Connexion

Heat
GP: 80 | W: 40 | L: 32 | OTL: 8 | P: 88
GF: 337 | GA: 351 | PP%: 23.62% | PK%: 77.43%
DG: Steve Landry | Morale : 39 | Moyenne d’équipe : 64
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Centre de jeu
Griffins
41-31-8, 90pts
4
FINAL
3 Heat
40-32-8, 88pts
Team Stats
W3StreakW1
20-16-4Home Record16-18-6
21-15-4Away Record24-14-2
5-4-1Last 10 Games7-3-0
4.15Buts par match 4.21
3.75Buts contre par match 4.39
21.73%Pourcentage en avantage numérique23.62%
80.84%Pourcentage en désavantage numérique77.43%
Heat
40-32-8, 88pts
4
FINAL
3 Senators
39-31-10, 88pts
Team Stats
W1StreakW1
16-18-6Home Record17-16-7
24-14-2Away Record22-15-3
7-3-0Last 10 Games5-5-0
4.21Buts par match 4.06
4.39Buts contre par match 4.13
23.62%Pourcentage en avantage numérique22.68%
77.43%Pourcentage en désavantage numérique79.65%
Meneurs d'équipe
Buts
Kevin Labanc
51
Passes
Kevin Labanc
73
Points
Kevin Labanc
124
Plus/Moins
Philip Varone
11
Victoires
Michael Hutchinson
36
Pourcentage d’arrêts
Michael Hutchinson
0.88

Statistiques d’équipe
Buts pour
337
4.21 GFG
Tirs pour
2646
33.08 Avg
Pourcentage en avantage numérique
23.6%
73 GF
Début de zone offensive
35.8%
Buts contre
351
4.39 GAA
Tirs contre
2611
32.64 Avg
Pourcentage en désavantage numérique
77.4%
79 GA
Début de la zone défensive
36.3%
Informations de l'équipe

Directeur généralSteve Landry
EntraîneurDan Bylsma
DivisionFritz-Kraatz
ConférenceRobert-Lebel
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,787
Billets de saison300


Informations de la formation

Équipe Pro32
Équipe Mineure21
Limite contact 53 / 250
Espoirs0


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
1Matthew Nieto (R)X100.007127787275797772758072636962584259710241900,000$
2Jake DeBrusk (R)X100.007552807376757370677376656948446661700201500,000$
3Kevin Labanc (R)X100.005927788672707279707170658252465959700204950,000$
4Evgeny Svechnikov (R)X100.006732846487747569766887486847456459690201500,000$
5Philip Varone (R)X100.006924677074737674777471596568633249690262900,000$
6Victor Rask (R)X100.006933777177717371756977617454474862690231950,000$
7Nico Sturm (R)X100.006129866873777461697253706544475449660212500,000$
8Barclay Goodrow (R)X100.007429717166676665626668676145474247650232800,000$
9Peter Cehlarik (R)X100.006445786864696869737167566744445759650211750,000$
10Chris Brown (R)X100.006141797169687263595580516849493321640251700,000$
11Jesper Bratt (R)X100.005647666559686465676462506740407959600182500,000$
12Mathieu Brodeur (R)X100.007028836670757570456858755662512846690261850,000$
13Greg Pateryn (R)X100.007237637172776565567164735861513039680261800,000$
14Rasmus Andersson (R)X100.006536797856616778367661684944456738670201500,000$
15Frank Corrado (R)X100.006740736872737270546755685647474345660231650,000$
16John Gilmour (R)X100.007032756259736472477056625445463741640231600,000$
17Dominik Masin (R)X100.006131826164586546235435724342425928600201500,000$
18Brandon Hickey (R)X100.005926795658585948326340724742424823590203600,000$
Rayé
1Ryan Spooner (R)X100.006231747172717167747768586450474040670242800,000$
2Eric Karlsson (R)X86.167933696376646962596269565344444519620221550,000$
3Ryan Donato (R)X100.007034716075636762696372446342426120620202600,000$
4Vladislav Kamenev (R)X100.006727704669636564565471547042426220590202600,000$
