Thème
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Connexion

Iowa
GP: 14 | W: 5 | L: 6 | OTL: 3 | P: 13
GF: 28 | GA: 39 | PP%: 18.52% | PK%: 77.42%
DG: Martin Mercier | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #192 vs Abbotsford

Centre de jeu
Iowa
5-6-3, 13pts
3
2 Texas
8-5-1, 17pts
Team Stats
W2SéquenceW1
4-3-1Fiche domicile3-3-1
1-3-2Fiche domicile5-2-0
5-4-1Derniers 10 matchs6-3-1
2.00Buts par match 3.29
2.79Buts contre par match 2.86
18.52%Pourcentage en avantage numérique23.33%
77.42%Pourcentage en désavantage numérique76.19%
Eagles
7-5-2, 16pts
1
2 Iowa
5-6-3, 13pts
Team Stats
L1SéquenceW2
4-1-2Fiche domicile4-3-1
3-4-0Fiche domicile1-3-2
5-3-2Derniers 10 matchs5-4-1
3.14Buts par match 2.00
2.71Buts contre par match 2.79
14.04%Pourcentage en avantage numérique18.52%
73.33%Pourcentage en désavantage numérique77.42%
Iowa
5-6-3, 13pts
Jour 29
Abbotsford
7-5-2, 16pts
Statistiques d’équipe
W2SéquenceL2
4-3-1Fiche domicile3-3-1
1-3-2Fiche visiteur4-2-1
5-4-110 derniers matchs4-4-2
2.00Buts par match 2.50
2.79Buts contre par match 2.50
18.52%Pourcentage en avantage numérique8.33%
77.42%Pourcentage en désavantage numérique86.00%
Iowa
5-6-3, 13pts
Jour 31
San Jose
9-5-0, 18pts
Statistiques d’équipe
W2SéquenceL2
4-3-1Fiche domicile5-2-0
1-3-2Fiche visiteur4-3-0
5-4-110 derniers matchs6-4-0
2.00Buts par match 3.57
2.79Buts contre par match 3.57
18.52%Pourcentage en avantage numérique18.18%
77.42%Pourcentage en désavantage numérique78.85%
Iowa
5-6-3, 13pts
Jour 34
Texas
8-5-1, 17pts
Statistiques d’équipe
W2SéquenceW1
4-3-1Fiche domicile3-3-1
1-3-2Fiche visiteur5-2-0
5-4-110 derniers matchs6-3-1
2.00Buts par match 3.29
2.79Buts contre par match 3.29
18.52%Pourcentage en avantage numérique23.33%
77.42%Pourcentage en désavantage numérique76.19%
Meneurs d'équipe
Buts
Linus Karlsson
6
Passes
Tarmo Reunanen
6
Points
Jonathan Dahlen
9
Plus/Moins
Linus Karlsson
3
Victoires
Riku Helenius
5
Pourcentage d’arrêts
Riku Helenius
0.925

Statistiques d’équipe
Buts pour
28
2.00 GFG
Tirs pour
412
29.43 Avg
Pourcentage en avantage numérique
18.5%
10 GF
Début de zone offensive
39.1%
Buts contre
39
2.79 GAA
Tirs contre
502
35.86 Avg
Pourcentage en désavantage numérique
77.4%%
14 GA
Début de la zone défensive
44.5%
Informations de l'équipe

Directeur généralMartin Mercier
EntraîneurManny Malhotra
DivisionCentrale
ConférenceConference ouest
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,212
Billets de saison300


