | 30 | 750,000$ | 750,000$ | 750,000$ | 750,000$ | UFA | ||||
Tyler Pitlick | RW | 32 | 787,500$ | 787,500$ | 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 |
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1 | Thunderbirds | 5 | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 16 | 12 | 4 | 8 | 0.800 | 16 | 30 | 46 | 0 | 0 | 2 | 6 | 11 | 2 | 149 | 65 | 51 | 71 | 7 | 104 | 35 | 14 | 66 | 9 | 1 | 11.11% | 7 | 2 | 71.43% | 0 | 56 | 102 | 54.90% | 35 | 77 | 45.45% | 59 | 111 | 53.15% | 143 | 86 | 132 | 55 | 105 | 52 | 60.0% | 10.7% | 88.5% | 99.2 | FUN |
2 | Crunch | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 4 | 1 | 2 | 1.000 | 5 | 8 | 13 | 0 | 0 | 2 | 6 | 11 | 2 | 45 | 65 | 51 | 71 | 7 | 29 | 19 | 6 | 9 | 5 | 2 | 40.00% | 3 | 0 | 100.00% | 0 | 56 | 102 | 54.90% | 35 | 77 | 45.45% | 59 | 111 | 53.15% | 143 | 86 | 132 | 55 | 105 | 52 | 42.9% | 11.1% | 86.2% | 97.3 | FUN |
_Vs Conference | 6 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 21 | 16 | 5 | 10 | 0.833 | 21 | 38 | 59 | 0 | 0 | 2 | 6 | 11 | 2 | 194 | 65 | 51 | 71 | 7 | 133 | 54 | 20 | 75 | 14 | 3 | 21.43% | 10 | 2 | 80.00% | 0 | 56 | 102 | 54.90% | 35 | 77 | 45.45% | 59 | 111 | 53.15% | 143 | 86 | 132 | 55 | 105 | 52 | 56.3% | 10.8% | 88.0% | 98.8 | FUN | |
_Since Last GM Reset | 6 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 21 | 16 | 5 | 10 | 0.833 | 21 | 38 | 59 | 0 | 0 | 2 | 6 | 11 | 2 | 194 | 65 | 51 | 71 | 7 | 133 | 54 | 20 | 75 | 14 | 3 | 21.43% | 10 | 2 | 80.00% | 0 | 56 | 102 | 54.90% | 35 | 77 | 45.45% | 59 | 111 | 53.15% | 143 | 86 | 132 | 55 | 105 | 52 | 56.3% | 10.8% | 88.0% | 98.8 | FUN | |
Total | 6 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 21 | 16 | 5 | 10 | 0.833 | 21 | 38 | 59 | 0 | 0 | 2 | 6 | 11 | 2 | 194 | 65 | 51 | 71 | 7 | 133 | 54 | 20 | 75 | 14 | 3 | 21.43% | 10 | 2 | 80.00% | 0 | 56 | 102 | 54.90% | 35 | 77 | 45.45% | 59 | 111 | 53.15% | 143 | 86 | 132 | 55 | 105 | 52 | 56.3% | 10.8% | 88.0% | 98.8 | FUN |
Puck Time | |
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Offensive Zone | 23 |
Neutral Zone | 17 |
Defensive Zone | 22 |
Puck Time | |
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Offensive Zone Start | 102 |
Neutral Zone Start | 111 |
Defensive Zone Start | 77 |
Puck Time | |
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With Puck | 32 |
Without Puck | 31 |
Faceoffs | |
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Faceoffs Won | 150 |
Faceoffs Lost | 140 |
Team Average Shots after | League Average Shots after | |
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1st Period | 10.8 | 9.57 |
2nd Period | 19.3 | 20.31 |
3rd Period | 31.2 | 30.68 |
Overtime | 32.3 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
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1st Period | 0.3 | 0.64 |
2nd Period | 1.3 | 1.65 |
3rd Period | 3.2 | 2.67 |
Overtime | 3.5 | 2.83 |
Even Strenght Goal | 18 |
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PP Goal | 3 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
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Win | 3 | 2 |
Lost | 1 | 0 |
Overtime Lost | 0 | 0 |
PP Attempt | 14 |
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PP Goal | 3 |
PK Attempt | 10 |
PK Goal Against | 2 |
Home | |
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Shots For | 32.3 |
Shots Against | 22.2 |
Goals For | 3.5 |
Goals Against | 2.7 |
Hits | 12.5 |
Shots Blocked | 9.0 |
Pim | 3.3 |
Date | Matchup | Result | Detail | |||||||||||
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2024-04-18 | SPR | VS | CLE | SPR4,CLE2 | RECAP | |||||||||
2024-04-20 | SPR | VS | CLE | SPR2,CLE4 | RECAP | |||||||||
2024-04-22 | CLE | VS | SPR | CLE5,SPR3 | RECAP | |||||||||
2024-04-24 | CLE | VS | SPR | CLE3,SPR2 | RECAP | |||||||||
2024-04-26 | SPR | VS | CLE | SPR1,CLE2 (OT) | RECAP | |||||||||
2024-05-02 | SYR | VS | CLE | SYR4,CLE5 (OT) | RECAP | |||||||||
2024-05-04 | SYR | VS | CLE | |||||||||||
2024-05-06 | CLE | VS | SYR | |||||||||||
2024-05-08 | CLE | VS | SYR | |||||||||||
Trade Deadline --- Trades can’t be done after this day is simulated! | ||||||||||||||
2024-05-10 | SYR | VS | CLE | |||||||||||
2024-05-12 | CLE | VS | SYR | |||||||||||
2024-05-14 | SYR | VS | CLE |
Salary Cap | |||
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Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
1,684,833$ | 0$ | 0$ | 75,000,000$ |
Arena | About us | |
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Name | ||
City | Cleveland | |
Capacity | 8000 | |
Season Ticket Holders | 20% |
Arena Capacity - Ticket Price Attendance - % | |||||
---|---|---|---|---|---|
Arena Capacity | 5000 | 3000 | |||
Ticket Price | 35$ | 15$ | $ | $ | $ |
Attendance | 19286 | 11335 | |||
Attendance PCT | 96.43% | 94.46% | 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 |
37 | 7655 - 95.69% | 190,133$ | 760,532$ | 8000 | 100 |
Expenses | |||
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Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
1,684,833$ | 1,684,833$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
0$ | 0$ | 0$ | 0$ |
Estimate | |||
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Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 12 | 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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