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Heat
GP: 80 | W: 42 | L: 33 | OTL: 5 | P: 89
GF: 325 | GA: 324 | PP%: 26.77% | PK%: 76.83%
DG: Steve Landry | Morale : 47 | Moyenne d’équipe : 65
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Centre de jeu
Penguins
42-28-10, 94pts
4
FINAL
2 Heat
42-33-5, 89pts
Team Stats
W2StreakW1
22-13-5Home Record22-15-3
20-15-5Away Record20-18-2
4-4-2Last 10 Games5-3-2
4.30Buts par match 4.06
4.19Buts contre par match 4.05
23.08%Pourcentage en avantage numérique26.77%
74.91%Pourcentage en désavantage numérique76.83%
Heat
42-33-5, 89pts
4
FINAL
1 Phantoms
38-33-9, 85pts
Team Stats
W1StreakL3
22-15-3Home Record16-19-5
20-18-2Away Record22-14-4
5-3-2Last 10 Games5-5-0
4.06Buts par match 4.30
4.05Buts contre par match 4.16
26.77%Pourcentage en avantage numérique21.92%
76.83%Pourcentage en désavantage numérique79.36%
Meneurs d'équipe
Buts
Matthew Nieto
51
Passes
Matthew Nieto
84
Points
Matthew Nieto
135
Plus/Moins
Evgeny Svechnikov
36
Victoires
Michael Hutchinson
38
Pourcentage d’arrêts
Michael Hutchinson
0.88

Statistiques d’équipe
Buts pour
325
4.06 GFG
Tirs pour
2637
32.96 Avg
Pourcentage en avantage numérique
26.8%
83 GF
Début de zone offensive
36.5%
Buts contre
324
4.05 GAA
Tirs contre
2552
31.90 Avg
Pourcentage en désavantage numérique
76.8%%
73 GA
Début de la zone défensive
36.2%
Informations de l'équipe

Directeur généralSteve Landry
EntraîneurCraig MacTavish
DivisionFritz-Kraatz
ConférenceRobert-Lebel
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,819
Billets de saison300


Informations de la formation

Équipe Pro32
Équipe Mineure20
Limite contact 52 / 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 NietoX100.007328797077817975748072647268633864720251950,000$
2Evgeny Svechnikov (R)X100.006932866886767772757088527054465867710212900,000$
3Philip VaroneX100.007124717273757875797672626673652947710271900,000$
4Victor Rask (R)X100.007234787376747573767179637660504449710242950,000$
5Peter Cehlarik (R)X100.006744797165727172737470597048465254680223800,000$
6Barclay Goodrow (R)X100.007629737168676868656971706446503867670241850,000$
7Chris BrownX100.006342807369707263605682536950502953660261750,000$
8Ryan Donato (R)X100.007237736278647065716473476543435321640211600,000$
9Jesper Bratt (R)X100.006047706963716768716967557041427146640191500,000$
10Vladislav Kamenev (R)X100.006928714971656767585774567143435421610211600,000$
11Tage Thompson (R)X100.005532836762756251626949595744436567590201500,000$
12Mathieu BrodeurX100.007228856872747472487157775969542551710271850,000$
13Rasmus Andersson (R)X100.007137828165667281427965725455476050710212950,000$
14Petteri Lindbohm (R)X100.005839746164666972456670675547523727650241600,000$
15Dominik Masin (R)X100.006431846567626853296042755046445352630213600,000$
16Brandon Hickey (R)X100.006227825960596050336642764943434243620212600,000$
17Christian Jaros (R)X100.006529756260595660326744705043444723620213600,000$
18Erik Brannstrom (R)X100.004829676944426982338057673340408557600182500,000$
Rayé
1Ryan SpoonerX100.006431757374737369757868616653483652680251850,000$
2Nico Sturm (R)X100.006429877175777663717356686848494962670221500,000$
3Eric Karlsson (R)X100.008033726777666862636471615447474162650233650,000$
4Taylor Raddysh (R)X100.005546786067675767675963556541416419610192500,000$
5Ivan Chekhovich (R)X100.006223734673545759565875336340407120570182500,000$
6Radim Zohorna (R)X100.005537735767716058525567415546445520570211500,000$
7Skyler Brind'Amour (R)X100.004331754952685544525351535140406920520182500,000$
8Frank Corrado (R)X100.006940736976757473577059686057503942680243800,000$
9Trevor Carrick (R)X100.006038748063647475397455654146473521660231600,000$
10John Gilmour (R)X100.006932756661746673507156645647493420650242700,000$
11Darren Raddysh (R)X100.006124906356666045446635653749455520600212500,000$
MOYENNE D’ÉQUIPE100.00643377666868686657686361594947494265
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 Hutchinson100.00727874737673737877697265632666740271975,000$
2Vitek Vanecek100.00626867585871765156746144445167620212600,000$
Rayé
1Collin Delia (R)100.00715263706855495761536641416120580231500,000$
MOYENNE D’ÉQUIPE100.0068666867676666626565665049465165
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Craig MacTavish78756975766752CAN553800,000$


