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IceHogs
GP: 75 | W: 27 | L: 30 | OTL: 18 | P: 72
GF: 152 | GA: 200 | PP%: 29.53% | PK%: 71.26%
DG: Pradeep Kumar | Morale : 27 | Moyenne d’équipe : 58
Prochains matchs #1167 vs Senators

Centre de jeu
Wolf Pack
28-34-12, 68pts
0
1 IceHogs
27-30-18, 72pts
Team Stats
OTL1SéquenceL1
15-19-3Fiche domicile15-15-8
13-15-9Fiche domicile12-15-10
3-3-4Derniers 10 matchs3-5-2
2.01Buts par match 2.03
2.96Buts contre par match 2.67
26.58%Pourcentage en avantage numérique29.53%
71.33%Pourcentage en désavantage numérique71.26%
Barracuda
51-18-6, 108pts
5
3 IceHogs
27-30-18, 72pts
Team Stats
W1SéquenceL1
24-11-2Fiche domicile15-15-8
27-7-4Fiche domicile12-15-10
8-2-0Derniers 10 matchs3-5-2
2.20Buts par match 2.03
1.72Buts contre par match 2.67
26.35%Pourcentage en avantage numérique29.53%
85.03%Pourcentage en désavantage numérique71.26%
IceHogs
27-30-18, 72pts
Jour 95
Senators
32-29-14, 78pts
Statistiques d’équipe
L1SéquenceL2
15-15-8Fiche domicile18-11-8
12-15-10Fiche visiteur14-18-6
3-5-210 derniers matchs3-5-2
2.03Buts par match 2.84
2.67Buts contre par match 2.84
29.53%Pourcentage en avantage numérique25.86%
71.26%Pourcentage en désavantage numérique69.89%
IceHogs
27-30-18, 72pts
Jour 96
Rocket
43-16-16, 102pts
Statistiques d’équipe
L1SéquenceL3
15-15-8Fiche domicile24-7-7
12-15-10Fiche visiteur19-9-9
3-5-210 derniers matchs4-3-3
2.03Buts par match 2.32
2.67Buts contre par match 2.32
29.53%Pourcentage en avantage numérique31.82%
71.26%Pourcentage en désavantage numérique73.12%
IceHogs
27-30-18, 72pts
Jour 97
Senators
32-29-14, 78pts
Statistiques d’équipe
L1SéquenceL2
15-15-8Fiche domicile18-11-8
12-15-10Fiche visiteur14-18-6
3-5-210 derniers matchs3-5-2
2.03Buts par match 2.84
2.67Buts contre par match 2.84
29.53%Pourcentage en avantage numérique25.86%
71.26%Pourcentage en désavantage numérique69.89%
Meneurs d'équipe
Buts
Jaret Anderson-Dolan
26
Passes
Marc Gatcomb
28
Points
Jaret Anderson-Dolan
52
Sebastian Aho2Plus/Moins
Sebastian Aho2
1
Victoires
Remi Poirier
25
Pourcentage d’arrêts
Nick Grabko
0.913

Statistiques d’équipe
Buts pour
152
2.03 GFG
Tirs pour
1097
14.63 Avg
Pourcentage en avantage numérique
29.5%
44 GF
Début de zone offensive
34.4%
Buts contre
200
2.67 GAA
Tirs contre
1494
19.92 Avg
Pourcentage en désavantage numérique
71.3%%
48 GA
Début de la zone défensive
38.5%
Informations de l'équipe

Directeur généralPradeep Kumar
EntraîneurAndrew Doty
DivisionDivision 2
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,130
Billets de saison1,500


