Connexion

Monkeys
GP: 8 | W: 8 | L: 0 | OTL: 0 | P: 16
GF: 51 | GA: 13 | PP%: 50.00% | PK%: 71.43%
DG: Fred Joanis | Morale : 61 | Moyenne d’équipe : 67
Prochains matchs #101 vs Vikings
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Centre de jeu
Guerriers du Nord
2-5-1, 5pts
1
FINAL
6 Monkeys
8-0-0, 16pts
Team Stats
W1SéquenceW5
1-2-1Fiche domicile4-0-0
1-3-0Fiche domicile4-0-0
2-5-1Derniers 10 matchs8-0-0
4.25Buts par match 6.38
6.00Buts contre par match 1.63
38.46%Pourcentage en avantage numérique50.00%
48.28%Pourcentage en désavantage numérique71.43%
Les Restants
3-6-0, 6pts
1
FINAL
3 Monkeys
8-0-0, 16pts
Team Stats
L4SéquenceW5
1-2-0Fiche domicile4-0-0
2-4-0Fiche domicile4-0-0
3-6-0Derniers 10 matchs8-0-0
3.33Buts par match 6.38
4.22Buts contre par match 1.63
41.18%Pourcentage en avantage numérique50.00%
61.29%Pourcentage en désavantage numérique71.43%
Vikings
2-5-1, 5pts
Jour 12
Monkeys
8-0-0, 16pts
Statistiques d’équipe
L1SéquenceW5
2-2-0Fiche domicile4-0-0
0-3-1Fiche visiteur4-0-0
2-5-110 derniers matchs8-0-0
3.38Buts par match 6.38
5.00Buts contre par match 6.38
45.45%Pourcentage en avantage numérique50.00%
50.00%Pourcentage en désavantage numérique71.43%
Monkeys
8-0-0, 16pts
Jour 13
Falcons
5-1-0, 10pts
Statistiques d’équipe
W5SéquenceW2
4-0-0Fiche domicile4-0-0
4-0-0Fiche visiteur1-1-0
8-0-010 derniers matchs5-1-0
6.38Buts par match 4.33
1.63Buts contre par match 4.33
50.00%Pourcentage en avantage numérique28.57%
71.43%Pourcentage en désavantage numérique55.00%
Guerriers du Nord
2-5-1, 5pts
Jour 17
Monkeys
8-0-0, 16pts
Statistiques d’équipe
W1SéquenceW5
1-2-1Fiche domicile4-0-0
1-3-0Fiche visiteur4-0-0
2-5-110 derniers matchs8-0-0
4.25Buts par match 6.38
6.00Buts contre par match 6.38
38.46%Pourcentage en avantage numérique50.00%
48.28%Pourcentage en désavantage numérique71.43%
Meneurs d'équipe
Buts
Matt Nieto
12
Passes
Casey Cizikas
23
Points
Casey Cizikas
30
Plus/Moins
Henri Jokiharju
14
Victoires
Chris Driedger
8
Pourcentage d’arrêts
Chris Driedger
0.924

Statistiques d’équipe
Buts pour
51
6.38 GFG
Tirs pour
271
33.88 Avg
Pourcentage en avantage numérique
50.0%
22 GF
Début de zone offensive
37.4%
Buts contre
13
1.63 GAA
Tirs contre
172
21.50 Avg
Pourcentage en désavantage numérique
71.4%%
4 GA
Début de la zone défensive
29.8%
Informations de l'équipe

Directeur généralFred Joanis
EntraîneurDean Evason
DivisionBourque
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro19
Équipe Mineure18
Limite contact 37 / 55
Espoirs38


Historique d'équipe

Saison actuelle8-0-0 (16PTS)
Historique159-78-11 (0.641%)
Apparitions en séries éliminatoires 3
Historique en séries éliminatoires (W-L)15-14
Coupe Stanley0


