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Connexion

Monkeys
GP: 36 | W: 14 | L: 18 | OTL: 4 | P: 32
GF: 200 | GA: 217 | PP%: 56.15% | PK%: 52.48%
DG: Fred Joanis | Morale : 39 | Moyenne d’équipe : 68
Prochains matchs #435 vs Dynamos

Centre de jeu
Monkeys
14-18-4, 32pts
3
FINAL
4 Falcons
22-12-2, 46pts
Team Stats
L1SéquenceW1
7-10-1Fiche domicile11-6-1
7-8-3Fiche domicile11-6-1
3-5-2Derniers 10 matchs8-2-0
5.56Buts par match 5.81
6.03Buts contre par match 4.08
56.15%Pourcentage en avantage numérique53.85%
52.48%Pourcentage en désavantage numérique57.26%
Falcons
22-12-2, 46pts
4
FINAL
2 Monkeys
14-18-4, 32pts
Team Stats
W1SéquenceL1
11-6-1Fiche domicile7-10-1
11-6-1Fiche domicile7-8-3
8-2-0Derniers 10 matchs3-5-2
5.81Buts par match 5.56
4.08Buts contre par match 6.03
53.85%Pourcentage en avantage numérique56.15%
57.26%Pourcentage en désavantage numérique52.48%
Dynamos
30-6-0, 60pts
Jour 70
Monkeys
14-18-4, 32pts
Statistiques d’équipe
W1SéquenceL1
15-3-0Fiche domicile7-10-1
15-3-0Fiche visiteur7-8-3
7-3-010 derniers matchs3-5-2
6.44Buts par match 5.56
3.64Buts contre par match 5.56
67.50%Pourcentage en avantage numérique56.15%
55.28%Pourcentage en désavantage numérique52.48%
Monkeys
14-18-4, 32pts
Jour 72
Distraction
19-15-2, 40pts
Statistiques d’équipe
L1SéquenceW1
7-10-1Fiche domicile10-7-1
7-8-3Fiche visiteur9-8-1
3-5-210 derniers matchs8-2-0
5.56Buts par match 6.31
6.03Buts contre par match 6.31
56.15%Pourcentage en avantage numérique58.27%
52.48%Pourcentage en désavantage numérique51.09%
Monkeys
14-18-4, 32pts
Jour 74
Wildcats
11-23-2, 24pts
Statistiques d’équipe
L1SéquenceL8
7-10-1Fiche domicile5-12-0
7-8-3Fiche visiteur6-11-2
3-5-210 derniers matchs0-9-1
5.56Buts par match 4.53
6.03Buts contre par match 4.53
56.15%Pourcentage en avantage numérique45.97%
52.48%Pourcentage en désavantage numérique46.10%
Meneurs d'équipe
Buts
Philipp Kurashev
34
Passes
Philipp Kurashev
35
Points
Philipp Kurashev
69
Plus/Moins
Connor McMichael
-3
Victoires
Chris Driedger
2
Pourcentage d’arrêts
Chris Driedger
0.9

