 | Barracuda |
| GP: 0 | W: 0 | L: 0 GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00% DG: Dominic Joyal | Morale : 50 | Moyenne d’équipe : 62 |
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 |
| # | Nom du joueur | # | C | L | R | D | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | TA | SP | Âge | Contrat | Salaire |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Cory Conacher | 0 | X | X | X | 100.00 | 73 | 68 | 71 | 71 | 63 | 72 | 77 | 60 | 50 | 44 | 44 | 67 | 59 | 64 | 65 | 0 | 50 | 66 | 0 | 30 | 1 | 780,000$ | ||
| 2 | Max Comtois (R) | 0 | X | 100.00 | 86 | 90 | 77 | 78 | 78 | 66 | 67 | 73 | 32 | 50 | 48 | 61 | 75 | 46 | 46 | 0 | 50 | 66 | 0 | 21 | 1 | 925,000$ | ||||
| 3 | Nikolay Goldobin | 0 | X | 100.00 | 69 | 58 | 91 | 81 | 67 | 72 | 75 | 71 | 42 | 47 | 46 | 64 | 62 | 55 | 55 | 0 | 50 | 66 | 0 | 24 | 2 | 900,000$ | ||||
| 4 | Jesper Bratt | 0 | X | 100.00 | 66 | 42 | 96 | 91 | 63 | 67 | 73 | 73 | 30 | 52 | 49 | 64 | 63 | 62 | 63 | 0 | 50 | 65 | 0 | 22 | 2 | 825,000$ | ||||
| 5 | Brett Seney | 0 | X | 100.00 | 60 | 56 | 70 | 77 | 56 | 82 | 87 | 63 | 79 | 41 | 41 | 58 | 59 | 49 | 49 | 0 | 50 | 65 | 0 | 24 | 1 | 825,000$ | ||||
| 6 | Carter Verhaeghe (R) | 0 | X | 100.00 | 72 | 51 | 91 | 64 | 68 | 63 | 81 | 56 | 46 | 46 | 47 | 62 | 25 | 59 | 59 | 0 | 50 | 62 | 0 | 25 | 2 | 700,000$ | ||||
| 7 | Ryan Poehling (R) | 0 | X | 100.00 | 79 | 44 | 94 | 77 | 69 | 56 | 67 | 57 | 33 | 46 | 45 | 68 | 25 | 46 | 46 | 0 | 50 | 60 | 0 | 21 | 1 | 1,491,667$ | ||||
| 8 | Evgeny Svechnikov (R) | 0 | X | 100.00 | 75 | 79 | 67 | 68 | 79 | 52 | 51 | 58 | 50 | 39 | 39 | 63 | 55 | 44 | 44 | 0 | 50 | 58 | 0 | 23 | 1 | 1,075,833$ | ||||
| 9 | Samuel Girard | 0 | X | 100.00 | 70 | 48 | 93 | 88 | 59 | 82 | 93 | 70 | 25 | 45 | 39 | 60 | 25 | 62 | 63 | 0 | 50 | 65 | 0 | 22 | 2 | 935,833$ | ||||
| 10 | Slater Koekkoek | 0 | X | 100.00 | 81 | 47 | 77 | 76 | 72 | 70 | 59 | 61 | 31 | 42 | 38 | 79 | 25 | 57 | 58 | 0 | 50 | 61 | 0 | 26 | 2 | 925,000$ | ||||
| 11 | Derrick Pouliot | 0 | X | 100.00 | 77 | 63 | 84 | 77 | 74 | 73 | 78 | 58 | 25 | 39 | 38 | 62 | 43 | 62 | 63 | 0 | 50 | 60 | 0 | 26 | 1 | 1,100,000$ | ||||
| 12 | Gustav Lindstrom (R) | 0 | X | 100.00 | 77 | 44 | 75 | 72 | 70 | 70 | 68 | 61 | 25 | 40 | 38 | 74 | 25 | 45 | 45 | 0 | 50 | 59 | 0 | 21 | 2 | 925,000$ | ||||
| 13 | Connor Clifton | 0 | X | 100.00 | 91 | 49 | 85 | 64 | 64 | 68 | 70 | 58 | 25 | 39 | 39 | 77 | 45 | 48 | 49 | 0 | 50 | 59 | 0 | 25 | 1 | 735,000$ | ||||
| 14 | Cale Fleury (R) | 0 | X | 100.00 | 90 | 46 | 94 | 77 | 74 | 64 | 73 | 53 | 25 | 39 | 38 | 69 | 25 | 47 | 47 | 0 | 50 | 57 | 0 | 21 | 2 | 883,333$ | ||||
| Rayé | ||||||||||||||||||||||||||||||
| 1 | Timothy Gettinger | 0 | X | 100.00 | 87 | 85 | 91 | 64 | 85 | 74 | 78 | 58 | 50 | 38 | 38 | 69 | 58 | 44 | 44 | 0 | 50 | 66 | 0 | 22 | 1 | 730,000$ | ||||
