Syracuse Crunch | |
GP: 0 | W: 0 | L: 0 GF: 0 | GA: 0 | PP%: 0% | PK%: 0% DG: Remi Baril | Morale : 50 | Moyenne d’équipe : N/A |
|
|
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 | Devin Shore | X | X | 100.00 | 70 | 37 | 95 | 65 | 79 | 77 | 80 | 63 | 81 | 66 | 60 | 64 | 62 | 72 | 73 | 54 | 45 | 0 | 0 | 30 | 3 | 1,999,999$ | |||
2 | Adam Erne | X | X | 100.00 | 81 | 71 | 86 | 65 | 80 | 79 | 84 | 63 | 64 | 62 | 61 | 73 | 63 | 71 | 72 | 62 | 50 | 0 | 0 | 29 | 2 | 1,800,000$ | |||
3 | Justin Kirkland | X | 100.00 | 70 | 39 | 84 | 63 | 80 | 78 | 75 | 59 | 71 | 61 | 58 | 60 | 62 | 68 | 70 | 56 | 50 | 0 | 0 | 28 | 1 | 700,000$ | ||||
4 | Logan Brown | X | 100.00 | 40 | 35 | 40 | 64 | 35 | 80 | 90 | 40 | 20 | 40 | 40 | 40 | 30 | 66 | 68 | 11 | 50 | 0 | 0 | 26 | 2 | 750,000$ | ||||
5 | Jack Quinn (R) | X | 100.00 | 68 | 38 | 90 | 74 | 76 | 86 | 79 | 71 | 55 | 72 | 73 | 61 | 72 | 64 | 66 | 86 | 36 | 0 | 0 | 23 | 1 | 925,000$ | ||||
6 | Tyler Angle | X | 100.00 | 66 | 36 | 86 | 66 | 64 | 75 | 80 | 62 | 63 | 58 | 65 | 59 | 62 | 65 | 66 | 48 | 50 | 0 | 0 | 24 | 4 | 867,500$ | ||||
7 | Ben McCartney (R) | X | 100.00 | 62 | 43 | 63 | 58 | 71 | 78 | 76 | 57 | 61 | 59 | 56 | 55 | 58 | 63 | 65 | 49 | 50 | 0 | 0 | 23 | 2 | 830,000$ | ||||
8 | Lauri Pajuniemi (R) | X | 100.00 | 40 | 35 | 40 | 62 | 35 | 80 | 90 | 40 | 20 | 40 | 40 | 40 | 30 | 64 | 66 | 11 | 50 | 0 | 0 | 25 | 1 | 600,000$ | ||||
9 | Elmer Soderblom (R) | X | 100.00 | 84 | 41 | 92 | 60 | 99 | 81 | 79 | 62 | 58 | 59 | 64 | 63 | 61 | 63 | 65 | 49 | 50 | 0 | 0 | 23 | 1 | 842,500$ | ||||
10 | Waltteri Merela (R) | X | 100.00 | 74 | 39 | 92 | 58 | 85 | 78 | 73 | 57 | 66 | 58 | 59 | 62 | 57 | 66 | 68 | 42 | 50 | 0 | 0 | 26 | 4 | 870,000$ | ||||
11 | Alex Goligoski | X | 100.00 | 68 | 33 | 87 | 65 | 67 | 87 | 75 | 62 | 30 | 71 | 54 | 65 | 49 | 90 | 80 | 26 | 52 | 0 | N | 0 | 39 | 4 | 1,999,999$ | |||
12 | Dysin Mayo | X | 100.00 | 71 | 39 | 72 | 63 | 76 | 77 | 83 | 59 | 30 | 57 | 55 | 66 | 48 | 68 | 70 | 48 | 50 | 0 | 0 | 28 | 1 | 700,000$ | ||||
13 | Peter DiLiberatore | X | 100.00 | 55 | 37 | 84 | 56 | 64 | 72 | 70 | 54 | 30 | 57 | 53 | 55 | 46 | 64 | 66 | 48 | 50 | 0 | 0 | 24 | 1 | 925,000$ | ||||
14 | Michael Callahan (R) | X | 100.00 | 71 | 39 | 85 | 57 | 80 | 64 | 83 | 56 | 30 | 55 | 53 | 58 | 46 | 65 | 67 | 54 | 50 | 0 | 0 | 25 | 4 | 925,000$ | ||||
15 | Eemil Viro (R) | X | 100.00 | 60 | 36 | 92 | 58 | 67 | 63 | 74 | 57 | 30 | 55 | 52 | 56 | 45 | 62 | 64 | 67 | 50 | 0 | 0 | 22 | 1 | 842,500$ | ||||
16 | Kim Nousiainen (R) | X | 100.00 | 63 | 36 | 89 | 56 | 63 | 61 | 76 | 55 | 30 | 54 | 51 | 52 | 45 | 64 | 66 | 58 | 50 | 0 | 0 | 23 | 1 | 842,500$ | ||||
17 | Uvis Balinskis | X | 100.00 | 66 | 39 | 80 | 64 | 74 | 82 | 71 | 63 | 30 | 65 | 59 | 61 | 50 | 68 | 70 | 36 | 50 | 0 | 0 | 28 | 4 | 870,000$ | ||||
