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Full Scoreboard ยป |
St. Louis Blues 0-0-0, 0pts · 10th in Western Conference |
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 | # | 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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![]() | 0 | C | 100.00 | 61 | 14 | 86 | 89 | 71 | 99 | 98 | 88 | 97 | 99 | 90 | 53 | 75 | 82 | 89 | 86 | 50 | 80 | 33 | 8,700,000$/2yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 46 | 11 | 90 | 85 | 66 | 99 | 99 | 94 | 98 | 98 | 78 | 63 | 63 | 80 | 84 | 82 | 50 | 79 | 32 | 8,275,000$/1yrs | |||
![]() | 0 | C/RW | 100.00 | 45 | 10 | 98 | 85 | 72 | 95 | 99 | 90 | 36 | 91 | 83 | 56 | 79 | 68 | 68 | 74 | 50 | 76 | 24 | 6,000,000$/3yrs | |||
![]() | 0 | C | 100.00 | 48 | 9 | 98 | 94 | 67 | 88 | 75 | 94 | 73 | 90 | 90 | 42 | 63 | 55 | 55 | 79 | 50 | 75 | 21 | 5,200,000$/4yrs | |||
![]() | 0 | C/LW | 100.00 | 52 | 13 | 89 | 82 | 79 | 93 | 99 | 78 | 85 | 77 | 81 | 53 | 61 | 71 | 72 | 79 | 50 | 73 | 28 | 6,000,000$/2yrs | |||
![]() | 0 | LW/RW | 100.00 | 52 | 20 | 90 | 83 | 71 | 91 | 96 | 72 | 40 | 79 | 84 | 48 | 25 | 64 | 64 | 76 | 50 | 70 | 28 | 1,750,000$/2yrs | |||
![]() | 0 | C/RW | 100.00 | 70 | 16 | 86 | 84 | 84 | 82 | 90 | 70 | 78 | 64 | 72 | 56 | 63 | 70 | 71 | 70 | 50 | 69 | 28 | 2,600,000$/2yrs | |||
![]() | 0 | C/RW | 100.00 | 50 | 36 | 88 | 79 | 74 | 86 | 95 | 80 | 71 | 72 | 73 | 57 | 76 | 42 | 42 | 91 | 50 | 69 | 19 | 925,000$/1yrs | |||
![]() | 0 | C/RW | 100.00 | 62 | 24 | 86 | 84 | 78 | 84 | 90 | 71 | 87 | 70 | 71 | 54 | 75 | 63 | 64 | 66 | 50 | 69 | 21 | 1,500,000$/1yrs | |||
![]() | 0 | C/LW/RW | 100.00 | 75 | 25 | 93 | 77 | 69 | 88 | 91 | 58 | 97 | 63 | 64 | 74 | 25 | 68 | 69 | 73 | 50 | 68 | 31 | 1,200,000$/2yrs | |||
![]() | 21 | C/RW | 100.00 | 59 | 43 | 76 | 66 | 73 | 82 | 67 | 70 | 80 | 60 | 73 | 59 | 69 | 58 | 59 | 70 | 50 | 64 | 30 | 685,000$/2yrs | |||
![]() | 0 | C | 100.00 | 72 | 53 | 70 | 76 | 72 | 70 | 84 | 67 | 69 | 68 | 53 | 60 | 56 | 47 | 47 | 85 | 50 | 63 | 21 | 796,667$/1yrs | |||
![]() | 0 | D | 100.00 | 54 | 13 | 87 | 85 | 80 | 99 | 98 | 97 | 25 | 85 | 60 | 89 | 75 | 75 | 80 | 77 | 50 | 79 | 30 | 8,000,000$/2yrs | |||
![]() | 0 | D | 100.00 | 65 | 15 | 86 | 79 | 82 | 94 | 99 | 60 | 25 | 55 | 50 | 85 | 75 | 71 | 72 | 65 | 50 | 73 | 29 | 1,500,000$/2yrs | |||
![]() | 0 | D | 100.00 | 54 | 11 | 85 | 86 | 73 | 95 | 95 | 64 | 25 | 60 | 51 | 84 | 25 | 65 | 66 | 62 | 50 | 72 | 26 | 4,875,000$/2yrs | |||
![]() | 0 | D | 100.00 | 46 | 9 | 96 | 88 | 68 | 90 | 95 | 93 | 25 | 71 | 56 | 72 | 53 | 67 | 68 | 63 | 50 | 72 | 27 | 4,500,000$/2yrs | |||
![]() | 0 | D | 100.00 | 75 | 37 | 66 | 84 | 84 | 91 | 84 | 56 | 21 | 48 | 44 | 83 | 25 | 69 | 70 | 59 | 50 | 72 | 27 | 685,000$/3yrs | |||
![]() | 0 | D | 100.00 | 63 | 23 | 88 | 73 | 61 | 95 | 92 | 58 | 25 | 54 | 48 | 87 | 51 | 78 | 80 | 65 | 50 | 71 | 33 | 2,500,000$/1yrs | |||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | D | 100.00 | 66 | 16 | 93 | 73 | 82 | 94 | 95 | 61 | 25 | 55 | 47 | 81 | 25 | 62 | 62 | 62 | 50 | 70 | 26 | 1,000,000$/4yrs | |||
TEAM AVERAGE | 100.00 | 59 | 21 | 87 | 82 | 74 | 90 | 92 | 75 | 57 | 72 | 67 | 66 | 56 | 66 | 67 | 73 | 50 | 72 |