5Tage Thompson (R)X100.005429826561746147616748575643427319570192500,000$
6Radim Zohorna (R)X100.005436725465695756515366405245436220560202500,000$
7Alexander True (R)X100.005939605461506456535350435341415420520191500,000$
8Trevor Carrick (R)X100.005838727761667372367252653744443825640222575,000$
9Petteri Lindbohm (R)X100.005639745962646770426569645345494019630232575,000$
10Christian Jaros (R)X100.006228725957575457296442684842435420590201500,000$
MOYENNE D’ÉQUIPE99.51653475666868686557676361604846513864
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
1Michael Hutchinson100.00697771727574727776707059582961730262975,000$
2Nathan Lieuwen100.00656565606068616669606360583127640252700,000$
Rayé
1Vitek Vanecek100.00606667535569754853725942425628600203600,000$
2Collin Delia (R)100.00704961686652475459516440407019560222500,000$
MOYENNE D’ÉQUIPE100.0066646663646664616463645050473463
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dan Bylsma77706870495064USA421800,000$


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
1Kevin LabancHeat (Cal)RW805173124-744012513137111124113.75%42167320.921331445326211251154146.56%13111126021.48370001164
2Matthew NietoHeat (Cal)LW804960109-1340138902847114217.25%42161720.22141933422531126937257.28%2136426021.3517000583
3Victor RaskHeat (Cal)C78325789-36151181361855012017.30%25136717.53132235322550001155151.97%16493623011.3001100364
4Jake DeBruskHeat (Cal)LW80363470-146101421162408114515.00%39150618.82108182721112372456045.35%864738010.9327002451
5Philip VaroneHeat (Cal)C66244266118801241501776110813.56%32134120.3349131416522471631355.12%17183227000.9800000414
6Rasmus AnderssonHeat (Cal)D716455113159414215661543.85%111182125.6511112192090227249100.00%05452000.5600100111
7Ryan SpoonerHeat (Cal)C76183149-1626010086130589313.85%2197912.890550490003553053.12%5293020001.0000000213
8Evgeny SvechnikovHeat (Cal)RW8022254768010367145548715.17%22128116.02729191990002781248.33%603615000.7301000213
9Peter CehlarikHeat (Cal)LW80133144-4100786416147998.07%1899112.390000221341162047.31%933111000.8900000111
10Frank CorradoHeat (Cal)D778303867201011209536278.42%87172522.41156161980330219100.00%01550000.4400000111
11Mathieu BrodeurHeat (Cal)D72102737-162009712711428468.77%113179124.883811202250116230010.00%01659000.4111000102
12Greg PaterynHeat (Cal)D6492332-1911001231079945509.09%84155124.244610121970115171100.00%02854000.4100000011
13Barclay GoodrowHeat (Cal)RW741811291300944397405818.56%2774710.1000003000002040.00%201812000.7800000002
14Nico SturmHeat (Cal)C8082129-510057898933578.99%2685610.710000611251401046.25%413918000.6800000110
15Jesper BrattHeat (Cal)LW80116170200402567315116.42%126207.7600000000173033.33%12145000.5500000010
16Trevor CarrickHeat (Cal)D4911314522030453916142.56%4368914.07000023011052000.00%01030000.4100000000
17John GilmourHeat (Cal)D7221113726047572713127.41%3789112.3910119000022000.00%0423000.2900000000
18Tyler ShattockFlamesRW447613-6260412151182613.73%144019.1200000000000035.71%14109000.6500000100
19Petteri LindbohmHeat (Cal)D49279-21401446371395.41%3368614.02101114000066000.00%0921000.2600000000
20Chris BrownHeat (Cal)C203253001411332189.09%31748.75000000000110046.74%9243000.5700000001
21Dominik MasinHeat (Cal)D2422411801640237138.70%2649720.74000251000061000.00%007000.1600000000