Rayé | |||||||||||||||||||||||||||||
1 | Kodie Curran | X | 100.00 | 40 | 35 | 40 | 40 | 35 | 80 | 90 | 40 | 20 | 40 | 40 | 40 | 30 | 25 | 25 | 11 | 50 | 0 | 0 | 34 | 1 | 1,000,000$ | ||||
2 | Michael Krutil (R) | X | 100.00 | 40 | 35 | 40 | 40 | 35 | 80 | 90 | 40 | 20 | 40 | 40 | 40 | 30 | 25 | 25 | 11 | 50 | 0 | 0 | 22 | 1 | 600,000$ | ||||
MOYENNE D’ÉQUIPE | 100.00 | 63 | 39 | 76 | 60 | 67 | 77 | 80 | 56 | 43 | 56 | 54 | 56 | 50 | 63 | 64 | 44 | 49 | 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 |
# |
Nom du gardien |
CON |
SK |
DU |
EN |
SZ |
AG |
RB |
SC |
HS |
RT |
PH |
PS |
EX |
LD |
PO |
MO |
OV |
TA |
SP | Âge | Contrat | Salaire |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Dustin Tokarski | 100.00 | 67 | 99 | 76 | 75 | 68 | 61 | 62 | 62 | 62 | 53 | 74 | 76 | 89 | 45 | 50 | 0 | 0 | 35 | 2 | 750,000$ | |
2 | Yaroslav Askarov (R) | 100.00 | 66 | 99 | 84 | 80 | 67 | 66 | 65 | 65 | 66 | 55 | 77 | 62 | 72 | 85 | 50 | 0 | 0 | 22 | 1 | 925,000$ | |
Rayé | |||||||||||||||||||||||
1 | Braden Holtby | 100.00 | 40 | 90 | 80 | 50 | 40 | 40 | 40 | 40 | 40 | 40 | 40 | 84 | 87 | 11 | 50 | 0 | 0 | 35 | 1 | 1,999,999$ | |
2 | Arvid Holm | 100.00 | 53 | 95 | 75 | 89 | 54 | 53 | 54 | 54 | 54 | 45 | 70 | 66 | 75 | 47 | 50 | 0 | 0 | 25 | 4 | 775,000$ | |
MOYENNE D’ÉQUIPE | 100.00 | 57 | 96 | 79 | 74 | 57 | 55 | 55 | 55 | 56 | 48 | 65 | 72 | 81 | 47 | 50 | 0 |
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 |
Pays |
Recrue |
Poids |
Taille |
Non-échange |
Disponible pour échange |
Acquis Par |
Date de la Dernière Transaction |
Ballotage forcé |
Waiver Possible |
Contrat |
Date du Signature du Contrat |
Forcer UFA |
Rappel d'urgence |
Type |
Salaire actuel |
Salaire restant | Plafond salarial |
Plafond salarial restant |
Exclus du plafond salarial |
Salaire année 2 | Salaire année 3 | Salaire année 4 | Salaire année 5 | Salaire année 6 | Salaire année 7 | Salaire année 8 | Salaire année 9 | Salaire année 10 | Plafond salarial année 2 | Plafond salarial année 3 | Plafond salarial année 4 | Plafond salarial année 5 | Plafond salarial année 6 | Plafond salarial année 7 | Plafond salarial année 8 | Plafond salarial année 9 | Plafond salarial année 10 | Non-échange année 2 | Non-échange année 3 | Non-échange année 4 | Non-échange année 5 | Non-échange année 6 | Non-échange année 7 | Non-échange année 8 | Non-échange année 9 | Non-échange année 10 | Lien |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Adam Erne | Syracuse Crunch (TAM) | LW/RW | 29 | 1995-04-20 | USA | No | 215 Lbs | 6 ft1 | No | No | N/A | No | No | 2 | False | False | Pro & Farm | 1,800,000$ | 771,429$ | 0$ | 0$ | No | 1,800,000$ | - | - | - | - | - | - | - | - | 1,800,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | Lien | ||
