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Connexion

Heat
GP: 82 | W: 35 | L: 40 | OTL: 7 | P: 77
GF: 287 | GA: 308 | PP%: 23.53% | PK%: 78.33%
DG: Martin Bétit | Morale : 50 | Moyenne d’équipe : 51
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Centre de jeu
Chill
32-44-6, 70pts
4
FINAL
7 Heat
35-40-7, 77pts
Team Stats
W1StreakL1
21-19-1Home Record19-17-5
11-25-5Away Record16-23-2
4-4-2Last 10 Games5-4-1
3.54Buts par match 3.50
4.13Buts contre par match 3.76
17.00%Pourcentage en avantage numérique23.53%
76.06%Pourcentage en désavantage numérique78.33%
Sharks
50-23-9, 109pts
4
FINAL
3 Heat
35-40-7, 77pts
Team Stats
W3StreakL1
28-9-4Home Record19-17-5
22-14-5Away Record16-23-2
8-2-0Last 10 Games5-4-1
4.02Buts par match 3.50
3.56Buts contre par match 3.76
19.78%Pourcentage en avantage numérique23.53%
75.69%Pourcentage en désavantage numérique78.33%
Meneurs d'équipe
Buts
Mikhail Maltsev
39
Passes
Grigori Denisenko
54
Points
Mikhail Maltsev
91
Plus/Moins
Ryan MacInnis
20
Victoires
Michael Dipietro
32
Pourcentage d’arrêts
Dylan Garand
0.919

Statistiques d’équipe
Buts pour
287
3.50 GFG
Tirs pour
3147
38.38 Avg
Pourcentage en avantage numérique
23.5%
56 GF
Début de zone offensive
40.3%
Buts contre
308
3.76 GAA
Tirs contre
3357
40.94 Avg
Pourcentage en désavantage numérique
78.3%%
44 GA
Début de la zone défensive
39.7%
Informations de l'équipe

Directeur généralMartin Bétit
DivisionWest
ConférenceOuest
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,881
Billets de saison300