22Eric KarlssonHeat (Cal)LW3122411204316227189.09%102768.92000001012370142.86%723000.2900000000
23Brandon HickeyHeat (Cal)D7101-5202331133.33%49413.481011900001000100.00%104000.2100000000
24Tage ThompsonHeat (Cal)RW6000-120301200.00%0467.810000000000000.00%000000.0000000000
Statistiques d’équipe totales ou en moyenne1440335559894-3472220174417322646886148912.66%8712363116.4173126199259235091625612165381152.30%5038580536060.76724202373431
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 HutchinsonHeat (Cal)67362270.8803.8738340124720561017640.63219663030
2Nathan LieuwenHeat (Cal)143710.8325.516860063374184000.66731414000
3Vitek VanecekHeat (Cal)101300.8195.87327003217782000.0000062000
Statistiques d’équipe totales ou en moyenne91403280.8694.2348490134226071283640.636228079030


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 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
Alexander TrueHeat (Cal)C191997-01-01Yes200 Lbs6 ft5NoNoNo1Pro & Farm500,000$0$0$No
Barclay GoodrowHeat (Cal)RW231993-01-01Yes215 Lbs6 ft2NoNoNo2Pro & Farm800,000$0$0$No850,000$
Brandon HickeyHeat (Cal)D201996-01-01Yes201 Lbs6 ft2NoNoNo3Pro & Farm600,000$0$0$No600,000$600,000$
Chris BrownHeat (Cal)C251991-01-01Yes215 Lbs6 ft2NoNoNo1Pro & Farm700,000$0$0$No
Christian JarosHeat (Cal)D201996-01-01Yes222 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$No
Collin DeliaHeat (Cal)G221994-01-01Yes207 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$
Dominik MasinHeat (Cal)D201996-01-01Yes196 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$No
Eric Karlsson (sur la masse salariale)Heat (Cal)LW221994-01-01Yes161 Lbs5 ft11NoNoNo1Pro & Farm550,000$0$0$Yes
Evgeny SvechnikovHeat (Cal)RW201996-01-01Yes208 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$No
Frank CorradoHeat (Cal)D231993-01-01Yes195 Lbs6 ft0NoNoNo1Pro & Farm650,000$0$0$No
Greg PaterynHeat (Cal)D261990-01-01Yes214 Lbs6 ft2NoNoNo1Pro & Farm800,000$0$0$No
Jake DeBruskHeat (Cal)LW201996-01-01Yes188 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$No
Jesper BrattHeat (Cal)LW181998-01-01Yes185 Lbs5 ft10NoNoNo2Pro & Farm500,000$0$0$No500,000$
John GilmourHeat (Cal)D231993-01-01Yes185 Lbs6 ft0NoNoNo1Pro & Farm600,000$0$0$No
Kevin LabancHeat (Cal)RW201996-01-01Yes185 Lbs5 ft11NoNoNo4Pro & Farm950,000$0$0$No1,200,000$1,900,000$2,800,000$
Mathieu BrodeurHeat (Cal)D261990-01-01Yes215 Lbs6 ft6NoNoNo1Pro & Farm850,000$0$0$No
Matthew NietoHeat (Cal)LW241992-01-01Yes190 Lbs5 ft11NoNoNo1Pro & Farm900,000$0$0$No
Michael HutchinsonHeat (Cal)G261990-01-01No202 Lbs6 ft3NoNoNo2Pro & Farm975,000$0$0$No975,000$
Nathan LieuwenHeat (Cal)G251991-01-01No189 Lbs6 ft5NoNoNo2Pro & Farm700,000$0$0$No700,000$
Nico SturmHeat (Cal)C211995-01-01Yes207 Lbs6 ft3NoNoNo2Pro & Farm500,000$0$0$No500,000$
Peter CehlarikHeat (Cal)LW211995-01-01Yes185 Lbs6 ft2NoNoNo1Pro & Farm750,000$0$0$No
Petteri LindbohmHeat (Cal)D231993-01-01Yes209 Lbs6 ft3NoNoNo2Pro & Farm575,000$0$0$No600,000$
Philip VaroneHeat (Cal)C261990-01-01Yes185 Lbs5 ft10NoNoNo2Pro & Farm900,000$0$0$No900,000$
Radim ZohornaHeat (Cal)LW201996-01-01Yes229 Lbs6 ft6NoNoNo2Pro & Farm500,000$0$0$No500,000$
Rasmus AnderssonHeat (Cal)D201996-01-01Yes214 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$No