| 2 | Keegan Kolesar (R) | 0 | X | 100.00 | 82 | 79 | 76 | 65 | 82 | 72 | 71 | 53 | 50 | 41 | 41 | 69 | 45 | 45 | 45 | 0 | 50 | 65 | 0 | 23 | 2 | 905,000$ | ||||
| 3 | Tyler Ennis | 0 | X | X | 100.00 | 78 | 43 | 93 | 85 | 58 | 64 | 78 | 74 | 45 | 50 | 49 | 58 | 65 | 73 | 74 | 0 | 50 | 65 | 0 | 30 | 1 | 780,000$ | |||
| 4 | Tyler Pitlick | 0 | X | 100.00 | 86 | 44 | 94 | 77 | 75 | 63 | 72 | 59 | 38 | 48 | 47 | 67 | 25 | 61 | 62 | 0 | 50 | 64 | 0 | 28 | 1 | 1,000,000$ | ||||
| 5 | Kerby Rychel | 0 | X | 100.00 | 78 | 72 | 82 | 57 | 77 | 62 | 55 | 47 | 50 | 38 | 38 | 64 | 42 | 48 | 48 | 0 | 50 | 60 | 0 | 25 | 1 | 725,000$ | ||||
| 6 | Lean Bergmann (R) | 0 | X | X | 100.00 | 89 | 46 | 89 | 75 | 76 | 51 | 64 | 51 | 26 | 47 | 45 | 56 | 25 | 45 | 45 | 0 | 50 | 57 | 0 | 21 | 2 | 925,000$ | |||
| 7 | Nick Jensen | 0 | X | 100.00 | 74 | 50 | 92 | 74 | 70 | 76 | 91 | 60 | 25 | 42 | 38 | 77 | 25 | 62 | 63 | 0 | 50 | 64 | 0 | 30 | 1 | 1,080,000$ | ||||
| 8 | Jonathon Merrill | 0 | X | 100.00 | 76 | 43 | 79 | 82 | 77 | 75 | 70 | 58 | 25 | 42 | 38 | 67 | 25 | 67 | 68 | 0 | 50 | 61 | 0 | 28 | 2 | 1,375,000$ | ||||
| 9 | Otto Leskinen (R) | 0 | X | 100.00 | 64 | 61 | 70 | 74 | 61 | 69 | 74 | 52 | 25 | 34 | 34 | 56 | 38 | 44 | 44 | 0 | 50 | 54 | 0 | 23 | 2 | 925,000$ | ||||
| MOYENNE D’ÉQUIPE | 100.00 | 77 | 57 | 84 | 75 | 70 | 68 | 73 | 60 | 37 | 43 | 42 | 66 | 42 | 54 | 54 | 0 | 50 | 62 | |||||||||||
| 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 |
| # | Nom du gardien | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | TA | SP |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Carter Hutton | 100.00 | 58 | 73 | 71 | 76 | 72 | 63 | 67 | 58 | 68 | 58 | 71 | 64 | 65 | 0 | 50 | 66 | 0 | |
| 2 | Malcolm Subban | 100.00 | 51 | 54 | 53 | 78 | 62 | 54 | 53 | 55 | 62 | 51 | 95 | 52 | 52 | 0 | 50 | 58 | 0 | |
| Rayé | ||||||||||||||||||||
| 1 | Landon Bow | 100.00 | 52 | 69 | 89 | 86 | 48 | 53 | 50 | 55 | 47 | 47 | 30 | 44 | 44 | 0 | 50 | 58 | 0 | |
| MOYENNE D’ÉQUIPE | 100.00 | 54 | 65 | 71 | 80 | 61 | 57 | 57 | 56 | 59 | 52 | 65 | 53 | 54 | 0 | 50 | 61 | |||
| Nom de l’entraîneur | PH | DF | OF | PD | EX | LD | PO | CNT | Âge | Contrat | Salaire |
|---|
| 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 |
| # | Nom du joueur | Nom de l’équipe | POS | GP | G | A | P | +/- | PIM | PIM5 | HIT | HTT | SHT | OSB | OSM | SHT% | SB | MP | AMG | PPG | PPA | PPP | PPS | PPM | PKG | PKA | PKP | PKS | PKM | GW | GT | FO% | FOT | GA | TA | EG | HT | P/20 | PSG | PSS | FW | FL | FT | S1 | S2 | S3 |
|---|
| 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 |
| # | Nom du gardien | Nom de l’équipe | GP | W | L | OTL | PCT | GAA | MP | PIM | SO | GA | SA | SAR | A | EG | PS % | PSA | ST | BG | S1 | S2 | S3 |
|---|
