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Heat
GP: 44 | W: 23 | L: 14 | OTL: 7 | P: 53
GF: 115 | GA: 109 | PP%: 27.43% | PK%: 80.00%
DG: Ray Whiddon | Morale : 51 | Moyenne d’équipe : 59
Prochains matchs #676 vs Canucks

Centre de jeu
Admirals
20-18-5, 45pts
4
1 Heat
23-14-7, 53pts
Team Stats
W2SéquenceW1
10-10-2Fiche domicile12-6-3
10-8-3Fiche domicile11-8-4
6-3-1Derniers 10 matchs6-3-1
2.40Buts par match 2.61
2.81Buts contre par match 2.48
30.00%Pourcentage en avantage numérique27.43%
65.45%Pourcentage en désavantage numérique80.00%
Heat
23-14-7, 53pts
3
1 Crunch
11-24-7, 29pts
Team Stats
W1SéquenceL2
12-6-3Fiche domicile7-10-5
11-8-4Fiche domicile4-14-2
6-3-1Derniers 10 matchs3-5-2
2.61Buts par match 2.24
2.48Buts contre par match 3.12
27.43%Pourcentage en avantage numérique22.68%
80.00%Pourcentage en désavantage numérique72.73%
Heat
23-14-7, 53pts
Jour 53
Canucks
17-21-6, 40pts
Statistiques d’équipe
W1SéquenceSOL1
12-6-3Fiche domicile10-8-3
11-8-4Fiche visiteur7-13-3
6-3-110 derniers matchs2-5-3
2.61Buts par match 2.70
2.48Buts contre par match 2.70
27.43%Pourcentage en avantage numérique31.87%
80.00%Pourcentage en désavantage numérique63.16%
Reign
24-17-2, 50pts
Jour 54
Heat
23-14-7, 53pts
Statistiques d’équipe
L2SéquenceW1
10-12-0Fiche domicile12-6-3
14-5-2Fiche visiteur11-8-4
5-4-110 derniers matchs6-3-1
3.88Buts par match 2.61
3.42Buts contre par match 2.61
26.40%Pourcentage en avantage numérique27.43%
72.06%Pourcentage en désavantage numérique80.00%
Eagles
12-20-10, 34pts
Jour 55
Heat
23-14-7, 53pts
Statistiques d’équipe
SOL2SéquenceW1
8-11-3Fiche domicile12-6-3
4-9-7Fiche visiteur11-8-4
3-4-310 derniers matchs6-3-1
2.17Buts par match 2.61
3.17Buts contre par match 2.61
37.37%Pourcentage en avantage numérique27.43%
68.75%Pourcentage en désavantage numérique80.00%
Meneurs d'équipe
Buts
Oskar Back
21
Passes
Shakir Mukhamadullin
26
Points
Oskar Back
45
Bokondji ImamaPlus/Moins
Bokondji Imama
8
Victoires
Erik Portillo
23
Pourcentage d’arrêts
Felix Sandstrom
0.9

Statistiques d’équipe
Buts pour
115
2.61 GFG
Tirs pour
915
20.80 Avg
Pourcentage en avantage numérique
27.4%
31 GF
Début de zone offensive
41.1%
Buts contre
109
2.48 GAA
Tirs contre
830
18.86 Avg
Pourcentage en désavantage numérique
80.0%%
23 GA
Début de la zone défensive
32.4%
Informations de l'équipe

Directeur généralRay Whiddon
EntraîneurAdam Gill
DivisionDivision 4
ConférenceConference 2
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance1,512
Billets de saison1,500