Informations de la formation

Équipe Pro23
Équipe Mineure18
Limite Contrat41 / 50
Espoirs22


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
1Carl HagelinXX99.00644680656974836653676759768165245000361850,000$
2Alexander TrueX100.0074317978967888707570676578504647500X0271850,000$
3Jayson MegnaXX100.0065269466756687656664666216956295000351700,000$
4Aaron PalushajXX97.00612992647263846253616258706649185000351500,000$
5Christian FischerXX100.00722995789181996670666768775955575000281925,000$
6Michael BuntingXX100.00772990797784916267596862726153585000291825,000$
7Michael FrolikXX96.00672688588062866868636758787982195000371850,000$
8Nick BoninoXX100.00573692487469836785656467796892265000371850,000$
9Joakim NygardX100.00642191727472826169626461746860355000321825,000$
10Linus Karlsson (R)XX99.00752988688073997174707169724747585000251500,000$
11Brendan SmithX100.00703271598770905450514588747764315000361725,000$
12Dysin MayoX100.00763080788889835750565692795648525000282950,000$
13Tarmo ReunanenX98.00783073888883885150505183785045555000271750,000$
14Connor CliftonX100.007939637870878456505453887863534650003031,150,000$
15Matt IrwinX100.00593084486868955350485391546965275000371500,000$
16Lawrence PilutX100.00674489857991895150504881755546545000291825,000$
17Emil Andrae (R)X100.00783092727880984950514687704141735000232700,000$
18Matthew Robertson (R)X100.00833090718789995350515490704444755000242700,000$
Rayé
1Kevin LabancXS1764188828091987176707152825750555000291975,000$
2Jonathan DahlenXX95.006339949080909472747171637951486650002721,100,000$
MOYENNE D’ÉQUIPE99.2070328671807890616260617271615545500
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
1David Rittich100.0065878580758383818183836463525000321500,000$
2Riku Helenius97.0058928681848484868568778786155000371700,000$
Rayé
1Nico Daws (R)100.0066857878778887858678793838735000242950,000$
MOYENNE D’ÉQUIPE99.006388838079858584847680636247500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Manny Malhotra79768970999964CAN5832,000,000$


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
1Jonathan DahlenIowa (MIN)LW/RW14549-1756155111319.80%020814.86224425000061145.92%19600000.8700010110
2Michael BuntingIowa (MIN)LW/RW14347-3803493082210.00%125318.12123845000000057.14%1400000.5500000000
3Lawrence PilutIowa (MIN)D143470203143113149.68%1831522.522241947000055100%000000.4400000002
4Linus KarlssonIowa (MIN)C/RW14617380234040113015.00%228120.143039420001490046.78%40400000.5011000020
5Tarmo ReunanenIowa (MIN)D14066-6140259268200%2533824.200221041000046000%000000.3500000001
6Connor CliftonIowa (MIN)D1424603403022268147.69%2129621.181231447000136110%000000.4000000000
7Carl HagelinIowa (MIN)LW/RW132350601514228149.09%227321.031123380000400059.09%2200000.3701000001
8Nick BoninoIowa (MIN)C/LW14145-500615154146.67%217912.8200000000000157.14%18900000.5600000000
9Christian FischerIowa (MIN)LW/RW14224-610099297236.90%020014.2900028000080043.48%2300000.4002000000
10Emil AndraeIowa (MIN)D1413402013131021010.00%1420914.9400000000120000%000000.3800000000
11Dysin MayoIowa (MIN)D10123-740711286123.57%1017217.300111220000129000%000000.3500000000
12Aaron PalushajIowa (MIN)LW/RW1403320089142110%126518.970111400003470031.58%1900000.2302000001
13Michael FrolikIowa (MIN)LW/RW14123300162191155.26%226018.610222410000261042.86%6300000.2300000000
14Matthew RobertsonIowa (MIN)D14033-2200258165250%1724517.51011421000022000%000000.2400000000
15Brendan SmithIowa (MIN)D7011260456120%811616.690000100003000%000000.1700000000
16Alexander TrueIowa (MIN)C14011-4401610155140%11299.2300002000050053.13%9600000.1500000000
17Jayson MegnaIowa (MIN)C/RW13011-30079117120%118714.400112220002260046.25%24000000.1100000000
18Kevin LabancIowa (MIN)RW10000-4215114191120%111711.7800000000000028.57%70000000000000
19Joakim NygardIowa (MIN)LW14000-220104160%0725.2000000000000020.00%100000000000000
Statistiques d’équipe totales ou en moyenne249274875-33148102592184121093016.55%126412416.561017279044700094244348.09%128300000.3616010135
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
1Riku HeleniusIowa (MIN)135620.9252.6579301354670000.8336131430
2David RittichIowa (MIN)10010.9143.0060003350000016000
Statistiques d’équipe totales ou en moyenne145630.9242.6785301385020006147430