Alex Goligoski | Syracuse Crunch (TAM) | D | 39 | 1985-07-30 | USA | No | 173 Lbs | 5 ft11 | Yes | No | Assign Manually | No | No | 4 | 2024-08-21 | False | False | Pro & Farm | 1,999,999$ | 857,142$ | 0$ | 0$ | No | 1,999,999$ | 1,999,999$ | 1,999,999$ | - | - | - | - | - | - | 600,000$ | 600,000$ | 600,000$ | - | - | - | - | - | - | No | No | No | - | - | - | - | - | - | Lien | |
Arvid Holm | Syracuse Crunch (TAM) | G | 25 | 1998-11-03 | SWE | No | 213 Lbs | 6 ft4 | No | No | N/A | No | No | 4 | 2024-05-19 | False | False | Pro & Farm | 775,000$ | 332,143$ | 0$ | 0$ | No | 775,000$ | 775,000$ | 775,000$ | - | - | - | - | - | - | 775,000$ | 775,000$ | 775,000$ | - | - | - | - | - | - | No | No | No | - | - | - | - | - | - | Lien | |
Ben McCartney | Syracuse Crunch (TAM) | LW | 23 | 2001-07-13 | CAN | Yes | 182 Lbs | 6 ft0 | No | No | N/A | No | No | 2 | 2024-05-19 | False | False | Pro & Farm | 830,000$ | 355,714$ | 0$ | 0$ | No | 830,000$ | - | - | - | - | - | - | - | - | 830,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | Lien | |
Braden Holtby | Syracuse Crunch (TAM) | G | 35 | 1989-09-16 | CAN | No | 215 Lbs | 6 ft1 | No | No | N/A | No | No | 1 | False | False | Pro & Farm | 1,999,999$ | 857,142$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Lien | ||
Devin Shore | Syracuse Crunch (TAM) | C/RW | 30 | 1994-07-19 | CAN | No | 206 Lbs | 6 ft1 | No | No | N/A | No | No | 3 | False | False | Pro & Farm | 1,999,999$ | 857,142$ | 0$ | 0$ | No | 1,999,999$ | 1,999,999$ | - | - | - | - | - | - | - | 600,000$ | 600,000$ | - | - | - | - | - | - | - | No | No | - | - | - | - | - | - | - | Lien | ||
Dustin Tokarski | Syracuse Crunch (TAM) | G | 35 | 1989-09-16 | CAN | No | 198 Lbs | 6 ft0 | No | No | N/A | No | No | 2 | False | False | Pro & Farm | 750,000$ | 321,429$ | 0$ | 0$ | No | 750,000$ | - | - | - | - | - | - | - | - | 750,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | Lien | ||
Dysin Mayo | Syracuse Crunch (TAM) | D | 28 | 1996-08-17 | CAN | No | 183 Lbs | 6 ft2 | No | No | N/A | No | No | 1 | False | False | Pro & Farm | 700,000$ | 300,000$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Lien | ||
Eemil Viro | Syracuse Crunch (TAM) | D | 22 | 2002-04-03 | FIN | Yes | 165 Lbs | 6 ft0 | No | No | N/A | No | No | 1 | False | False | Pro & Farm | 842,500$ | 361,071$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Lien | ||
Elmer Soderblom | Syracuse Crunch (TAM) | LW | 23 | 2001-07-05 | SWE | Yes | 246 Lbs | 6 ft8 | No | No | N/A | No | No | 1 | False | False | Pro & Farm | 842,500$ | 361,071$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Lien | ||
