Connexion

Monkeys
GP: 65 | W: 41 | L: 24 | OTL: 0 | P: 82
GF: 422 | GA: 352 | PP%: 56.97% | PK%: 56.67%
DG: Fred Joanis | Morale : 67 | Moyenne d’équipe : 67
Prochains matchs #779 vs Monsters
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Centre de jeu
Prospects
28-33-4, 60pts
9
FINAL
6 Monkeys
41-24-0, 82pts
Team Stats
L1SéquenceW1
14-15-3Fiche domicile25-7-0
14-18-1Fiche domicile16-17-0
6-4-0Derniers 10 matchs5-5-0
5.14Buts par match 6.49
5.91Buts contre par match 5.42
41.33%Pourcentage en avantage numérique56.97%
49.36%Pourcentage en désavantage numérique56.67%
Monkeys
41-24-0, 82pts
9
FINAL
2 Dynamos
19-42-4, 42pts
Team Stats
W1SéquenceL1
25-7-0Fiche domicile9-21-2
16-17-0Fiche domicile10-21-2
5-5-0Derniers 10 matchs6-4-0
6.49Buts par match 3.83
5.42Buts contre par match 6.20
56.97%Pourcentage en avantage numérique36.84%
56.67%Pourcentage en désavantage numérique42.31%
Monkeys
41-24-0, 82pts
Jour 109
Monsters
23-39-2, 48pts
Statistiques d’équipe
W1SéquenceL1
25-7-0Fiche domicile11-20-1
16-17-0Fiche visiteur12-19-1
5-5-010 derniers matchs4-6-0
6.49Buts par match 3.98
5.42Buts contre par match 3.98
56.97%Pourcentage en avantage numérique48.55%
56.67%Pourcentage en désavantage numérique48.50%
Bolt
27-34-3, 57pts
Jour 110
Monkeys
41-24-0, 82pts
Statistiques d’équipe
L2SéquenceW1
13-17-2Fiche domicile25-7-0
14-17-1Fiche visiteur16-17-0
3-7-010 derniers matchs5-5-0
4.25Buts par match 6.49
5.27Buts contre par match 6.49
41.52%Pourcentage en avantage numérique56.97%
49.75%Pourcentage en désavantage numérique56.67%
Monkeys
41-24-0, 82pts
Jour 111
Senators
18-41-5, 41pts
Statistiques d’équipe
W1SéquenceL1
25-7-0Fiche domicile10-18-5
16-17-0Fiche visiteur8-23-0
5-5-010 derniers matchs7-2-1
6.49Buts par match 4.17
5.42Buts contre par match 4.17
56.97%Pourcentage en avantage numérique40.00%
56.67%Pourcentage en désavantage numérique48.11%
Meneurs d'équipe
Buts
Matt Nieto
83
Passes
Philipp Kurashev
104
Points
Philipp Kurashev
155
Plus/Moins
Pius Suter
30
Victoires
Chris Driedger
1
Pourcentage d’arrêts
Chris Driedger
0.938

Statistiques d’équipe
Buts pour
422
6.49 GFG
Tirs pour
2646
40.71 Avg
Pourcentage en avantage numérique
57.0%
139 GF
Début de zone offensive
35.1%
Buts contre
352
5.42 GAA
Tirs contre
2025
31.15 Avg
Pourcentage en désavantage numérique
56.7%%
78 GA
Début de la zone défensive
24.0%
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 Pro17
Équipe Mineure20
Limite contact 37 / 55
Espoirs38


Historique d'équipe

Saison actuelle41-24-0 (82PTS)
Historique200-102-12 (0.637%)
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
1Derek GrantXX100.007466888285805172757568845076770657103411,500,000$
2Pius SuterXX100.007053988774808870676674816470740697002811,975,000$
3Matt NietoXX100.00705695867979906960677177508179080700311850,000$
4Janne Kuokkanen (R)XX100.007155968075796271507171765069720806902611,825,000$
5Philipp Kurashev (R)XXX100.00715695937683807159717070637071080690241925,000$
6Connor McMichael (R)XX100.00735696877576737161687371516869080690232925,000$
7Julien Gauthier (R)X100.009174968292765367506667695069690806802611,225,000$
8Boris Katchouk (R)X100.00866290848578646850696673506970080680262758,333$
9Filip Zadina (R)XX100.007455938777794067506767725071720696702431,825,000$
10Nils Aman (R)X100.00725594907578756658686476506870066670242925,000$
11Fredrik Olofsson (R)X100.00505050505050505050505050505050042490281750,000$
12Jack Studnicka (R)X100.00505050505050505050505050505050020490252762,500$
13J.J. Moser (R)X100.00785491907587967250766879506873057740242925,000$
14Henri Jokiharju (R)X100.007959898981877067506865735072760627102522,500,000$
15Cale Fleury (R)X100.00926496848879406250646065507070064670251883,333$
16Ryan Merkley (R)X100.006355958873814367506866595066690806602311,225,000$
Rayé
MOYENNE D’ÉQUIPE100.0073588882767664665567667052686906767
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
1Laurent Brossoit100.00756664917275717575727771730737103111,750,000$
Rayé
MOYENNE D’ÉQUIPE100.007566649172757175757277717307371
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
1Philipp KurashevMonkeys (IDS)C/LW/RW65511041552700614836712023113.90%16114017.5519426133101000007370.37%278938022.721100071811
2Matt NietoMonkeys (IDS)LW/RW658368151-155666443013426719.30%46135220.81332861631711011127064.71%6813359092.231201015910
3Pius SuterMonkeys (IDS)C/LW517759136306050473589120821.51%2491217.892827554183000013462.96%2770460102.98010001886
4Connor McMichaelMonkeys (IDS)C/LW65153045-614103851161521139.32%2265510.0802217000091071.31%9484819001.3701011045
5Janne KuokkanenMonkeys (IDS)LW/RW65182442-6404244158517711.39%1565810.13011120001203170.51%784330001.2800000313
6Casey CizikasIcedogsC1916223831610363780234820.00%1440921.55671313470112333074.47%6582021021.8600002122
7Ryan MerkleyMonkeys (IDS)D6513132-2255293510746500.93%28104516.08033133000217100%02150000.6100001025
8Sean KuralyIcedogsC/LW1881927318031178537559.41%1037220.700779451011250075.00%282016001.4500000001
9Julien GauthierMonkeys (IDS)RW65121022-61410513990426813.33%176209.5400000000002072.22%542523000.7111200113
10Henri JokiharjuMonkeys (IDS)D164182272023214317259.30%2843527.204913659000028100%01232001.0100000013
11Cale FleuryMonkeys (IDS)D5431518-515580396219244.84%4887616.22213435000015000%0755000.4101100000
12Filip ZadinaMonkeys (IDS)LW/RW3531518-12018177430344.05%2147513.59000000000000100.00%11320000.7600000001
13Boris KatchoukMonkeys (IDS)LW65336-50019725121912.00%11692.61224419000080059.09%2248000.7111000000
14Jacob MiddletonIcedogsD3022055835120%27926.6501111500002000%013000.5000010000
Statistiques d’équipe totales ou en moyenne65129442071438126505524692045675122114.38%292920214.1494130224177624213717628871.95%19115064200231.5548334454650
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 DriedgerIcedogs21000.9381.90950034829000020000
Statistiques d’équipe totales ou en moyenne21000.9381.9095003482900020000


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)LW261998-06-18 12:12:50Yes206 Lbs6 ft2NoNoN/ANoNo2Pro & Farm758,333$151,667$0$0$No758,333$--------No--------
Cale FleuryMonkeys (IDS)D251998-11-19 15:04:50Yes205 Lbs6 ft1NoNoFree AgentNoNo12024-03-03Pro & Farm883,333$176,667$0$0$No------------------Lien
Connor McMichaelMonkeys (IDS)C/LW232001-01-15 15:26:21Yes180 Lbs6 ft0NoNoN/ANoNo2Pro & Farm925,000$185,000$0$0$No925,000$--------No--------
Derek GrantMonkeys (IDS)C/LW341990-04-20 16:02:45No215 Lbs6 ft3NoNoN/ANoNo1Pro & Farm1,500,000$300,000$0$0$No------------------Lien
Filip ZadinaMonkeys (IDS)LW/RW241999-11-27 15:09:35Yes189 Lbs6 ft0NoNoFree AgentNoNo32024-03-03Pro & Farm1,825,000$365,000$0$0$No1,825,000$1,825,000$-------NoNo-------Lien
Fredrik OlofssonMonkeys (IDS)LW281996-05-27 12:19:10Yes190 Lbs6 ft2NoNoN/ANoNo1Pro & Farm750,000$150,000$0$0$No------------------
Henri JokiharjuMonkeys (IDS)D251999-06-17 14:47:01Yes195 Lbs6 ft0NoNoN/ANoNo2Pro & Farm2,500,000$500,000$0$0$No2,500,000$--------No--------Lien
J.J. MoserMonkeys (IDS)D242000-06-06 04:20:50Yes173 Lbs6 ft1NoNoN/ANoNo2Pro & Farm925,000$185,000$0$0$No925,000$--------No--------
Jack StudnickaMonkeys (IDS)C251999-02-18 12:28:57Yes187 Lbs6 ft1NoNoN/ANoNo2Pro & Farm762,500$152,500$0$0$No762,500$--------No--------
Janne KuokkanenMonkeys (IDS)LW/RW261998-05-25 14:47:44Yes193 Lbs6 ft1NoNoN/ANoNo1Pro & Farm1,825,000$365,000$0$0$No------------------Lien
Julien GauthierMonkeys (IDS)RW261997-10-15 15:17:21Yes227 Lbs6 ft4NoNoFree AgentNoNo12024-03-03Pro & Farm1,225,000$245,000$0$0$No------------------Lien
Laurent BrossoitMonkeys (IDS)G311993-03-23 17:36:37No215 Lbs6 ft3NoNoN/ANoNo1Pro & Farm1,750,000$350,000$0$0$No------------------
Matt NietoMonkeys (IDS)LW/RW311992-11-05 15:26:19No190 Lbs5 ft11NoNoN/ANoNo1Pro & Farm850,000$170,000$0$0$No------------------Lien
Nils AmanMonkeys (IDS)C242000-02-07 12:35:33Yes179 Lbs6 ft2NoNoN/ANoNo2Pro & Farm925,000$185,000$0$0$No925,000$--------No--------
Philipp KurashevMonkeys (IDS)C/LW/RW241999-10-12 15:29:07Yes190 Lbs6 ft0NoNoFree AgentNoNo12024-03-03Pro & Farm925,000$185,000$0$0$No------------------Lien
Pius SuterMonkeys (IDS)C/LW281996-05-24 15:52:51No174 Lbs5 ft11NoNoN/ANoNo1Pro & Farm1,975,000$395,000$0$0$No------------------Lien
Ryan MerkleyMonkeys (IDS)D232000-08-14 15:31:58Yes186 Lbs6 ft0NoNoN/ANoNo1Pro & Farm1,225,000$245,000$0$0$No------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
1726.29194 Lbs6 ft11.471,266,422$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Matt Nieto40122
2Philipp Kurashev30122
3Janne KuokkanenConnor McMichaelJulien Gauthier20122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
140122
2Ryan Merkley30122
320122
410122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Matt Nieto60122
2Philipp Kurashev40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2Ryan Merkley40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
160122
2Matt Nieto40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2Ryan Merkley40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
16012260122
240122Ryan Merkley40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
160122
2Matt Nieto40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2Ryan Merkley40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Matt Nieto
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Matt Nieto
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Boris Katchouk, Connor McMichael, Janne KuokkanenBoris Katchouk, Connor McMichaelJanne Kuokkanen
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
, Ryan Merkley, Ryan Merkley,
Tirs de pénalité
, , , Matt Nieto,
Gardien
#1 : , #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
1Bolt2110000013850000000000021100000138520.50013223500981671555749308898269632016288450.00%8187.50%0752127159.17%47686954.78%862147658.40%1607102012504981048568
2Brawlers2200000013762200000013760000000000041.00013203300981671555759308898269542716298562.50%8450.00%0752127159.17%47686954.78%862147658.40%1607102012504981048568
3Destroyers303000001323-101010000048-420200000915-600.0001324370098167155511693088982691406018434125.00%9722.22%1752127159.17%47686954.78%862147658.40%1607102012504981048568
4Distraction20200000615-91010000036-31010000039-600.0006111700981671555729308898269812520335240.00%5420.00%0752127159.17%47686954.78%862147658.40%1607102012504981048568
5Dynamos22000000197121100000010551100000092741.000193150009816715558193088982694111183810770.00%9366.67%1752127159.17%47686954.78%862147658.40%1607102012504981048568
6Extreme220000001394110000005411100000085341.00013233600981671555829308898269582112418562.50%6266.67%0752127159.17%47686954.78%862147658.40%1607102012504981048568
7Falcons43100000301812110000001046321000002014660.75030487800981671555154930889826910020127816956.25%6183.33%1752127159.17%47686954.78%862147658.40%1607102012504981048568
8Guerriers du Nord43100000301713330000002612141010000045-160.750305181009816715551719308898269121372077201155.00%10640.00%0752127159.17%47686954.78%862147658.40%1607102012504981048568
9Intrepides44000000311417330000002711161100000043181.0003152830098167155518393088982697623146718950.00%7357.14%0752127159.17%47686954.78%862147658.40%1607102012504981048568
10L'Euphorie321000002115611000000743211000001411340.6672134550098167155513293088982697616166514857.14%8362.50%1752127159.17%47686954.78%862147658.40%1607102012504981048568
11Les Restants211000001211100000000000211000001211120.50012193100981671555899308898269632012276350.00%6433.33%0752127159.17%47686954.78%862147658.40%1607102012504981048568
12Monster330000002111102200000014681100000075261.000213859009816715551119308898269942216457571.43%8450.00%0752127159.17%47686954.78%862147658.40%1607102012504981048568
13Monsters4310000028199211000001112-1220000001771060.75028467410981671555166930889826910332166012541.67%8450.00%1752127159.17%47686954.78%862147658.40%1607102012504981048568
14National404000001133-221010000039-630300000824-1600.0001121320098167155516093088982692026145639444.44%10370.00%0752127159.17%47686954.78%862147658.40%1607102012504981048568
15Patriotes30300000821-130000000000030300000821-1300.000815230098167155510193088982691204823508337.50%9366.67%0752127159.17%47686954.78%862147658.40%1607102012504981048568
16Prospects321000002621532100000262150000000000040.6672644700098167155512693088982697620163912975.00%8362.50%1752127159.17%47686954.78%862147658.40%1607102012504981048568
17Senators320010002517822000000201371000100054161.0002541660098167155513593088982698423145317952.94%7271.43%0752127159.17%47686954.78%862147658.40%1607102012504981048568
18Sharks2200000016971100000062411000000107341.00016254100981671555929308898269642510248675.00%5260.00%0752127159.17%47686954.78%862147658.40%1607102012504981048568
19Shokers201000101315-2100000108711010000058-320.50013223500981671555809308898269742618293266.67%9455.56%0752127159.17%47686954.78%862147658.40%1607102012504981048568
20Vikings220000001881000000000000220000001881041.0001829470098167155594930889826959171438151280.00%7442.86%1752127159.17%47686954.78%862147658.40%1607102012504981048568
21Warriors514000002636-10312000001420-6202000001216-420.20026477300981671555195930889826918245468118738.89%19857.89%1752127159.17%47686954.78%862147658.40%1607102012504981048568
22Wildcats2200000013852200000013850000000000041.000132235009816715556993088982694816122910660.00%6266.67%0752127159.17%47686954.78%862147658.40%1607102012504981048568
23Youngblood2200000016106110000007431100000096341.0001627430098167155588930889826946154398787.50%2150.00%0752127159.17%47686954.78%862147658.40%1607102012504981048568
Total6539240101042235270322470001022716364331517010001951896820.631422712113410981671555264693088982692025630408107624413956.97%1807856.67%8752127159.17%47686954.78%862147658.40%1607102012504981048568
_Since Last GM Reset6539240101042235270322470001022716364331517010001951896820.631422712113410981671555264693088982692025630408107624413956.97%1807856.67%8752127159.17%47686954.78%862147658.40%1607102012504981048568
_Vs Conference341914010002221843815114000001088127198100100011410311400.588222371593109816715551377930889826910673402095741347253.73%984653.06%6752127159.17%47686954.78%862147658.40%1607102012504981048568
_Vs Division15107000001038122652000003537-295500000684424200.667103172275109816715556259308898269448125106244613455.74%492353.06%4752127159.17%47686954.78%862147658.40%1607102012504981048568

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
6582W1422712113426462025630408107610
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
6539241010422352
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
322470010227163
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3315171000195189
Derniers 10 matchs
WLOTWOTL SOWSOL
550000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
24413956.97%1807856.67%8
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
9308898269981671555
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
752127159.17%47686954.78%862147658.40%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1607102012504981048568


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
110Warriors2Monkeys 8BWSommaire du match
218Monkeys 8Falcons4AWSommaire du match
428Monkeys 1Patriotes5ALSommaire du match
642Intrepides2Monkeys 9BWSommaire du match
856Warriors10Monkeys 2BLSommaire du match
1069Guerriers du Nord2Monkeys 10BWSommaire du match
1280Monkeys 4Les Restants7ALSommaire du match
1487Monkeys 8Vikings2AWSommaire du match
16102Guerriers du Nord4Monkeys 8BWSommaire du match
18114Monkeys 8Monsters4AWSommaire du match
20128Prospects7Monkeys 9BWSommaire du match
21138Monkeys 4Falcons6ALSommaire du match
22148Brawlers2Monkeys 7BWSommaire du match
24164Monkeys 8Falcons4AWSommaire du match
26170Monkeys 4Patriotes5ALSommaire du match
28183Monsters8Monkeys 6BLSommaire du match
30194Monkeys 2National10ALSommaire du match
31210Monkeys 10Sharks7AWSommaire du match
32213Warriors8Monkeys 4BLSommaire du match
34232Monkeys 4Intrepides3AWSommaire du match
36238Intrepides3Monkeys 8BWSommaire du match
38250Youngblood4Monkeys 7BWSommaire du match
40271Monkeys 8Extreme5AWSommaire du match
42275Monkeys 10L'Euphorie5AWSommaire du match
43287Senators7Monkeys 9BWSommaire du match
44305Monster4Monkeys 6BWSommaire du match
46315Monkeys 10Vikings6AWSommaire du match
48322Monkeys 4L'Euphorie6ALSommaire du match
49333Senators6Monkeys 11BWSommaire du match
51352Monkeys 9Monsters3AWSommaire du match
52355Dynamos5Monkeys 10BWSommaire du match
53371Monkeys 9Youngblood6AWSommaire du match
55384Monsters4Monkeys 5BWSommaire du match
57399Sharks2Monkeys 6BWSommaire du match
60413Monkeys 5Destroyers7ALSommaire du match
61423Monkeys 3Distraction9ALSommaire du match
62432National9Monkeys 3BLSommaire du match
64448Shokers7Monkeys 8BWXXSommaire du match
66460Distraction6Monkeys 3BLSommaire du match
69481Guerriers du Nord6Monkeys 8BWSommaire du match
70488Monkeys 5Warriors6ALSommaire du match
72504Monkeys 4Destroyers8ALSommaire du match
74513Intrepides6Monkeys 10BWSommaire du match
76528Monkeys 5Shokers8ALSommaire du match
77533Monkeys 10Bolt4AWSommaire du match
79543Wildcats4Monkeys 5BWSommaire du match
80555Monkeys 5Senators4AWXSommaire du match
82565Monkeys 3National7ALSommaire du match
83577Monster2Monkeys 8BWSommaire du match
85593Wildcats4Monkeys 8BWSommaire du match
86608Monkeys 7Monster5AWSommaire du match
87617L'Euphorie4Monkeys 7BWSommaire du match
89634Extreme4Monkeys 5BWSommaire du match
90644Monkeys 3National7ALSommaire du match
91655Monkeys 7Warriors10ALSommaire du match
93664Falcons4Monkeys 10BWSommaire du match
94679Monkeys 3Bolt4ALSommaire du match
96689Monkeys 4Guerriers du Nord5ALSommaire du match
98693Monkeys 3Patriotes11ALSommaire du match
99703Brawlers5Monkeys 6BWSommaire du match
100718Destroyers8Monkeys 4BLSommaire du match
102729Monkeys 8Les Restants4AWSommaire du match
103740Prospects5Monkeys 11BWSommaire du match
105757Prospects9Monkeys 6BLSommaire du match
107762Monkeys 9Dynamos2AWSommaire du match
109779Monkeys -Monsters-
110786Bolt-Monkeys -
111797Monkeys -Senators-
112809Falcons-Monkeys -
114824Monkeys -Guerriers du Nord-
115834L'Euphorie-Monkeys -
117853Monkeys -Falcons-
118861Les Restants-Monkeys -
119880Vikings-Monkeys -
120885Monkeys -Brawlers-
122904Patriotes-Monkeys -
125921Patriotes-Monkeys -
126927Monkeys -Dynamos-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
128940Monkeys -Wildcats-
130955Les Restants-Monkeys -
133973Vikings-Monkeys -
134982Monkeys -Prospects-



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
9 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,256,735$ 2,152,916$ 2,152,916$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 1,816,743$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 27 20,022$ 540,594$




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
2Adam Gaudette137153181334102521618389717.06%70277720.27429013282000719568.90%182.4001
3Ryan Poehling20014715730412912426918289116.50%91381319.0741509178426910461.82%111.5935
4Ty Dellandrea16613014727711013528620675317.26%71298617.99405797722241321266.96%101.8602
5Erik Brannstrom131521832351291021901515429.59%196338425.8338661049002253275.00%01.3902

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
3Cayden Primeau4438400.9122.492604401081230700401.0006

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
20236447110132042623119533256010102201269431225003102061051011034267121138007018816532926940101397091909631345126125217368.65%1606658.75%3901136366.10%662105362.87%901137165.72%1642103811864691023579
Total Saison régulière3111861020107422080161546515599430643010557602951568759043121025855170409208035045584335237977462112695431642944063499932317521165040120764553.44%88542152.43%433566593660.07%2698477556.50%4185701059.70%757447506026239451182814
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