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Connexion

Snowbirds
GP: 42 | W: 19 | L: 20 | OTL: 3 | P: 41
GF: 126 | GA: 133 | PP%: 11.39% | PK%: 78.33%
DG: Matthew Gagne | Morale : 90 | Moyenne d’équipe : 58
Prochains matchs #664 vs Smirnoff Ice

Centre de jeu
Snowbirds
19-20-3, 41pts		1
Sommaire du match
 3 Igloos
23-15-3, 49pts
Team Stats
L3SéquenceW2
11-9-1Fiche domicile14-6-1
8-11-2Fiche domicile9-9-2
4-5-1Derniers 10 matchs6-2-2
3.00Buts par match 3.76
3.17Buts contre par match 3.12
11.39%Pourcentage en avantage numérique18.75%
78.33%Pourcentage en désavantage numérique83.84%
Grizzlies
25-14-4, 54pts		6
Sommaire du match
 2 Snowbirds
19-20-3, 41pts
Team Stats
W1SéquenceL3
12-6-2Fiche domicile11-9-1
13-8-2Fiche domicile8-11-2
5-4-1Derniers 10 matchs4-5-1
3.79Buts par match 3.00
3.21Buts contre par match 3.17
19.38%Pourcentage en avantage numérique11.39%
83.19%Pourcentage en désavantage numérique78.33%
Smirnoff Ice
18-21-3, 39pts
Jour 53
 Snowbirds
19-20-3, 41pts
Statistiques d’équipe
W3SéquenceL3
7-12-1Fiche domicile11-9-1
11-9-2Fiche visiteur8-11-2
6-4-010 derniers matchs4-5-1
2.05Buts par match 3.00
2.83Buts contre par match 3.00
12.22%Pourcentage en avantage numérique11.39%
83.46%Pourcentage en désavantage numérique78.33%
Snowbirds
19-20-3, 41pts
Jour 54
 Hunters
22-17-4, 48pts
Statistiques d’équipe
L3SéquenceL2
11-9-1Fiche domicile11-6-3
8-11-2Fiche visiteur11-11-1
4-5-110 derniers matchs4-6-0
3.00Buts par match 3.47
3.17Buts contre par match 3.47
11.39%Pourcentage en avantage numérique14.90%
78.33%Pourcentage en désavantage numérique86.21%
Marlies
19-19-4, 42pts
Jour 55
 Snowbirds
19-20-3, 41pts
Statistiques d’équipe
L1SéquenceL3
9-8-3Fiche domicile11-9-1
10-11-1Fiche visiteur8-11-2
7-3-010 derniers matchs4-5-1
3.19Buts par match 3.00
3.48Buts contre par match 3.00
16.16%Pourcentage en avantage numérique11.39%
81.96%Pourcentage en désavantage numérique78.33%
Meneurs d'équipe
Oliver KylingtonButs
Oliver Kylington
4		 Oliver KylingtonPasses
Oliver Kylington
5
Oliver KylingtonPoints
Oliver Kylington
9		 Jeremy DaviesPlus/Moins
Jeremy Davies
5
Connor IngramVictoires
Connor Ingram
5		 Nico DawsPourcentage d’arrêts
Nico Daws
0.915

Statistiques d’équipe
Buts pour
126
3.00 GFG		 Tirs pour
1341
31.93 Avg		 Pourcentage en avantage numérique
11.4%
23 GF		 Début de zone offensive
39.7%
Buts contre
133
3.17 GAA		 Tirs contre
1429
34.02 Avg		 Pourcentage en désavantage numérique
78.3%%
44 GA		 Début de la zone défensive
42.4%
Informations de l'équipe

Directeur généralMatthew Gagne
EntraîneurJeff Blashill
DivisionDivision Est
ConférenceConference 2
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité5,000
Assistance4,988
Billets de saison2,000


