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Tucson Roadrunners 1-4-0, 2pts |
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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Nathan Walker (R) | 0 | LW | 100.00 | 77 | 65 | 78 | 75 | 73 | 80 | 84 | 70 | 81 | 68 | 62 | 72 | 69 | 75 | 65 | 1 | 63 | 0 | 30 | 750,000$/1yrs | |||
Raphael Lavoie | 0 | C/RW | 100.00 | 66 | 45 | 65 | 70 | 66 | 61 | 62 | 66 | 43 | 62 | 63 | 63 | 66 | 50 | 50 | 1 | 63 | 0 | 23 | 875,000$/1yrs | |||
Tarmo Reunanen | 0 | D | 100.00 | 64 | 36 | 86 | 65 | 71 | 78 | 73 | 64 | 30 | 66 | 57 | 63 | 51 | 64 | 66 | 62 | 85 | 0 | 26 | 750,000$/1yrs | |||
Scratches |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Connor Hellebuyck | 0 | 100.00 | 94 | 93 | 95 | 90 | 95 | 95 | 95 | 94 | 95 | 95 | 89 | 80 | 73 | 1 | 66 | 0 | 30 | 6,166,666$/1yrs |
Scratches |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Chris Kelly | 60 | 60 | 60 | 60 | 55 | 55 | 1 | CAN | 42 | 2 | 1,000,000$ |
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 |
---|---|---|---|---|---|---|---|---|---|---|---|
Connor Hellebuyck | G | 30 | 6,166,666$ | 6,166,666$ | UFA | ||||||
Nathan Walker | LW | 30 | 750,000$ | 750,000$ | UFA | ||||||
Raphael Lavoie | C/RW | 23 | 875,000$ | 875,000$ | RFA | ||||||
Tarmo Reunanen | D | 26 | 750,000$ | 750,000$ | RFA |
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 | Griffins | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 19 | 17 | 2 | 2 | 0.200 | 19 | 33 | 52 | 0 | 0 | 1 | 13 | 5 | 0 | 81 | 20 | 31 | 30 | 0 | 102 | 33 | 21 | 68 | 13 | 7 | 53.85% | 8 | 4 | 50.00% | 0 | 28 | 55 | 50.91% | 27 | 60 | 45.00% | 47 | 98 | 47.96% | 103 | 59 | 112 | 43 | 83 | 41 | 48.0% | 23.5% | 83.3% | 106.8 | FUN |
_Vs Conference | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 19 | 17 | 2 | 2 | 0.200 | 19 | 33 | 52 | 0 | 0 | 1 | 13 | 5 | 0 | 81 | 20 | 31 | 30 | 0 | 102 | 33 | 21 | 68 | 13 | 7 | 53.85% | 8 | 4 | 50.00% | 0 | 28 | 55 | 50.91% | 27 | 60 | 45.00% | 47 | 98 | 47.96% | 103 | 59 | 112 | 43 | 83 | 41 | 48.0% | 23.5% | 83.3% | 106.8 | FUN | |
_Since Last GM Reset | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 19 | 17 | 2 | 2 | 0.200 | 19 | 33 | 52 | 0 | 0 | 1 | 13 | 5 | 0 | 81 | 20 | 31 | 30 | 0 | 102 | 33 | 21 | 68 | 13 | 7 | 53.85% | 8 | 4 | 50.00% | 0 | 28 | 55 | 50.91% | 27 | 60 | 45.00% | 47 | 98 | 47.96% | 103 | 59 | 112 | 43 | 83 | 41 | 48.0% | 23.5% | 83.3% | 106.8 | FUN | |
Total | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 19 | 17 | 2 | 2 | 0.200 | 19 | 33 | 52 | 0 | 0 | 1 | 13 | 5 | 0 | 81 | 20 | 31 | 30 | 0 | 102 | 33 | 21 | 68 | 13 | 7 | 53.85% | 8 | 4 | 50.00% | 0 | 28 | 55 | 50.91% | 27 | 60 | 45.00% | 47 | 98 | 47.96% | 103 | 59 | 112 | 43 | 83 | 41 | 48.0% | 23.5% | 83.3% | 106.8 | FUN |
Puck Time | |
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Offensive Zone | 20 |
Neutral Zone | 16 |
Defensive Zone | 22 |
Puck Time | |
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Offensive Zone Start | 55 |
Neutral Zone Start | 98 |
Defensive Zone Start | 60 |
Puck Time | |
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With Puck | 28 |
Without Puck | 31 |
Faceoffs | |
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Faceoffs Won | 102 |
Faceoffs Lost | 111 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 4.0 | 9.57 |
2nd Period | 10.2 | 20.31 |
3rd Period | 16.2 | 30.68 |
Overtime | 16.2 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.2 | 0.64 |
2nd Period | 2.8 | 1.65 |
3rd Period | 3.8 | 2.67 |
Overtime | 3.8 | 2.83 |
Even Strenght Goal | 12 |
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PP Goal | 7 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 0 | 1 |
Lost | 2 | 2 |
Overtime Lost | 0 | 0 |
PP Attempt | 13 |
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PP Goal | 7 |
PK Attempt | 8 |
PK Goal Against | 4 |
Home | |
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Shots For | 16.2 |
Shots Against | 20.4 |
Goals For | 3.8 |
Goals Against | 3.4 |
Hits | 13.6 |
Shots Blocked | 6.6 |
Pim | 4.2 |
Date | Matchup | Result | Detail | ||
---|---|---|---|---|---|
2024-04-19 | TUC | VS | GRG | TUC4,GRG5 | RECAP |
2024-04-21 | TUC | VS | GRG | TUC8,GRG1 | RECAP |
2024-04-23 | GRG | VS | TUC | GRG4,TUC3 | RECAP |
2024-04-25 | GRG | VS | TUC | GRG2,TUC1 | RECAP |
2024-04-27 | TUC | VS | GRG | TUC3,GRG5 | RECAP |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
237,500$ | 0$ | 0$ | 75,000,000$ |
Arena | About us | |
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Name | ||
City | Tucson | |
Capacity | 8000 | |
Season Ticket Holders | 20% |
Arena Capacity - Ticket Price Attendance - % | |||||
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Arena Capacity | 5000 | 3000 | |||
Ticket Price | 25$ | 12$ | $ | $ | $ |
Attendance | 10000 | 6000 | |||
Attendance PCT | 100.00% | 100.00% | 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 |
39 | 8000 - 100.00% | 144,900$ | 289,800$ | 8000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
237,500$ | 237,500$ | 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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