Informations de la formation

Équipe Pro22
Équipe Mineure18
Limite contact 40 / 100
Espoirs101


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
1Connor BrownX100.0059419679676799633768727725757770666903222,800,000$
2Ryan Suzuki (R)X100.0078728769738186668170586654464663756502421,243,000$
3Mike HardmanX96.008076887476737663505965665949496382640271990,000$
4Dylan Roobroeck (R)X97.0081818267828288597350636559464662736202131,390,000$
5Benoit-Olivier GroulxX100.0074737666735249638062626259464661645902621,340,000$
6Bokondji ImamaX100.009499497983436057255259612548485759590291914,000$
7Dylan Peterson (R)X100.0070775966786669557046606058454559625702431,353,000$
8Curtis DouglasX100.0080945165945353546949556453454558625702621,066,000$
9Aku RatyX100.0075718466725454545056486145464654735602431,108,000$
10Luca Pinelli (R)X100.0061596480595352577166445642444455625602031,284,000$
11Anthony Romano (R)XXX100.0076679763674545486146456044454553635202531,320,000$
12Nathan Aspinall (R)XXX100.0084779981783432435537446242464650615201931,269,000$
13Michael KesselringX100.0076866879847299672563536825626262686902621,144,000$
14Shakir Mukhamadullin (R)X100.0071439272787568682561528025494962686702411,294,167$
15Kyle BurroughsX100.0078956767724755612549476725646455676103012,555,000$
16Shai Buium (R)X100.0083799366805455512547406438464652605902231,287,000$
17William VilleneuveX100.007269796870525156255542603945455365570231817,778$
18Aaron NessX100.0070668263666469472537415739454550525503511,000,000$
19Cole ClaytonX100.0076738264735254482541396037454550215502631,336,000$
Rayé
1Oskar Back (R)X100.0063429774775990665867617525555464666502631,485,000$
MOYENNE D’ÉQUIPE99.65757280707559655748545365415050586360
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
1Erik Portillo (R)100.00484860904748555752503046464882550251875,000$
2Felix Sandstrom100.004944558149495455515030444450735302921,585,000$
Rayé
MOYENNE D’ÉQUIPE100.0049465886484955565250304545497854
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Adam Gill40404040404040TUR8111,000,000$


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
1Oskar BackHeat (CAL)C37212445-3205175100285321.00%1578521.22761320762134823251.26%796148011.1505000514
2Mike HardmanHeat (CAL)LW44201939-788406676101367619.80%2399422.59681420850002908250.82%612822000.7800413622
3Connor BrownHeat (CAL)RW37142034-2553447118305311.86%1072919.724481454000001341.98%1313114000.9305001323
4Ryan SuzukiHeat (CAL)C441021316135766987387111.49%1486019.5643715730112363060.00%3552311000.7223100127
5Shakir MukhamadullinHeat (CAL)D4452631-512038696329307.94%36111825.4221214151030111103110%01229000.5500000151
6Bokondji ImamaHeat (CAL)LW4411142589335874976305514.47%1182018.6523510742022542017.39%23247000.6100151312
7Dylan RoobroeckHeat (CAL)C44131023-13115635583244515.66%485619.463147570222532051.10%2272010100.5400102141
8Michael KesselringHeat (CAL)D4231619-11065064537422354.05%3092221.951561476112271000%01417000.4100334210
9Aku RatyHeat (CAL)RW44791683315555546132015.22%777517.63044374000001040.00%1576000.4100102202
10Benoit-Olivier GroulxHeat (CAL)C442810-68038372911186.90%257012.960220160000211056.00%150712000.3500000010
11Kyle BurroughsHeat (CAL)D441895723054502610123.85%2388420.10011168000150000%01222000.2000222000
12William VilleneuveHeat (CAL)D44325210045381810916.67%1875117.09213320000028000%079000.1301000010
13Shai BuiumHeat (CAL)D44044524204361217150%2390120.49000070000081000%0412000.0900310000
14Nathan AspinallHeat (CAL)C/LW/RW44314-5271537483617288.33%661914.0800001000000041.67%121511000.1300012001
15Aaron NessHeat (CAL)D3803304016319180%860015.8100007000013000%1410000.1000000000
16Anthony RomanoHeat (CAL)C/LW/RW441230004032289163.57%760213.70011080000170163.64%11311000.1000000000
17Cole ClaytonHeat (CAL)D15011-400980000%115210.180000100009000%000000.1300000000
18Dylan PetersonHeat (CAL)C44000-100950100%11312.9800000000020070.00%103100000000000
19Curtis DouglasHeat (CAL)C44000000300000%0200.4700000000000050.00%20000000000000
20Luca PinelliHeat (CAL)C44000000000000%050.120000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne829114188302-152823082885891531654412.46%2391310415.8131518212286956111672022952.23%1794228212110.46214161317242023
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
1Erik PortilloHeat (CAL)44231260.8722.3424870597759484310.58312431101
2Felix SandstromHeat (CAL)70210.9002.3517900770450002143000
Statistiques d’équipe totales ou en moyenne51231470.8752.3426660510482952931144444101