Jack Quinn | Syracuse Crunch (TAM) | RW | 23 | 2001-09-19 | CAN | Yes | 185 Lbs | 6 ft1 | No | No | N/A | No | No | 1 | False | False | Pro & Farm | 925,000$ | 396,429$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Lien | ||
Justin Kirkland | Syracuse Crunch (TAM) | LW | 28 | 1996-08-02 | CAN | No | 183 Lbs | 6 ft3 | No | No | N/A | No | No | 1 | False | False | Pro & Farm | 700,000$ | 300,000$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Lien | ||
Kim Nousiainen | Syracuse Crunch (TAM) | D | 23 | 2000-11-14 | FIN | Yes | 170 Lbs | 5 ft9 | No | No | N/A | No | No | 1 | False | False | Pro & Farm | 842,500$ | 361,071$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Lien | ||
Kodie Curran | Syracuse Crunch (TAM) | D | 34 | 1989-12-18 | CAN | No | 200 Lbs | 6 ft2 | No | No | N/A | No | No | 1 | False | False | Pro & Farm | 1,000,000$ | 428,571$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Lien | ||
Lauri Pajuniemi | Syracuse Crunch (TAM) | RW | 25 | 1999-09-12 | FIN | Yes | 196 Lbs | 6 ft0 | No | No | Assign Manually | No | No | 1 | 2024-08-18 | False | False | Pro & Farm | 600,000$ | 257,143$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Lien | |
Logan Brown | Syracuse Crunch (TAM) | C | 26 | 1998-03-05 | USA | No | 218 Lbs | 6 ft6 | No | No | N/A | No | No | 2 | False | False | Pro & Farm | 750,000$ | 321,429$ | 0$ | 0$ | No | 750,000$ | - | - | - | - | - | - | - | - | 750,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | Lien | ||
Michael Callahan | Syracuse Crunch (TAM) | D | 25 | 1999-09-23 | USA | Yes | 197 Lbs | 6 ft2 | No | No | Assign Manually | No | No | 4 | 2024-08-18 | False | False | Pro & Farm | 925,000$ | 396,429$ | 0$ | 0$ | No | 925,000$ | 925,000$ | 925,000$ | - | - | - | - | - | - | 600,000$ | 600,000$ | 600,000$ | - | - | - | - | - | - | No | No | No | - | - | - | - | - | - | Lien | |
Michael Krutil | Syracuse Crunch (TAM) | D | 22 | 2002-06-03 | CZE | Yes | 202 Lbs | 6 ft3 | No | No | Assign Manually | No | No | 1 | 2024-08-18 | False | False | Pro & Farm | 600,000$ | 257,143$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Lien | |
Peter DiLiberatore | Syracuse Crunch (TAM) | D | 24 | 2000-03-31 | CAN | No | 160 Lbs | 5 ft11 | No | No | N/A | No | No | 1 | False | False | Pro & Farm | 925,000$ | 396,429$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Lien | ||
Tyler Angle | Syracuse Crunch (TAM) | C | 24 | 2000-09-30 | CAN | No | 166 Lbs | 5 ft10 | No | No | N/A | No | No | 4 | 2024-05-19 | False | False | Pro & Farm | 867,500$ | 371,786$ | 0$ | 0$ | No | 867,500$ | 867,500$ | 867,500$ | - | - | - | - | - | - | 867,500$ | 867,500$ | 867,500$ | - | - | - | - | - | - | No | No | No | - | - | - | - | - | - | Lien | |