Informations de la formation

Équipe Pro24
Équipe Mineure30
Limite contact 54 / 100
Espoirs136


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
1Marc Gatcomb (R)X96.009861917974559159375672572549496746630262973,000$
2Max JonesXX96.0092478176805481572556586025676759346202821,392,000$
3Jaret Anderson-DolanXX100.0075728377727175587055576450626358546202611,172,000$
4Adam SykoraX99.0073639768658289575057546048474757576002131,279,000$
5Jesse YlonenX100.0077728966726364615061586353474759456002621,864,000$
6Anton Wahlberg (R)X96.0082759968775453617558606554474759616002031,286,000$
7Jackson Kunz (R)X100.0087839982853630607672456742464658225902331,385,000$
8Ondrej Becher (R)X100.0078719667735252536946566154474757475602231,278,000$
9Mark SendenX100.0076718865715353546952536150474655415602812,999,000$
10Ryan McGregorX100.007971986371474652655346644445445422540272991,000$
11Gavin Hayes (R)X100.0073669566686265485049455944464653355402131,279,000$
12Kyle CapobiancoX100.0073746867747681582557426239565654436202821,305,000$
13Adam Ginning (R)X100.007574746774778550254243593848485131600261925,000$
14Guillaume Richard (R)X100.0072708281715049562546516048464556135802331,297,000$
15Luke Prokop (R)X99.0086849363865254452535396538474650355702431,352,000$
16Gavin WhiteX100.0074689465706064462538405838474650255602331,271,000$
17Daniil Misyul (R)X100.0071688167686165462537405737474748495602531,348,000$
18Sebastian Aho2X100.0071649164645050532552405837464750365503011,995,000$
19Lucas JohansenX100.0071697963695658482542385737464750305502821,001,000$
Rayé
1Hank Kempf (R)X100.0082759980753531532552396537444455205702400$
2Tyler Inamoto (R)X100.0076728561723634492543396137444451195302731,320,000$
MOYENNE D’ÉQUIPE99.33787089697356605442504861424949553658
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
1Remi Poirier100.00564050805962636366603046465374590241836,667$
2Magnus Chrona100.00504050885350545753533044445159540251867,500$
Rayé
1Nick Grabko (R)80.864440506945914650918145444460525902611,000,000$
MOYENNE D’ÉQUIPE93.6250405079526854577065354545556257
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Andrew Doty40404040404040TUR8111,000,000$


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
1Jaret Anderson-DolanIceHogs (CHI)C/RW73262652-12924094125145277617.93%31151020.6910122231801125956147.11%2424217010.69411323542
2Anton WahlbergIceHogs (CHI)C75222244-15323094122145429315.17%41158721.1771818961016872355.51%6723523000.55413204263
3Adam SykoraIceHogs (CHI)LW75201838-2608812399315620.20%14162621.69459141000003994047.75%2222225000.4719000345