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
Aaron PalushajIowa (MIN)LW/RW351989-09-07USANo199 Lbs5 ft11NoNoFree AgentNoNo12026-09-27FalseFalsePro & Farm500,000$415,663$0$0$No---------------------------Lien
Alexander TrueIowa (MIN)C271997-07-17DENNo202 Lbs6 ft5NoYesN/ANoNo12026-09-04FalseFalsePro & Farm850,000$706,627$0$0$No---------------------------Lien
Brendan SmithIowa (MIN)D361989-02-08CANNo216 Lbs6 ft2NoNoTrade2026-08-24NoNo12025-09-11FalseFalsePro & Farm725,000$602,711$0$0$No---------------------------Lien / Lien NHL
Carl HagelinIowa (MIN)LW/RW361988-08-23SWENo195 Lbs5 ft11NoNoFree AgentNoNo12026-09-19FalseFalsePro & Farm850,000$706,627$0$0$No---------------------------Lien
Christian FischerIowa (MIN)LW/RW281997-04-15USANo214 Lbs6 ft2NoNoTrade2025-03-01NoNo12025-09-11FalseFalsePro & Farm925,000$768,976$0$0$No---------------------------Lien / Lien NHL
Connor CliftonIowa (MIN)D301995-04-28USANo176 Lbs5 ft11NoNoN/ANoNo32026-09-04FalseFalsePro & Farm1,150,000$956,024$0$0$No1,150,000$1,150,000$-------1,150,000$1,150,000$-------NoNo-------Lien / Lien NHL
David RittichIowa (MIN)G321992-08-08CZENo208 Lbs6 ft3NoNoFree AgentNoNo12026-09-27FalseFalsePro & Farm500,000$415,663$0$0$No---------------------------Lien / Lien NHL
Dysin MayoIowa (MIN)D281996-08-17CANNo195 Lbs6 ft2NoNoN/ANoNo22024-09-15FalseFalsePro & Farm950,000$789,759$0$0$No950,000$--------950,000$--------No--------Lien
Emil AndraeIowa (MIN)D232002-02-23SWEYes189 Lbs5 ft9NoNoProspectNoNo22026-08-17FalseFalsePro & Farm700,000$581,928$0$0$No700,000$--------700,000$--------No--------
Jayson MegnaIowa (MIN)C/RW351990-02-01USANo197 Lbs6 ft1NoNoFree AgentNoNo12026-09-20FalseFalsePro & Farm700,000$581,928$0$0$No---------------------------Lien
Joakim NygardIowa (MIN)LW321993-01-08SWENo180 Lbs6 ft0NoNoTrade2026-08-24NoNo1FalseFalsePro & Farm825,000$685,843$0$0$No---------------------------Lien
Jonathan DahlenIowa (MIN)LW/RW271997-12-20SWENo180 Lbs5 ft11NoNoN/ANoNo22026-09-04FalseFalsePro & Farm1,100,000$914,458$0$0$No1,100,000$--------1,100,000$--------No--------Lien
Kevin LabancIowa (MIN)RW291995-12-12USANo189 Lbs5 ft11NoNoN/ANoNo12025-09-11FalseFalsePro & Farm975,000$810,542$0$0$No---------------------------Lien / Lien NHL
Lawrence PilutIowa (MIN)D291995-12-30SWENo186 Lbs5 ft11NoNoN/ANoNo12024-09-15FalseFalsePro & Farm825,000$685,843$0$0$No---------------------------Lien
Linus KarlssonIowa (MIN)C/RW251999-11-16SWEYes178 Lbs6 ft1NoNoProspectNoNo12025-10-16FalseFalsePro & Farm500,000$415,663$0$0$No---------------------------
Matt Irwin (contrat à 1 volet)Iowa (MIN)D371987-11-29CANNo217 Lbs6 ft2NoNoTrade2025-07-25YesYes12024-09-28FalseFalsePro & Farm500,000$416,667$5,000$4,167$No---------------------------Lien
Matthew RobertsonIowa (MIN)D242001-03-09CANYes211 Lbs6 ft3NoNoProspectNoNo22026-08-17FalseFalsePro & Farm700,000$581,928$0$0$No700,000$--------700,000$--------No--------
Michael BuntingIowa (MIN)LW/RW291995-09-17CANNo197 Lbs5 ft11NoNoTrade2026-08-24NoNo12025-09-09FalseFalsePro & Farm825,000$685,843$0$0$No---------------------------Lien / Lien NHL
Michael FrolikIowa (MIN)LW/RW371988-02-17CZENo192 Lbs6 ft1NoNoFree AgentNoNo12026-09-19FalseFalsePro & Farm850,000$706,627$0$0$No---------------------------Lien
Nick BoninoIowa (MIN)C/LW371988-04-20USANo200 Lbs6 ft1NoNoFree AgentNoNo12026-09-19FalseFalsePro & Farm850,000$706,627$0$0$No---------------------------Lien / Lien NHL
Nico DawsIowa (MIN)G242000-12-22CANYes197 Lbs6 ft2NoNoN/ANoNo22026-09-04FalseFalsePro & Farm950,000$789,759$0$0$No950,000$--------950,000$--------No--------Lien NHL
Riku HeleniusIowa (MIN)G371988-01-10FINNo218 Lbs6 ft3NoNoFree AgentNoNo12026-09-19FalseFalsePro & Farm700,000$581,928$0$0$No---------------------------
Tarmo ReunanenIowa (MIN)D271998-03-01FINNo186 Lbs6 ft0NoNoN/ANoNo12024-09-15FalseFalsePro & Farm750,000$623,494$0$0$No---------------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2330.61197 Lbs6 ft11.30791,304$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jayson MegnaMichael Bunting35122
2Carl HagelinLinus KarlssonMichael Frolik30122
3Christian FischerNick BoninoAlexander True25122
4Alexander TrueJoakim Nygard10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brendan SmithTarmo Reunanen35122
2Connor CliftonLawrence Pilut30122
3Emil AndraeMatthew Robertson25122
4Matthew RobertsonTarmo Reunanen10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Christian FischerMichael Bunting50122
2Alexander TrueLinus KarlssonMichael Frolik50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Matthew RobertsonTarmo Reunanen50122
2Connor CliftonLawrence Pilut50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Michael Frolik50122
2Linus KarlssonChristian Fischer50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Matthew RobertsonTarmo Reunanen50122
2Connor CliftonLawrence Pilut50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Michael Frolik50122Matthew RobertsonTarmo Reunanen50122
2Linus Karlsson50122Connor CliftonLawrence Pilut50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Michael Frolik50122
2Linus KarlssonMichael Bunting50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Emil AndraeTarmo Reunanen50122
2Connor CliftonLawrence Pilut50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Christian FischerMichael BuntingMatthew RobertsonTarmo Reunanen
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Linus KarlssonMichael FrolikConnor CliftonLawrence Pilut
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Michael Frolik, , Linus KarlssonMichael Frolik, Michael Frolik
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Lawrence Pilut, Emil Andrae, Matthew RobertsonLawrence PilutLawrence Pilut, Emil Andrae
Tirs de pénalité
Linus Karlsson, , Christian Fischer, Michael Bunting, Michael Frolik
Gardien
#1 : Riku Helenius, #2 : David Rittich
Lignes d’attaque personnalisées en prolongation
Jayson Megna, Carl Hagelin, Christian Fischer, Michael Bunting, Michael Frolik, , Alexander True, Linus Karlsson, Joakim Nygard, Nick Bonino
Lignes de défense personnalisées en prolongation
Matthew Robertson, Tarmo Reunanen, Connor Clifton, Lawrence Pilut, Emil Andrae


