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Heat
GP: 71 | W: 40 | L: 18 | OTL: 13 | P: 93
GF: 191 | GA: 167 | PP%: 30.68% | PK%: 79.19%
DG: Ray Whiddon | Morale : 58 | Moyenne d’équipe : 59
Prochains matchs #1095 vs Roadrunners

Centre de jeu
Stars
47-13-11, 105pts
1
0 Heat
40-18-13, 93pts
Team Stats
L1SéquenceL1
23-7-5Fiche domicile22-8-5
24-6-6Fiche domicile18-10-8
5-2-3Derniers 10 matchs7-1-2
3.13Buts par match 2.69
2.24Buts contre par match 2.35
28.67%Pourcentage en avantage numérique30.68%
75.00%Pourcentage en désavantage numérique79.19%
Heat
40-18-13, 93pts
2
4 Rocket
43-13-15, 101pts
Team Stats
L1SéquenceW3
22-8-5Fiche domicile24-5-6
18-10-8Fiche domicile19-8-9
7-1-2Derniers 10 matchs6-0-4
2.69Buts par match 2.37
2.35Buts contre par match 1.89
30.68%Pourcentage en avantage numérique32.17%
79.19%Pourcentage en désavantage numérique73.03%
Heat
40-18-13, 93pts
Jour 88
Roadrunners
32-28-10, 74pts
Statistiques d’équipe
L1SéquenceW2
22-8-5Fiche domicile17-13-5
18-10-8Fiche visiteur15-15-5
7-1-210 derniers matchs4-5-1
2.69Buts par match 3.84
2.35Buts contre par match 3.84
30.68%Pourcentage en avantage numérique24.44%
79.19%Pourcentage en désavantage numérique72.41%
Bruins
41-20-10, 92pts
Jour 90
Heat
40-18-13, 93pts
Statistiques d’équipe
W2SéquenceL1
19-9-6Fiche domicile22-8-5
22-11-4Fiche visiteur18-10-8
7-1-210 derniers matchs7-1-2
2.25Buts par match 2.69
2.03Buts contre par match 2.69
29.87%Pourcentage en avantage numérique30.68%
64.29%Pourcentage en désavantage numérique79.19%
Heat
40-18-13, 93pts
Jour 91
Bruins
41-20-10, 92pts
Statistiques d’équipe
L1SéquenceW2
22-8-5Fiche domicile19-9-6
18-10-8Fiche visiteur22-11-4
7-1-210 derniers matchs7-1-2
2.69Buts par match 2.25
2.35Buts contre par match 2.25
30.68%Pourcentage en avantage numérique29.87%
79.19%Pourcentage en désavantage numérique64.29%
Meneurs d'équipe
Buts
Mike Hardman
36
Passes
Mike Hardman
38
Points
Mike Hardman
74
Bokondji ImamaPlus/Moins
Bokondji Imama
21
Victoires
Erik Portillo
40
Pourcentage d’arrêts
Felix Sandstrom
0.9

Statistiques d’équipe
Buts pour
191
2.69 GFG
Tirs pour
1461
20.58 Avg
Pourcentage en avantage numérique
30.7%
54 GF
Début de zone offensive
40.5%
Buts contre
167
2.35 GAA
Tirs contre
1278
18.00 Avg
Pourcentage en désavantage numérique
79.2%%
36 GA
Début de la zone défensive
32.1%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance1,521
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 BrownX100.0059419679676799643770737625767870796903222,800,000$
2Ryan Suzuki (R)X100.0078728870748186668170596554474662816502421,243,000$
3Mike HardmanX97.008076887476737665506067655950496282640271990,000$
4Dylan Roobroeck (R)X97.0082818268838288597351646459474661836302131,390,000$
5Benoit-Olivier GroulxX100.0074737666735249638062616159474660785902621,340,000$
6Bokondji ImamaX100.009499497983436058255259602549485679590291914,000$
7Dylan Peterson (R)X100.0070776067796669547045595958464658755702431,353,000$
8Curtis DouglasX100.0080945165945353536949556353464657765702621,066,000$
9Aku RatyX100.0075718467735454545056486145474653825602431,108,000$
10Luca Pinelli (R)X100.0060596581605352567165435542454554765602131,284,000$
11Nathan Aspinall (R)XXX100.0084779982793432435537446142474649765302031,269,000$
12Anthony Romano (R)XXX100.0075679763674545476146455944464652785202531,320,000$
13Michael KesselringX100.0077866879847299682565566925636261797002621,144,000$
14Kyle BurroughsX100.0078956767724755612549476725656454796103012,555,000$
15Shai Buium (R)X100.0082799467815455502547406438474651795902331,287,000$
16William VilleneuveX99.007269796971525156255443593946465278570241817,778$
17Aaron NessX100.0070668263666469462536405639464649655503511,000,000$
18Cole ClaytonX100.0075738364735254472540395937464649355502631,336,000$
Rayé
1Oskar Back (R)X100.0063429774775990665867617525555464396502631,485,000$
2Shakir Mukhamadullin (R)X100.0071439273797568692562528025494962646702411,294,167$
MOYENNE D’ÉQUIPE99.65757280717659655748545364415150577360
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)100.00484860904750576054503046464789560251875,000$
2Felix Sandstrom100.004944558149495456525030444449815302921,585,000$
Rayé
MOYENNE D’ÉQUIPE100.0049465886485056585350304545488555
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
1Mike HardmanHeat (CAL)LW71363874-10138701001112056112417.56%31160022.5511172842131000213514342.70%894833000.92006351044
2Connor BrownHeat (CAL)RW64253863-4754876182448913.74%15123619.329112030100000001341.14%5814217201.0205001646