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
Aaron NessHeat (CAL)D351990-05-18USANo188 Lbs5 ft10NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm1,000,000$535,714$0$0$No---------------------------Lien / Lien NHL
Aku RatyHeat (CAL)RW242001-07-05FINNo190 Lbs6 ft1NoNoN/ANoNo32025-10-17FalseFalsePro & Farm1,108,000$593,571$0$0$No1,108,000$1,108,000$-------1,108,000$1,108,000$-------NoNo-------Lien
Anthony RomanoHeat (CAL)C/LW/RW252000-10-07ONYes185 Lbs5 ft11NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,320,000$707,143$0$0$No1,320,000$1,320,000$-------1,320,000$1,320,000$-------NoNo-------Lien
Benoit-Olivier GroulxHeat (CAL)C262000-02-06FRANo198 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm1,340,000$717,857$0$0$No1,340,000$--------1,340,000$--------No--------Lien
Bokondji ImamaHeat (CAL)LW291996-08-03CANNo221 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm914,000$489,643$0$0$No---------------------------Lien / Lien NHL
Cole ClaytonHeat (CAL)D262000-02-29ABNo198 Lbs6 ft2NoNoTrade2025-01-31NoNo32025-10-22FalseFalsePro & Farm1,336,000$715,714$0$0$No1,336,000$1,336,000$-------1,336,000$1,336,000$-------NoNo-------Lien
Connor BrownHeat (CAL)RW321994-01-14CANNo184 Lbs6 ft0NoNoTrade2025-09-03NoNo22024-09-16FalseFalsePro & Farm2,800,000$1,500,000$0$0$No2,800,000$--------2,800,000$--------No--------Lien / Lien NHL
Curtis DouglasHeat (CAL)C262000-03-06ONTNo242 Lbs6 ft9NoNoN/ANoNo2FalseFalsePro & Farm1,066,000$571,071$0$0$No1,066,000$--------1,066,000$--------No--------Lien
Dylan PetersonHeat (CAL)C242002-01-08USAYes203 Lbs6 ft4NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,353,000$724,821$0$0$No1,353,000$1,353,000$-------1,353,000$1,353,000$-------NoNo-------Lien
Dylan RoobroeckHeat (CAL)C212004-07-27CANYes205 Lbs6 ft7NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,390,000$744,643$0$0$No1,390,000$1,390,000$-------1,390,000$1,390,000$-------NoNo-------Lien
Erik PortilloHeat (CAL)G252000-09-03SWEYes218 Lbs6 ft6NoNoN/ANoNo1FalseFalsePro & Farm875,000$468,750$0$0$No---------------------------Lien
Felix SandstromHeat (CAL)G291997-01-12SWENo214 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm1,585,000$849,107$0$0$No1,585,000$--------1,585,000$--------No--------Lien
Kyle BurroughsHeat (CAL)D301995-07-12CANNo193 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm2,555,000$1,368,750$0$0$No---------------------------Lien / Lien NHL
Luca PinelliHeat (CAL)C202005-04-05CANYes168 Lbs5 ft9NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,284,000$687,857$0$0$No1,284,000$1,284,000$-------1,284,000$1,284,000$-------NoNo-------Lien
Michael KesselringHeat (CAL)D262000-01-13USANo215 Lbs6 ft5NoNoN/ANoNo2FalseFalsePro & Farm1,144,000$612,857$0$0$No1,144,000$--------1,144,000$--------No--------Lien
Mike HardmanHeat (CAL)LW271999-02-05USANo205 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm990,000$530,357$0$0$No---------------------------Lien
Nathan AspinallHeat (CAL)C/LW/RW192006-03-30ONYes194 Lbs6 ft7NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,269,000$679,821$0$0$No1,269,000$1,269,000$-------1,269,000$1,269,000$-------NoNo-------Lien