4Max JonesIceHogs (CHI)LW/RW63152237-7240947998285615.31%21119418.9654910601125664138.10%1682613000.6211000604
5Jesse YlonenIceHogs (CHI)RW75172037-122210100109109386415.60%23143619.16671316920001252245.16%1242818010.5228002414
6Marc GatcombIceHogs (CHI)C6492837-211810659411333577.96%15112617.603141712700001252141.46%6033512000.6605101141
7Jackson KunzIceHogs (CHI)C67111425-151915457366234316.67%984512.61491316540000161059.62%530229000.5923102121
8Kyle CapobiancoIceHogs (CHI)D7031720-23146301011176227254.84%67173424.78134583011469010%33237000.2300411110
9Adam GinningIceHogs (CHI)D7531518-1616490991316129204.92%67185124.6914511125011177000%02441000.1900198013
10Mark SendenIceHogs (CHI)C696612-12643064792581624.00%15111016.0900006000011158.56%111518000.2214312030
11Ondrej BecherIceHogs (CHI)C757411-1320718432132221.88%8127016.950223811015442061.16%1211120000.1722000130
12Daniil MisyulIceHogs (CHI)D752911-327552791961110.53%39134417.9216751061013134000%0721000.1600001001
13Sebastian Aho2IceHogs (CHI)D732681403549205610.00%1695513.09000016011059010%9511000.1700000000
14Jake BeanBlackhawksD17268012101328251188.00%2844326.12044326000233000%0910100.3600011110
15Luke ProkopIceHogs (CHI)D75077-16363054803320150%64129017.20011246000075000%1928000.1100141000
16Guillaume RichardIceHogs (CHI)D65156-72152340911411.11%1773111.25101124011122010%0710000.1601001000
17Gavin HayesIceHogs (CHI)LW68145-2402536196135.26%45448.0100002011090075.00%463000.1800000001
18Gavin WhiteIceHogs (CHI)D69123-8552161105210.00%15102114.80101117000080025.00%4419000.0600100001
19Sam BittenBlackhawksC/LW/RW19022-315517130120%025913.6500003000080048.00%2560000.1500100000
20Ryan McGregorIceHogs (CHI)C151011006332033.33%1775.1800000000000052.63%1910000.2600000000
21Adam ErneBlackhawksC/LW/RW2000-1175440000%02713.7500000000000066.67%30000000001000
22Lucas JohansenIceHogs (CHI)D55000-12022183220%34177.59000020000110012.50%80200000000000
23Travis MitchellBlackhawksD39000120811010%0651.680000000001000%00100000000000
24Tyler InamotoIceHogs (CHI)D7000000000000%0101.530000000000000%00000000000000
25Hunter SkinnerBlackhawksD41000-100110000%0250.630000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne1401149233382-18773432011961549109736859213.58%4982251016.0744721161481099571237973241250.44%2869336338120.341757181828253026
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
1Remi PoirierIceHogs (CHI)702527170.8772.393998081591296740030.50046700413
2Nick GrabkoIceHogs (CHI)52110.9131.572670278029000.625850020
3Magnus ChronaIceHogs (CHI)110200.8423.423160018114720100075000
Statistiques d’équipe totales ou en moyenne862730180.8772.414582010184149084104547575433