Statistiques d’équipe
Buts pour
200
5.56 GFG
Tirs pour
1330
36.94 Avg
Pourcentage en avantage numérique
56.2%
73 GF
Début de zone offensive
37.0%
Buts contre
217
6.03 GAA
Tirs contre
1291
35.86 Avg
Pourcentage en désavantage numérique
52.5%%
48 GA
Début de la zone défensive
25.9%
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 actuelle14-18-4 (32PTS)
Historique222-128-14 (0.610%)
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
1Pius SuterXX100.0075539487747875736870768455727604071N02921,975,000$
2Sean KuralyXX99.009367868489756869716771805079780327103221,775,500$
3Connor McMichael (R)XX100.00715691877578907371697774607074036700241925,000$
4Zachary Benson (R)X100.007054899271767973507472775068700486902031,600,000$
5Filip Zadina (R)XX100.007455948777757971506774635673740216802521,825,000$
6Nils Aman (R)X100.00725594907578756658686476506870033670251925,000$
7Lukas Reichel (R)X100.005050505050505050505050505050500184902311,337,500$
8J.J. MoserX99.00825490907688927050746679507075042740251925,000$
9Jacob MiddletonX99.009078807790869269507068805072760427402922,450,000$
10Henri Jokiharju (R)X100.008259938981848568507164775074770487302612,500,000$
11Matt BenningX100.008463798284834065506762835076760407103131,900,000$
12Olen Zellweger (R)X100.00705896927685407150746766506567048690213863,334$
13Ryan Johnson (R)X100.00505050505050505050505050505050048490232925,000$
Rayé
1Philipp Kurashev (R)XXX96.896856939376858681638379665772760347402522,250,000$
MOYENNE D’ÉQUIPE99.5074588482757772685668677252697103868
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 Driedger99.0064595890656865636065646970038640311850,000$
Rayé
MOYENNE D’ÉQUIPE99.006459589065686563606564697003864
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
1Philipp KurashevMonkeys (IDS)C/LW/RW31343569-2116105158175577419.43%1975524.3813243728720003583064.85%8995425031.8301002822
2Zachary BensonMonkeys (IDS)LW36272653-122067291925913514.06%2577821.630443141121182155.10%496233011.3601000232
3Pius SuterMonkeys (IDS)C/LW33232750-15004747125497418.40%1361218.5510132322601124314065.56%4824016021.6301000311
4Sean KuralyMonkeys (IDS)C/LW28211738-20135472895285922.11%2264322.991192022600112572165.43%812526031.1800010321
5Jacob MiddletonMonkeys (IDS)D3282937-34261068408934168.99%5288027.50814222287000458000%01159000.8400002002
6J.J. MoserMonkeys (IDS)D2662834-256042479328446.45%5072027.70515201867000147000%02144000.9400000021
7Henri JokiharjuMonkeys (IDS)D3442933-92027366127376.56%3871721.1144810570221510050.00%81656000.9200000032
8Filip ZadinaMonkeys (IDS)LW/RW22121729-2095331293285612.90%844920.43561112430001121073.08%262915001.2900100032
9Nils AmanMonkeys (IDS)C26151429-13003842101267514.85%1649719.12112160001110074.15%2052318031.1700000112
10Connor McMichaelMonkeys (IDS)C/LW16131225-375281055112223.64%1225916.2166129271012100081.82%11157001.9300001114
11Matt BenningMonkeys (IDS)D3401919-25582064365724250%4774121.810446510000370050.00%2746000.5100211020
12Olen ZellwegerMonkeys (IDS)D3621517-30025304720274.26%2055115.3310125011181025.00%41124000.6200000001
13Lukas ReichelMonkeys (IDS)LW194610-1155154319211819.05%1336619.30123224000010065.45%55011000.5500011001
14Ryan JohnsonMonkeys (IDS)D36358-1222017142110714.29%1854115.0400004000022010%0024000.3000000000
15Jack StudnickaIcedogsC322432015110718.18%14816.1400000000000150.00%1622001.6500000000
16Boris KatchoukIcedogsLW1101-1004154120.00%02121.60000000000110100.00%122000.9300000000
17Gustav OlofssonIcedogsD3000-140113010%23010.290000000000000%01200000000000
Statistiques d’équipe totales ou en moyenne416175281456-22222270603455124440666814.07%356861620.71651021671575853692143214465.80%18393194100121.0603337182021
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)72310.9003.733540022219113000070000
Statistiques d’équipe totales ou en moyenne72310.9003.73354002221911300070000