Oskar BackHeat (CAL)C262000-03-12SWEYes202 Lbs6 ft4NoNoN/ANoNo32025-10-17FalseFalsePro & Farm1,485,000$795,536$0$0$No1,485,000$1,485,000$-------1,485,000$1,485,000$-------NoNo-------Lien
Ryan SuzukiHeat (CAL)C242001-05-28CANYes196 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm1,243,000$665,893$0$0$No1,243,000$--------1,243,000$--------No--------Lien
Shai BuiumHeat (CAL)D222003-03-26USAYes210 Lbs6 ft3NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,287,000$689,464$0$0$No1,287,000$1,287,000$-------1,287,000$1,287,000$-------NoNo-------Lien
Shakir MukhamadullinHeat (CAL)D242002-01-10RUSYes200 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm1,294,167$693,304$0$0$No---------------------------Lien
William VilleneuveHeat (CAL)D232002-03-20QUENo183 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm817,778$438,095$0$0$No---------------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2225.59201 Lbs6 ft32.091,338,907$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Mike HardmanConnor BrownDylan Roobroeck40122
2Bokondji ImamaRyan SuzukiAku Raty30122
3Nathan AspinallDylan RoobroeckAnthony Romano20122
4Mike HardmanBenoit-Olivier GroulxRyan Suzuki10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Michael KesselringShakir Mukhamadullin40122
2Kyle BurroughsShai Buium30122
3William VilleneuveAaron Ness20122
4Michael KesselringShakir Mukhamadullin10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Mike HardmanConnor BrownDylan Roobroeck60122
2Bokondji ImamaRyan SuzukiAku Raty40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Michael KesselringShakir Mukhamadullin60122
2Kyle BurroughsShai Buium40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Dylan RoobroeckMike Hardman60122
2Ryan SuzukiBokondji Imama40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Michael KesselringShakir Mukhamadullin60122
2Kyle BurroughsShai Buium40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Mike Hardman60122Michael KesselringShakir Mukhamadullin60122
2Ryan Suzuki40122Kyle BurroughsShai Buium40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Dylan RoobroeckMike Hardman60122
2Ryan SuzukiBokondji Imama40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Michael KesselringShakir Mukhamadullin60122
2Kyle BurroughsShai Buium40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Mike HardmanConnor BrownRyan SuzukiMichael KesselringShakir Mukhamadullin
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Mike HardmanConnor BrownRyan SuzukiMichael KesselringShakir Mukhamadullin
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Dylan Roobroeck, Benoit-Olivier Groulx, Bokondji ImamaDylan Roobroeck, Benoit-Olivier GroulxDylan Roobroeck
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Shai Buium, William Villeneuve, Aaron NessShai BuiumShai Buium, William Villeneuve
Tirs de pénalité
Bokondji Imama, Benoit-Olivier Groulx, Ryan Suzuki, Mike Hardman, Dylan Roobroeck
Gardien
#1 : Erik Portillo, #2 : Felix Sandstrom