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
1Casey CizikasX99.009269868388809067836965835085800597203351,500,000$
2Sean KuralyXX97.009367808489818069836672785078770627103131,775,500$
3Pius SuterXX100.007053988774808870676674816470740637002711,975,000$
4Matt NietoXX99.00705695867979906960677177508179063700311850,000$
5Janne Kuokkanen (R)XX100.007155968075796271507171765069720636902511,825,000$
6Philipp Kurashev (R)XXX100.00715695937683807159717070637071063690241925,000$
7Connor McMichael (R)XX100.00735696877576737161687371516869063690232925,000$
8Julien Gauthier (R)X100.009174968292765367506667695069690636802611,225,000$
9Boris Katchouk (R)X100.00866290848578646850696673506970052680252758,333$
10Filip Zadina (R)XX100.007455938777794067506767725071720636702431,825,000$
11Nils Aman (R)X100.00725594907578756658686476506870050670242925,000$
12Jacob Middleton (R)X99.0085788177908591665067648650707506273N02832,450,000$
13Henri Jokiharju (R)X100.007959898981877067506865735072760647102422,500,000$
14Cale Fleury (R)X100.00926496848879406250646065507070063670251883,333$
15Ryan Merkley (R)X100.006355958873814367506866595066690636602311,225,000$
Rayé
1Derek GrantXX64.607466888285805172757568845076770527103311,500,000$
2Fredrik Olofsson (R)X100.00505050505050505050505050505050060490271750,000$
3Jack Studnicka (R)X100.00505050505050505050505050505050042490252762,500$
MOYENNE D’ÉQUIPE97.6775608781787766665866667252707105967
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
1Chris Driedger100.0064595890656865636065646970065640292850,000$
Rayé
MOYENNE D’ÉQUIPE100.006459589065686563606564697006564
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dean Evason76898089737099CAN591550,000$


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
1Casey CizikasMonkeys (IDS)C8723301075202229212124.14%619023.82116173270002101180.09%221210003.1501010320
2Matt NietoMonkeys (IDS)LW/RW81292170014849132924.49%316520.6576131327000043068.75%1697022.5400000212
3Sean KuralyMonkeys (IDS)C/LW88917114017732172625.00%318923.6964108270000101077.78%1896011.7901000111
4Derek GrantMonkeys (IDS)C/LW847119401992241618.18%414918.68134220000021081.91%9433001.4711000102
5Philipp KurashevMonkeys (IDS)C/LW/RW8561192010228101517.86%314718.40011420000000275.00%477001.4900000012
6Henri JokiharjuMonkeys (IDS)D84591475214146428.57%1521226.5842653000019000%0413010.8500001010
7Pius SuterMonkeys (IDS)C/LW8257900631431014.29%414518.16022320000000075.00%475000.9600000000
8Jacob MiddletonMonkeys (IDS)D824612401812195510.53%321827.30213330000110000%0215000.5500000000
9Janne KuokkanenMonkeys (IDS)LW/RW8134-100104207115.00%313416.76101210001600100.00%406000.6000000000
10Ryan MerkleyMonkeys (IDS)D80444201148120%815919.9600011700009000%0311000.5000000000
11Filip ZadinaMonkeys (IDS)LW/RW821330020101920.00%312015.050000000000100%134000.5000000011
12Connor McMichaelMonkeys (IDS)C/LW8303000941491421.43%312816.0500002000020071.43%4236000.4700000000
13Cale FleuryMonkeys (IDS)D80226209126530%316520.66000018000010000%0216000.2400000000
14Julien GauthierMonkeys (IDS)RW8011-1001756090%311814.79000000000000100.00%216000.1700000000
15Boris KatchoukMonkeys (IDS)LW8011000720010%0354.3801102000040080.00%501000.5700000000
16Fredrik OlofssonMonkeys (IDS)LW7000160510110%29113.080000000000000%00400000000000
Statistiques d’équipe totales ou en moyenne12750801309338101959927110317618.45%66237018.67223658442480005807379.08%41155120041.1013011778
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
1Chris DriedgerMonkeys (IDS)88000.9241.61485001317288001.000380100
Statistiques d’équipe totales ou en moyenne88000.9241.6148500131728800380100