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$451,020$0$0$No---------------------------
Connor McMichaelMonkeys (IDS)C/LW242001-01-15CANYes180 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm925,000$490,816$0$0$No---------------------------
Filip ZadinaMonkeys (IDS)LW/RW251999-11-27CZEYes189 Lbs6 ft0NoNoFree AgentNoNo22024-03-03FalseFalsePro & Farm1,825,000$968,367$0$0$No1,825,000$--------1,825,000$--------No--------Lien
Henri JokiharjuMonkeys (IDS)D261999-06-17FINYes195 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm2,500,000$1,326,531$0$0$No---------------------------Lien
J.J. MoserMonkeys (IDS)D252000-06-06CHENo173 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm925,000$490,816$0$0$No---------------------------
Jacob MiddletonMonkeys (IDS)D291996-01-02CANNo219 Lbs6 ft3NoNoFree AgentNoNo22024-03-15FalseFalsePro & Farm2,450,000$1,300,000$0$0$No2,450,000$--------2,450,000$--------No--------
Lukas ReichelMonkeys (IDS)LW232002-05-17ALLYes170 Lbs6 ft0NoNoDraftNoNo12025-01-02FalseFalsePro & Farm1,337,500$709,694$0$0$No---------------------------
Matt BenningMonkeys (IDS)D311994-05-25CANNo203 Lbs6 ft1NoNoFree AgentNoNo32024-03-15FalseFalsePro & Farm1,900,000$1,008,163$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$490,816$0$0$No---------------------------
Olen ZellwegerMonkeys (IDS)D212003-09-10CANYes187 Lbs5 ft10NoNoDraftNoNo32025-01-02FalseFalsePro & Farm863,334$458,096$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$1,193,878$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$1,047,959$0$0$No1,975,000$--------1,975,000$--------Yes--------Lien
Ryan JohnsonMonkeys (IDS)D232001-07-24USAYes195 Lbs6 ft1NoNoDraftNoNo22025-01-02FalseFalsePro & Farm925,000$490,816$0$0$No925,000$--------925,000$--------No--------
Sean KuralyMonkeys (IDS)C/LW321993-01-20USANo213 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm1,775,500$942,102$0$0$No1,775,500$--------1,775,500$--------No--------Lien
Zachary BensonMonkeys (IDS)LW202005-05-12CANYes170 Lbs5 ft10NoNoDraftNoNo32025-03-12FalseFalsePro & Farm1,600,000$848,980$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
1525.93190 Lbs6 ft11.801,535,089$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Sean KuralyFilip Zadina40122
2Connor McMichaelPius SuterLukas Reichel30122
3Zachary BensonNils Aman20122
4Lukas ReichelSean 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 KuralyFilip Zadina60122
2Connor McMichaelPius 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
1Sean Kuraly60122
2Pius SuterConnor McMichael40122
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
160122Jacob MiddletonJ.J. Moser60122
2Sean Kuraly40122Henri JokiharjuMatt Benning40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Sean Kuraly60122
2Pius SuterConnor McMichael40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob MiddletonJ.J. Moser60122
2Henri JokiharjuMatt Benning40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Sean KuralyFilip ZadinaJacob MiddletonJ.J. Moser
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Sean KuralyFilip 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
, Sean Kuraly, Pius Suter, Connor McMichael, Zachary Benson
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
1Bolt1100000011290000000000011000000112921.00011162700647066042433453444232147168787.50%10100.00%047775862.93%34453164.78%48775864.25%857497684257625374
2Brawlers11000000862110000008620000000000021.000815230064706604643345344423362215480.00%10100.00%047775862.93%34453164.78%48775864.25%857497684257625374
3Destroyers20200000418-140000000000020200000418-1400.0004812006470660674334534442100381634600.00%330.00%047775862.93%34453164.78%48775864.25%857497684257625374
4Dynamos20100001812-41010000014-31000000178-110.25081321006470660694334534442862319508562.50%7442.86%047775862.93%34453164.78%48775864.25%857497684257625374
5Falcons614001001932-1320200000514-9412001001418-430.2501928470064706602104334534442215683414220735.00%181044.44%047775862.93%34453164.78%48775864.25%857497684257625374
6Guerriers du Nord320001002417721000100171521100000072550.83324406400647066011343345344421003918589555.56%9366.67%047775862.93%34453164.78%48775864.25%857497684257625374
7Intrepides22000000175121100000063311000000112941.00017264300647066091433453444272248287571.43%40100.00%047775862.93%34453164.78%48775864.25%857497684257625374
8L'Euphorie20200000422-1820200000422-180000000000000.0004711006470660714334534442932728426350.00%9544.44%047775862.93%34453164.78%48775864.25%857497684257625374
9Les Restants211000001114-300000000000211000001114-320.500112031006470660714334534442642623378225.00%5260.00%047775862.93%34453164.78%48775864.25%857497684257625374
10Monster22000000198111100000010551100000093641.00019325100647066010043345344423813849141071.43%4175.00%047775862.93%34453164.78%48775864.25%857497684257625374
11Monsters1100000010371100000010370000000000021.00010142400647066038433453444228514236583.33%2150.00%047775862.93%34453164.78%48775864.25%857497684257625374
12National20200000819-1120200000819-110000000000000.000812200064706606343345344421083926317228.57%8625.00%047775862.93%34453164.78%48775864.25%857497684257625374
13Patriotes2020000079-21010000056-11010000023-100.00071219006470660734334534442651719494250.00%7271.43%047775862.93%34453164.78%48775864.25%857497684257625374
14Prospects21100000151231010000078-11100000084420.50015233800647066085433453444256733456583.33%9455.56%247775862.93%34453164.78%48775864.25%857497684257625374
15Sharks1000010045-1000000000001000010045-110.5004610006470660204334534442269223100.00%10100.00%047775862.93%34453164.78%48775864.25%857497684257625374
16Vikings312000001619-3211000001112-11010000057-220.33316274300647066010343345344421174116578675.00%8537.50%147775862.93%34453164.78%48775864.25%857497684257625374
17Warriors2110000015141110000009541010000069-320.500152439006470660684334534442581815427571.43%5260.00%147775862.93%34453164.78%48775864.25%857497684257625374
Total36141800301200217-171871000100101122-2118780020199954320.4442003235230064706601330433453444212914142887471307356.15%1014852.48%447775862.93%34453164.78%48775864.25%857497684257625374
_Since Last GM Reset36141800301200217-171871000100101122-2118780020199954320.4442003235230064706601330433453444212914142887471307356.15%1014852.48%447775862.93%34453164.78%48775864.25%857497684257625374
_Vs Conference2481300201122144-22115500100666511338001015679-23190.3961222013230064706608584334534442866281176513814150.62%653250.77%247775862.93%34453164.78%48775864.25%857497684257625374
_Vs Division1068002006062-25330010031247535001002938-9140.7006098158006470660349433453444235311387209372362.16%271448.15%247775862.93%34453164.78%48775864.25%857497684257625374