Uvis Balinskis | Syracuse Crunch (TAM) | D | 28 | 1996-08-01 | LVA | No | 196 Lbs | 6 ft0 | No | No | Assign Manually | No | No | 4 | 2024-08-18 | False | False | Pro & Farm | 870,000$ | 372,857$ | 0$ | 0$ | No | 870,000$ | 870,000$ | 870,000$ | - | - | - | - | - | - | 600,000$ | 600,000$ | 600,000$ | - | - | - | - | - | - | No | No | No | - | - | - | - | - | - | Lien | |
Waltteri Merela | Syracuse Crunch (TAM) | C | 26 | 1998-07-06 | FIN | Yes | 210 Lbs | 6 ft3 | No | No | Assign Manually | No | No | 4 | 2024-08-18 | False | False | Pro & Farm | 870,000$ | 372,857$ | 0$ | 0$ | No | 870,000$ | 870,000$ | 870,000$ | - | - | - | - | - | - | 600,000$ | 600,000$ | 600,000$ | - | - | - | - | - | - | No | No | No | - | - | - | - | - | - | Lien | |
Yaroslav Askarov | Syracuse Crunch (TAM) | G | 22 | 2002-06-16 | RUS | Yes | 178 Lbs | 6 ft3 | No | No | N/A | No | No | 1 | False | False | Pro & Farm | 925,000$ | 396,429$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | Lien |
Nombre de joueurs | Âge moyen | Poids moyen | Taille moyenne | Contrat moyen | Salaire moyen 1e année |
---|---|---|---|---|---|
23 | 26.91 | 194 Lbs | 6 ft1 | 2.04 | 1,014,782$ |
Attaque à 5 contre 5 | |||||||
---|---|---|---|---|---|---|---|
Ligne # | Ailier gauche | Centre | Ailier droit | % temps | PHY | DF | OF |
1 | 38 | 1 | 2 | 2 | |||
2 | Elmer Soderblom | 30 | 1 | 2 | 2 | ||
3 | Tyler Angle | 22 | 1 | 2 | 2 | ||
4 | Ben McCartney | 10 | 1 | 2 | 2 |
Défense à 5 contre 5 | |||||||
---|---|---|---|---|---|---|---|
Ligne # | Défense | Défense | % temps | PHY | DF | OF | |
1 | 38 | 1 | 2 | 2 | |||
2 | 30 | 1 | 2 | 2 | |||
3 | Kim Nousiainen | Eemil Viro | 22 | 1 | 2 | 2 | |
4 | 10 | 1 | 2 | 2 |
Attaque en avantage numérique | |||||||
---|---|---|---|---|---|---|---|
Ligne # | Ailier gauche | Centre | Ailier droit | % temps | PHY | DF | OF |
1 | 60 | 1 | 2 | 2 | |||
2 | Elmer Soderblom | 40 | 1 | 2 | 2 |
Défense en avantage numérique | |||||||
---|---|---|---|---|---|---|---|
Ligne # | Défense | Défense | % temps | PHY | DF | OF | |
1 | 60 | 1 | 2 | 2 | |||
2 | 40 | 1 | 2 | 2 |
Attaque à 4 en désavantage numérique | ||||||
---|---|---|---|---|---|---|
Ligne # | Centre | Ailier | % temps | PHY | DF | OF |
1 | 60 | 1 | 2 | 2 | ||
2 | 40 | 1 | 2 | 2 |
Défense à 4 en désavantage numérique | ||||||
---|---|---|---|---|---|---|
Ligne # | Défense | Défense | % temps | PHY | DF | OF |
1 | 60 | 1 | 2 | 2 | ||
2 | 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 | 60 | 1 | 2 | 2 | |||
2 | 40 | 1 | 2 | 2 | 40 | 1 | 2 | 2 |
Attaque à 4 contre 4 | ||||||
---|---|---|---|---|---|---|
Ligne # | Centre | Ailier | % temps | PHY | DF | OF |
1 | 60 | 1 | 2 | 2 | ||
2 | 40 | 1 | 2 | 2 |
Défense à 4 contre 4 | ||||||
---|---|---|---|---|---|---|
Ligne # | Défense | Défense | % temps | PHY | DF | OF |
1 | 60 | 1 | 2 | 2 | ||
2 | 40 | 1 | 2 | 2 |
Attaque dernière minute | ||||