Ryan DonatoHeat (Cal)C201996-01-01Yes193 Lbs6 ft0NoNoNo2Pro & Farm600,000$0$0$No600,000$
Ryan SpoonerHeat (Cal)C241992-01-01Yes181 Lbs5 ft11NoNoNo2Pro & Farm800,000$0$0$No850,000$
Tage ThompsonHeat (Cal)RW191997-01-01Yes218 Lbs6 ft7NoNoNo2Pro & Farm500,000$0$0$No500,000$
Trevor CarrickHeat (Cal)D221994-01-01Yes171 Lbs6 ft1NoNoNo2Pro & Farm575,000$0$0$No600,000$
Victor RaskHeat (Cal)C231993-01-01Yes200 Lbs6 ft2NoNoNo1Pro & Farm950,000$0$0$No
Vitek VanecekHeat (Cal)G201996-01-01No190 Lbs5 ft11NoNoNo3Pro & Farm600,000$0$0$No600,000$600,000$
Vladislav KamenevHeat (Cal)C201996-01-01Yes194 Lbs6 ft2NoNoNo2Pro & Farm600,000$0$0$No600,000$
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3221.91198 Lbs6 ft21.66653,906$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Matthew NietoPhilip VaroneKevin Labanc40122
2Jake DeBruskVictor RaskEvgeny Svechnikov30122
3Peter CehlarikChris BrownBarclay Goodrow20122
4Jesper BrattNico SturmBrandon Hickey10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Frank CorradoRasmus Andersson40122
2Dominik MasinMathieu Brodeur30122
3John GilmourGreg Pateryn20122
4Frank CorradoRasmus Andersson10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Matthew NietoVictor RaskKevin Labanc60122
2Jake DeBruskPhilip VaroneEvgeny Svechnikov40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Frank CorradoRasmus Andersson60122
2Dominik MasinMathieu Brodeur40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Philip VaroneJake DeBrusk60122
2Nico SturmEvgeny Svechnikov40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Frank CorradoRasmus Andersson60122
2Dominik MasinMathieu Brodeur40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Matthew Nieto60122Frank CorradoRasmus Andersson60122
2Kevin Labanc40122Dominik MasinMathieu Brodeur40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Victor RaskMatthew Nieto60122
2Philip VaroneKevin Labanc40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Frank CorradoRasmus Andersson60122
2Dominik MasinMathieu Brodeur40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Matthew NietoPhilip VaroneKevin LabancFrank CorradoRasmus Andersson
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Matthew NietoPhilip VaroneKevin LabancDominik MasinRasmus Andersson
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Jake DeBrusk, Nico Sturm, Peter CehlarikChris Brown, Nico SturmPeter Cehlarik
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
John Gilmour, Mathieu Brodeur, Dominik MasinJohn GilmourMathieu Brodeur, Dominik Masin
Tirs de pénalité
Matthew Nieto, Jake DeBrusk, Kevin Labanc, Evgeny Svechnikov, Victor Rask
Gardien
#1 : Michael Hutchinson, #2 : Nathan Lieuwen


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
1Admirals32100000168822000000144101010000024-240.6671628441096121115997915866843458147207913323.08%10190.00%1920180650.94%995183154.34%720140151.39%171495716907601448713
2Barracuda312000001219-710100000310-72110000099020.3331219310096121115998915866843459932456211327.27%15473.33%0920180650.94%995183154.34%720140151.39%171495716907601448713
3Bears20200000614-81010000036-31010000038-500.0006915009612111595691586684345731930407228.57%15473.33%0920180650.94%995183154.34%720140151.39%171495716907601448713