Informations de la formation

Équipe Pro22
Équipe Mineure20
Limite contact 42 / 50
Espoirs14


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 moyen
1Adam GaudetteXXX100.007754907765597566476359647563630506202511,800,000$
2Mikhail MaltsevXX100.00824596747451806673505568254949050600232750,000$
3Charles HudonXX100.00706876636857556650606863654444050590271750,000$
4Ryan MacInnisXX100.00787781647761626075575866554646050590251850,000$
5Grigori Denisenko (R)XX100.00746791786753516150566163584444050580213925,000$
6Riley TufteX100.00734587688948765744505966254444050580232950,000$
7Hudson FaschingX100.00804499657455625525505567755555050570263600,000$
8Alexander Campbell (R)X100.00393099705561774848414739495454050500204700,000$
9John Farinacci (R)X100.00484399656954694353364243445454050480204700,000$
10Alexandr Darin (R)X100.00443799656250673647313438365858050450214650,000$
11Ville HeinolaX100.00714277806466646225694769254646050620202925,002$
12Jacob MoverareX100.00714396687470645725494776254545050620233900,000$
13Nicolas BeaudinX100.00666372666368744825404057384646050550212894,168$
14Julius Honka (R)X100.00696688666651534725393859384444050530251950,000$
15Ryan Johnson (R)X100.00443899646356793625372941305454050490204825,000$
16Mattias Norlinder (R)X100.00474199626745623125273042325858050470214700,000$
17Anthony Florentino (R)X100.00293737377625252937282837313230050350261560,000$
Rayé
1Aapeli Rasanen (R)XHO3137373767292931373030373332300503402300$
2Cole Ully (R)XXHO2937373746252529372828373132300503202600$
3Ryan Pilon (R)X100.00303737376827273037292937323230050350241600,000$
MOYENNE D’ÉQUIPE100.0058488062685159484144445341474605051
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 moyen
1Michael Dipietro (R)100.0049415173514950545151304444050510221792,500$
2Dylan Garand (R)100.0044526467394249494243294441050470193650,000$
Rayé
MOYENNE D’ÉQUIPE100.004747587045465052474730444305049
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Mikhail MaltsevHeat (Cal)C/LW80395291181601162103338623111.71%29149918.7491019531680117905258.23%162800021.2125000743
2Grigori DenisenkoHeat (Cal)LW/RW8031548519255551633521032558.81%23137217.166131947170000043345.92%9800001.2400001471
3Adam GaudetteHeat (Cal)C/LW/RW78364985153151541953538925710.20%40161920.7689176019310161688145.70%54700021.0514010357
4Ryan MacInnisHeat (Cal)C/LW782949782080201411222658518910.94%22136317.4881422451670001244256.17%41300011.1401112433
5Jacob MoverareHeat (Cal)D8020547457410155116206581269.71%188175521.9491726792180001145310.00%000000.8400010515
6Charles HudonHeat (Cal)LW/RW78283765134820112108301772079.30%34142018.2141216481930003742239.66%11600000.9201103332
7Riley TufteHeat (Cal)LW80272956-26275871313131032438.63%37122615.3325720550000161345.28%10600000.9100001430
8Hudson FaschingHeat (Cal)RW78211940-43275122135283681917.42%45112314.40224525000012133.75%8000010.7100000333
9Ville HeinolaHeat (Cal)D34928377180826362204914.52%5781223.903473387011051120.00%000000.9100000013
10Cody GlassCalgaryC/RW3813173049581137163371127.98%1488723.3711215870001705055.63%126900100.6803001124
11Nicolas BeaudinHeat (Cal)D80520253540159427319546.85%119148218.54257241550003107000.00%000000.3400000002
12John FarinacciHeat (Cal)C8022224-410011186214423.23%11112614.09000130000150046.67%130700000.4300000002
13Julius HonkaHeat (Cal)D7841822530091395824396.90%94143218.37145211530000108000.00%000000.3100000010
14Alexander CampbellHeat (Cal)LW8081220-2600148511835896.78%1184910.62000040001900040.91%8800000.4700000000
15Alexandr DarinHeat (Cal)RW804812-132015274912348.16%75887.36000011000000154.55%4400000.4100000000
16Ryan JohnsonHeat (Cal)D8011112-25407217173195.88%72108813.6001122000003000.00%000000.2200000000
17Mattias NorlinderHeat (Cal)D37066-41203249560.00%3856815.3500000000022000.00%000000.2100000000
18Anthony FlorentinoHeat (Cal)D78134-98047690411.11%345016.4300005000015000.00%100000.1600000000
Statistiques d’équipe totales ou en moyenne1297278488766-784657515361718302683821479.19%8752072015.9855971524531721123231013341852.17%569700160.74314238343335
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
1Michael DipietroHeat (Cal)68322850.9073.6038984023425280300.72711680535
2Dylan GarandHeat (Cal)1931020.9193.6291100556760210.33361280100
Statistiques d’équipe totales ou en moyenne87353870.9103.614810402893204051178080635