3Ryan SuzukiHeat (CAL)C71163551161810118104143509211.19%16141019.877512211090222525059.53%5513716000.72361013410
4Oskar BackHeat (CAL)C37212445-3205175100285321.00%1578521.22761320762134823251.26%796148011.1505000514
5Dylan RoobroeckHeat (CAL)C71242044-26630111102144457116.67%13148520.927310251030333943054.73%4022719100.5900303381
6Bokondji ImamaHeat (CAL)LW71202343211355513082116447617.24%13132718.70358141084046843120.00%352912010.6504362514
7Shakir MukhamadullinHeat (CAL)D64637430120521039743396.19%52162325.3631720241460112146110%02340000.5300000162
8Michael KesselringHeat (CAL)D6910314141821001079012836597.81%64157122.7841014211241232119110%02729000.5200569323
9Aku RatyHeat (CAL)RW71121426164220998665173518.46%12126417.810664110000003036.36%221213000.4100103233
10Benoit-Olivier GroulxHeat (CAL)C7151217-5220678245162811.11%12100714.190220230001473054.34%2651119000.3414000111
11Kyle BurroughsHeat (CAL)D71113149944079894120202.44%29143520.220113101000382000%01629000.2000332010
12Nathan AspinallHeat (CAL)C/LW/RW71459-5271565695427397.41%9101514.3000002000010050.00%202220000.1800012001
13William VilleneuveHeat (CAL)D7144833010756429131513.79%26124517.54213329000043000%01213000.1301101010
14Anthony RomanoHeat (CAL)C/LW/RW7144840052574715198.51%10103514.590110120001320157.14%141115000.1500000100
15Shai BuiumHeat (CAL)D711567393562944210212.38%39145320.4711221050002122100%0722000.0800520000
16Aaron NessHeat (CAL)D65033-2803349213120%15105616.25000010000021000%1615000.0600000000
17Cole ClaytonHeat (CAL)D42011-4001080000%12596.170000100009000%000000.0800000000
18Dylan PetersonHeat (CAL)C71000-32021161110%12904.10000000000120058.06%314200000000000
19Curtis DouglasHeat (CAL)C71000000410000%0510.7200000000000050.00%60000000000000
20Luca PinelliHeat (CAL)C71000000111000%0180.260000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne13351893074964282439012851359146147379312.94%3732117415.86548614020912977916281090381250.87%2813348322320.47425282129403639
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)714016120.8742.2040980111501187766310.54522701321
2Felix SandstromHeat (CAL)80210.9002.5820900990590002170000
Statistiques d’équipe totales ou en moyenne794018130.8752.214308011159127782531247171321


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$223,214$0$0$No---------------------------Lien / Lien NHL
Aku RatyHeat (CAL)RW242001-07-05FINNo190 Lbs6 ft1NoNoN/ANoNo32025-10-17FalseFalsePro & Farm1,108,000$247,321$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$294,643$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$299,107$0$0$No1,340,000$--------1,340,000$--------No--------Lien
Bokondji ImamaHeat (CAL)LW291996-08-03CANNo221 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm914,000$204,018$0$0$No---------------------------Lien / Lien NHL
Cole ClaytonHeat (CAL)D262000-02-29ABNo198 Lbs6 ft2NoNoTrade2025-01-31NoNo32025-10-22FalseFalsePro & Farm1,336,000$298,214$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$625,000$0$0$No2,800,000$--------2,800,000$--------No--------Lien / Lien NHL
Curtis DouglasHeat (CAL)C262000-03-06ONTNo242 Lbs6 ft9NoNoN/ANoNo2FalseFalsePro & Farm1,066,000$237,946$0$0$No1,066,000$--------1,066,000$--------No--------Lien
Dylan PetersonHeat (CAL)C242002-01-08USAYes203 Lbs6 ft4NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,353,000$302,009$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$310,268$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$195,312$0$0$No---------------------------Lien
Felix SandstromHeat (CAL)G291997-01-12SWENo214 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm1,585,000$353,795$0$0$No1,585,000$--------1,585,000$--------No--------Lien
Kyle BurroughsHeat (CAL)D301995-07-12CANNo193 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm2,555,000$570,312$0$0$No---------------------------Lien / Lien NHL
Luca PinelliHeat (CAL)C212005-04-05CANYes168 Lbs5 ft9NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,284,000$286,607$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$255,357$0$0$No1,144,000$--------1,144,000$--------No--------Lien
Mike HardmanHeat (CAL)LW271999-02-05USANo205 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm990,000$220,982$0$0$No---------------------------Lien
Nathan AspinallHeat (CAL)C/LW/RW202006-03-30ONYes194 Lbs6 ft7NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,269,000$283,259$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$331,473$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$277,455$0$0$No1,243,000$--------1,243,000$--------No--------Lien