4Comets2200000012210110000005231100000070741.000122436019612111597291586684345431616445360.00%80100.00%2920180650.94%995183154.34%720140151.39%171495716907601448713
5Condors301010011519-420100001914-51000100065130.500152641009612111591079158668434511344206311327.27%10190.00%1920180650.94%995183154.34%720140151.39%171495716907601448713
6Crunch220000001183110000006421100000054141.000111728009612111596991586684345661610548337.50%50100.00%0920180650.94%995183154.34%720140151.39%171495716907601448713
7Devils20101000101001010000045-11000100065120.500101727009612111596791586684345612924654250.00%12650.00%0920180650.94%995183154.34%720140151.39%171495716907601448713
8Eagles20200000913-41010000057-21010000046-200.00091726009612111596091586684345603120374250.00%10460.00%0920180650.94%995183154.34%720140151.39%171495716907601448713
9Griffins3120000011110211000009631010000025-320.33311172800961211159100915866843451013124738112.50%12283.33%1920180650.94%995183154.34%720140151.39%171495716907601448713
10Icehogs33000000151051100000053222000000107361.00015233800961211159106915866843458530205922940.91%10280.00%0920180650.94%995183154.34%720140151.39%171495716907601448713
11Little Stars21100000710-31010000048-41100000032120.5007101700961211159679158668434572261243600.00%60100.00%0920180650.94%995183154.34%720140151.39%171495716907601448713
12Marlies62300010222023120000079-2311000101511460.5002235570096121115919091586684345207636813628517.86%33778.79%1920180650.94%995183154.34%720140151.39%171495716907601448713
13Monsters53100001191723200000111922110000088070.7001932510096121115918191586684345165463210916637.50%16381.25%0920180650.94%995183154.34%720140151.39%171495716907601448713
14Moose41300000916-7211000007702020000029-720.25091726009612111591229158668434512540328815320.00%16475.00%0920180650.94%995183154.34%720140151.39%171495716907601448713
15Penguins21000100111101000010045-11100000076130.7501118290096121115964915866843456815164413215.38%8187.50%0920180650.94%995183154.34%720140151.39%171495716907601448713
16Phantoms633000002628-2303000001015-5330000001613360.5002639651096121115919191586684345182646610730516.67%33681.82%2920180650.94%995183154.34%720140151.39%171495716907601448713
17Punishers211000001082110000006151010000047-320.500101626009612111598091586684345653016417114.29%8275.00%0920180650.94%995183154.34%720140151.39%171495716907601448713
18Rampage211000001011-11010000036-31100000075220.500101828009612111596291586684345651518487228.57%9277.78%1920180650.94%995183154.34%720140151.39%171495716907601448713
19Reign10530100142420522010001820-25310000124222130.650427011200961211159338915866843453109111019939717.95%551474.55%0920180650.94%995183154.34%720140151.39%171495716907601448713
20Rocket311001001415-11000010045-1211000001010030.50014233710961211159879158668434510632345912216.67%17664.71%0920180650.94%995183154.34%720140151.39%171495716907601448713
21Senators321000001114-31010000038-52200000086240.6671119300096121115989915866843451183220576233.33%10460.00%0920180650.94%995183154.34%720140151.39%171495716907601448713
22Sound Tigers30200001917-82010000169-31010000038-510.167916250096121115910191586684345963025711218.33%10280.00%0920180650.94%995183154.34%720140151.39%171495716907601448713
23Thunderbirds2010000169-31000000134-11010000035-210.25061117109612111596391586684345673220469111.11%10370.00%0920180650.94%995183154.34%720140151.39%171495716907601448713