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
Adam GinningIceHogs (CHI)D262000-01-13SWEYes196 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm925,000$156,920$0$0$No---------------------------Lien
Adam SykoraIceHogs (CHI)LW212004-09-07SVKNo179 Lbs5 ft10NoNoTrade2025-10-15NoNo32025-10-22FalseFalsePro & Farm1,279,000$216,973$0$0$No1,279,000$1,279,000$-------1,279,000$1,279,000$-------NoNo-------Lien
Anton WahlbergIceHogs (CHI)C202005-07-04SWEYes198 Lbs6 ft4NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,286,000$218,161$0$0$No1,286,000$1,286,000$-------1,286,000$1,286,000$-------NoNo-------Lien
Daniil MisyulIceHogs (CHI)D252000-10-20BLRYes176 Lbs6 ft3NoNoN/ANoNo32025-10-22FalseFalsePro & Farm1,348,000$228,679$0$0$No1,348,000$1,348,000$-------1,348,000$1,348,000$-------NoNo-------Lien
Gavin HayesIceHogs (CHI)LW212004-05-14USAYes176 Lbs6 ft1NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,279,000$216,973$0$0$No1,279,000$1,279,000$-------1,279,000$1,279,000$-------NoNo-------Lien
Gavin WhiteIceHogs (CHI)D232002-11-12CANNo185 Lbs6 ft0NoNoN/ANoNo32025-10-22FalseFalsePro & Farm1,271,000$215,616$0$0$No1,271,000$1,271,000$-------1,271,000$1,271,000$-------NoNo-------Lien
Guillaume RichardIceHogs (CHI)D232003-02-10CANYes187 Lbs6 ft2NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,297,000$220,027$0$0$No1,297,000$1,297,000$-------1,297,000$1,297,000$-------NoNo-------Lien
Hank KempfIceHogs (CHI)D242002-04-15USAYes200 Lbs6 ft2NoNoProspectNoNo02025-10-16FalseFalsePro & Farm0$0$No---------------------------Lien
Jackson KunzIceHogs (CHI)C232002-08-13USAYes227 Lbs6 ft3NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,385,000$234,955$0$0$No1,385,000$1,385,000$-------1,385,000$1,385,000$-------NoNo-------Lien
Jaret Anderson-DolanIceHogs (CHI)C/RW261999-09-12CANNo200 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm1,172,000$198,821$0$0$No---------------------------Lien
Jesse YlonenIceHogs (CHI)RW261999-10-03USANo193 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm1,864,000$316,214$0$0$No1,864,000$--------1,864,000$--------No--------Lien
Kyle CapobiancoIceHogs (CHI)D281997-08-13CANNo198 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm1,305,000$221,384$0$0$No1,305,000$--------1,305,000$--------No--------Lien / Lien NHL
Lucas JohansenIceHogs (CHI)D281997-11-16CANNo181 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm1,001,000$169,812$0$0$No1,001,000$--------1,001,000$--------No--------Lien
Luke ProkopIceHogs (CHI)D242002-05-06CANYes223 Lbs6 ft5NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,352,000$229,357$0$0$No1,352,000$1,352,000$-------1,352,000$1,352,000$-------NoNo-------Lien
Magnus ChronaIceHogs (CHI)G252000-08-08SWENo210 Lbs6 ft5NoNoN/ANoNo1FalseFalsePro & Farm867,500$147,165$0$0$No---------------------------Lien
Marc GatcombIceHogs (CHI)C261999-07-22USAYes195 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm973,000$165,062$0$0$No973,000$--------973,000$--------No--------Lien
Mark SendenIceHogs (CHI)C281998-01-22USANo201 Lbs5 ft10NoNoFree AgentNoNo12025-08-28FalseFalsePro & Farm2,999,000$508,759$0$0$No---------------------------Lien