Shai BuiumHeat (CAL)D232003-03-26USAYes210 Lbs6 ft3NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,287,000$287,277$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$288,877$0$0$No---------------------------Lien
William VilleneuveHeat (CAL)D242002-03-20QUENo183 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm817,778$182,540$0$0$No---------------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2225.77201 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 KesselringWilliam Villeneuve40122
2Kyle BurroughsShai Buium30122
3William VilleneuveAaron Ness20122
4Michael KesselringKyle Burroughs10122
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 KesselringWilliam Villeneuve60122
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 KesselringWilliam Villeneuve60122
2Kyle BurroughsShai Buium40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Mike Hardman60122Michael KesselringAaron Ness60122
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 KesselringWilliam Villeneuve60122
2Kyle BurroughsShai Buium40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Mike HardmanConnor BrownRyan SuzukiMichael KesselringKyle Burroughs
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Mike HardmanConnor BrownRyan SuzukiMichael KesselringKyle Burroughs
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
1Admirals512011001416-22010100057-23110010099050.5001424380135766913115345509580518328947217741.18%12558.33%1599111753.63%44488550.17%38875751.25%126248812727921778886
2Americans412010001011-1110000003213020100079-240.5001018280035766913104345509580519839948116531.25%12283.33%0599111753.63%44488550.17%38875751.25%126248812727921778886
3Barracuda1000010034-11000010034-10000000000010.5003580035766913173455095805121320163133.33%5260.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
4Bears2110000047-3110000003211010000015-420.50047110035766913343455095805161121241100.00%6350.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
5Canucks22000000725110000003211100000040441.000712190135766913323455095805128517374375.00%10100.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
6Checkers300011011112-100000000000300011011112-140.66711182900357669135734550958051411138576350.00%9366.67%1599111753.63%44488550.17%38875751.25%126248812727921778886
7Comets1000000134-11000000134-10000000000010.500358003576691331345509580511914184250.00%2150.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
8Condors31100001660211000004311000000123-130.5006121801357669136034550958051641527616233.33%6266.67%0599111753.63%44488550.17%38875751.25%126248812727921778886
9Crunch22000000624110000003121100000031241.000691500357669133834550958051321113349222.22%40100.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
10Eagles412000011011-12020000014-32100000197230.375101626003576691381345509580515219286912216.67%4175.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
11Griffins211000004401010000024-21100000020220.50047110135766913563455095805129547439222.22%7185.71%0599111753.63%44488550.17%38875751.25%126248812727921778886
12Gulls11000000422000000000001100000042221.000461000357669132734550958051215141911100.00%20100.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
13IceHogs20002000312100010001011000100021141.000336013576691328345509580511748235120.00%40100.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
14Islanders10000010321100000103210000000000021.00033600357669133134550958051458621200.00%30100.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
15Marlies2000000224-21000000112-11000000112-120.5002240035766913413455095805130112633200.00%30100.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
16Monsters21100000330110000002021010000013-220.50034711357669132534550958051219638200.00%30100.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
17Moose6310200013853200100072531101000660100.83313193201357669131073455095805169192712712325.00%11190.91%0599111753.63%44488550.17%38875751.25%126248812727921778886
18Penguins63101100131123300000010553010110036-390.7501321340135766913123345509580517325651259222.22%15286.67%0599111753.63%44488550.17%38875751.25%126248812727921778886
19Phantoms211000005411010000023-11100000031220.500581300357669134434550958051401221385120.00%80100.00%3599111753.63%44488550.17%38875751.25%126248812727921778886