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 Nouveau joueur Poids Taille Non-échange Disponible pour échange Ballotage forcé Contrat Type Salaire actuel Salaire moyen restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Aapeli RasanenHeat (Cal)C231998-06-01Yes196 Lbs6 ft0NoNoNo0Pro & Farm0$0$NoLien
Adam GaudetteHeat (Cal)C/LW/RW251996-10-02No170 Lbs6 ft1NoNoYes1Pro & Farm1,800,000$0$0$NoLien
Alexander CampbellHeat (Cal)LW202001-02-27Yes150 Lbs5 ft10NoNoNo4Pro & Farm700,000$0$0$No700,000$700,000$700,000$Lien
Alexandr DarinHeat (Cal)RW212000-08-16Yes170 Lbs5 ft11NoNoNo4Pro & Farm650,000$0$0$No650,000$650,000$650,000$Lien
Anthony Florentino (contrat à 1 volet)Heat (Cal)D261995-01-30Yes227 Lbs6 ft1NoNoYes1Pro & Farm560,000$0$0$NoLien
Charles Hudon (contrat à 1 volet)Heat (Cal)LW/RW271994-06-23No190 Lbs5 ft10NoNoYes1Pro & Farm750,000$0$0$NoLien
Cole Ully (contrat à 1 volet)Heat (Cal)LW/RW261995-02-20Yes164 Lbs5 ft10NoNoYes0Pro & Farm0$0$NoLien
Dylan GarandHeat (Cal)G192002-06-07Yes179 Lbs6 ft1NoNoNo3Pro & Farm650,000$0$0$No650,000$650,000$Lien
Grigori DenisenkoHeat (Cal)LW/RW212000-06-24Yes186 Lbs5 ft11NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$Lien
Hudson Fasching (contrat à 1 volet)Heat (Cal)RW261995-07-28No204 Lbs6 ft1NoNoYes3Pro & Farm600,000$0$0$No600,000$600,000$Lien
Jacob MoverareHeat (Cal)D231998-08-31No198 Lbs6 ft3NoNoNo3Pro & Farm900,000$0$0$No900,000$900,000$Lien
John FarinacciHeat (Cal)C202001-02-14Yes190 Lbs6 ft0NoNoNo4Pro & Farm700,000$0$0$No700,000$700,000$700,000$Lien
Julius HonkaHeat (Cal)D251995-12-03Yes180 Lbs5 ft11NoNoYes1Pro & Farm950,000$0$0$NoLien
Mattias NorlinderHeat (Cal)D212000-04-12Yes185 Lbs6 ft0NoNoNo4Pro & Farm700,000$0$0$No700,000$700,000$700,000$Lien
Michael DipietroHeat (Cal)G221999-06-08Yes200 Lbs6 ft0NoNoNo1Pro & Farm792,500$0$0$NoLien
Mikhail MaltsevHeat (Cal)C/LW231998-03-12No198 Lbs6 ft3NoNoNo2Pro & Farm750,000$0$0$No750,000$Lien
Nicolas BeaudinHeat (Cal)D211999-10-07No174 Lbs5 ft11NoNoNo2Pro & Farm894,168$0$0$No894,168$Lien
Riley TufteHeat (Cal)LW231998-04-10No235 Lbs6 ft6NoNoNo2Pro & Farm950,000$0$0$No950,000$Lien
Ryan JohnsonHeat (Cal)D202001-07-24Yes170 Lbs6 ft0NoNoNo4Pro & Farm825,000$0$0$No825,000$825,000$825,000$Lien
Ryan MacInnisHeat (Cal)C/LW251996-02-14No201 Lbs6 ft4NoNoYes1Pro & Farm850,000$0$0$NoLien
Ryan PilonHeat (Cal)D241996-10-10Yes206 Lbs6 ft2NoNoYes1Pro & Farm600,000$0$0$NoLien
Ville HeinolaHeat (Cal)D202001-03-02No178 Lbs5 ft11NoNoNo2Pro & Farm925,002$0$0$No925,002$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2222.77189 Lbs6 ft12.14748,712$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Mikhail MaltsevAdam GaudetteCharles Hudon40122
2Riley TufteRyan MacInnisGrigori Denisenko30122
3Alexander CampbellJohn FarinacciHudson Fasching20122
4Mikhail MaltsevAdam GaudetteAlexandr Darin10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ville HeinolaJacob Moverare40122
2Nicolas BeaudinJulius Honka30122
3Ryan JohnsonMattias Norlinder20122
4Anthony FlorentinoVille Heinola10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Mikhail MaltsevAdam GaudetteCharles Hudon60122
2Riley TufteRyan MacInnisGrigori Denisenko40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ville HeinolaJacob Moverare60122
2Nicolas BeaudinJulius Honka40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Adam GaudetteMikhail Maltsev60122
2Charles HudonRyan MacInnis40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ville HeinolaJacob Moverare60122
2Nicolas BeaudinJulius Honka40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Adam Gaudette60122Ville HeinolaJacob Moverare60122
2Mikhail Maltsev40122Nicolas BeaudinJulius Honka40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Adam GaudetteMikhail Maltsev60122
2Charles HudonRyan MacInnis40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ville HeinolaJacob Moverare60122
2Nicolas BeaudinJulius Honka40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Mikhail MaltsevAdam GaudetteCharles HudonVille HeinolaJacob Moverare
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Mikhail MaltsevAdam GaudetteCharles HudonVille HeinolaJacob Moverare
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Hudson Fasching, Alexander Campbell, John FarinacciHudson Fasching, Alexander CampbellJohn Farinacci
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Ryan Johnson, Mattias Norlinder, Anthony FlorentinoRyan JohnsonMattias Norlinder, Anthony Florentino
Tirs de pénalité
Adam Gaudette, Mikhail Maltsev, Charles Hudon, Ryan MacInnis, Riley Tufte
Gardien
#1 : Michael Dipietro, #2 : Dylan Garand