Informations de la formation

Équipe Pro13
Équipe Mineure19
Limite Contrat32 / 50
Espoirs16


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
1Ivan Miroshnichenko (R)X100.00784595815950405330525455668168090560212950,000$
2Filip Hallander (R)X100.00504595776050404530405055508269090520251775,000$
3Oliver KylingtonX100.00504584835151405630565669678775090610281775,000$
4Jeremy DaviesX100.00504595786050404530405055508673090560283775,000$
5Reilly Walsh (R)X100.00504595786050404530405055508471090560262775,000$
Rayé
1Ivan Demidov (R)X100.005045957862694049304454595079700905501951,200,000$
2Jonathan ToewsX100.005045958660504045304050555094890905403742,000,000$
3Quinn Hutson (R)X72.81504592804767404530405055508373090530235800,000$
4John St. Ivany (R)X100.00904872757068404730445085508575090650262800,000$
5Simon Nemec (R)X100.005045818056624053304659626681700905902121,200,000$
6Alec RegulaX100.00504595746050404530405055508273090550252775,000$
MOYENNE D’ÉQUIPE97.4556459079595640483044526054847309057
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
1Connor Ingram100.00725675917371717273727087790906402831,600,000$
2Nico Daws (R)92.00705060897070707070707184720906202411,000,000$
MOYENNE D’ÉQUIPE96.007153689072717171727171867609063
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jeff Blashill65656565847872CAN5321,000,000$


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
1Oliver KylingtonSnowbirds (MIA)D18459-980132628102614.29%1837720.99314183700012601100.00%100000.4800000221
2Jeremy DaviesSnowbirds (MIA)D42358528048203510218.57%2956013.35000040000121033.33%2400000.2903000243
3Quinn HutsonSnowbirds (MIA)RW1823512018191451014.29%323613.131124480001310143.24%11100000.4201000023
4John St. IvanySnowbirds (MIA)D10044-41002019166140%1419619.630001531000024000%100000.4100000110
5Alec RegulaSnowbirds (MIA)D170444401115102110%728516.800001440000130038.85%13900000.2800000112
6Ivan DemidovSnowbirds (MIA)RW11224-3005182611197.69%123121.091015450001340027.27%2200000.3402000100
7Reilly WalshSnowbirds (MIA)D18123-61202715146127.14%1630817.1400028000061080.00%500000.1900000220
8Jeremy LauzonMiami HeatD5112-1100246901211.11%912525.1200041800009000%000000.3200000100
9Jonathan ToewsSnowbirds (MIA)C5101-12021381412.50%09619.34000420000080046.00%10000000.2111000000
10Simon NemecSnowbirds (MIA)D4011240831330%47318.41000113000010000%000000.2700000000
11Beck MalenstynMiami HeatLW1000000704220%01717.9500012000040020.00%100000000000001
Statistiques d’équipe totales ou en moyenne149142741-12800183154165561348.48%101251016.855275527400031822240.92%41300000.3317000101210
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
1Connor IngramSnowbirds (MIA)135710.8923.5768900413790200.6005130213
2Nico DawsSnowbirds (MIA)82300.9153.01399212023400000518312
Statistiques d’équipe totales ou en moyenne2171010.9003.361088216161302051818525