Max JonesIceHogs (CHI)LW/RW281998-02-17USANo216 Lbs6 ft3NoNoTrade2025-01-22NoNo2FalseFalsePro & Farm1,392,000$236,143$0$0$No1,392,000$--------1,392,000$--------No--------Lien
Nick Grabko (sur la masse salariale)IceHogs (CHI)G262000-02-06USAYes187 Lbs6 ft0NoNoAssign ManuallyNoNo12026-04-20FalseFalsePro & Farm1,000,000$169,643$0$0$Yes---------------------------Lien
Ondrej BecherIceHogs (CHI)C222004-02-22CZEYes190 Lbs6 ft1NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,278,000$216,804$0$0$No1,278,000$1,278,000$-------1,278,000$1,278,000$-------NoNo-------Lien
Remi PoirierIceHogs (CHI)G242001-10-06QUENo210 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm836,667$141,935$0$0$No---------------------------Lien
Ryan McGregorIceHogs (CHI)C271999-01-29ONTNo195 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm991,000$168,116$0$0$No991,000$--------991,000$--------No--------Lien
Sebastian Aho2IceHogs (CHI)D301996-02-17SWENo177 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm1,995,000$338,438$0$0$No---------------------------Lien / Lien NHL
Tyler InamotoIceHogs (CHI)D271999-05-06USAYes194 Lbs6 ft2NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,320,000$223,929$0$0$No1,320,000$1,320,000$-------1,320,000$1,320,000$-------NoNo-------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2425.04196 Lbs6 ft22.041,267,340$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Mark SendenMax JonesMarc Gatcomb40122
2Jesse YlonenAnton WahlbergAdam Sykora30122
3Anton WahlbergMarc GatcombOndrej Becher20122
4Jesse YlonenAnton WahlbergAdam Sykora10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Luke ProkopAdam Ginning40122
2Kyle CapobiancoGavin White30122
3Luke ProkopAdam Ginning20122
4Daniil MisyulAdam Ginning10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jesse YlonenMax JonesMarc Gatcomb60122
2Ondrej BecherAnton WahlbergAdam Sykora40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Daniil MisyulAdam Ginning60122
2Kyle CapobiancoLuke Prokop40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Adam SykoraMarc Gatcomb60122
2Ondrej BecherAnton Wahlberg40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Luke ProkopDaniil Misyul60122
2Gavin WhiteAdam Ginning40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Adam Sykora60122Kyle CapobiancoDaniil Misyul60122
2Anton Wahlberg40122Luke ProkopAdam Ginning40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Marc GatcombAnton Wahlberg60122
2Adam SykoraOndrej Becher40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Daniil MisyulAdam Ginning60122
2Gavin WhiteLuke Prokop40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Max JonesAnton WahlbergMarc GatcombAdam GinningKyle Capobianco
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Max JonesAnton WahlbergMarc GatcombAdam GinningKyle Capobianco
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Ondrej Becher, Anton Wahlberg, Adam SykoraAdam Sykora, Anton WahlbergAnton Wahlberg
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Luke Prokop, Adam Ginning, Daniil MisyulAdam GinningAdam Ginning, Luke Prokop
Tirs de pénalité
Adam Sykora, Jesse Ylonen, Anton Wahlberg, Marc Gatcomb, Ondrej Becher
Gardien
#1 : Remi Poirier, #2 : Magnus Chrona