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
1Admirals42101000141132110000056-12100100095460.750142640001061086610162973108310555213339299210220.00%12375.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
2Baby Hawks3030000059-42020000047-31010000012-100.0005101500106108661097973108310555212242276010110.00%13469.23%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
3Bears2020000059-41010000025-31010000034-100.0005914001061086610649731083105552682412376116.67%5180.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
4Bruins2100000110731000000145-11100000062430.7501017270010610866108097310831055528522214510330.00%3166.67%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
5Cabaret Lady Mary Ann220000001587110000008441100000074341.000152540001061086610152973108310555275168523133.33%40100.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
6Caroline2020000059-41010000025-31010000034-100.000591400106108661050973108310555281268416233.33%4250.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
7Chiefs30101001810-21000000123-12010100067-130.500815230010610866101089731083105552151442065500.00%10190.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
8Chill32100000141132200000012661010000025-340.667142539001061086610109973108310555213143414613646.15%60100.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
9Comets4200110014122210010007522100010077070.87514253900106108661015597310831055521403536801500.00%17194.12%11413290048.72%1294285645.31%715144049.65%1898131720125991060517
10Cougars210010001064100010005411100000052341.000102030001061086610889731083105552832528419333.33%8275.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
11Crunch21100000101001010000045-11100000065120.50010182800106108661076973108310555275189334125.00%20100.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
12Jayhawks312000001112-11100000042220200000710-320.3331121320010610866109597310831055521564929585120.00%12375.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
13Las Vegas41200010161602100001011742020000059-440.500162642101061086610183973108310555222246217714428.57%8450.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
14Manchots211000005501010000034-11100000021120.5005101500106108661073973108310555265198427114.29%4250.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
15Marlies2020000048-41010000035-21010000013-200.000471100106108661057973108310555259258467228.57%40100.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
16Minnesota321000001091220000007521010000034-140.66710152500106108661013597310831055521063919786233.33%7185.71%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
17Monarchs431000001813522000000835211000001010060.750183048001061086610188973108310555213133108819631.58%50100.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
18Monsters2010100078-11010000035-21000100043120.500712190010610866108097310831055528425850400.00%40100.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
19Monsters30300000816-820200000310-71010000056-100.0008142200106108661015497310831055521473923639444.44%9455.56%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
20Oceanics30300000510-51010000023-12020000037-400.00059140010610866109097310831055521123020617114.29%9455.56%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
21Oil Kings312000001013-3211000007701010000036-320.3331019290010610866101049731083105552116261049800.00%5260.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
22Phantoms211000007611010000035-21100000041320.5007132000106108661078973108310555288198348112.50%3166.67%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
23Rocket2110000079-21010000036-31100000043120.5007132000106108661071973108310555277188489333.33%40100.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
24Seattle301001011115-41000010045-120100001710-320.3331121320010610866101219731083105552125536637114.29%20100.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
25Senators22000000936110000006151100000032141.0009172600106108661074973108310555256264419333.33%20100.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
26Sharks4220000015150211000007702110000088040.50015284300106108661013997310831055522006329985240.00%12283.33%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
27Sound Tigers2020000047-31010000035-21010000012-100.0004812001061086610619731083105552942712255240.00%5180.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
28Spiders20100001511-61000000145-11010000016-510.2505712001061086610649731083105552772717423133.33%6266.67%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
29Stars30201000814-61000100032120200000512-720.33381523001061086610859731083105552129561259300.00%6266.67%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
30Thunder210001008711000010034-11100000053230.7508142200106108661075973108310555276261430800.00%7185.71%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
31Wolf Pack21100000990110000004311010000056-120.50091726001061086610799731083105552932410404250.00%50100.00%01413290048.72%1294285645.31%715144049.65%1898131720125991060517
Total82284006314287308-2141151703213146149-341132303101141159-18770.470287515802101061086610314797310831055523357100451516842385623.53%2034478.33%11413290048.72%1294285645.31%715144049.65%1898131720125991060517
_Since Last GM Reset82284006314287308-2141151703213146149-341132303101141159-18770.470287515802101061086610314797310831055523357100451516842385623.53%2034478.33%11413290048.72%1294285645.31%715144049.65%1898131720125991060517
_Vs Conference42122104212148168-202178031117477-321513011017491-17380.4521482664141010610866101674973108310555218055322648671132320.35%1112676.58%11413290048.72%1294285645.31%715144049.65%1898131720125991060517