| 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 |
| Nom du joueur | Nom de l’équipe | POS | Âge | Date de naissance | Nouveau joueur | Poids | Taille | Non-échange | Disponible pour échange | Ballotage forcé | Contrat | Type | Salaire actuel | Salaire restant | Plafond salarial | Plafond salarial restant | Exclus du plafond salarial | Salaire annuel 2 | Salaire annuel 3 | Salaire annuel 4 | Salaire annuel 5 | Salaire annuel 6 | Salaire annuel 7 | Salaire annuel 8 | Salaire annuel 9 | Salaire annuel 10 | Link |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Brett Seney | Barracuda (ICE) | C | 24 | 1996-02-28 | No | 156 Lbs | 175 CM | No | No | No | 1 | Pro & Farm | 825,000$ | 471,428$ | 0$ | 0$ | No | Lien / Lien NHL | |||||||||
| Cale Fleury | Barracuda (ICE) | D | 21 | 1998-11-19 | Yes | 203 Lbs | 185 CM | No | No | No | 2 | Pro & Farm | 883,333$ | 504,761$ | 0$ | 0$ | No | 883,333$ | Lien / Lien NHL | ||||||||
| Carter Hutton | Barracuda (ICE) | G | 34 | 1985-12-18 | No | 202 Lbs | 185 CM | No | No | No | 1 | Pro & Farm | 650,000$ | 371,428$ | 0$ | 0$ | No | Lien / Lien NHL | |||||||||
| Carter Verhaeghe | Barracuda (ICE) | C | 25 | 1995-08-14 | Yes | 181 Lbs | 185 CM | No | No | No | 2 | Pro & Farm | 700,000$ | 400,000$ | 0$ | 0$ | No | 700,000$ | Lien / Lien NHL | ||||||||
| Connor Clifton | Barracuda (ICE) | D | 25 | 1995-04-28 | No | 175 Lbs | 180 CM | No | No | No | 1 | Pro & Farm | 735,000$ | 420,000$ | 0$ | 0$ | No | Lien / Lien NHL | |||||||||
| Cory Conacher | Barracuda (ICE) | C/LW/RW | 30 | 1989-12-14 | No | 180 Lbs | 173 CM | No | No | No | 1 | Pro & Farm | 780,000$ | 445,714$ | 0$ | 0$ | No | Lien / Lien NHL | |||||||||
| Derrick Pouliot | Barracuda (ICE) | D | 26 | 1994-01-16 | No | 208 Lbs | 183 CM | No | No | No | 1 | Pro & Farm | 1,100,000$ | 628,571$ | 0$ | 0$ | No | Lien / Lien NHL | |||||||||
| Evgeny Svechnikov | Barracuda (ICE) | RW | 23 | 1996-10-31 | Yes | 212 Lbs | 191 CM | No | No | No | 1 | Pro & Farm | 1,075,833$ | 614,761$ | 0$ | 0$ | No | Lien / Lien NHL | |||||||||
| Gustav Lindstrom | Barracuda (ICE) | D | 21 | 1998-10-20 | Yes | 187 Lbs | 188 CM | No | No | No | 2 | Pro & Farm | 925,000$ | 528,571$ | 0$ | 0$ | No | 925,000$ | Lien NHL | ||||||||
| Jesper Bratt | Barracuda (ICE) | LW | 22 | 1998-07-30 | No | 175 Lbs | 178 CM | No | No | No | 2 | Pro & Farm | 825,000$ | 471,428$ | 0$ | 0$ | No | 825,000$ | Lien / Lien NHL | ||||||||
| Jonathon Merrill | Barracuda (ICE) | D | 28 | 1992-02-03 | No | 205 Lbs | 191 CM | No | No | No | 2 | Pro & Farm | 1,375,000$ | 785,714$ | 0$ | 0$ | No | 1,375,000$ | Lien | ||||||||
| Keegan Kolesar | Barracuda (ICE) | RW | 23 | 1997-04-08 | Yes | 227 Lbs | 188 CM | No | No | No | 2 | Pro & Farm | 905,000$ | 517,142$ | 0$ | 0$ | No | 905,000$ | Lien / Lien NHL | ||||||||