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
1Admirals20000011220100000102111000000101-130.75022400194279261918936451289234213011100.00%30100.00%049896351.71%539107750.05%41075854.09%124441513978541946971
2Americans2020000025-31010000012-11010000013-200.0002460019427926291893645128946231733000%6350.00%049896351.71%539107750.05%41075854.09%124441513978541946971
3Barracuda51300001713-63110000167-12020000016-530.3007121911194279265618936451289891734821000.00%12375.00%049896351.71%539107750.05%41075854.09%124441513978541946971
4Bears1010000004-41010000004-40000000000000.00000000194279261318936451289199713200.00%10100.00%049896351.71%539107750.05%41075854.09%124441513978541946971
5Bruins3000100256-11000000112-12000100144040.667581300194279263618936451289378245100.00%110.00%049896351.71%539107750.05%41075854.09%124441513978541946971
6Canucks2010010069-31010000035-21000010034-110.250612180019427926241893645128945164236300.00%6433.33%049896351.71%539107750.05%41075854.09%124441513978541946971
7Checkers210001005411000010023-11100000031230.75057120019427926251893645128937116285480.00%30100.00%049896351.71%539107750.05%41075854.09%124441513978541946971
8Comets41200001910-12010000124-22110000076130.3759132210194279264918936451289681420716233.33%5260.00%049896351.71%539107750.05%41075854.09%124441513978541946971
9Condors2010100025-3100010002111010000004-420.5002240019427926291893645128951212130400.00%30100.00%049896351.71%539107750.05%41075854.09%124441513978541946971
10Crunch11000000422000000000001100000042221.00046100019427926131893645128922516224250.00%30100.00%049896351.71%539107750.05%41075854.09%124441513978541946971
11Eagles2010010016-51010000004-41000010012-110.2501230019427926261893645128925616315120.00%3166.67%049896351.71%539107750.05%41075854.09%124441513978541946971
12Griffins2110000045-1110000003211010000013-220.5004590019427926241893645128937916305120.00%3233.33%049896351.71%539107750.05%41075854.09%124441513978541946971
13Gulls21000001431110000002021000000123-130.75046100119427926261893645128919845392150.00%50100.00%049896351.71%539107750.05%41075854.09%124441513978541946971
14Heat2000020013-21000010012-11000010001-120.5001230019427926171893645128928161032400.00%5180.00%049896351.71%539107750.05%41075854.09%124441513978541946971
15Islanders30100002913-42010000158-31000000145-120.3339142310194279265418936451289933330509222.22%10280.00%249896351.71%539107750.05%41075854.09%124441513978541946971
16Marlies2010100012-1100010001011010000002-220.500112111942792615189364512891563136200.00%30100.00%049896351.71%539107750.05%41075854.09%124441513978541946971
17Monsters30101001710-30000000000030101001710-330.5007111800194279264618936451289491621583133.33%8450.00%049896351.71%539107750.05%41075854.09%124441513978541946971
18Moose211000001101010000001-11100000010120.50011201194279263218936451289248831300.00%4175.00%149896351.71%539107750.05%41075854.09%124441513978541946971
19Penguins211000008801010000037-41100000051420.5008111900194279264818936451289361544356350.00%7271.43%049896351.71%539107750.05%41075854.09%124441513978541946971
20Phantoms21000010624100000102111100000041341.00068140019427926271893645128923208337114.29%4175.00%049896351.71%539107750.05%41075854.09%124441513978541946971
21Reign220000001376110000006241100000075241.00013223500194279264618936451289411351238562.50%80100.00%049896351.71%539107750.05%41075854.09%124441513978541946971
22Roadrunners30300000415-111010000026-42020000029-700.0004610001942792667189364512899729714610220.00%8362.50%049896351.71%539107750.05%41075854.09%124441513978541946971
23Rocket4110000258-33010000227-51100000031240.500581300194279265718936451289663339484125.00%12283.33%049896351.71%539107750.05%41075854.09%124441513978541946971
24Senators4210100014954210100014950000000000060.7501422360019427926831893645128912353466912758.33%13469.23%149896351.71%539107750.05%41075854.09%124441513978541946971
25Silver Knights2010100067-1100010004311010000024-220.50069150019427926331893645128925816306233.33%3233.33%149896351.71%539107750.05%41075854.09%124441513978541946971
26Stars20100010440100000103211010000012-120.5004610001942792626189364512895115102322100.00%50100.00%049896351.71%539107750.05%41075854.09%124441513978541946971
27Thunderbirds20200000310-71010000014-31010000026-400.00035800194279262818936451289771418314250.00%4325.00%049896351.71%539107750.05%41075854.09%124441513978541946971
28Wild20200000210-81010000012-11010000018-700.000235001942792640189364512897725633400.00%3233.33%049896351.71%539107750.05%41075854.09%124441513978541946971
29Wolf Pack30002100651100010001012000110055050.833681401194279264718936451289632218457114.29%4250.00%049896351.71%539107750.05%41075854.09%124441513978541946971
30Wolves512010011112-1211000004403010100178-150.500111728011942792662189364512898821448310330.00%12375.00%049896351.71%539107750.05%41075854.09%124441513978541946971
Total751530096312152200-4838715052367493-19378150440678107-29720.4801522333854619427926109718936451289149449873411961494429.53%1674871.26%549896351.71%539107750.05%41075854.09%124441513978541946971
_Since Last GM Reset751530096312152200-4838715052367493-19378150440678107-29720.4801522333854619427926109718936451289149449873411961494429.53%1674871.26%549896351.71%539107750.05%41075854.09%124441513978541946971
_Vs Conference428150820988109-212157040054244-22138042044665-19430.51288137225241942792660118936451289822267370691762026.32%902967.78%249896351.71%539107750.05%41075854.09%124441513978541946971
_Vs Division15610030061748-3174501004920-1182502002828-20240.80017254201194279262381893645128937410115022529827.59%301066.67%149896351.71%539107750.05%41075854.09%124441513978541946971