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8277L1287515802314733571004515168410
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8228406314287308
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4115173213146149
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4113233101141159
Derniers 10 matchs
WLOTWOTL SOWSOL
540100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2385623.53%2034478.33%1
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
97310831055521061086610
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
1413290048.72%1294285645.31%715144049.65%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1898131720125991060517


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
7 - 2022-10-1318Monsters7Heat2BLSommaire du match
9 - 2022-10-1537Heat3Oil Kings6ALSommaire du match
12 - 2022-10-1855Las Vegas3Heat4BWXXSommaire du match
14 - 2022-10-2068Crunch5Heat4BLSommaire du match
16 - 2022-10-2286Caroline5Heat2BLSommaire du match
19 - 2022-10-25104Manchots4Heat3BLSommaire du match
23 - 2022-10-29138Oil Kings3Heat4BWSommaire du match
26 - 2022-11-01155Seattle5Heat4BLXSommaire du match
28 - 2022-11-03169Chill2Heat5BWSommaire du match
30 - 2022-11-05187Spiders5Heat4BLXXSommaire du match
32 - 2022-11-07193Heat1Sound Tigers2ALSommaire du match
33 - 2022-11-08197Heat1Spiders6ALSommaire du match
35 - 2022-11-10211Heat6Bruins2AWSommaire du match
37 - 2022-11-12236Oceanics3Heat2BLSommaire du match
39 - 2022-11-14245Monarchs2Heat4BWSommaire du match
42 - 2022-11-17260Heat5Thunder3AWSommaire du match
44 - 2022-11-19275Heat7Cabaret Lady Mary Ann4AWSommaire du match
46 - 2022-11-21292Heat4Phantoms1AWSommaire du match
48 - 2022-11-23306Heat2Manchots1AWSommaire du match
50 - 2022-11-25322Heat3Bears4ALSommaire du match
51 - 2022-11-26333Heat3Caroline4ALSommaire du match
54 - 2022-11-29358Cabaret Lady Mary Ann4Heat8BWSommaire du match
56 - 2022-12-01372Rocket6Heat3BLSommaire du match
58 - 2022-12-03390Bears5Heat2BLSommaire du match
60 - 2022-12-05401Jayhawks2Heat4BWSommaire du match
62 - 2022-12-07414Minnesota2Heat3BWSommaire du match
64 - 2022-12-09424Heat4Monsters3AWXSommaire du match
65 - 2022-12-10438Heat1Marlies3ALSommaire du match
67 - 2022-12-12448Heat4Rocket3AWSommaire du match
69 - 2022-12-14468Comets2Heat3BWSommaire du match
71 - 2022-12-16482Chiefs3Heat2BLXXSommaire du match
73 - 2022-12-18501Heat3Sharks4ALSommaire du match
75 - 2022-12-20517Heat5Sharks4AWSommaire du match
77 - 2022-12-22531Heat4Monarchs3AWSommaire du match
78 - 2022-12-23544Heat4Admirals3AWXSommaire du match
82 - 2022-12-27555Oil Kings4Heat3BLSommaire du match
83 - 2022-12-28561Heat4Seattle6ALSommaire du match
86 - 2022-12-31587Comets3Heat4BWXSommaire du match
89 - 2023-01-03603Heat0Oceanics3ALSommaire du match
92 - 2023-01-06626Sound Tigers5Heat3BLSommaire du match