| Kerby Rychel | Barracuda (ICE) | LW | 25 | 1994-10-07 | No | 213 Lbs | 185 CM | No | No | No | 1 | Pro & Farm | 725,000$ | 414,285$ | 0$ | 0$ | No | Lien | |||||||||
| Landon Bow | Barracuda (ICE) | G | 25 | 1995-08-23 | No | 214 Lbs | 193 CM | No | No | No | 1 | Pro & Farm | 697,500$ | 398,571$ | 0$ | 0$ | No | Lien / Lien NHL | |||||||||
| Lean Bergmann | Barracuda (ICE) | LW/RW | 21 | 1998-10-04 | Yes | 205 Lbs | 188 CM | No | No | No | 2 | Pro & Farm | 925,000$ | 528,571$ | 0$ | 0$ | No | 925,000$ | Lien NHL | ||||||||
| Malcolm Subban | Barracuda (ICE) | G | 26 | 1993-12-21 | No | 200 Lbs | 188 CM | No | No | No | 2 | Pro & Farm | 850,000$ | 485,714$ | 0$ | 0$ | No | 850,000$ | Lien / Lien NHL | ||||||||
| Max Comtois | Barracuda (ICE) | LW | 21 | 1999-01-08 | Yes | 207 Lbs | 188 CM | No | No | No | 1 | Pro & Farm | 925,000$ | 528,571$ | 0$ | 0$ | No | Lien / Lien NHL | |||||||||
| Nick Jensen | Barracuda (ICE) | D | 30 | 1990-09-20 | No | 194 Lbs | 183 CM | No | No | No | 1 | Pro & Farm | 1,080,000$ | 617,142$ | 0$ | 0$ | No | Lien / Lien NHL | |||||||||
| Nikolay Goldobin | Barracuda (ICE) | LW | 24 | 1995-10-07 | No | 185 Lbs | 180 CM | No | No | No | 2 | Pro & Farm | 900,000$ | 514,285$ | 0$ | 0$ | No | 900,000$ | Lien / Lien NHL | ||||||||
| Otto Leskinen | Barracuda (ICE) | D | 23 | 1997-02-06 | Yes | 168 Lbs | 180 CM | No | No | No | 2 | Pro & Farm | 925,000$ | 528,571$ | 0$ | 0$ | No | 925,000$ | Lien NHL | ||||||||
| Ryan Poehling | Barracuda (ICE) | RW | 21 | 1999-01-02 | Yes | 183 Lbs | 188 CM | No | No | No | 1 | Pro & Farm | 1,491,667$ | 852,381$ | 0$ | 0$ | No | Lien / Lien NHL | |||||||||
| Samuel Girard | Barracuda (ICE) | D | 22 | 1998-05-12 | No | 162 Lbs | 178 CM | No | No | No | 2 | Pro & Farm | 935,833$ | 534,761$ | 0$ | 0$ | No | 935,833$ | Lien / Lien NHL | ||||||||
| Slater Koekkoek | Barracuda (ICE) | D | 26 | 1994-02-18 | No | 193 Lbs | 188 CM | No | No | No | 2 | Pro & Farm | 925,000$ | 528,571$ | 0$ | 0$ | No | 925,000$ | Lien / Lien NHL | ||||||||
| Timothy Gettinger | Barracuda (ICE) | LW | 22 | 1998-04-14 | No | 220 Lbs | 198 CM | No | No | No | 1 | Pro & Farm | 730,000$ | 417,142$ | 0$ | 0$ | No | Lien | |||||||||
| Tyler Ennis | Barracuda (ICE) | C/LW | 30 | 1989-10-06 | No | 161 Lbs | 175 CM | No | No | No | 1 | Pro & Farm | 780,000$ | 445,714$ | 0$ | 0$ | No | Lien / Lien NHL | |||||||||
| Tyler Pitlick | Barracuda (ICE) | RW | 28 | 1991-10-31 | No | 200 Lbs | 188 CM | No | No | No | 1 | Pro & Farm | 1,000,000$ | 571,428$ | 0$ | 0$ | No | Lien / Lien NHL |
| Nombre de joueurs | Âge moyen | Poids moyen | Taille moyenne | Contrat moyen | Salaire moyen 1e année |
|---|---|---|---|---|---|
| 26 | 24.85 | 193 Lbs | 185 CM | 1.46 | 910,353$ |
| Attaque à 5 contre 5 | |||||||
|---|---|---|---|---|---|---|---|