Priority | Type | Description |
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1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | AGE | CONTRACT |
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![]() | 0 | 100.00 | 82 | 87 | 99 | 84 | 84 | 87 | 83 | 85 | 85 | 85 | 91 | 79 | 82 | 79 | 50 | 82 | 33 | 5,500,000$/2yrs |
![]() | 0 | 100.00 | 83 | 72 | 99 | 75 | 86 | 86 | 86 | 86 | 86 | 82 | 82 | 51 | 51 | 47 | 50 | 78 | 26 | 2,655,000$/4yrs |
Scratches | ||||||||||||||||||||
TEAM AVERAGE | 100.00 | 83 | 80 | 99 | 80 | 85 | 87 | 85 | 86 | 86 | 84 | 87 | 65 | 67 | 63 | 50 | 80 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Bill Peters | 63 | 83 | 90 | 73 | 83 | 64 | 67 | CAN | 57 | 3 | 2,500,000$ |
General Manager | Paul Gagne |
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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 | 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 |
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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 |
# | 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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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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Total | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.000 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0 | 0.0% | 0.0% | 0.0% | 0.0 | Unlucky |
Puck Time | |
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Offensive Zone | 0 |
Neutral Zone | 0 |
Defensive Zone | 0 |
Puck Time | |
---|---|
Offensive Zone Start | 0 |
Neutral Zone Start | 0 |
Defensive Zone Start | 0 |
Puck Time | |
---|---|
With Puck | 0 |
Without Puck | 0 |
Faceoffs | |
---|---|
Faceoffs Won | 0 |
Faceoffs Lost | 0 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 0.0 | 9.57 |
2nd Period | 0.0 | 20.31 |
3rd Period | 0.0 | 30.68 |
Overtime | 0.0 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 0.0 | 0.64 |
2nd Period | 0.0 | 1.65 |
3rd Period | 0.0 | 2.67 |
Overtime | 0.0 | 2.83 |
Even Strenght Goal | 0 |
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PP Goal | 0 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 0 | 0 |
Lost | 0 | 0 |
Overtime Lost | 0 | 0 |
PP Attempt | 0 |
---|---|
PP Goal | 0 |
PK Attempt | 0 |
PK Goal Against | 0 |
Home | |
---|---|
Shots For | 0.0 |
Shots Against | 0.0 |
Goals For | 0.0 |
Goals Against | 0.0 |
Hits | 0.0 |
Shots Blocked | 0.0 |
Pim | 0.0 |
Projected Total Cap Hit | 74,846,667$ |
Projected Cap Space | 11,653,333$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 516,184$ |
Players In Salary Cap | 21 |
LTIR Players | 0 |
Player Name | Pos | Age | Cap Hit | 2013-2014 | 2014-2015 | 2015-2016 | 2016-2017 | 2017-2018 | 2018-2019 | 2019-2020 | 2020-2021 |
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Adam Pelech ![]() | D | 26 | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | 1,000,000$ | ||||
Brock Nelson | C/LW | 28 | 6,000,000$ | 6,000,000$ | 6,000,000$ | ||||||
Carey Price | D | 33 | 5,500,000$ | 5,500,000$ | 5,500,000$ | ||||||
Charlie Lindgren ![]() | C/RW | 26 | 2,655,000$ | 2,655,000$ | 2,655,000$ | 2,655,000$ | 2,655,000$ | ||||