94 - 2023-01-08641Heat1Baby Hawks2ALSommaire du match
96 - 2023-01-10655Heat2Chiefs4ALSommaire du match
98 - 2023-01-12670Heat4Chiefs3AWXSommaire du match
100 - 2023-01-14677Heat2Stars6ALSommaire du match
102 - 2023-01-16703Heat2Chill5ALSommaire du match
104 - 2023-01-18715Monsters3Heat1BLSommaire du match
107 - 2023-01-21733Thunder4Heat3BLXSommaire du match
109 - 2023-01-23754Monsters5Heat3BLSommaire du match
112 - 2023-01-26777Baby Hawks3Heat2BLSommaire du match
113 - 2023-01-27786Heat3Seattle4ALXXSommaire du match
123 - 2023-02-06809Heat5Wolf Pack6ALSommaire du match
126 - 2023-02-09825Heat5Cougars2AWSommaire du match
128 - 2023-02-11833Heat6Crunch5AWSommaire du match
130 - 2023-02-13850Heat3Senators2AWSommaire du match
133 - 2023-02-16875Cougars4Heat5BWXSommaire du match
135 - 2023-02-18891Wolf Pack3Heat4BWSommaire du match
137 - 2023-02-20905Phantoms5Heat3BLSommaire du match
139 - 2023-02-22919Heat2Jayhawks4ALSommaire du match
140 - 2023-02-23928Heat2Las Vegas4ALSommaire du match
142 - 2023-02-25945Heat5Monsters6ALSommaire du match
145 - 2023-02-28965Bruins5Heat4BLXXSommaire du match
147 - 2023-03-02979Marlies5Heat3BLSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2023-03-04999Minnesota3Heat4BWSommaire du match
151 - 2023-03-061008Heat3Stars6ALSommaire du match
152 - 2023-03-071018Heat3Minnesota4ALSommaire du match
155 - 2023-03-101037Admirals2Heat3BWSommaire du match
157 - 2023-03-121058Senators1Heat6BWSommaire du match
159 - 2023-03-141072Heat5Jayhawks6ALSommaire du match
161 - 2023-03-161087Heat3Las Vegas5ALSommaire du match
163 - 2023-03-181105Stars2Heat3BWXSommaire du match
165 - 2023-03-201119Heat6Monarchs7ALSommaire du match
166 - 2023-03-211131Heat5Admirals2AWSommaire du match
168 - 2023-03-231144Las Vegas4Heat7BWSommaire du match
170 - 2023-03-251154Sharks3Heat4BWSommaire du match
173 - 2023-03-281183Monarchs1Heat4BWSommaire du match
176 - 2023-03-311202Heat5Comets4AWSommaire du match
178 - 2023-04-021225Admirals4Heat2BLSommaire du match
180 - 2023-04-041236Baby Hawks4Heat2BLSommaire du match
181 - 2023-04-051240Heat3Oceanics4ALSommaire du match
184 - 2023-04-081270Heat2Comets3ALXSommaire du match
186 - 2023-04-101282Chill4Heat7BWSommaire du match
188 - 2023-04-121297Sharks4Heat3BLSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance78,34739,791
Assistance PCT95.55%97.05%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2881 - 96.05% 81,439$3,339,010$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,502,296$ 1,456,167$ 1,456,167$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
7,664$ 1,502,296$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 7,664$ 0$




Heat Leaders statistiques (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 (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