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
1Admirals31200000810-21010000014-32110000076120.3338142201254342663230318353275116365013538.46%8450.00%039772654.68%28357249.48%25746854.91%8003177874811082544
2Americans412010001011-1110000003213020100079-240.500101828002543426104230318353279839948116531.25%12283.33%039772654.68%28357249.48%25746854.91%8003177874811082544
3Barracuda1000010034-11000010034-10000000000010.500358002543426172303183532721320163133.33%5260.00%039772654.68%28357249.48%25746854.91%8003177874811082544
4Bears1010000015-4000000000001010000015-400.0001230025434261923031835327346822100.00%4250.00%039772654.68%28357249.48%25746854.91%8003177874811082544
5Canucks11000000321110000003210000000000021.00035800254342612230318353271847173266.67%10100.00%039772654.68%28357249.48%25746854.91%8003177874811082544
6Checkers20001001880000000000002000100188030.75081321002543426382303183532723318423133.33%4175.00%139772654.68%28357249.48%25746854.91%8003177874811082544
7Comets1000000134-11000000134-10000000000010.50035800254342631230318353271914184250.00%2150.00%039772654.68%28357249.48%25746854.91%8003177874811082544
8Condors21100000431211000004310000000000020.5004812012543426462303183532747816414250.00%3166.67%039772654.68%28357249.48%25746854.91%8003177874811082544
9Crunch22000000624110000003121100000031241.00069150025434263823031835327321113349222.22%40100.00%039772654.68%28357249.48%25746854.91%8003177874811082544
10Eagles2010000157-21010000001-11000000156-110.250571200254342649230318353272961631600.00%3166.67%039772654.68%28357249.48%25746854.91%8003177874811082544
11Griffins1010000024-21010000024-20000000000000.000235002543426202303183532716130255120.00%6183.33%039772654.68%28357249.48%25746854.91%8003177874811082544
12Islanders10000010321100000103210000000000021.0003360025434263123031835327458621200.00%30100.00%039772654.68%28357249.48%25746854.91%8003177874811082544
13Marlies1000000112-1000000000001000000112-110.5001120025434262523031835327177714100.00%10100.00%039772654.68%28357249.48%25746854.91%8003177874811082544
14Monsters1010000013-2000000000001010000013-200.000112102543426102303183532784222100.00%10100.00%039772654.68%28357249.48%25746854.91%8003177874811082544
15Moose31101000541110000002022010100034-140.667571201254342641230318353273181666400.00%8187.50%039772654.68%28357249.48%25746854.91%8003177874811082544
16Penguins63101100131123300000010553010110036-390.750132134012543426123230318353277325651259222.22%15286.67%039772654.68%28357249.48%25746854.91%8003177874811082544
17Phantoms211000005411010000023-11100000031220.50058130025434264423031835327401221385120.00%80100.00%339772654.68%28357249.48%25746854.91%8003177874811082544
18Reign11000000862000000000001100000086221.00081422002543426352303183532746111518000%5180.00%139772654.68%28357249.48%25746854.91%8003177874811082544
19Roadrunners11000000615110000006150000000000021.00061016002543426232303183532730811188337.50%30100.00%039772654.68%28357249.48%25746854.91%8003177874811082544
20Senators11000000532110000005320000000000021.0005914002543426262303183532726141214300.00%10100.00%039772654.68%28357249.48%25746854.91%8003177874811082544
21Silver Knights2110000045-1110000004311010000002-220.50046100025434262623031835327321473345120.00%9366.67%039772654.68%28357249.48%25746854.91%8003177874811082544
22Stars320001007341000010001-12200000072550.833712190125434265823031835327391120545240.00%5180.00%039772654.68%28357249.48%25746854.91%8003177874811082544
23Thunderbirds1010000014-31010000014-30000000000000.0001230025434261623031835327317914200.00%20100.00%039772654.68%28357249.48%25746854.91%8003177874811082544
24Wild11000000312000000000001100000031221.0003580025434262023031835327241291311100.00%20100.00%039772654.68%28357249.48%25746854.91%8003177874811082544
Total4418140431411510962111600211554782378041036062-2530.602115188303152543426915230318353278302395288281133127.43%1152380.00%539772654.68%28357249.48%25746854.91%8003177874811082544
_Since Last GM Reset4418140431411510962111600211554782378041036062-2530.602115188303152543426915230318353278302395288281133127.43%1152380.00%539772654.68%28357249.48%25746854.91%8003177874811082544
_Vs Conference3211110421383821136500110302731956041035355-2370.5788313521804254342668923031835327603168372619802025.00%871681.61%539772654.68%28357249.48%25746854.91%8003177874811082544
_Vs Division1287042022629-3652001001814463504102815-7281.167264066112543426258230318353272195610624622522.73%33584.85%339772654.68%28357249.48%25746854.91%8003177874811082544