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
1Abbotsford21000100633110000005141000010012-130.7506101600981016314113313212731716289333.33%80100.00%025049450.61%26256246.62%10520850.48%32120733911319294
2Bridgeport1010000024-2000000000001010000024-200.000235009810139141133132123994212150.00%2150.00%025049450.61%26256246.62%10520850.48%32120733911319294
3Coachella Valley1000010023-1000000000001000010023-110.50023500981012914113313212351210186116.67%4250.00%025049450.61%26256246.62%10520850.48%32120733911319294
4Eagles11000000211110000002110000000000021.00024600981012114113313212404820100.00%4175.00%025049450.61%26256246.62%10520850.48%32120733911319294
5Grand Rapids11000000404110000004040000000000021.000481201981012914113313212345815300.00%40100.00%025049450.61%26256246.62%10520850.48%32120733911319294
6Hershey1010000014-31010000014-30000000000000.0001230098101361411331321231814287114.29%7271.43%025049450.61%26256246.62%10520850.48%32120733911319294
7Rochester1010000013-21010000013-20000000000000.0001120098101251411331321236101018200.00%5180.00%025049450.61%26256246.62%10520850.48%32120733911319294
8Springfield1000000112-11000000112-10000000000010.500123009810135141133132123291021200.00%50100.00%025049450.61%26256246.62%10520850.48%32120733911319294
9Syracuse11000000422110000004220000000000021.000471100981012714113313212521423112150.00%50100.00%025049450.61%26256246.62%10520850.48%32120733911319294
10Texas30200010413-91010000004-42010001049-520.33346100098101871411331321210932305714321.43%15566.67%025049450.61%26256246.62%10520850.48%32120733911319294
11Wilkes-Barre/Scranton1010000014-3000000000001010000014-300.000123009810121141133132122161522600.00%3233.33%025049450.61%26256246.62%10520850.48%32120733911319294
Total1446002112839-118430000118171603002101022-12130.464284876019810141214113313212502126148259541018.52%621477.42%025049450.61%26256246.62%10520850.48%32120733911319294
_Since Last GM Reset1446002112839-118430000118171603002101022-12130.464284876019810141214113313212502126148259541018.52%621477.42%025049450.61%26256246.62%10520850.48%32120733911319294
_Vs Conference822002111522-74210000188040100210714-790.563152540009810123514113313212289747414432721.88%36877.78%025049450.61%26256246.62%10520850.48%32120733911319294
_Vs Division51200011716-93110000137-42010001049-550.5007121900981011431411331321218145489817317.65%24675.00%025049450.61%26256246.62%10520850.48%32120733911319294