| Ligne # | Ailier gauche | Centre | Ailier droit | % temps | PHY | DF | OF |
| 1 | Nikolay Goldobin | Cory Conacher | 40 | 1 | 2 | 2 | |
| 2 | Max Comtois | Ryan Poehling | 30 | 1 | 2 | 2 | |
| 3 | Jesper Bratt | Evgeny Svechnikov | 20 | 1 | 2 | 2 | |
| 4 | Brett Seney | Nikolay Goldobin | 10 | 1 | 2 | 2 | |
| Défense à 5 contre 5 | |||||||
|---|---|---|---|---|---|---|---|
| Ligne # | Défense | Défense | % temps | PHY | DF | OF | |
| 1 | Samuel Girard | Slater Koekkoek | 40 | 1 | 2 | 2 | |
| 2 | Derrick Pouliot | Connor Clifton | 30 | 1 | 2 | 2 | |
| 3 | Gustav Lindstrom | Cale Fleury | 20 | 1 | 2 | 2 | |
| 4 | Samuel Girard | Slater Koekkoek | 10 | 1 | 2 | 2 | |
| Attaque en svantage numérique | |||||||
|---|---|---|---|---|---|---|---|
| Ligne # | Ailier gauche | Centre | Ailier droit | % temps | PHY | DF | OF |
| 1 | Nikolay Goldobin | Cory Conacher | 60 | 1 | 2 | 2 | |
| 2 | Max Comtois | Ryan Poehling | 40 | 1 | 2 | 2 | |
| Défense en svantage numérique | |||||||
|---|---|---|---|---|---|---|---|
| Ligne # | Défense | Défense | % temps | PHY | DF | OF | |
| 1 | Samuel Girard | Slater Koekkoek | 60 | 1 | 2 | 2 | |
| 2 | Derrick Pouliot | Connor Clifton | 40 | 1 | 2 | 2 | |
| Attaque à 4 en désavantage numérique | ||||||
|---|---|---|---|---|---|---|
| Ligne # | Centre | Ailier | % temps | PHY | DF | OF |
| 1 | Nikolay Goldobin | 60 | 1 | 2 | 2 | |
| 2 | Cory Conacher | 40 | 1 | 2 | 2 | |
| Défense à 4 en désavantage numérique | ||||||
|---|---|---|---|---|---|---|
| Ligne # | Défense | Défense | % temps | PHY | DF | OF |
| 1 | Samuel Girard | Slater Koekkoek | 60 | 1 | 2 | 2 |
| 2 | Derrick Pouliot | Connor Clifton | 40 | 1 | 2 | 2 |
| 3 joueurs en désavantage numérique | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Ligne # | Ailier | % temps | PHY | DF | OF | Défense | Défense | % temps | PHY | DF | OF |
| 1 | 60 | 1 | 2 | 2 | Samuel Girard | Slater Koekkoek | 60 | 1 | 2 | 2 | |
| 2 | Nikolay Goldobin | 40 | 1 | 2 | 2 | Derrick Pouliot | Connor Clifton | 40 | 1 | 2 | 2 |
| Attaque à 4 contre 4 | ||||||
|---|---|---|---|---|---|---|
| Ligne # | Centre | Ailier | % temps | PHY | DF | OF |
| 1 | Nikolay Goldobin | 60 | 1 | 2 | 2 | |
| 2 | Cory Conacher | 40 | 1 | 2 | 2 | |
| Défense à 4 contre 4 | ||||||
|---|---|---|---|---|---|---|
| Ligne # | Défense | Défense | % temps | PHY | DF | OF |
| 1 | Samuel Girard | Slater Koekkoek | 60 | 1 | 2 | 2 |
| 2 | Derrick Pouliot | Connor Clifton | 40 | 1 | 2 | 2 |
| Attaque dernière minute | ||||
|---|---|---|---|---|
| Ailier gauche | Centre | Ailier droit | Défense | Défense |
| Nikolay Goldobin | Cory Conacher | Samuel Girard | Slater Koekkoek | |
| Défense dernière minute | ||||
|---|---|---|---|---|
| Ailier gauche | Centre | Ailier droit | Défense | Défense |
| Nikolay Goldobin | Cory Conacher | Samuel Girard | Slater Koekkoek | |