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
3632L12003235231330129141428874700
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
3614180301200217
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
187100100101122
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
187802019995
Derniers 10 matchs
WLOTWOTL SOWSOL
350200
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1307356.15%1014852.48%4
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
43345344426470660
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
47775862.93%34453164.78%48775864.25%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
857497684257625374


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 1Falcons3LSommaire du match
22141L'Euphorie12Monkeys 2LSommaire du match
24153Falcons10Monkeys 3LSommaire du match
27168Monkeys 2Falcons7LSommaire du match
28178Vikings8Monkeys 5LSommaire du match
30192Monkeys 7Dynamos8LXXSommaire du match
32203Monkeys 8Prospects4WSommaire du match
34205Brawlers6Monkeys 8WSommaire du match
37228Monkeys 8Falcons4WSommaire du match
38234Patriotes6Monkeys 5LSommaire du match
40246Monkeys 11Intrepides2WSommaire du match
42259Intrepides3Monkeys 6WSommaire du match
44268Dynamos4Monkeys 1LSommaire du match
47286Monkeys 11Bolt2WSommaire du match
49300Guerriers du Nord7Monkeys 10WSommaire du match
50305Monkeys 1Destroyers9LSommaire du match
52316Monkeys 1Les Restants8LSommaire du match
54334Prospects8Monkeys 7LSommaire du match
56342Monkeys 4Sharks5LXSommaire du match
58356Monster5Monkeys 10WSommaire du match
60368Monkeys 9Monster3WSommaire du match
62378National11Monkeys 3LSommaire du match
64392Monsters3Monkeys 10WSommaire du match
65401Monkeys 2Patriotes3LSommaire du match
67415Monkeys 3Falcons4LXSommaire du match
69421Falcons4Monkeys 2LSommaire du match
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
23 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,270,973$ 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$ 1,012,807$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 78 19,406$ 1,513,668$




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 Gaudette18821626147716912301243122417.65%97384620.46631181811121231328668.24%272.4802
2Micheal Ferland20515222838015725128616481318.70%126370318.075494148915161021862.36%122.0514
3Ty Dellandrea19216218634814315732925891217.76%88355118.505171122902241427465.60%141.9602
4Ryan Poehling20014715730412912426918289116.50%91381319.0741509178426910461.82%111.5935
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 Daws3130100.9182.5018512077938440501.0005

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
202436141800301200217-171871000100101122-2118780020199954322003235230064706601330433453444212914142887471307356.15%1014852.48%447775862.93%34453164.78%48775864.25%857497684257625374
Total Saison régulière36420812801010442379193244718211058065301203932271182987004514117610001764582379400063793360790885021146144930494347175611727376525216024140475453.70%104249552.50%494207698860.20%3158552057.21%4897818459.84%881354777075279260223332
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