24Wolfpack3200010014122110000005412100010098150.83314243800961211159969158668434511036187410330.00%9188.89%0920180650.94%995183154.34%720140151.39%171495716907601448713
25Wolves210000101073110000007521000001032141.00010142400961211159839158668434573246466233.33%30100.00%0920180650.94%995183154.34%720140151.39%171495716907601448713
Total80353203325337351-1440151801204161176-15402014021211761751880.55033755989641961211159264691586684345261187172217443097323.62%3507977.43%9920180650.94%995183154.34%720140151.39%171495716907601448713
_Since Last GM Reset80353203325337351-1440151801204161176-15402014021211761751880.55033755989641961211159264691586684345261187172217443097323.62%3507977.43%9920180650.94%995183154.34%720140151.39%171495716907601448713
_Vs Conference52242102113212219-726101201102100110-1026149010111121093580.55821234856030961211159170691586684345169255249110912114923.22%2375477.22%6920180650.94%995183154.34%720140151.39%171495716907601448713
_Vs Division2210901011909001137010003544-911720001155469250.568901442341096121115971991586684345699218244442971717.53%1212777.69%3920180650.94%995183154.34%720140151.39%171495716907601448713

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8088W133755989626462611871722174441
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8035323325337351
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4015181204161176
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4020142121176175
Derniers 10 matchs
WLOTWOTL SOWSOL
730000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3097323.62%3507977.43%9
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
91586684345961211159
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
920180650.94%995183154.34%720140151.39%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
171495716907601448713


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
3 - 2021-12-0213Reign3Heat4BWR1Sommaire du match
6 - 2021-12-0522Heat6Reign5AWSommaire du match
8 - 2021-12-0735Heat5Phantoms4AWSommaire du match
9 - 2021-12-0843Heat5Reign3AWR1Sommaire du match
10 - 2021-12-0949Heat6Marlies2AWSommaire du match
11 - 2021-12-1052Reign6Heat1BLR1Sommaire du match
16 - 2021-12-1576Phantoms6Heat5BLSommaire du match
20 - 2021-12-1994Marlies2Heat3BWSommaire du match
21 - 2021-12-20102Heat3Reign4ALR1Sommaire du match
25 - 2021-12-24122Monsters3Heat2BLXXSommaire du match
27 - 2021-12-26135Heat4Barracuda6ALSommaire du match
29 - 2021-12-28144Reign4Heat5BWXR1Sommaire du match
31 - 2021-12-30155Heat3Marlies4ALSommaire du match
34 - 2022-01-02170Heat4Icehogs3AWSommaire du match
36 - 2022-01-04180Sound Tigers5Heat4BLXXSommaire du match
38 - 2022-01-06191Heat4Rocket6ALSommaire du match
40 - 2022-01-08205Moose4Heat2BLSommaire du match
42 - 2022-01-10219Heat2Admirals4ALSommaire du match
44 - 2022-01-12229Heat2Wolfpack3ALXSommaire du match
45 - 2022-01-13234Little Stars8Heat4BLSommaire du match
48 - 2022-01-16255Heat6Marlies5AWXXSommaire du match
49 - 2022-01-17259Condors8Heat4BLSommaire du match
53 - 2022-01-21277Heat6Icehogs4AWSommaire du match
54 - 2022-01-22285Wolves5Heat7BWSommaire du match
58 - 2022-01-26304Moose3Heat5BWSommaire du match
60 - 2022-01-28313Heat5Barracuda3AWSommaire du match