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 Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Type Salaire actuel Salaire restantPlafond salarial Non Activé 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 10Non-échange Année 2Non-échange Année 3Non-échange Année 4Non-échange Année 5Non-échange Année 6Non-échange Année 7Non-échange Année 8Non-échange Année 9Non-échange Année 10Lien
Boris KatchoukMonkeys (IDS)LW251998-06-18 12:12:50Yes206 Lbs6 ft2NoNoN/ANoNo2Pro & Farm758,333$758,333$0$0$No758,333$--------No--------
Cale FleuryMonkeys (IDS)D251998-11-19 15:04:50Yes205 Lbs6 ft1NoNoFree AgentNoNo12024-03-03Pro & Farm883,333$883,333$0$0$No------------------Lien
Casey CizikasMonkeys (IDS)C331991-02-27 09:26:19No201 Lbs5 ft11NoNoN/ANoNo5Pro & Farm1,500,000$1,500,000$0$0$No1,500,000$1,500,000$1,500,000$1,500,000$-----NoNoNoNo-----Lien
Chris DriedgerMonkeys (IDS)G291994-05-18 07:13:17No208 Lbs6 ft4NoNoN/ANoNo2Pro & Farm850,000$850,000$0$0$No850,000$--------No--------
Connor McMichaelMonkeys (IDS)C/LW232001-01-15 15:26:21Yes180 Lbs6 ft0NoNoN/ANoNo2Pro & Farm925,000$925,000$0$0$No925,000$--------No--------
Derek Grant (sur la masse salariale)Monkeys (IDS)C/LW331990-04-20 16:02:45No215 Lbs6 ft3NoNoN/ANoNo1Pro & Farm1,500,000$1,500,000$0$0$No------------------Lien
Filip ZadinaMonkeys (IDS)LW/RW241999-11-27 15:09:35Yes189 Lbs6 ft0NoNoFree AgentNoNo32024-03-03Pro & Farm1,825,000$1,825,000$0$0$No1,825,000$1,825,000$-------NoNo-------Lien
Fredrik OlofssonMonkeys (IDS)LW271996-05-27 12:19:10Yes190 Lbs6 ft2NoNoN/ANoNo1Pro & Farm750,000$750,000$0$0$No------------------
Henri JokiharjuMonkeys (IDS)D241999-06-17 14:47:01Yes195 Lbs6 ft0NoNoN/ANoNo2Pro & Farm2,500,000$2,500,000$0$0$No2,500,000$--------No--------Lien
Jack StudnickaMonkeys (IDS)C251999-02-18 12:28:57Yes187 Lbs6 ft1NoNoN/ANoNo2Pro & Farm762,500$762,500$0$0$No762,500$--------No--------
Jacob MiddletonMonkeys (IDS)D281996-01-02 05:04:03Yes219 Lbs6 ft3YesNoFree AgentNoNo32024-03-15Pro & Farm2,450,000$2,450,000$0$0$No2,450,000$2,450,000$-------YesYes-------
Janne KuokkanenMonkeys (IDS)LW/RW251998-05-25 14:47:44Yes193 Lbs6 ft1NoNoN/ANoNo1Pro & Farm1,825,000$1,825,000$0$0$No------------------Lien
Julien GauthierMonkeys (IDS)RW261997-10-15 15:17:21Yes227 Lbs6 ft4NoNoFree AgentNoNo12024-03-03Pro & Farm1,225,000$1,225,000$0$0$No------------------Lien
Matt NietoMonkeys (IDS)LW/RW311992-11-05 15:26:19No190 Lbs5 ft11NoNoN/ANoNo1Pro & Farm850,000$850,000$0$0$No------------------Lien
Nils AmanMonkeys (IDS)C242000-02-07 12:35:33Yes179 Lbs6 ft2NoNoN/ANoNo2Pro & Farm925,000$925,000$0$0$No925,000$--------No--------
Philipp KurashevMonkeys (IDS)C/LW/RW241999-10-12 15:29:07Yes190 Lbs6 ft0NoNoFree AgentNoNo12024-03-03Pro & Farm925,000$925,000$0$0$No------------------Lien
Pius SuterMonkeys (IDS)C/LW271996-05-24 15:52:51No174 Lbs5 ft11NoNoN/ANoNo1Pro & Farm1,975,000$1,975,000$0$0$No------------------Lien
Ryan MerkleyMonkeys (IDS)D232000-08-14 15:31:58Yes186 Lbs6 ft0NoNoN/ANoNo1Pro & Farm1,225,000$1,225,000$0$0$No------------------
Sean KuralyMonkeys (IDS)C/LW311993-01-20 04:32:57No213 Lbs6 ft2NoNoN/ANoNo3Pro & Farm1,775,500$1,775,500$0$0$No1,775,500$1,775,500$-------NoNo-------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
1926.68197 Lbs6 ft11.841,338,403$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Sean KuralyCasey CizikasMatt Nieto40122
2Pius SuterPhilipp Kurashev30122
3Janne KuokkanenConnor McMichaelJulien Gauthier20122
4Filip ZadinaCasey CizikasSean Kuraly10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob MiddletonHenri Jokiharju40122
2Cale FleuryRyan Merkley30122
3Filip Zadina20122
4Jacob MiddletonHenri Jokiharju10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Sean KuralyCasey CizikasMatt Nieto60122
2Pius SuterPhilipp Kurashev40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob MiddletonHenri Jokiharju60122
2Cale FleuryRyan Merkley40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Casey CizikasSean Kuraly60122
2Matt Nieto40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob MiddletonHenri Jokiharju60122
2Cale FleuryRyan Merkley40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Casey Cizikas60122Jacob MiddletonHenri Jokiharju60122
2Sean Kuraly40122Cale FleuryRyan Merkley40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Casey CizikasSean Kuraly60122
2Matt Nieto40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob MiddletonHenri Jokiharju60122
2Cale FleuryRyan Merkley40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Sean KuralyCasey CizikasMatt NietoJacob MiddletonHenri Jokiharju
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Sean KuralyCasey CizikasMatt NietoJacob MiddletonHenri Jokiharju
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Boris Katchouk, Connor McMichael, Janne KuokkanenBoris Katchouk, Connor McMichaelJanne Kuokkanen
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Cale Fleury, Ryan Merkley, Jacob MiddletonCale FleuryRyan Merkley, Jacob Middleton
Tirs de pénalité
Casey Cizikas, Sean Kuraly, , Matt Nieto, Pius Suter
Gardien
#1 : Chris Driedger, #2 :