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 ParDate de la Dernière TransactionBallotage forcé Waiver Possible Contrat Date du Signature du ContratForcer 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
Alec RegulaSnowbirds (MIA)D252000-08-06USANo208 Lbs6 ft4NoNoN/ANoNo22026-03-08FalseFalsePro & Farm775,000$409,028$0$0$No775,000$--------775,000$--------No--------Lien NHL
Connor IngramSnowbirds (MIA)G281997-03-31CANNo196 Lbs6 ft2NoNoN/ANoNo32026-03-08FalseFalsePro & Farm1,600,000$844,444$0$0$No1,600,000$1,600,000$-------1,600,000$1,600,000$-------NoNo-------Lien NHL
Filip HallanderSnowbirds (MIA)C252000-06-29SWEYes190 Lbs6 ft1NoNoN/ANoNo12026-03-08FalseFalsePro & Farm775,000$409,028$0$0$No---------------------------
Ivan DemidovSnowbirds (MIA)RW192005-12-10CANYes192 Lbs6 ft1NoNoDraftNoNo52026-03-08FalseFalsePro & Farm1,200,000$633,333$0$0$No1,200,000$1,200,000$1,200,000$1,200,000$-----1,200,000$1,200,000$1,200,000$1,200,000$-----NoNoNoNo-----Lien NHL
Ivan MiroshnichenkoSnowbirds (MIA)LW212004-02-04RUSYes185 Lbs6 ft1NoNoN/ANoNo22026-03-08FalseFalsePro & Farm950,000$501,389$0$0$No950,000$--------950,000$--------No--------Lien NHL
Jeremy DaviesSnowbirds (MIA)D281996-12-04CANNo180 Lbs5 ft11NoNoN/ANoNo32026-03-08FalseFalsePro & Farm775,000$409,028$0$0$No775,000$775,000$-------775,000$775,000$-------NoNo-------Lien NHL
John St. IvanySnowbirds (MIA)D261999-07-22USAYes198 Lbs6 ft3NoNoN/ANoNo22026-03-08FalseFalsePro & Farm800,000$422,222$0$0$No800,000$--------800,000$--------No--------
Jonathan ToewsSnowbirds (MIA)C371988-04-29CANNo201 Lbs6 ft2NoNoTrade2025-07-03NoNo42026-03-08FalseFalsePro & Farm2,000,000$1,055,556$0$0$No2,000,000$2,000,000$2,000,000$------2,000,000$2,000,000$2,000,000$------NoNoNo------
Nico DawsSnowbirds (MIA)G242000-12-22DEUYes205 Lbs6 ft4NoNoTrade2025-01-18NoNo12026-03-08FalseFalsePro & Farm1,000,000$527,778$0$0$No---------------------------Lien NHL
Oliver KylingtonSnowbirds (MIA)D281997-05-19SWENo183 Lbs6 ft0NoNoN/ANoNo12026-03-08FalseFalsePro & Farm775,000$409,028$0$0$No---------------------------Lien NHL
Quinn Hutson (sur la masse salariale)Snowbirds (MIA)RW232002-01-01USAYes170 Lbs5 ft11NoNoProspectNoNo52026-03-08FalseFalsePro & Farm800,000$422,222$0$0$Yes800,000$800,000$800,000$800,000$-----800,000$800,000$800,000$800,000$-----NoNoNoNo-----Lien NHL
Reilly WalshSnowbirds (MIA)D261999-04-21USAYes185 Lbs6 ft0NoNoN/ANoNo22026-03-08FalseFalsePro & Farm775,000$409,028$0$0$No775,000$--------775,000$--------No--------Lien NHL
Simon NemecSnowbirds (MIA)D212004-02-15SLKYes190 Lbs6 ft1NoNoN/ANoNo22026-03-08FalseFalsePro & Farm1,200,000$633,333$0$0$No1,200,000$--------1,200,000$--------No--------Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
1325.46191 Lbs6 ft12.541,032,692$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
135122
230122
325122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
135122
2Oliver Kylington30122
3Reilly WalshJeremy Davies25122
410122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
155122
245122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
155122
2Oliver Kylington45122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
155122
245122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
155122
2Oliver Kylington45122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
15512255122
245122Oliver Kylington45122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
155122
245122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
155122
2Oliver Kylington45122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, , ,
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Reilly Walsh, Jeremy Davies, Reilly WalshJeremy Davies,
Tirs de pénalité
, , , ,
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
TotalDomicile Visiteur
# 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 RI
1Bandits30300000613-72020000049-51010000024-200.0006101600523537210243343945327823130781516.67%15660.00%0713141050.57%727150648.27%31463749.29%10237361033286487242
2Barracudas1010000016-51010000016-50000000000000.0001230052353722443343945327401324224125.00%11281.82%0713141050.57%727150648.27%31463749.29%10237361033286487242
3Bayou1010000046-2000000000001010000046-200.00048120052353723043343945327431014316116.67%7271.43%0713141050.57%727150648.27%31463749.29%10237361033286487242
4Chiwawa11000000321110000003210000000000021.0003690052353723443343945327381318293133.33%8275.00%0713141050.57%727150648.27%31463749.29%10237361033286487242