| Attaquants supplémentaires | ||
|---|---|---|
| Normal | Avantage numérique | Désavantage numérique |
| , , | , | |
| Défenseurs supplémentaires | ||
|---|---|---|
| Normal | Avantage numérique | Désavantage numérique |
| Gustav Lindstrom, Cale Fleury, Derrick Pouliot | Gustav Lindstrom | Cale Fleury, Derrick Pouliot |
| Tirs de pénalité |
|---|
| , Nikolay Goldobin, , Cory Conacher, Max Comtois |
| Gardien |
|---|
| #1 : Carter Hutton, #2 : Malcolm Subban |
| 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 |
| Total | Domicile | Visiteur | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| # | VS Équipe | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | 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 |
| Total | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 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 | |
| Total pour les joueurs | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Matchs joués | Points | Séquence | Buts | Passes | Points | Tirs pour | Tirs contre | Tirs bloqués | Minutes de pénalités | Mises en échec | Buts en filet désert | Blanchissages |
| 0 | 0 | N/A | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Tous les matchs | ||||||||
|---|---|---|---|---|---|---|---|---|
| GP | W | L | OTW | OTL | SOW | SOL | GF | GA |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Matchs locaux | ||||||||
|---|---|---|---|---|---|---|---|---|
| GP | W | L | OTW | OTL | SOW | SOL | GF | GA |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Matchs extérieurs | ||||||||
|---|---|---|---|---|---|---|---|---|
| GP | W | L | OTW | OTL | SOW | SOL | GF | GA |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Derniers 10 matchs | |||||
|---|---|---|---|---|---|
| W | L | OTW | OTL | SOW | SOL |
| 0 | 0 | 0 | 0 | 0 | 0 |
| Tentatives en avantage numérique | Buts en avantage numérique | % en avantage numérique | Tentatives en désavantage numérique | Buts contre en désavantage numérique | % en désavantage numérique | Buts pour en désavantage numérique |
|---|---|---|---|---|---|---|
| 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 |
| Tirs en 1e période | Tirs en 2e période | Tirs en 3e période | Tirs en 4e période | Buts en 1e période | Buts en 2e période | Buts en 3e période | Buts en 4e période |
|---|---|---|---|---|---|---|---|
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Mises en jeu | ||||||||
|---|---|---|---|---|---|---|---|---|
| Gagnées en zone offensive | Total en zone offensive | % gagnées en zone offensive | Gagnées en zone défensive | Total en zone défensive | % gagnées en zone défensive | Gagnées en zone neutre | Total en zone neutre | % gagnées en zone neutre |
| 0 | 0 | 0.00% | 0 | 0 | 0.00% | 0 | 0 | 0.00% |
| Temps avec la rondelle | |||||
|---|---|---|---|---|---|