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1413W228487641250212614825901
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
144602112839
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
84300011817
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
60302101022
Derniers 10 matchs
WLOTWOTL SOWSOL
540100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
541018.52%621477.42%0
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
1411331321298101
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
25049450.61%26256246.62%10520850.48%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
32120733911319294


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
15Springfield2Iowa1LXXSommaire du match
425Hershey4Iowa1LSommaire du match
529Iowa1Texas7LSommaire du match
748Iowa1Abbotsford2LXSommaire du match
961Rochester3Iowa1LSommaire du match
1279Grand Rapids0Iowa4WSommaire du match
1388Iowa2Bridgeport4LSommaire du match
1597Iowa2Coachella Valley3LXSommaire du match
17111Abbotsford1Iowa5WSommaire du match
20130Syracuse2Iowa4WSommaire du match
21141Texas4Iowa0LSommaire du match
23154Iowa1Wilkes-Barre/Scranton4LSommaire du match
25162Iowa3Texas2WXXSommaire du match
27178Eagles1Iowa2WSommaire du match
29192Iowa-Abbotsford-
31205Iowa-San Jose-
34219Iowa-Texas-
35227Hartford-Iowa-
37239Iowa-San Jose-
39255Rochester-Iowa-
41270Wilkes-Barre/Scranton-Iowa-
42279Iowa-Hartford-
45295Bakersfield-Iowa-
47310Bridgeport-Iowa-
48321Iowa-Bridgeport-
51337Iowa-Lehigh Valley-
53351Charlotte-Iowa-
55368Syracuse-Iowa-
57380Iowa-Laval-
58390Iowa-Grand Rapids-
60401Hartford-Iowa-
61416Iowa-Rockford-
63426Hershey-Iowa-
65443Iowa-Charlotte-
67452Hershey-Iowa-
69468Iowa-Tucson-
70477Iowa-Cleveland-
72489Coachella Valley-Iowa-
74504Iowa-Utica -
75515San Diego-Iowa-
78532Eagles-Iowa-
79544Iowa-Lehigh Valley-
81554Iowa-Syracuse-
82567Providence-Iowa-
85581Utica -Iowa-
86595Iowa-Charlotte-
88607Providence-Iowa-
90619Iowa-San Diego-
92632Iowa-Utica -
93642Iowa-Rochester-
95654Cleveland-Iowa-
97667Grand Rapids-Iowa-
99684Laval-Iowa-
101695Iowa-Providence-
103707Iowa-Tucson-
105722San Jose-Iowa-
107733Iowa-Tucson-
108745Iowa-Coachella Valley-
110752Manitoba-Iowa-
113771San Jose-Iowa-
115784Iowa-Eagles-
117798Lehigh Valley-Iowa-
119813Rockford-Iowa-
121826Iowa-Hershey-
123840Iowa-Wilkes-Barre/Scranton-
125850Ontario-Iowa-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
127864Iowa-Springfield-
129874Abbotsford-Iowa-
130888Iowa-Springfield-
132897Iowa-Bakersfield-
134908Lehigh Valley-Iowa-
136924Laval-Iowa-
137933Iowa-Ontario-
140950Springfield-Iowa-
142964Iowa-Bakersfield-
144976Cleveland-Iowa-
147998Iowa-Ontario-
1481006Rockford-Iowa-
1521025Tucson-Iowa-
1551043Tucson-Iowa-
1571057Iowa-San Diego-
1581063Iowa-Manitoba-
1641081Springfield-Iowa-
1651091Iowa-Manitoba-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5030
Assistance11,9135,785
Assistance PCT74.46%72.31%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
34 2212 - 73.74% 129,803$1,038,420$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
630,616$ 1,672,500$ 1,672,500$ 2,000,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
10,075$ 293,272$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
4,413,285$ 138 22,123$ 3,052,974$




Iowa 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

Iowa 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

Iowa 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

Iowa 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

Iowa 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