Connexion

Monsters
GP: 10 | W: 6 | L: 3 | OTL: 1 | P: 13
GF: 23 | GA: 23 | PP%: 18.18% | PK%: 88.00%
DG: Yvon Poulin | Morale : 50 | Moyenne d’équipe : N/A
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Centre de jeu
Phantoms
4-4-2, 10pts
5
FINAL
2 Monsters
6-3-1, 13pts
Team Stats
L2SéquenceW1
2-2-1Fiche domicile3-2-0
2-2-1Fiche domicile3-1-1
4-4-2Derniers 10 matchs6-3-1
2.50Buts par match 2.30
2.70Buts contre par match 2.30
7.55%Pourcentage en avantage numérique18.18%
83.56%Pourcentage en désavantage numérique88.00%
Wolf Pack
3-6-1, 7pts
2
FINAL
3 Monsters
6-3-1, 13pts
Team Stats
L1SéquenceW1
2-3-0Fiche domicile3-2-0
1-3-1Fiche domicile3-1-1
3-6-1Derniers 10 matchs6-3-1
2.20Buts par match 2.30
3.10Buts contre par match 2.30
18.64%Pourcentage en avantage numérique18.18%
84.38%Pourcentage en désavantage numérique88.00%
Meneurs d'équipe
Buts
Craig Smith
3
Passes
Cale Fleury
7
Points
Cale Fleury
8
Plus/Moins
Ville Heinola
2
Victoires
Mackenzie Blackwood
6
Pourcentage d’arrêts
Mackenzie Blackwood
0.866

Statistiques d’équipe
Buts pour
23
2.30 GFG
Tirs pour
192
19.20 Avg
Pourcentage en avantage numérique
18.2%
10 GF
Début de zone offensive
40.0%
Buts contre
23
2.30 GAA
Tirs contre
171
17.10 Avg
Pourcentage en désavantage numérique
88.0%%
6 GA
Début de la zone défensive
40.8%
Informations de l'équipe

Directeur généralYvon Poulin
EntraîneurRick Tocchet
DivisionDivision 2
ConférenceConference 1
CapitaineCraig Smith
Assistant #1Nicolas Roy
Assistant #2Rasmus Asplund


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro33
Équipe Mineure18
Limite contact 51 / 60
Espoirs17


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
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
10textAny 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 SPÂgeContratSalaire
1Jack Drury (R)0X100.00614088716357906864635762254747635000232925,000$
2Jesse Ylonen (R)0XX100.00634199666965886844727065754747715000241925,000$
3Craig Smith (C)0XX100.007143907975588663316066645481846750003413,100,000$
4Nicolas Roy (A)0XX100.00784488797774897582707381616466765000262750,000$
5Georgii Merkulov (R)0XX100.0073668963667071658062656462444466500N02231,202,513$
6Lucas Edmonds (R)0XX100.00746594646572765950526263594444635000223950,000$
7Rasmus Asplund (A)0XX100.00654296776958805941615672256161635000251825,000$
8Tyler Benson0XX100.00757380677361635850605064484747595000251750,000$
9Charles Hudon (R)0XXX100.00726882636880846680606864654444685000291750,000$
10Sonny Milano0XX100.006742908370648565257770602563637150002721,700,000$
11Mikhail Maltsev0XX100.00797492747468706480586568625050675000251925,000$
12Connor Dewar0XX100.00805682656258856065625879255859655000244800,000$
13Cale Fleury0X100.00884694747562595825474771255151605000242750,000$
14Robin Salo (R)0X100.00654188686757715925536067254545645000242937,750$
15David Jiricek (R)0X100.007471816471626457255545624344445750001931,950,000$
16Gabriel Carlsson0X100.00777580787564694925413965375858545000264750,000$
17Riley Stillman0X100.008193807675656860255147742560606150002541,350,000$
18Casey Fitzgerald0X100.00784394726759635325494775255151605000264750,000$
Rayé
1Jan Jenik0X100.00626556746564656379635958564545615000231902,500$
2Cole Reinhardt (R)0X100.00717463637479846050595662534444615000232813,333$
3Adam Raska (R)0XX100.00576343676367724950464652444444515000222900,000$
4Ryan Jones0XX100.00777875637859624950474662444444545000271750,000$
5Ryker Evans (R)0X100.00696772636777835525534259404444555000213925,000$
6Donovan Sebrango (R)0X100.00746985636964694625344360414444525000211925,000$
7Albert Johansson (R)0X100.00676279646265704825394257404444525000223919,167$
8Kaedan Korczak (R)0X100.00717367737366714825394159394545535000221905,000$
9John Ludvig (R)0X100.00717464657450515025444159394444515000233925,000$
10Drew Helleson (R)0X100.00777778697758614825404162394444535000222750,000$
11Ville Heinola0X100.006764738064687257255642604047475750002231,075,833$
MOYENNE D’ÉQUIPE100.0072628170706573584354536443505061500
Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
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
10textAny 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 SPÂgeContratSalaire
1Eetu Makiniemi (R)0100.00494455685053505454533044445150002421,000,000$
Rayé
1Jakub Skarek (R)0100.0049516478485150545151304444515000233913,333$
2Mackenzie Blackwood0100.0061545590655671626561756060625000271913,333$
3Isaiah Saville (R)0100.0052526574525250565151304444525000232862,417$
MOYENNE D’ÉQUIPE100.005350607854535557555441484854500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Rick Tocchet83917886848062CAN6021,500,000$