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
4453W111518830391583023952882815
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
4418144314115109
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2111602115547
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
237841036062
Derniers 10 matchs
WLOTWOTL SOWSOL
630100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1133127.43%1152380.00%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
230318353272543426
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
39772654.68%28357249.48%25746854.91%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
8003177874811082544


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
17Heat5Admirals6LSommaire du match
217Heat5Checkers4WXSommaire du match
331Penguins4Heat5WSommaire du match
550Eagles1Heat0LSommaire du match
666Heat2Moose1WXSommaire du match
881Heat2Americans4LSommaire du match
990Moose0Heat2WSommaire du match
10114Condors3Heat1LSommaire du match
11129Heat1Moose3LSommaire du match
12143Comets4Heat3LXXSommaire du match
13150Heat0Penguins3LSommaire du match
15176Stars1Heat0LXSommaire du match
16191Heat3Checkers4LXXSommaire du match
17202Americans2Heat3WSommaire du match
18220Roadrunners1Heat6WSommaire du match
20241Heat4Stars0WSommaire du match
21255Penguins0Heat2WSommaire du match
23268Heat1Marlies2LXXSommaire du match
24281Heat5Eagles6LXXSommaire du match
25292Heat3Phantoms1WSommaire du match
26307Senators3Heat5WSommaire du match
28329Phantoms3Heat2LSommaire du match
29342Heat1Bears5LSommaire du match
30352Heat1Monsters3LSommaire du match
31370Crunch1Heat3WSommaire du match
32391Islanders2Heat3WXXSommaire du match
34411Condors0Heat3WSommaire du match
35425Heat8Reign6WSommaire du match
36440Heat3Wild1WSommaire du match
37453Heat3Stars2WSommaire du match
38463Thunderbirds4Heat1LSommaire du match
40486Barracuda4Heat3LXSommaire du match
41497Heat2Penguins1WXSommaire du match
42515Griffins4Heat2LSommaire du match
43528Heat3Americans2WXSommaire du match
44547Heat2Americans3LSommaire du match
45559Silver Knights3Heat4WSommaire du match
46574Heat0Silver Knights2LSommaire du match
47589Canucks2Heat3WSommaire du match
48606Heat2Admirals0WSommaire du match
49619Penguins1Heat3WSommaire du match
50638Heat1Penguins2LXSommaire du match
51648Admirals4Heat1LSommaire du match
52662Heat3Crunch1WSommaire du match
53676Heat-Canucks-
54688Reign-Heat-
55709Eagles-Heat-
57726Heat-Admirals-
58738IceHogs-Heat-
59761Admirals-Heat-
61777Heat-Eagles-
62790Heat-Checkers-
63803Monsters-Heat-
65822Heat-IceHogs-
66832Wolf Pack-Heat-
67848Heat-Thunderbirds-
68860Heat-Condors-
69869Wild-Heat-
71893Marlies-Heat-
72910Heat-Senators-
74924Wolves-Heat-
75937Heat-Wolf Pack-
76954Moose-Heat-
78974Heat-Griffins-
79985Moose-Heat-
811005Rocket-Heat-
821015Heat-Gulls-
831029Heat-Moose-
851047Bears-Heat-
861070Stars-Heat-
871079Heat-Rocket-
881095Heat-Roadrunners-
901110Bruins-Heat-
911122Heat-Bruins-
921142Checkers-Heat-
941165Gulls-Heat-
961178Heat-Barracuda-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
971195Heat-Wolves-
981200Comets-Heat-
1001227Eagles-Heat-
1011236Heat-Islanders-
1031257Americans-Heat-
1041270Heat-Islanders-
1061292Stars-Heat-
1071299Heat-Comets-
1101326Checkers-Heat-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5030
Assistance21,24910,500
Assistance PCT50.59%50.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
22 1512 - 50.40% 97,733$2,052,400$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,829,408$ 2,945,595$ 2,945,595$ 1,000,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
26,300$ 1,365,100$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
2,150,133$ 60 35,229$ 2,113,740$




Heat 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

Heat 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

Heat 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

Heat 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

Heat 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