20Reign2100100013103100010005411100000086241.00013213400357669135934550958051822027356116.67%6266.67%1599111753.63%44488550.17%38875751.25%126248812727921778886
21Roadrunners11000000615110000006150000000000021.000610160035766913233455095805130811188337.50%30100.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
22Rocket2010001045-1100000102111010000024-220.50044800357669133934550958051361115394250.00%5420.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
23Senators220000001064110000005321100000053241.00010162600357669134134550958051411621335240.00%30100.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
24Silver Knights2110000045-1110000004311010000002-220.500461000357669132634550958051321473345120.00%9366.67%0599111753.63%44488550.17%38875751.25%126248812727921778886
25Stars420001017432000010102-22200000072560.7507121901357669137034550958051551728696233.33%9188.89%0599111753.63%44488550.17%38875751.25%126248812727921778886
26Thunderbirds20200000410-61010000014-31010000036-300.000461000357669133934550958051691422346233.33%6183.33%0599111753.63%44488550.17%38875751.25%126248812727921778886
27Wild2110000067-11010000036-31100000031220.500691500357669134534550958051572326273133.33%8275.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
28Wolf Pack21000100853110000006241000010023-130.750814220035766913463455095805125728307342.86%40100.00%0599111753.63%44488550.17%38875751.25%126248812727921778886
29Wolves11000000505110000005050000000000021.000510150135766913223455095805171613100.00%30100.00%1599111753.63%44488550.17%38875751.25%126248812727921778886
Total712918096271911672435168042239373203613100540498944930.65519130749811035766913146134550958051127837382412851765430.68%1733679.19%7599111753.63%44488550.17%38875751.25%126248812727921778886
_Since Last GM Reset712918096271911672435168042239373203613100540498944930.65519130749811035766913146134550958051127837382412851765430.68%1733679.19%7599111753.63%44488550.17%38875751.25%126248812727921778886
_Vs Conference461613074151191154218603112494452587043037071-1570.6201191923110535766913984345509580518572485468631173328.21%1142280.70%6599111753.63%44488550.17%38875751.25%126248812727921778886
_Vs Division171180640344368106302101341816755043021018-8411.20644721161335766913356345509580512917514832431825.81%44686.36%4599111753.63%44488550.17%38875751.25%126248812727921778886

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
7193L1191307498146112783738241285110
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
7129189627191167
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3516842239373
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
36131054049894
Derniers 10 matchs
WLOTWOTL SOWSOL
710101
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1765430.68%1733679.19%7
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
3455095805135766913
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
599111753.63%44488550.17%38875751.25%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
126248812727921778886


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
53676Heat4Canucks0WSommaire du match
54688Reign4Heat5WXSommaire du match
55709Eagles3Heat1LSommaire du match
57726Heat2Admirals3LXSommaire du match
58738IceHogs0Heat1WXSommaire du match
59761Admirals3Heat4WXSommaire du match
61777Heat4Eagles1WSommaire du match
62790Heat3Checkers4LXSommaire du match
63803Monsters0Heat2WSommaire du match
65822Heat2IceHogs1WXSommaire du match
66832Wolf Pack2Heat6WSommaire du match
67848Heat3Thunderbirds6LSommaire du match
68860Heat2Condors3LXXSommaire du match
69869Wild6Heat3LSommaire du match
71893Marlies2Heat1LXXSommaire du match
72910Heat5Senators3WSommaire du match
74924Wolves0Heat5WSommaire du match
75937Heat2Wolf Pack3LXSommaire du match
76954Moose1Heat3WSommaire du match
78974Heat2Griffins0WSommaire du match
79985Moose1Heat2WXSommaire du match
811005Rocket1Heat2WXXSommaire du match
821015Heat4Gulls2WSommaire du match
831029Heat3Moose2WSommaire du match
851047Bears2Heat3WSommaire du match
861070Stars1Heat0LXXSommaire du match
871079Heat2Rocket4LSommaire du match
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
Assistance35,72717,500
Assistance PCT51.04%50.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
8 1521 - 50.69% 98,397$3,443,911$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
3,062,423$ 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$ 2,285,600$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
787,180$ 25 35,229$ 880,725$




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