| En zone offensive | Contrôle en zone offensive | En zone défensive | Contrôle en zone défensive | En zone neutre | Contrôle en zone neutre |
| 0 | 0 | 0 | 0 | 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 |
| Jour | Match | Équipe visiteuse | Score | Équipe locale | Score | ST | OT | SO | RI | Lien |
|---|
| Capacité de l’aréna - Tendance du prix des billets - % | ||
|---|---|---|
| Niveau 1 | Niveau 2 | |
| Capacité | 2000 | 1000 |
| Prix des billets | 35 | 15 |
| Assistance | 0.00% | 0.00% |
| Assistance PCT | 0.00% | 0.00% |
| Revenu | |||||
|---|---|---|---|---|---|
| Matchs à domicile restants | Assistance moyenne - % | Revenu moyen par match | Revenu annuel à ce jour | Capacité | Popularité de l’équipe |
| 42 | 0 - 0.00% | 0$ | 0$ | 3000 | 100 |
| Dépenses | |||
|---|---|---|---|
| Dépenses annuelles à ce jour | Salaire total des joueurs | Salaire total moyen des joueurs | Salaire des entraineurs |
| 0$ | 2,366,916$ | 2,079,249$ | 0$ |
| Plafond salarial par jour | Plafond salarial à ce jour | Joueurs Inclus dans le plafond salarial | Joueurs exclut du plafond Salarial |
|---|---|---|---|
| 0$ | 0$ | 0 | 0 |
| Estimation | |||
|---|---|---|---|
| Revenus de la saison estimés | Jours restants de la saison | Dépenses par jour | Dépenses de la saison estimées |
| 0$ | 8 | 0$ | 0$ |
| Total | Domicile | Visiteur | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Année | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | P | 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 |
| Saison régulière | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 2016 | 83 | 20 | 48 | 0 | 1 | 5 | 7 | 2 | 274 | 308 | -34 | 41 | 10 | 23 | 0 | 1 | 3 | 3 | 1 | 153 | 138 | 15 | 42 | 10 | 25 | 0 | 0 | 2 | 4 | 1 | 121 | 170 | -49 | 63 | 274 | 450 | 724 | 1 | 0 | 0 | 82 | 114 | 70 | 2242 | 0 | 753 | 750 | 717 | 2801 | 1068 | 1206 | 1190 | 239 | 42 | 17.57% | 315 | 91 | 71.11% | 8 | 664 | 1483 | 44.77% | 722 | 1883 | 38.34% | 481 | 1171 | 41.08% | 1684 | 1083 | 2135 | 666 | 1216 | 579 |
| 2017 | 84 | 15 | 54 | 0 | 2 | 4 | 5 | 4 | 258 | 239 | 19 | 42 | 11 | 22 | 0 | 1 | 2 | 3 | 3 | 155 | 112 | 43 | 42 | 4 | 32 | 0 | 1 | 2 | 2 | 1 | 103 | 127 | -24 | 52 | 258 | 448 | 706 | 1 | 5 | 0 | 90 | 82 | 79 | 2063 | 0 | 645 | 660 | 725 | 2563 | 879 | 734 | 1580 | 254 | 44 | 17.32% | 353 | 69 | 80.45% | 18 | 669 | 1466 | 45.63% | 774 | 1738 | 44.53% | 513 | 1057 | 48.53% | 1739 | 1019 | 1989 | 726 | 1367 | 684 |
| 2018 | 82 | 50 | 23 | 0 | 3 | 3 | 3 | 0 | 484 | 240 | 244 | 41 | 32 | 4 | 0 | 1 | 3 | 1 | 0 | 265 | 101 | 164 | 41 | 18 | 19 | 0 | 2 | 0 | 2 | 0 | 219 | 139 | 80 | 115 | 484 | 854 | 1338 | 0 | 3 | 0 | 182 | 161 | 135 | 3097 | 0 | 1118 | 1036 | 926 | 2746 | 956 | 981 | 1448 | 299 | 75 | 25.08% | 417 | 75 | 82.01% | 29 | 1042 | 1847 | 56.42% | 1014 | 1892 | 53.59% | 794 | 1294 | 61.36% | 1931 | 1257 | 1766 | 654 | 1247 | 635 |