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
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
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’équipePOSGP 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
1Cale FleuryMonsters (CLB)D10178114014463316.67%920820.81044340011035100%000000.7700000100
2Sonny MilanoMonsters (CLB)LW/RW10257020681541613.33%219719.711238420000412033.33%1800000.7101000011
3Nicolas RoyMonsters (CLB)C/RW1024601601433278197.41%421121.1622410430001400062.60%24600000.5711000000
4Riley StillmanMonsters (CLB)D10246-3751713101620.00%321721.77123738000041100%000000.5500001002
5Jesse YlonenMonsters (CLB)LW/RW10145-300114135217.69%219319.371123420000340058.33%1200000.5200000010
6Craig SmithMonsters (CLB)C/RW103251805101721317.65%017817.800111411011251030.77%2600000.5600000011
7Georgii MerkulovMonsters (CLB)C/RW9235-18058122716.67%013915.48112537000010045.45%1100000.7200000001
8Mikhail MaltsevMonsters (CLB)C/LW10235-2401418242148.33%015715.73134943000000057.64%14400000.6400000020
9Rasmus AsplundMonsters (CLB)C/LW1021312041288925.00%213713.7700002000070031.82%2200000.4400000100
10Charles HudonMonsters (CLB)C/LW/RW1012306099121148.33%214414.46101260000110161.11%1800000.4100000000
11Casey FitzgeraldMonsters (CLB)D10303-16048132323.08%620820.872021039000036000%000000.2900000001
12David JiricekMonsters (CLB)D10022-11801023030%416816.8400006000015000%000000.2400000000
13Ville HeinolaMonsters (CLB)D3022220120120%05217.470110400001000%000000.7600000000
14Connor DewarMonsters (CLB)C/LW10112120181695611.11%213613.6401104000030150.53%9500000.2900000100
15Robin SaloMonsters (CLB)D10011-4202610220%321321.34000739000039000%000000.0900000000
16Jan JenikMonsters (CLB)C3000020114000%0155.0500011000050050.00%40000000000000
17Jack DruryMonsters (CLB)C10000-4001155200%1858.53000000000110054.84%620000000000000
18Gabriel CarlssonMonsters (CLB)D7000-5201211110%611716.850001800006000%00000000000000
19Lucas EdmondsMonsters (CLB)LW/RW10000-320221210%0858.5200000000040075.00%40000000000000
20Tyler BensonMonsters (CLB)LW/RW7000-4801072240%0507.19000000000000100.00%20000000000000
Statistiques d’équipe totales ou en moyenne179224163-2511151501891925314411.46%46291816.301018286744411223655255.72%66400000.4312001356
Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
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
10textAny text entered in the filter will match text found within the column
# Nom du gardien Nom de l’équipeGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Mackenzie BlackwoodMonsters (CLB)106210.8662.0954501191420001.0003100001
2Eetu MakiniemiMonsters (CLB)20100.8624.0060004290000007000
Statistiques d’équipe totales ou en moyenne126310.8652.2860501231710003107001