Claude Giroux | C/LW/RW | 32 | 8,275,000$ | 8,275,000$ | |||||||
David Savard ![]() | D | 29 | 1,500,000$ | 1,500,000$ | 1,500,000$ | ||||||
Dylan Cozens ![]() | C/RW | 19 | 925,000$ | 925,000$ | |||||||
Elias Pettersson ![]() | C | 21 | 5,200,000$ | 5,200,000$ | 5,200,000$ | 5,200,000$ | 5,200,000$ | ||||
Joel Edmundson ![]() | D | 27 | 685,000$ | 685,000$ | 685,000$ | 685,000$ | |||||
John Carlson | D | 30 | 8,000,000$ | 8,000,000$ | 8,000,000$ | ||||||
Kris Russell ![]() | D | 33 | 2,500,000$ | 2,500,000$ | |||||||
Luke Glendening ![]() | C/LW/RW | 31 | 1,200,000$ | 1,200,000$ | 1,200,000$ | ||||||
Martin Pospisil ![]() | C | 21 | 796,667$ | 796,667$ | |||||||
Mike Matheson | D | 26 | 4,875,000$ | 4,875,000$ | 4,875,000$ | ||||||
Nick Bjugstad | C/RW | 28 | 2,600,000$ | 2,600,000$ | 2,600,000$ | ||||||
Nolan Patrick ![]() | C/RW | 21 | 1,500,000$ | 1,500,000$ | |||||||
Ryan Dzingel ![]() | LW/RW | 28 | 1,750,000$ | 1,750,000$ | 1,750,000$ | ||||||
Sam Reinhart | C/RW | 24 | 6,000,000$ | 6,000,000$ | 6,000,000$ | 6,000,000$ | |||||
Shayne Gostisbehere | D | 27 | 4,500,000$ | 4,500,000$ | 4,500,000$ | ||||||
Sidney Crosby | C | 33 | 8,700,000$ | 8,700,000$ | 8,700,000$ | ||||||
Zac Dalpe ![]() | C/RW | 30 | 685,000$ | 685,000$ | 685,000$ |
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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 |
Prospect | Team Name | Draft Year | Overall Pick | Information | Lien |
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Alec Belanger | 2 | 87 | |||
Carson Bantle | 2 | 39 | |||
Daniel Torgersson | 2 | 42 | |||
Dmitri Semykin | 1 | ||||
John-Jason Peterka | 2 | 15 | |||
Josh Pillar | 2 | 63 | |||
Michael Benning | 2 | 38 | |||
Oliver Suni | 2 | 33 | |||
Zachary Lauzon | 1 |
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Salary Cap | |||
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Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
74,846,667$ | 0$ | 74,846,667$ | 11,653,333$ |
Arena | Goal Horn | About us | |
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![]() | Name | Enterprise Center | |
City | St. Louis | ||
Capacity | 18000 | ||
Season Ticket Holders | 50% |
Arena Capacity - Ticket Price Attendance - % | |||||
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Arena Capacity | 6000 | 5000 | 2000 | 4000 | 1000 |
Ticket Price | 300$ | 150$ | 100$ | 75$ | 400$ |
Attendance | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
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 |
41 | 0 - 0.00% | 0$ | 0$ | 18000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
74,846,667$ | 74,846,667$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
533,425$ | 74,846,667$ | 516,184$ | 0$ |
Estimate | |||
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Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 144 | 533,425$ | 76,813,200$ |
Team Total Estimate | |||
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Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
79,813,830$ | 74,846,667$ | 233,279,180$ | 153,465,350$ |
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 |
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4 | ||||
5 | ||||
6 | ||||
7 | ||||
8 |