63 - 2022-01-31333Phantoms6Heat3BLSommaire du match
67 - 2022-02-04352Heat2Griffins5ALSommaire du match
68 - 2022-02-05359Sound Tigers4Heat2BLSommaire du match
71 - 2022-02-08379Phantoms3Heat2BLSommaire du match
75 - 2022-02-12400Heat3Wolves2AWXXSommaire du match
77 - 2022-02-14408Punishers1Heat6BWSommaire du match
79 - 2022-02-16420Heat4Eagles6ALSommaire du match
82 - 2022-02-19432Bears6Heat3BLSommaire du match
86 - 2022-02-23453Penguins5Heat4BLXSommaire du match
88 - 2022-02-25461Heat3Sound Tigers8ALSommaire du match
91 - 2022-02-28479Heat6Devils5AWXSommaire du match
92 - 2022-03-01485Thunderbirds4Heat3BLXXSommaire du match
95 - 2022-03-04504Icehogs3Heat5BWSommaire du match
97 - 2022-03-06509Heat5Reign4AWR1Sommaire du match
101 - 2022-03-10530Senators8Heat3BLSommaire du match
103 - 2022-03-12538Heat3Bears8ALSommaire du match
105 - 2022-03-14550Heat7Comets0AWSommaire du match
107 - 2022-03-16559Reign3Heat7BWR1Sommaire du match
111 - 2022-03-20578Heat6Rocket4AWSommaire du match
113 - 2022-03-22585Heat5Reign6ALXXR1Sommaire du match
115 - 2022-03-24592Crunch4Heat6BWSommaire du match
117 - 2022-03-26605Heat5Crunch4AWSommaire du match
119 - 2022-03-28615Barracuda10Heat3BLSommaire du match
123 - 2022-04-01636Rampage6Heat3BLSommaire du match
125 - 2022-04-03646Heat3Little Stars2AWSommaire du match
128 - 2022-04-06666Eagles7Heat5BLSommaire du match
131 - 2022-04-09686Devils5Heat4BLSommaire du match
133 - 2022-04-11697Heat7Wolfpack5AWSommaire du match
135 - 2022-04-13708Heat5Monsters3AWSommaire du match
137 - 2022-04-15716Wolfpack4Heat5BWSommaire du match
139 - 2022-04-17727Heat7Penguins6AWSommaire du match
141 - 2022-04-19741Condors6Heat5BLXXSommaire du match
144 - 2022-04-22756Heat6Condors5AWXSommaire du match
146 - 2022-04-24764Heat4Punishers7ALSommaire du match
147 - 2022-04-25773Rocket5Heat4BLXSommaire du match
150 - 2022-04-28792Heat3Thunderbirds5ALSommaire du match
152 - 2022-04-30799Comets2Heat5BWSommaire du match
156 - 2022-05-04822Reign4Heat1BLR1Sommaire du match
159 - 2022-05-07842Marlies4Heat3BLSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
161 - 2022-05-09852Heat7Rampage5AWSommaire du match
162 - 2022-05-10860Heat3Monsters5ALSommaire du match
165 - 2022-05-13874Monsters2Heat4BWSommaire du match
167 - 2022-05-15884Heat4Senators3AWSommaire du match
169 - 2022-05-17896Marlies3Heat1BLSommaire du match
172 - 2022-05-20908Heat1Moose6ALSommaire du match
176 - 2022-05-24928Monsters4Heat5BWSommaire du match
177 - 2022-05-25932Heat6Phantoms5AWSommaire du match
181 - 2022-05-29952Admirals2Heat6BWSommaire du match
185 - 2022-06-02975Admirals2Heat8BWSommaire du match
188 - 2022-06-05986Heat1Moose3ALSommaire du match
191 - 2022-06-08999Griffins2Heat6BWSommaire du match
192 - 2022-06-091010Heat5Phantoms4AWSommaire du match
196 - 2022-06-131022Griffins4Heat3BLSommaire du match
197 - 2022-06-141023Heat4Senators3AWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance74,18137,312
Assistance PCT92.73%93.28%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2787 - 92.91% 82,845$3,313,812$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,926,368$ 2,092,500$ 1,515,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
10,188$ 2,107,700$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 14,462$ 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