5CoolFm11000000202110000002020000000000021.00024601523537218433439453272792225300.00%110100.00%1713141050.57%727150648.27%31463749.29%10237361033286487242
6Farmers11000000321110000003210000000000021.00036900523537224433439453273210832300.00%4175.00%0713141050.57%727150648.27%31463749.29%10237361033286487242
7Goons20101000550100010003211010000023-120.5005914005235372644334394532750231630700.00%8275.00%0713141050.57%727150648.27%31463749.29%10237361033286487242
8Grizzlies21100000981211000009810000000000020.5009182700523537267433439453277614304810330.00%13376.92%0713141050.57%727150648.27%31463749.29%10237361033286487242
9Hunters2020000036-31010000024-21010000012-100.00035800523537256433439453277323235210110.00%80100.00%0713141050.57%727150648.27%31463749.29%10237361033286487242
10Husky22000000734000000000002200000073441.000711180052353727943343945327682012511000.00%6183.33%0713141050.57%727150648.27%31463749.29%10237361033286487242
11Igloos1010000013-2000000000001010000013-200.000123005235372214334394532734191921500.00%7271.43%0713141050.57%727150648.27%31463749.29%10237361033286487242
12Marlies11000000431110000004310000000000021.00048120052353724343343945327451310167114.29%5180.00%1713141050.57%727150648.27%31463749.29%10237361033286487242
13Marmots21100000321110000003031010000002-220.500358015235372624334394532744716421119.09%7271.43%0713141050.57%727150648.27%31463749.29%10237361033286487242
14Outlaws1010000034-1000000000001010000034-100.000369005235372294334394532736910274125.00%5340.00%0713141050.57%727150648.27%31463749.29%10237361033286487242
15Predateurs21000010752110000004311000001032141.000710170052353725543343945327712626448112.50%9188.89%0713141050.57%727150648.27%31463749.29%10237361033286487242
16Raptors11000000523110000005230000000000021.00051015005235372474334394532729710252150.00%4175.00%0713141050.57%727150648.27%31463749.29%10237361033286487242
17Rockets20100001611-51010000037-41000000134-110.250612180052353725643343945327691920551100.00%11372.73%0713141050.57%727150648.27%31463749.29%10237361033286487242
18Sags2110000035-2110000003211010000003-320.50036900523537254433439453273710835300.00%4175.00%0713141050.57%727150648.27%31463749.29%10237361033286487242
19Scorpions211000001010021100000101000000000000020.50010182800523537277433439453277219183415213.33%9277.78%0713141050.57%727150648.27%31463749.29%10237361033286487242
20Spartans210000017611000000123-11100000053230.750712190052353726243343945327821423491218.33%9188.89%1713141050.57%727150648.27%31463749.29%10237361033286487242
21Supreme1010000023-1000000000001010000023-100.000246005235372234334394532741121626400.00%80100.00%0713141050.57%727150648.27%31463749.29%10237361033286487242
22Thugs11000000211000000000001100000021121.00024600523537234433439453274274299111.11%2150.00%0713141050.57%727150648.27%31463749.29%10237361033286487242
23TigersCats2010000157-2000000000002010000157-210.250591400523537252433439453277616264012216.67%10280.00%0713141050.57%727150648.27%31463749.29%10237361033286487242
24Twins2110000010640000000000021100000106420.5001020300052353728643343945327761416658225.00%6350.00%0713141050.57%727150648.27%31463749.29%10237361033286487242
25Vipers211000007701010000034-11100000043120.500713200052353727143343945327902310439111.11%5180.00%0713141050.57%727150648.27%31463749.29%10237361033286487242
26Warriors1010000023-11010000023-10000000000000.000246005235372304334394532716718324125.00%9188.89%0713141050.57%727150648.27%31463749.29%10237361033286487242
27Xpress11000000642000000000001100000064221.000610160052353724143343945327405615700.00%20100.00%0713141050.57%727150648.27%31463749.29%10237361033286487242
Total42172001013126133-721109010016670-421711000126063-3410.48812623235802523537213414334394532714293934539962022311.39%2034478.33%3713141050.57%727150648.27%31463749.29%10237361033286487242
_Since Last GM Reset42172001013126133-721109010016670-421711000126063-3410.48812623235802523537213414334394532714293934539962022311.39%2034478.33%3713141050.57%727150648.27%31463749.29%10237361033286487242
_Vs Conference19980001164631953000013132-110450001033312210.5536411918300523537262643343945327697177197459871314.94%872077.01%1713141050.57%727150648.27%31463749.29%10237361033286487242
_Vs Division10630000132293641000012319442200000910-1130.65032609200523537233143343945327341829722748612.50%44881.82%1713141050.57%727150648.27%31463749.29%10237361033286487242