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
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
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Recrue Poids Taille Non-échange Disponible pour échange Ballotage forcé Waiver Possible Contrat Type Salaire actuel Salaire restantSalaire moyenSalaire moyen restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Lien
Adam RaskaMonsters (CLB)LW/RW222001-09-25Yes178 Lbs5 ft10NoNoNoNo2Pro & Farm900,000$900,000$900,000$900,000$0$0$No900,000$Lien
Albert JohanssonMonsters (CLB)D222001-04-01Yes168 Lbs6 ft0NoNoNoNo3Pro & Farm919,167$919,167$919,167$919,167$0$0$No919,167$919,167$
Cale FleuryMonsters (CLB)D241998-11-18No205 Lbs6 ft1NoNoNoNo2Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$Lien
Casey FitzgeraldMonsters (CLB)D261997-02-24No185 Lbs5 ft11NoNoNoNo4Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$750,000$Lien
Charles HudonMonsters (CLB)C/LW/RW291994-06-23Yes190 Lbs5 ft10NoNoNoNo1Pro & Farm750,000$750,000$750,000$750,000$0$0$NoLien
Cole ReinhardtMonsters (CLB)LW232000-02-01Yes203 Lbs6 ft1NoNoNoNo2Pro & Farm813,333$813,333$813,333$813,333$0$0$No813,333$Lien
Connor DewarMonsters (CLB)C/LW241999-06-26No170 Lbs5 ft10NoNoNoNo4Pro & Farm800,000$800,000$800,000$800,000$0$0$No800,000$800,000$800,000$Lien
Craig SmithMonsters (CLB)C/RW341989-09-05No208 Lbs6 ft1NoNoNoNo1Pro & Farm3,100,000$3,100,000$3,100,000$3,100,000$0$0$NoLien
David JiricekMonsters (CLB)D192003-11-28Yes189 Lbs6 ft3NoNoNoNo3Pro & Farm1,950,000$1,950,000$1,950,000$1,950,000$0$0$No1,950,000$1,950,000$
Donovan SebrangoMonsters (CLB)D212002-01-12Yes189 Lbs6 ft1NoNoNoNo1Pro & Farm925,000$925,000$925,000$925,000$0$0$NoLien
Drew HellesonMonsters (CLB)D222001-03-26Yes205 Lbs6 ft3NoNoNoNo2Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$Lien
Eetu MakiniemiMonsters (CLB)G241999-04-19Yes176 Lbs6 ft2NoNoNoNo2Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$No1,000,000$Lien
Gabriel CarlssonMonsters (CLB)D261997-01-02No192 Lbs6 ft5NoNoNoNo4Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$750,000$Lien
Georgii MerkulovMonsters (CLB)C/RW222000-10-10Yes181 Lbs5 ft11YesNoNoNo3Pro & Farm1,202,513$1,202,513$1,202,513$1,202,513$0$0$No1,202,513$1,202,513$Lien
Isaiah SavilleMonsters (CLB)G232000-09-21Yes195 Lbs6 ft1NoNoNoNo2Pro & Farm862,417$862,417$862,417$862,417$0$0$No862,417$Lien
Jack DruryMonsters (CLB)C232000-02-03Yes174 Lbs5 ft11NoNoNoNo2Pro & Farm925,000$925,000$925,000$925,000$0$0$No925,000$Lien
Jakub SkarekMonsters (CLB)G231999-11-10Yes192 Lbs6 ft3NoNoNoNo3Pro & Farm913,333$913,333$913,333$913,333$0$0$No913,333$913,333$Lien
Jan JenikMonsters (CLB)C232000-09-15No171 Lbs6 ft1NoNoNoNo1Pro & Farm902,500$902,500$795,000$795,000$0$0$NoLien
Jesse YlonenMonsters (CLB)LW/RW241999-10-03Yes188 Lbs6 ft1NoNoNoNo1Pro & Farm925,000$925,000$880,833$880,833$0$0$NoLien
John LudvigMonsters (CLB)D232000-02-08Yes201 Lbs6 ft1NoNoNoNo3Pro & Farm925,000$925,000$925,000$925,000$0$0$No925,000$925,000$
Kaedan KorczakMonsters (CLB)D222001-01-29Yes192 Lbs6 ft3NoNoNoNo1Pro & Farm905,000$905,000$795,000$795,000$0$0$NoLien
Lucas EdmondsMonsters (CLB)LW/RW222001-01-27Yes181 Lbs5 ft10NoNoNoNo3Pro & Farm950,000$950,000$950,000$950,000$0$0$No950,000$950,000$
Mackenzie BlackwoodMonsters (CLB)G271996-09-12No225 Lbs6 ft4NoNoNoNo1Pro & Farm913,333$913,333$913,333$913,333$0$0$NoLien
Mikhail MaltsevMonsters (CLB)C/LW251998-03-12No198 Lbs6 ft3NoNoNoNo1Pro & Farm925,000$925,000$925,000$925,000$0$0$NoLien
Nicolas RoyMonsters (CLB)C/RW261997-02-05No200 Lbs6 ft4NoNoNoNo2Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$Lien
Rasmus AsplundMonsters (CLB)C/LW251997-12-03No190 Lbs5 ft11NoNoNoNo1Pro & Farm825,000$825,000$825,000$825,000$0$0$NoLien
Riley StillmanMonsters (CLB)D251998-03-09No196 Lbs6 ft1NoNoNoNo4Pro & Farm1,350,000$1,350,000$1,350,000$1,350,000$0$0$No1,350,000$1,350,000$1,350,000$Lien
Robin SaloMonsters (CLB)D241998-10-13Yes181 Lbs6 ft0NoNoNoNo2Pro & Farm937,750$937,750$937,750$937,750$0$0$No937,750$Lien
Ryan JonesMonsters (CLB)LW/RW271996-05-26No214 Lbs6 ft2NoNoNoNo1Pro & Farm750,000$750,000$750,000$750,000$0$0$NoLien
Ryker EvansMonsters (CLB)D212001-12-13Yes189 Lbs5 ft11NoNoNoNo3Pro & Farm925,000$925,000$925,000$925,000$0$0$No925,000$925,000$
Sonny MilanoMonsters (CLB)LW/RW271996-05-12No194 Lbs6 ft0NoNoNoNo2Pro & Farm1,700,000$1,700,000$1,700,000$1,700,000$0$0$No1,700,000$Lien
Tyler BensonMonsters (CLB)LW/RW251998-03-15No201 Lbs6 ft0NoNoNoNo1Pro & Farm750,000$750,000$750,000$750,000$0$0$NoLien
Ville HeinolaMonsters (CLB)D222001-03-02No178 Lbs5 ft11NoNoNoNo3Pro & Farm1,075,833$1,075,833$1,075,833$1,075,833$0$0$No1,075,833$1,075,833$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3324.09191 Lbs6 ft12.151,017,278$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Sonny MilanoNicolas RoyCraig Smith35122
2Jesse YlonenMikhail MaltsevGeorgii Merkulov30122
3Rasmus AsplundConnor DewarCharles Hudon25122
4Lucas EdmondsJack DruryTyler Benson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Riley StillmanRobin Salo35122
2Cale FleuryCasey Fitzgerald30122
3Gabriel CarlssonDavid Jiricek25122
4Riley StillmanRobin Salo10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Sonny MilanoNicolas RoyCraig Smith60122
2Jesse YlonenMikhail MaltsevGeorgii Merkulov40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Riley StillmanRobin Salo60122
2Cale FleuryCasey Fitzgerald40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Nicolas RoySonny Milano60122
2Craig SmithJesse Ylonen40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Riley StillmanRobin Salo60122
2Cale FleuryCasey Fitzgerald40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Nicolas Roy60122Riley StillmanRobin Salo60122
2Sonny Milano40122Cale FleuryCasey Fitzgerald40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Nicolas RoySonny Milano60122
2Craig SmithJesse Ylonen40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Riley StillmanRobin Salo60122
2Cale FleuryCasey Fitzgerald40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Sonny MilanoNicolas RoyCraig SmithRiley StillmanRobin Salo
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Sonny MilanoNicolas RoyCraig SmithRiley StillmanRobin Salo
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Connor Dewar, Rasmus Asplund, Charles HudonConnor Dewar, Rasmus AsplundCharles Hudon
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Gabriel Carlsson, David Jiricek, Cale FleuryGabriel CarlssonDavid Jiricek, Cale Fleury
Tirs de pénalité
Nicolas Roy, Sonny Milano, Craig Smith, Jesse Ylonen, Mikhail Maltsev
Gardien
#1 : , #2 : Eetu Makiniemi
Lignes d’attaque personnalisées en prolongation
Nicolas Roy, Sonny Milano, Craig Smith, Jesse Ylonen, Mikhail Maltsev, Connor Dewar, Connor Dewar, Rasmus Asplund, Georgii Merkulov, Charles Hudon, Jack Drury
Lignes de défense personnalisées en prolongation
Riley Stillman, Robin Salo, Cale Fleury, Casey Fitzgerald, Gabriel Carlsson