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
7572L115223338510971494498734119646
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
75153096312152200
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3871552367493
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
37815440678107
Derniers 10 matchs
WLOTWOTL SOWSOL
350101
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1494429.53%1674871.26%5
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
1893645128919427926
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
49896351.71%539107750.05%41075854.09%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
124441513978541946971


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
19Senators3IceHogs2LSommaire du match
225IceHogs2Bruins1WXSommaire du match
437Barracuda2IceHogs1LXXSommaire du match
557IceHogs3Wolves2WXSommaire du match
667Rocket3IceHogs2LXXSommaire du match
779IceHogs2Comets4LSommaire du match
997IceHogs0Monsters1LXXSommaire du match
10107IceHogs1Barracuda3LSommaire du match
11123Barracuda0IceHogs2WSommaire du match
12142IceHogs0Roadrunners6LSommaire du match
13151Senators2IceHogs5WSommaire du match
15175Islanders4IceHogs2LSommaire du match
16186IceHogs0Wolf Pack1LXSommaire du match
17207Bruins2IceHogs1LXXSommaire du match
18221Rocket1IceHogs0LXXSommaire du match
19231IceHogs6Monsters5WXSommaire du match
20249IceHogs3Wolves4LXXSommaire du match
23267Islanders4IceHogs3LXXSommaire du match
24280IceHogs1Griffins3LSommaire du match
25296Canucks5IceHogs3LSommaire du match
27313IceHogs1Wolves2LSommaire du match
28325Griffins2IceHogs3WSommaire du match
29343IceHogs2Thunderbirds6LSommaire du match
30359Silver Knights3IceHogs4WXSommaire du match
31372IceHogs3Checkers1WSommaire du match
32386IceHogs1Wild8LSommaire du match
33397IceHogs4Phantoms1WSommaire du match
34405Admirals1IceHogs2WXXSommaire du match
35427Checkers3IceHogs2LXSommaire du match
37451Wild2IceHogs1LSommaire du match
38462IceHogs1Americans3LSommaire du match
39482IceHogs2Silver Knights4LSommaire du match
40489IceHogs2Bruins3LXXSommaire du match
41499Wolves0IceHogs2WSommaire du match
42521Rocket3IceHogs0LSommaire du match
44549Bears4IceHogs0LSommaire du match
45562IceHogs0Marlies2LSommaire du match
46577Marlies0IceHogs1WXSommaire du match
47596IceHogs4Crunch2WSommaire du match
48609Stars2IceHogs3WXXSommaire du match
49624IceHogs0Admirals1LXXSommaire du match
50637IceHogs0Barracuda3LSommaire du match
51647IceHogs3Canucks4LXSommaire du match
52661Gulls0IceHogs2WSommaire du match
53677Americans2IceHogs1LSommaire du match
54699Phantoms1IceHogs2WXXSommaire du match
55712IceHogs2Roadrunners3LSommaire du match
57730IceHogs4Islanders5LXXSommaire du match
58738IceHogs0Heat1LXSommaire du match
59749Condors1IceHogs2WXSommaire du match
60771Thunderbirds4IceHogs1LSommaire du match
62793Eagles4IceHogs0LSommaire du match
64812IceHogs1Monsters4LSommaire du match
65822Heat2IceHogs1LXSommaire du match
67841IceHogs5Wolf Pack4WXSommaire du match
68853Penguins7IceHogs3LSommaire du match
69867IceHogs5Comets2WSommaire du match
70886IceHogs5Penguins1WSommaire du match
71897Senators1IceHogs3WSommaire du match
73914Reign2IceHogs6WSommaire du match
74936Roadrunners6IceHogs2LSommaire du match
76950IceHogs1Stars2LSommaire du match
78969IceHogs1Moose0WSommaire du match
79977Comets1IceHogs0LXXSommaire du match
811002Senators3IceHogs4WXSommaire du match
821017IceHogs0Condors4LSommaire du match
831034Wolves4IceHogs2LSommaire du match
841043IceHogs2Gulls3LXXSommaire du match
861062IceHogs1Eagles2LXSommaire du match
871074Moose1IceHogs0LSommaire du match
881093Comets3IceHogs2LSommaire du match
901108IceHogs7Reign5WSommaire du match
911125IceHogs3Rocket1WSommaire du match
921136Wolf Pack0IceHogs1WXSommaire du match
931154Barracuda5IceHogs3LSommaire du match
951167IceHogs-Senators-
961187IceHogs-Rocket-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
971196IceHogs-Senators-
981201Monsters-IceHogs-
991221IceHogs-Bears-
1001229IceHogs-Comets-
1011239Monsters-IceHogs-
1021250IceHogs-Bears-
1041269Crunch-IceHogs-
1071300Barracuda-IceHogs-
1101324Crunch-IceHogs-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance52,48828,459
Assistance PCT69.06%74.89%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
5 2130 - 71.01% 88,771$3,373,310$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
3,513,541$ 3,041,617$ 3,041,617$ 1,000,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
26,264$ 2,673,322$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
443,857$ 19 36,086$ 685,634$




IceHogs 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

IceHogs 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

IceHogs 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

IceHogs 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

IceHogs 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