| 2018 | 82 | 30 | 43 | 0 | 1 | 3 | 2 | 3 | 346 | 321 | 25 | 41 | 16 | 20 | 0 | 1 | 2 | 1 | 1 | 177 | 173 | 4 | 41 | 14 | 23 | 0 | 0 | 1 | 1 | 2 | 169 | 148 | 21 | 72 | 346 | 586 | 932 | 2 | 1 | 0 | 119 | 121 | 103 | 2507 | 0 | 810 | 808 | 851 | 3025 | 1037 | 514 | 1650 | 284 | 60 | 21.13% | 242 | 59 | 75.62% | 5 | 653 | 1532 | 42.62% | 765 | 1830 | 41.80% | 526 | 1206 | 43.62% | 1686 | 1005 | 1958 | 677 | 1306 | 666 |
| 2019 | 84 | 37 | 35 | 0 | 5 | 1 | 1 | 5 | 290 | 255 | 35 | 42 | 26 | 13 | 0 | 2 | 0 | 0 | 1 | 177 | 107 | 70 | 42 | 11 | 22 | 0 | 3 | 1 | 1 | 4 | 113 | 148 | -35 | 92 | 290 | 508 | 798 | 3 | 2 | 0 | 88 | 89 | 107 | 2677 | 0 | 858 | 884 | 908 | 2981 | 1025 | 684 | 1922 | 293 | 76 | 25.94% | 332 | 66 | 80.12% | 13 | 851 | 1787 | 47.62% | 874 | 1924 | 45.43% | 526 | 1113 | 47.26% | 1815 | 1143 | 2030 | 665 | 1232 | 614 |
| 2020 | 84 | 26 | 52 | 0 | 2 | 0 | 3 | 1 | 366 | 447 | -81 | 42 | 15 | 24 | 0 | 2 | 0 | 1 | 0 | 210 | 200 | 10 | 42 | 11 | 28 | 0 | 0 | 0 | 2 | 1 | 156 | 247 | -91 | 63 | 366 | 600 | 966 | 0 | 0 | 129 | 122 | 110 | 6 | 2964 | 1032 | 1024 | 904 | 16 | 2943 | 1180 | 589 | 1580 | 320 | 97 | 30.31% | 290 | 104 | 64.14% | 7 | 430 | 1656 | 25.97% | 387 | 1485 | 26.06% | 377 | 1400 | 26.93% | 1858 | 1228 | 1989 | 655 | 1215 | 580 |
| Total Saison régulière | 499 | 178 | 255 | 0 | 14 | 16 | 21 | 15 | 2018 | 1810 | 208 | 249 | 110 | 106 | 0 | 8 | 10 | 9 | 6 | 1137 | 831 | 306 | 250 | 68 | 149 | 0 | 6 | 6 | 12 | 9 | 881 | 979 | -98 | 457 | 2018 | 3446 | 5464 | 7 | 11 | 129 | 683 | 677 | 500 | 15550 | 1032 | 5208 | 5042 | 4143 | 17059 | 6145 | 4708 | 9370 | 1689 | 394 | 23.33% | 1949 | 464 | 76.19% | 80 | 4309 | 9771 | 44.10% | 4536 | 10752 | 42.19% | 3217 | 7241 | 44.43% | 10716 | 6737 | 11868 | 4046 | 7585 | 3762 |
| Séries éliminatoires | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 2016 | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 6 | 12 | -6 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 3 | 9 | -6 | 2 | 6 | 9 | 15 | 0 | 0 | 0 | 0 | 4 | 1 | 119 | 0 | 33 | 37 | 48 | 185 | 65 | 26 | 69 | 15 | 0 | 0.00% | 8 | 2 | 75.00% | 0 | 31 | 85 | 36.47% | 45 | 128 | 35.16% | 19 | 56 | 33.93% | 90 | 58 | 139 | 42 | 73 | 29 |
| Total Séries éliminatoires | 5 | 1 | 4 | 0 | 0 | 0 | 0 | 0 | 6 | 12 | -6 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 3 | 3 | 0 | 3 | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 3 | 9 | -6 | 2 | 6 | 9 | 15 | 0 | 0 | 0 | 0 | 4 | 1 | 119 | 0 | 33 | 37 | 48 | 185 | 65 | 26 | 69 | 15 | 0 | 0.00% | 8 | 2 | 75.00% | 0 | 31 | 85 | 36.47% | 45 | 128 | 35.16% | 19 | 56 | 33.93% | 90 | 58 | 139 | 42 | 73 | 29 |
Caribou
Casse-Tete
Chevalier
Hybrides
Royaux
Werewolves
Benchwarmers
Diabotins
Hooligans
Jardiniers
Leftovers
Pirates
Requins
Vagabond