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
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
10textAny text entered in the filter will match text found within the column
TotalDomicileVisiteur
# 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
1Penguins40101110811-32010001058-32000110033050.625813210085828464626267712555019210.53%24483.33%016126460.98%14126952.42%6812753.54%2331582477712561
2Phantoms211000006511010000025-31100000040420.50061117018582326462626431424427228.57%120100.00%116126460.98%14126952.42%6812753.54%2331582477712561
3Sound Tigers22000000532110000002111100000032141.000510150085823164626263014183113323.08%8187.50%016126460.98%14126952.42%6812753.54%2331582477712561
4Wolf Pack21100000440110000003211010000012-120.5004711008582456462626216142716318.75%6183.33%016126460.98%14126952.42%6812753.54%2331582477712561
Total10430111023230522000101216-4521011001174130.650234164018582192646262617146111150551018.18%50688.00%116126460.98%14126952.42%6812753.54%2331582477712561
_Since Last GM Reset10430111023230522000101216-4521011001174130.650234164018582192646262617146111150551018.18%50688.00%116126460.98%14126952.42%6812753.54%2331582477712561
_Vs Conference823011101820-2412000101015-54110110085390.5631831490185821616462626141329311942716.67%42588.10%116126460.98%14126952.42%6812753.54%2331582477712561
_Vs Division10230111023230512000101216-451101100117490.450234164018582192646262617146111150551018.18%50688.00%116126460.98%14126952.42%6812753.54%2331582477712561