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
1Bolt10000010211000000000001000001021121.00021300132413131859584102914228200.00%110.00%012315280.92%10212184.30%10013375.19%21311511952151104
2Falcons11000000422110000004220000000000021.0004711001324131378595841027124286350.00%20100.00%012315280.92%10212184.30%10013375.19%21311511952151104
3Guerriers du Nord2200000015411110000006151100000093641.00015243900132413160859584104217174911654.55%6266.67%012315280.92%10212184.30%10013375.19%21311511952151104
4Les Restants22000000844110000003121100000053241.00081220001324131658595841041114406116.67%2150.00%012315280.92%10212184.30%10013375.19%21311511952151104
5Vikings11000000817000000000001100000081721.00081422001324131498595841018792210660.00%20100.00%012315280.92%10212184.30%10013375.19%21311511952151104
6Warriors110000001411311000000141130000000000021.00014223600132413129859584101552289666.67%10100.00%012315280.92%10212184.30%10013375.19%21311511952151104
Total8700001051133844000000275224300001024816161.0005180131001324131271859584101726638195442250.00%14471.43%012315280.92%10212184.30%10013375.19%21311511952151104
_Since Last GM Reset8700001051133844000000275224300001024816161.0005180131001324131271859584101726638195442250.00%14471.43%012315280.92%10212184.30%10013375.19%21311511952151104
_Vs Conference7700000049123744000000275223300000022715141.0004979128001324131240859584101435236167422252.38%13376.92%012315280.92%10212184.30%10013375.19%21311511952151104
_Vs Division47000000306242400000017215230000001349141.7503048780013241311438595841074231590251352.00%5180.00%012315280.92%10212184.30%10013375.19%21311511952151104