---|---|---|---|---|
Ailier gauche | Centre | Ailier droit | Défense | Défense |
Défense dernière minute | ||||
---|---|---|---|---|
Ailier gauche | Centre | Ailier droit | Défense | Défense |
Attaquants supplémentaires | ||
---|---|---|
Normal | Avantage numérique | Désavantage numérique |
, Tyler Angle, | , Tyler Angle |
Défenseurs supplémentaires | ||
---|---|---|
Normal | Avantage numérique | Désavantage numérique |
Kim Nousiainen, Eemil Viro, | Kim Nousiainen | Eemil Viro, |
Tirs de pénalité |
---|
, , , , |
Gardien |
---|
#1 : , #2 : |
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% | 0 | 0 | 0% | 0 | 0 | 0 | 0% | 0 | 0 | 0% | 0 | 0 | 0% | 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% | 0 | 0 | 0% | 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% | 0 | 0 | 0% | 0 | 0 | 0% |
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% | 0% |
Assistance PCT | 0% | 0% |
Revenu | |||||
---|---|---|---|---|---|
Matchs à domicile restants | Assistance moyenne - % | Revenu moyen par match | Revenu annuel à ce jour | Capacité | Popularité de l’équipe |
36 | 0 - 0% | 0$ | 0$ | 3000 | 100 |
Dépenses | |||
---|---|---|---|
Dépenses annuelles à ce jour | Salaire total des joueurs | Plafond Salariale total des joueurs | Salaire des entraineurs |
0$ | 2,334,000$ | 1,649,750$ | 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$ | 12 | 0$ | 0$ |
# |
Nom du joueur |
GP |
G |
A |
P |
+/- |
PIM |
HIT |
HTT |
SHT |
SHT% |
SB |
MP |
AMG |
PPG |
PPA |
PPP |
PPS |
PKG |
PKA |
PKP |
PKS |
GW |
GT |
FO% |
HT |
P/20 |
PSG |
PSS |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 72 | 57 | 12 | 69 | 29 | 18 | 145 | 103 | 307 | 18.57% | 19 | 800 | 11.12 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 77.66% | 4 | 1.72 | 2 | 4 | |
2 | 72 | 58 | 9 | 67 | 23 | 76 | 241 | 99 | 469 | 12.37% | 38 | 1110 | 15.42 | 1 | 1 | 2 | 3 | 0 | 0 | 0 | 0 | 11 | 2 | 71.93% | 6 | 1.21 | 1 | 4 | |
3 | 64 | 9 | 49 | 58 | 26 | 42 | 140 | 69 | 74 | 12.16% | 65 | 1004 | 15.69 | 1 | 1 | 2 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | 0% | 0 | 1.16 | 0 | 0 | |
4 | 72 | 5 | 36 | 41 | 14 | 30 | 67 | 32 | 46 | 10.87% | 30 | 787 | 10.94 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0% | 0 | 1.04 | 0 | 0 | |
5 | 72 | 21 | 12 | 33 | 21 | 16 | 81 | 33 | 126 | 16.67% | 22 | 354 | 4.92 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 80.95% | 0 | 1.86 | 1 | 1 |
# |
Nom du gardien |
GP |
W |
L |
OTL |
PCT |
GAA |
MP |
PIM |
SO |
GA |
SA |
SAR |
A |
EG |
PS % |
PSA |
---|
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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