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
4241L31262323581341142939345399602
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
4217201013126133
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2110910016670
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
2171100126063
Derniers 10 matchs
WLOTWOTL SOWSOL
450001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2022311.39%2034478.33%3
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
433439453275235372
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
713141050.57%727150648.27%31463749.29%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
10237361033286487242


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
113Bandits4Snowbirds3LSommaire du match
226Snowbirds7Twins2WSommaire du match
445Warriors3Snowbirds2LSommaire du match
667Marlies3Snowbirds4WSommaire du match
891Snowbirds1Hunters2LSommaire du match
998Grizzlies2Snowbirds7WSommaire du match
10114Snowbirds0Marmots2LSommaire du match
11130CoolFm0Snowbirds2WSommaire du match
12144Snowbirds2TigersCats3LXXSommaire du match
14160Scorpions4Snowbirds6WSommaire du match
15176Snowbirds3Rockets4LXXSommaire du match
16184Snowbirds3Twins4LSommaire du match
17196Snowbirds6Xpress4WSommaire du match
18210Goons2Snowbirds3WXSommaire du match
19231Vipers4Snowbirds3LSommaire du match
21250Snowbirds5Husky2WSommaire du match
22262Barracudas6Snowbirds1LSommaire du match
23280Raptors2Snowbirds5WSommaire du match
24289Snowbirds3Outlaws4LSommaire du match
26308Snowbirds2Bandits4LSommaire du match
27321Snowbirds2Husky1WSommaire du match
28334Hunters4Snowbirds2LSommaire du match
29350Snowbirds5Spartans3WSommaire du match
30363Chiwawa2Snowbirds3WSommaire du match
31382Farmers2Snowbirds3WSommaire du match
33399Snowbirds3Predateurs2WXXSommaire du match
34406Snowbirds2Supreme3LSommaire du match
35419Scorpions6Snowbirds4LSommaire du match
36440Rockets7Snowbirds3LSommaire du match
37456Snowbirds0Sags3LSommaire du match
39476Sags2Snowbirds3WSommaire du match
41497Snowbirds2Goons3LSommaire du match
42507Snowbirds3TigersCats4LSommaire du match
43521Bandits5Snowbirds1LSommaire du match
44542Spartans3Snowbirds2LXXSommaire du match
45563Snowbirds2Thugs1WSommaire du match
46572Predateurs3Snowbirds4WSommaire du match
47587Snowbirds4Vipers3WSommaire du match
48602Marmots0Snowbirds3WSommaire du match
49620Snowbirds4Bayou6LSommaire du match
50628Snowbirds1Igloos3LSommaire du match
51642Grizzlies6Snowbirds2LSommaire du match
53664Smirnoff Ice-Snowbirds-
54679Snowbirds-Hunters-
55696Marlies-Snowbirds-
57714Snowbirds-Wolves-
58729Smirnoff Ice-Snowbirds-
59743Snowbirds-Smirnoff Ice-
60759Snowbirds-Thugs-
61772Xpress-Snowbirds-
63792Twins-Snowbirds-
64805Snowbirds-Grizzlies-
65821Warriors-Snowbirds-
67843Thugs-Snowbirds-
68856Snowbirds-Vandals-
69873Husky-Snowbirds-
71892Snowbirds-Xpress-
72906Chiwawa-Snowbirds-
73916Snowbirds-Smirnoff Ice-
75935Snowbirds-Marlies-
76945Bayou-Snowbirds-
77965TigersCats-Snowbirds-
78979Snowbirds-Marmots-
80998Vandals-Snowbirds-
821022Snowbirds-Farmers-
831031Snowbirds-Chiwawa-
841044CoolFm-Snowbirds-
851061Igloos-Snowbirds-
881088Igloos-Snowbirds-
891103Snowbirds-Warriors-
901117Wolves-Snowbirds-
911127Snowbirds-Barracudas-
921137Snowbirds-Farmers-
941155Outlaws-Snowbirds-
951160Snowbirds-Rockets-
971184Supreme-Snowbirds-
981194Snowbirds-Twins-
991202Snowbirds-Raptors-
1011220Snowbirds-Scorpions-
1021222Vipers-Snowbirds-
1061249Goons-Snowbirds-
1071261Snowbirds-CoolFm-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité30002000
Prix des billets3515
Assistance62,88441,857
Assistance PCT99.82%99.66%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
20 4988 - 99.75% 161,645$3,394,554$5000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,157,922$ 1,262,500$ 1,262,500$ 1,000,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 685,686$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
3,232,909$ 57 20,949$ 1,194,093$




Snowbirds 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

Snowbirds 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

Snowbirds 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

Snowbirds 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

Snowbirds 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





Site web créé par le SimonT Hockey Simulator (STHS) pour Michael Langlois - English Version of the Website - La base de données a été créé : 01/06/2026 11:53:36