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
816W55180131271172663819500
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
87000105113
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4400000275
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4300010248
Derniers 10 matchs
WLOTWOTL SOWSOL
700010
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
442250.00%14471.43%0
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
859584101324131
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
12315280.92%10212184.30%10013375.19%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
21311511952151104


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
15Warriors1Monkeys 14BWSommaire du match
322Monkeys 9Guerriers du Nord3AWSommaire du match
430Monkeys 2Bolt1AWXXSommaire du match
538Monkeys 8Vikings1AWSommaire du match
645Falcons2Monkeys 4BWSommaire du match
861Monkeys 5Les Restants3AWSommaire du match
969Guerriers du Nord1Monkeys 6BWSommaire du match
1189Les Restants1Monkeys 3BWSommaire du match
12101Vikings-Monkeys -
13103Monkeys -Falcons-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
17126Guerriers du Nord-Monkeys -
18131Monkeys -Warriors-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
2 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 2,392,966$ 2,392,966$ 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$ 9 0$ 0$




Monkeys 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
1Micheal Ferland20515222838015725128616481318.70%126370318.075494148915161021862.36%122.0514
2Ryan Poehling20014715730412912426918289116.50%91381319.0741509178426910461.82%111.5935
3Erik Brannstrom131521832351291021901515429.59%196338425.8338661049002253275.00%01.3902
4Xavier Ouellet21140167207120682581846436.22%209421619.9824386251033125285.71%00.9813
5Ty Dellandrea131871051926711122115754615.93%52227117.3429396852123715263.35%51.6901

Monkeys 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
1Braden Holtby1401191340.9022.99828784413421021961810.87023
2Cory Schneider6052330.9093.1535468218620331046400.66715

Monkeys 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
Saison régulière
202082669002325803232574134400111298158140413250012128216511714258097315530211325421093515116012341115302794897725130530919462.78%2439361.73%141048159165.87%1032162963.35%1166181664.21%1999124916336221320734
2021826214022205352652704131602200257120137413180002027814513313453589014251211521520163441110611661164172490836769150631018960.97%2658767.17%12978165858.99%926165455.99%1018165861.40%1951118016056571380749
2022826611021116013192824135401010290142148413170110131117713414060199815991213724521633646128612411114152557834767154531918357.37%2499362.65%61020159663.91%899152758.87%1129181462.24%2088132715326001314742
Total Saison régulière24614778097321658126339512375360642082859723112372420331283066616432716582792445023425630591161004933863405323740790725451708396496350652.54%70534351.35%352814466560.32%2222390656.89%3323553460.05%596637304775189540702246
Séries éliminatoires
202022139000001331294137600000848049630000049490261332173500035494819733283153291680218120382793645.57%482547.92%127341865.31%18026069.23%36351370.76%578369393148349206
2021191450000011880381091000007339349540000045414281182083260028434618162802572745715225241340654467.69%643151.56%120538353.52%21541451.93%23239958.15%437277402150302154
2022191450000012491331091000007140319540000053512281242153390130454817602422852321716234249326734460.27%582360.34%119837253.23%20541449.52%22240554.81%417260411158311152
Total Séries éliminatoires29151400000187193-615780000094102-814860000093912301873135000044825921036332368333310813452214281026260.78%995544.44%830150559.60%23247149.26%37266955.61%654408623227463245

Monkeys 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
1Micheal Ferland57464995-1594915725318.18%39105718.552224464100034251.04%41.8000
2Erik Brannstrom37196584225515218710.16%5396526.0914314540000151100.00%11.7401
3Ty Dellandrea302636622024404713619.12%2153417.811010202110120058.93%12.3200
4Valeri Nichushkin23282957139402512222.95%1145819.9598172100011071.77%22.4900
5Ryan Poehling322531562437422416015.63%1563119.7261824801133153.29%21.7700

Monkeys 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
1Braden Holtby2523110.9153.08150001779024712000
2Cory Schneider11000.9292.006000228180000