21 | 72 | 24 | 34 | 0 | 0 | 10 | 0 | 4 | 210 | 251 | -41 | 36 | 15 | 14 | 0 | 0 | 5 | 0 | 2 | 127 | 128 | -1 | 36 | 9 | 20 | 0 | 0 | 5 | 0 | 2 | 83 | 123 | -40 | 62 | 210 | 356 | 566 | 2 | 0 | 83 | 63 | 64 | 4 | 2280 | 772 | 720 | 758 | 44 | 2109 | 575 | 305 | 1492 | 157 | 14 | 8.92% | 133 | 29 | 78.20% | 1 | 930 | 1793 | 51.87% | 674 | 1523 | 44.25% | 541 | 1121 | 48.26% | 1876 | 1453 | 1738 | 416 | 758 | 378 |
Total Saison régulière | 72 | 24 | 34 | 0 | 0 | 10 | 0 | 4 | 210 | 251 | -41 | 36 | 15 | 14 | 0 | 0 | 5 | 0 | 2 | 127 | 128 | -1 | 36 | 9 | 20 | 0 | 0 | 5 | 0 | 2 | 83 | 123 | -40 | 62 | 210 | 356 | 566 | 2 | 0 | 83 | 63 | 64 | 4 | 2280 | 772 | 720 | 758 | 44 | 2109 | 575 | 305 | 1492 | 157 | 14 | 8.92% | 133 | 29 | 78.20% | 1 | 930 | 1793 | 51.87% | 674 | 1523 | 44.25% | 541 | 1121 | 48.26% | 1876 | 1453 | 1738 | 416 | 758 | 378 |
Séries éliminatoires | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
20 | 4 | 0 | 4 | 0 | 0 | 0 | 0 | 0 | 5 | 19 | -14 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 2 | 8 | -6 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 3 | 11 | -8 | 0 | 5 | 7 | 12 | 0 | 0 | 1 | 3 | 1 | 0 | 128 | 48 | 42 | 38 | 0 | 90 | 22 | 30 | 107 | 12 | 0 | 0.00% | 9 | 4 | 55.56% | 0 | 94 | 148 | 63.51% | 47 | 71 | 66.20% | 29 | 62 | 46.77% | 120 | 95 | 77 | 21 | 41 | 22 |
Total Séries éliminatoires | 4 | 0 | 4 | 0 | 0 | 0 | 0 | 0 | 5 | 19 | -14 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 2 | 8 | -6 | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 3 | 11 | -8 | 0 | 5 | 7 | 12 | 0 | 0 | 1 | 3 | 1 | 0 | 128 | 48 | 42 | 38 | 0 | 90 | 22 | 30 | 107 | 12 | 0 | 0.00% | 9 | 4 | 55.56% | 0 | 94 | 148 | 63.51% | 47 | 71 | 66.20% | 29 | 62 | 46.77% | 120 | 95 | 77 | 21 | 41 | 22 |
# |
Nom du joueur |
GP |
G |
A |
P |
+/- |
PIM |
HIT |
HTT |
SHT |
SHT% |
SB |
MP |
AMG |
PPG |
PPA |
PPP |
PPS |
PKG |
PKA |
PKP |
PKS |
GW |
GT |
FO% |
HT |
P/20 |
PSG |
PSS |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Lauri Pajuniemi | 4 | 1 | 2 | 3 | -2 | 0 | 1 | 7 | 5 | 20.00% | 1 | 43 | 10.80 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 100.00% | 0 | 1.39 | 0 | 0 |
2 | Tyler Angle | 4 | 1 | 1 | 2 | -2 | 2 | 2 | 8 | 15 | 6.67% | 1 | 44 | 11.07 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 93.44% | 0 | 0.90 | 0 | 0 |
3 | Matthew Kessel | 3 | 0 | 1 | 1 | -4 | 0 | 14 | 5 | 7 | 0% | 3 | 56 | 18.99 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 0 | 0 | 0 | 0% | 0 | 0.35 | 0 | 0 |
4 | Justin Kirkland | 4 | 0 | 1 | 1 | -2 | 5 | 4 | 6 | 9 | 0% | 0 | 43 | 10.85 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 100.00% | 0 | 0.46 | 0 | 0 |
5 | Jack Quinn | 4 | 1 | 0 | 1 | -2 | 0 | 1 | 7 | 19 | 5.26% | 0 | 61 | 15.31 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 50.00% | 0 | 0.33 | 0 | 0 |
# |
Nom du gardien |
GP |
W |
L |
OTL |
PCT |
GAA |
MP |
PIM |
SO |
GA |
SA |
SAR |
A |
EG |
PS % |
PSA |
---|