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1013W12341641921714611115001
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
104311102323
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
52200101216
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
5211100117
Derniers 10 matchs
WLOTWOTL SOWSOL
630100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
551018.18%50688.00%1
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
64626268582
Mises en jeu
Gagnées en zone offensiveTotal en zone offensive% gagnées en zone offensive Gagnées en zone défensiveTotal en zone défensive% gagnées en zone défensiveGagnées en zone neutreTotal en zone neutre% gagnées en zone neutre
16126460.98%14126952.42%6812753.54%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2331582477712561


Derniers matchs joués
Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
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
10textAny text entered in the filter will match text found within the column
JourMatch Équipe visiteuse Score Équipe locale Score ST OT SO RI Lien
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
18Penguins3Monsters4BWXXSommaire du match
216Monsters1Penguins2ALXSommaire du match
327Monsters2Penguins1AWXSommaire du match
434Monsters1Wolf Pack2ALSommaire du match
544Penguins5Monsters1BLSommaire du match
760Sound Tigers1Monsters2BWSommaire du match
864Monsters3Sound Tigers2AWSommaire du match
974Monsters4Phantoms0AWSommaire du match
1088Phantoms5Monsters2BLSommaire du match
14107Wolf Pack2Monsters3BWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3520
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
31 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 3,357,017$ 3,330,850$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 0$ 0$




Monsters Leaders statistiques des joueurs (saison régulière)

# 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

Monsters Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Monsters Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
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

Monsters Leaders statistiques des joueurs (séries éliminatoires)

# 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

Monsters Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA