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Connexion

Monkeys
GP: 10 | W: 4 | L: 5 | OTL: 1 | P: 9
GF: 60 | GA: 68 | PP%: 48.28% | PK%: 50.00%
DG: Fred Joanis | Morale : 47 | Moyenne d’équipe : 68
Prochains matchs #126 vs Falcons

Centre de jeu
Monkeys
4-5-1, 9pts
6
FINAL
9 Warriors
3-6-1, 7pts
Team Stats
L2SéquenceL1
2-2-1Fiche domicile3-2-0
2-3-0Fiche domicile0-4-1
4-5-1Derniers 10 matchs3-6-1
6.00Buts par match 4.70
6.80Buts contre par match 7.40
48.28%Pourcentage en avantage numérique51.61%
50.00%Pourcentage en désavantage numérique35.71%
L'Euphorie
10-0-0, 20pts
10
FINAL
2 Monkeys
4-5-1, 9pts
Team Stats
W10SéquenceL2
5-0-0Fiche domicile2-2-1
5-0-0Fiche domicile2-3-0
10-0-0Derniers 10 matchs4-5-1
6.80Buts par match 6.00
2.20Buts contre par match 6.80
66.67%Pourcentage en avantage numérique48.28%
75.00%Pourcentage en désavantage numérique50.00%
Monkeys
4-5-1, 9pts
Jour 20
Falcons
8-2-0, 16pts
Statistiques d’équipe
L2SéquenceW6
2-2-1Fiche domicile3-2-0
2-3-0Fiche visiteur5-0-0
4-5-110 derniers matchs8-2-0
6.00Buts par match 6.80
6.80Buts contre par match 6.80
48.28%Pourcentage en avantage numérique63.64%
50.00%Pourcentage en désavantage numérique53.49%
L'Euphorie
10-0-0, 20pts
Jour 22
Monkeys
4-5-1, 9pts
Statistiques d’équipe
W10SéquenceL2
5-0-0Fiche domicile2-2-1
5-0-0Fiche visiteur2-3-0
10-0-010 derniers matchs4-5-1
6.80Buts par match 6.00
2.20Buts contre par match 6.00
66.67%Pourcentage en avantage numérique48.28%
75.00%Pourcentage en désavantage numérique50.00%
Falcons
8-2-0, 16pts
Jour 24
Monkeys
4-5-1, 9pts
Statistiques d’équipe
W6SéquenceL2
3-2-0Fiche domicile2-2-1
5-0-0Fiche visiteur2-3-0
8-2-010 derniers matchs4-5-1
6.80Buts par match 6.00
4.00Buts contre par match 6.00
63.64%Pourcentage en avantage numérique48.28%
53.49%Pourcentage en désavantage numérique50.00%
Meneurs d'équipe
Buts
Zachary Benson
10
Passes
Filip Zadina
14
Points
Filip Zadina
21
Plus/Moins
Pius Suter
3

Statistiques d’équipe
Buts pour
60
6.00 GFG
Tirs pour
355
35.50 Avg
Pourcentage en avantage numérique
48.3%
14 GF
Début de zone offensive
31.3%
Buts contre
68
6.80 GAA
Tirs contre
368
36.80 Avg
Pourcentage en désavantage numérique
50.0%%
15 GA
Début de la zone défensive
25.0%
Informations de l'équipe

Directeur généralFred Joanis
EntraîneurD.J. Smith
DivisionBourque
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro15
Équipe Mineure18
Limite contact 33 / 55
Espoirs32


Historique d'équipe

Saison actuelle4-5-1 (9PTS)
Historique212-115-13 (0.624%)
Apparitions en séries éliminatoires 4
Historique en séries éliminatoires (W-L)15 - 18 (0.455%)
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
1Philipp Kurashev (R)XXX99.006856939376858681638379665772760427402522,250,000$
2Pius SuterXX100.0075539487747875736870768455727604271N02921,975,000$
3Sean KuralyXX99.009367868489756869716771805079780507103221,775,500$
4Zachary Benson (R)X99.007054899271767973507472775068700506902031,600,000$
5Filip Zadina (R)XX100.007455948777757971506774635673740506802521,825,000$
6Nils Aman (R)X100.00725594907578756658686476506870050670251925,000$
7Lukas Reichel (R)X99.005050505050505050505050505050500434902311,337,500$
8J.J. MoserX100.00825490907688927050746679507075042740241925,000$
9Jacob MiddletonX99.009078807790869269507068805072760437402922,450,000$
10Henri Jokiharju (R)X100.008259938981848568507164775074770507302512,500,000$
11Matt BenningX100.008463798284834065506762835076760537103131,900,000$
12Olen Zellweger (R)X100.00705896927685407150746766506567050690213863,334$
13Ryan Johnson (R)X100.00505050505050505050505050505050050490232925,000$
Rayé
1Connor McMichael (R)XX100.00715691877578907371697774607074034700241925,000$
MOYENNE D’ÉQUIPE99.6474588482757772685668677252697104668
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
Rayé
1Chris Driedger100.0064595890656865636065646970043640311850,000$
MOYENNE D’ÉQUIPE100.006459589065686563606564697004364
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
D.J. Smith88798487747099CAN473550,000$


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
1Filip ZadinaMonkeys (IDS)LW/RW1071421-32011553142313.21%420820.87246317000041066.67%6128002.0100000022
2Pius SuterMonkeys (IDS)C/LW7711183009730141323.33%312317.60325413112472064.04%8943012.9200000201
3Sean KuralyMonkeys (IDS)C/LW109817-74018114492120.45%823123.114377170001220071.79%391116011.4700000200
4Zachary BensonMonkeys (IDS)LW1010717-20012748163720.83%920320.3502208000060080.00%101810001.6700000201
5Philipp KurashevMonkeys (IDS)C/LW/RW77815-52071634181020.59%316223.202353120000150068.93%206810001.8500000110
6Nils AmanMonkeys (IDS)C103912-7001413366228.33%718718.7601103000150078.57%981110001.2800000010
7Jacob MiddletonMonkeys (IDS)D81910-300131113617.69%1621627.05145320000215000%0318000.9200000000
8Matt BenningMonkeys (IDS)D10077-11359714570%1318518.510000800009000%0214000.7600100020
9Henri JokiharjuMonkeys (IDS)D8077-20061210490%716720.97011010022110000%0014000.8300000011
10Lukas ReichelMonkeys (IDS)LW10426330101710100840.00%418418.45101212000000077.78%907000.6500010001
11J.J. MoserMonkeys (IDS)D4044-420455140%1310827.170110900006000%018000.7400000000
12Jack StudnickaIcedogsC322432015110718.18%14816.1400000000000150.00%1622001.6500000000
13Olen ZellwegerMonkeys (IDS)D10044-6005781240%715415.4000000000030050.00%207000.5200000000
14Connor McMichaelMonkeys (IDS)C/LW22132001150140.00%12010.20000001011100100.00%123002.9400000001
15Boris KatchoukIcedogsLW1101-1004154120.00%02121.60000000000110100.00%122000.9300000000
16Ryan JohnsonMonkeys (IDS)D10011-1180233120%313013.040000100003000%007000.1500000000
17Gustav OlofssonIcedogsD3000-140113010%23010.290000000000000%01200000000000
Statistiques d’équipe totales ou en moyenne1235394147-42671513412233211017115.96%101238419.3913213422137235101134170.02%47777141021.2300110777
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)10001.0000130001311000010000
Statistiques d’équipe totales ou en moyenne10001.0000.0013000131100010000


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 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 restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 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
Chris DriedgerMonkeys (IDS)G311994-05-18CANNo208 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm850,000$745,918$0$0$No---------------------------
Connor McMichaelMonkeys (IDS)C/LW242001-01-15CANYes180 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm925,000$811,735$0$0$No---------------------------
Filip ZadinaMonkeys (IDS)LW/RW251999-11-27CZEYes189 Lbs6 ft0NoNoFree AgentNoNo22024-03-03FalseFalsePro & Farm1,825,000$1,601,531$0$0$No1,825,000$--------1,825,000$--------No--------Lien
Henri JokiharjuMonkeys (IDS)D251999-06-17FINYes195 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm2,500,000$2,193,878$0$0$No---------------------------Lien
J.J. MoserMonkeys (IDS)D242000-06-06CHENo173 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm925,000$811,735$0$0$No---------------------------
Jacob MiddletonMonkeys (IDS)D291996-01-02CANNo219 Lbs6 ft3NoNoFree AgentNoNo22024-03-15FalseFalsePro & Farm2,450,000$2,150,000$0$0$No2,450,000$--------2,450,000$--------No--------
Lukas ReichelMonkeys (IDS)LW232002-05-17ALLYes170 Lbs6 ft0NoNoDraftNoNo12025-01-02FalseFalsePro & Farm1,337,500$1,173,724$0$0$No---------------------------
Matt BenningMonkeys (IDS)D311994-05-25CANNo203 Lbs6 ft1NoNoFree AgentNoNo32024-03-15FalseFalsePro & Farm1,900,000$1,667,347$0$0$No1,900,000$1,900,000$-------1,900,000$1,900,000$-------NoNo-------Lien
Nils AmanMonkeys (IDS)C252000-02-07SUÈYes179 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm925,000$811,735$0$0$No---------------------------
Olen ZellwegerMonkeys (IDS)D212003-09-10CANYes187 Lbs5 ft10NoNoDraftNoNo32025-01-02FalseFalsePro & Farm863,334$757,620$0$0$No863,334$863,334$-------863,334$863,334$-------NoNo-------
Philipp KurashevMonkeys (IDS)C/LW/RW251999-10-12SUIYes190 Lbs6 ft0NoNoFree AgentNoNo22025-04-11FalseFalsePro & Farm2,250,000$1,974,490$0$0$No2,250,000$--------2,250,000$--------No--------Lien
Pius SuterMonkeys (IDS)C/LW291996-05-24SUINo174 Lbs5 ft11YesNoFree AgentNoNo22025-04-21FalseFalsePro & Farm1,975,000$1,733,163$0$0$No1,975,000$--------1,975,000$--------Yes--------Lien
Ryan JohnsonMonkeys (IDS)D232001-07-24USAYes195 Lbs6 ft1NoNoDraftNoNo22025-01-02FalseFalsePro & Farm925,000$811,735$0$0$No925,000$--------925,000$--------No--------
Sean KuralyMonkeys (IDS)C/LW321993-01-20USANo213 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm1,775,500$1,558,092$0$0$No1,775,500$--------1,775,500$--------No--------Lien
Zachary BensonMonkeys (IDS)LW202005-05-12CANYes170 Lbs5 ft10NoNoDraftNoNo32025-03-12FalseFalsePro & Farm1,600,000$1,404,082$0$0$No1,600,000$1,600,000$-------1,600,000$1,600,000$-------NoNo-------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
1525.80190 Lbs6 ft11.801,535,089$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Sean KuralyPhilipp KurashevFilip Zadina40122
2Pius SuterLukas Reichel30122
3Zachary BensonNils Aman20122
4Lukas ReichelPhilipp KurashevSean Kuraly10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob MiddletonJ.J. Moser40122
2Henri JokiharjuMatt Benning30122
3Olen ZellwegerRyan Johnson20122
4Jacob MiddletonJ.J. Moser10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Sean KuralyPhilipp KurashevFilip Zadina60122
2Pius SuterLukas Reichel40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob MiddletonJ.J. Moser60122
2Henri JokiharjuMatt Benning40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Philipp KurashevSean Kuraly60122
2Pius Suter40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob MiddletonJ.J. Moser60122
2Henri JokiharjuMatt Benning40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Philipp Kurashev60122Jacob MiddletonJ.J. Moser60122
2Sean Kuraly40122Henri JokiharjuMatt Benning40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Philipp KurashevSean Kuraly60122
2Pius Suter40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob MiddletonJ.J. Moser60122
2Henri JokiharjuMatt Benning40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Sean KuralyPhilipp KurashevFilip ZadinaJacob MiddletonJ.J. Moser
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Sean KuralyPhilipp KurashevFilip ZadinaJacob MiddletonJ.J. Moser
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Zachary Benson, Nils Aman, Filip ZadinaZachary Benson, Nils AmanFilip Zadina
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Olen Zellweger, Ryan Johnson, Henri JokiharjuOlen ZellwegerRyan Johnson, Henri Jokiharju
Tirs de pénalité
Philipp Kurashev, Sean Kuraly, Pius Suter, , Zachary Benson
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
1Destroyers1010000039-6000000000001010000039-600.0003690018222002311512711305723414300.00%220.00%011516669.28%9713372.93%15323265.95%23513319568170105
2Guerriers du Nord21000100141041000010078-11100000072530.750142135001822200761151271130552012405240.00%6183.33%011516669.28%9713372.93%15323265.95%23513319568170105
3L'Euphorie10100000210-810100000210-80000000000000.000246001822200411151271130441117173266.67%6350.00%011516669.28%9713372.93%15323265.95%23513319568170105
4Les Restants1100000010640000000000011000000106421.000101929001822200491151271130332219113133.33%3233.33%011516669.28%9713372.93%15323265.95%23513319568170105
5National1010000058-31010000058-30000000000000.000581300182220038115127113052176184125.00%3166.67%011516669.28%9713372.93%15323265.95%23513319568170105
6Vikings2110000011110110000006421010000057-220.500112132001822200601151271130692010284375.00%5420.00%111516669.28%9713372.93%15323265.95%23513319568170105
7Warriors2110000015141110000009541010000069-320.500152439001822200681151271130581815427571.43%5260.00%111516669.28%9713372.93%15323265.95%23513319568170105
Total1045001006068-8522001002935-6523000003133-290.45060103163001822200355115127113036813183170291448.28%301550.00%211516669.28%9713372.93%15323265.95%23513319568170105
_Since Last GM Reset1045001006068-8522001002935-6523000003133-290.45060103163001822200355115127113036813183170291448.28%301550.00%211516669.28%9713372.93%15323265.95%23513319568170105
_Vs Conference84300100535033200010022175523000003133-290.5635391144001822200276115127113027210360135221150.00%211147.62%211516669.28%9713372.93%15323265.95%23513319568170105
_Vs Division5420010036315220001001596322000002122-190.9003664100001822200177115127113016060448114964.29%13838.46%211516669.28%9713372.93%15323265.95%23513319568170105

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
109L2601031633553681318317000
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
104501006068
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
52201002935
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
52300003133
Derniers 10 matchs
WLOTWOTL SOWSOL
450100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
291448.28%301550.00%2
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
11512711301822200
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
11516669.28%9713372.93%15323265.95%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
23513319568170105


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
111Guerriers du Nord8Monkeys 7LXSommaire du match
323Monkeys 10Les Restants6WSommaire du match
430Vikings4Monkeys 6WSommaire du match
642Monkeys 5Vikings7LSommaire du match
858Warriors5Monkeys 9WSommaire du match
1171National8Monkeys 5LSommaire du match
1382Monkeys 3Destroyers9LSommaire du match
1492Monkeys 7Guerriers du Nord2WSommaire du match
16102Monkeys 6Warriors9LSommaire du match
18110L'Euphorie10Monkeys 2LSommaire du match
20126Monkeys -Falcons-
22141L'Euphorie-Monkeys -
24153Falcons-Monkeys -
27168Monkeys -Falcons-
28178Vikings-Monkeys -
30192Monkeys -Dynamos-
32203Monkeys -Prospects-
34205Brawlers-Monkeys -
37228Monkeys -Falcons-
38234Patriotes-Monkeys -
40246Monkeys -Intrepides-
42259Intrepides-Monkeys -
44268Dynamos-Monkeys -
47286Monkeys -Bolt-
49300Guerriers du Nord-Monkeys -
50305Monkeys -Destroyers-
52316Monkeys -Les Restants-
54334Prospects-Monkeys -
56342Monkeys -Sharks-
58356Monster-Monkeys -
60368Monkeys -Monster-
62378National-Monkeys -
64392Monsters-Monkeys -
65401Monkeys -Patriotes-
67415Monkeys -Falcons-
69421Falcons-Monkeys -
70435Dynamos-Monkeys -
72450Monkeys -Distraction-
74458Monkeys -Wildcats-
76469Monkeys -Destroyers-
78480Prospects-Monkeys -
80498Warriors-Monkeys -
82513Guerriers du Nord-Monkeys -
83525Les Restants-Monkeys -
85534Monkeys -Youngblood-
86549Monkeys -Guerriers du Nord-
88559Monkeys -Youngblood-
90570Les Restants-Monkeys -
91579Monkeys -Monsters-
93595Warriors-Monkeys -
94607Shokers-Monkeys -
96618Monkeys -Les Restants-
99636Wildcats-Monkeys -
100649Senators-Monkeys -
102662Monkeys -Monsters-
103677Vikings-Monkeys -
105687Monkeys -Monsters-
107696Monkeys -National-
108708Wildcats-Monkeys -
110725National-Monkeys -
112738Monkeys -Warriors-
113749Les Restants-Monkeys -
115762Monkeys -Intrepides-
116768Monkeys -Vikings-
117778Vikings-Monkeys -
119791Monkeys -Vikings-
120803Sharks-Monkeys -
122815Monkeys -Brawlers-
123827Monsters-Monkeys -
125841Monkeys -Guerriers du Nord-
126850Falcons-Monkeys -
128863Monkeys -Warriors-
129872Monkeys -L'Euphorie-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
130882Senators-Monkeys -
131894Monkeys -Brawlers-
133903Brawlers-Monkeys -
135919Monkeys -Senators-
136926Monkeys -Extreme-
137935Destroyers-Monkeys -
141954L'Euphorie-Monkeys -
144971L'Euphorie-Monkeys -
145982Monkeys -Patriotes-



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
36 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
326,701$ 2,302,633$ 2,302,633$ 550,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 259,358$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 129 19,406$ 2,503,374$




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
1Adam Gaudette16319423242614412263208108017.96%83334220.51561061621001011124569.65%252.5501
2Micheal Ferland20515222838015725128616481318.70%126370318.075494148915161021862.36%122.0514
3Ryan Poehling20014715730412912426918289116.50%91381319.0741509178426910461.82%111.5935
4Ty Dellandrea17613715729411614830421980517.02%79318818.124160101742241323366.17%111.8402
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
2Cayden Primeau6054400.9152.313564441371606920501.0006
3Cory Schneider6052330.9093.1535468218620331046400.66715
4Nico Daws66000.9232.503600015196960000

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
2020824236031005745155941211702100268241274121190100030627432915749601534001542181993346712271137109852739874587114629914749.16%25314443.08%13896155057.81%631114155.30%1169201058.16%1952127316676681307655
202182581404330545320225413050312028215612641289012102631649913354592214671214319520083266107111061081172639837565130230217959.27%24610059.35%15822150254.73%858158854.03%964174055.40%1940120316416471363741
2022824728023025394281114124140120027820078412314011022612283310353991014491112821719253316108811621058182529834556151636218049.72%2069951.94%71096161367.95%733117762.28%1190178466.70%2074125314665791399849
2023824732010115214526941281200010274213614119200100124723989952188514061011820819353235111110851036142529806525131331117556.27%23610455.93%10916156558.53%592108354.66%1087189257.45%1988124916156381326712
20241045001006068-8522001002935-6523000003133-2960103163001822200355115127113036813183170291448.28%301550.00%211516669.28%9713372.93%15323265.95%23513319568170105
Total Saison régulière338198115010843223917834561691055006530113184528616993650431311089381704352239378060193356186080421136394612461743865410804348223165447130369553.34%97146252.42%473845639660.12%2911512256.83%4563765859.58%819151136586260255683063
Séries éliminatoires
2020514000002536-1120200000818-10312000001718-122546710051460144574740022062406115640.00%201240.00%1266838.24%419941.41%4210838.89%9659126447634
20211055000005567-12624000002842-144310000027252105594149009242112687910286137012662125241250.00%331942.42%17812462.90%7918143.65%13324354.73%1931122419016579
20221495000001079017752000005842167430000049481181071732800030443216241962192072491157119242634469.84%462447.83%619731362.94%11219158.64%19731861.95%36423625591220131
202340400000730-2320200000419-1520200000311-8071219001510120345036018281404212541.67%151126.67%0437855.13%357646.05%419145.05%7143107356026
Total Séries éliminatoires33151800000194223-29177100000098121-2316880000096102-6301943255190045876021156366418369312634262614701146758.77%1146642.11%834458359.01%26754748.81%41376054.34%725451731262524271

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 Dellandrea423744812434576019618.88%2575517.981414282920251160.31%22.1400
4Adam Gaudette2530316165412917617.05%1347619.061016261300012059.30%22.5600
5Valeri Nichushkin23282957139402512222.95%1145819.9598172100011071.77%22.4900

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