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
1Matthew NietoHeat (Cal)LW7751841353564015210534811120114.66%36160220.82223052762520002316361.29%1245739021.683110005148
2Victor RaskHeat (Cal)C724982131344601211582888117317.01%27144820.1213375040241101144153.71%21043826041.81350001282
3Evgeny SvechnikovHeat (Cal)RW8046539936160121702637314217.49%31161120.1515173240260000034050.33%1514027011.23211000764
4Rasmus AnderssonHeat (Cal)D6886068-9381010213323573683.40%106177326.0841822422400338180010.00%06957000.7700001043
5Barclay GoodrowHeat (Cal)RW80203252-84201731001786511111.24%33139617.46113141319132541644250.72%693425010.7400000203
6Philip VaroneHeat (Cal)C56242448-23001071001564310815.38%27102718.347291111121351901255.82%9373913100.9311000416
7Jesper BrattHeat (Cal)LW66192039-8635916193356920.43%27104815.887310111551011893062.50%402917000.7459010100
8Ryan SpoonerHeat (Cal)C77191433-2730095641653810011.52%2791311.86000020113371048.64%5142916000.7222000201
9Erik BrannstromHeat (Cal)D7692332-13815338068324213.24%68135917.8926814165000037100.00%02537000.4700000004
10Peter CehlarikHeat (Cal)LW68191332-14807563140417013.57%2181512.0020232420251434158.33%362312000.7822000024
11Chris BrownHeat (Cal)C68161329-1100745284294019.05%1184012.3644810980002651047.87%399219000.6901000101
12Nico SturmHeat (Cal)C77101424-2420666710332649.71%1587211.320001013451642248.12%3992916000.5511000021
13Frank CorradoHeat (Cal)D6671522-2174010210810040347.00%89155823.6145921218112284100.00%02848000.2800000120
14Mathieu BrodeurHeat (Cal)D72318211160991119839453.06%100164422.8403381550002168000.00%03057000.2600000101
15Eric KarlssonHeat (Cal)LW778917-17240123468834469.09%1089011.570113400115920141.18%171111100.3800000210
16Trevor CarrickHeat (Cal)D4821113-1726051446026373.33%2376315.9202266300017500100.00%31518000.3400000000
17Brandon HickeyHeat (Cal)D68189-310053734710212.13%54105415.510000140110166000.00%4224000.1700000000
18Petteri LindbohmHeat (Cal)D242791322013172211129.09%1839516.48101319000037000.00%1612000.4600000000
19Dominik MasinHeat (Cal)D75088-12220511023419140.00%81124216.570330540110251000.00%0047000.1300000000
20Christian JarosHeat (Cal)D14145146059112100.00%916611.920000000006100.00%004000.6000000001
21Taylor RaddyshHeat (Cal)RW30123-18195221217855.88%630110.0500005000001040.00%1042000.2000000010
22John GilmourHeat (Cal)D14022-440159113110.00%215010.7200000000010050.00%213000.2700000000
23Tage ThompsonHeat (Cal)RW79022-1410021371410120.00%136077.6900004000000050.00%1005000.0700000000
24Jake DeBruskFlamesLW11010000322050.00%02222.1210111000020040.00%500000.9000000000
25Kevin LabancFlamesRW11010001062416.67%02222.120000100002000.00%300000.9000000000
26Ryan DonatoHeat (Cal)C14000-50014614590.00%214510.3800000000030035.71%1421000.00%00000000
27Vladislav KamenevHeat (Cal)C50001001012000.00%1346.8500000000030037.50%1600000.00%00000000
Statistiques d’équipe totales ou en moyenne1453317518835-8366325179016312637863144012.02%8372371016.32831442273032323111425462008341352.53%4858532526280.701943011384139
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)72382640.8803.7841004025821451058600.694367010330
2Vitek VanecekHeat (Cal)174710.8455.017550063407214100.62581069000
Statistiques d’équipe totales ou en moyenne89423350.8743.974856403212552127270448079330


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
Barclay GoodrowHeat (Cal)RW241993-01-01Yes215 Lbs6 ft2NoNoNo1Pro & Farm850,000$0$0$No
Brandon HickeyHeat (Cal)D211996-01-01Yes201 Lbs6 ft2NoNoNo2Pro & Farm600,000$0$0$No600,000$Lien
Chris BrownHeat (Cal)C261991-01-01No215 Lbs6 ft2NoNoNo1Pro & Farm750,000$0$0$No
Christian JarosHeat (Cal)D211996-01-01Yes222 Lbs6 ft3NoNoNo3Pro & Farm600,000$0$0$No650,000$700,000$Lien
Collin DeliaHeat (Cal)G231994-01-01Yes207 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$NoLien
Darren RaddyshHeat (Cal)D211996-01-01Yes200 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Dominik MasinHeat (Cal)D211996-01-01Yes196 Lbs6 ft2NoNoNo3Pro & Farm600,000$0$0$No650,000$700,000$Lien
Eric KarlssonHeat (Cal)LW231994-01-01Yes161 Lbs5 ft11NoNoNo3Pro & Farm650,000$0$0$No750,000$850,000$
Erik BrannstromHeat (Cal)D181999-01-01Yes185 Lbs5 ft10NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Evgeny SvechnikovHeat (Cal)RW211996-01-01Yes208 Lbs6 ft3NoNoNo2Pro & Farm900,000$0$0$No975,000$Lien
Frank CorradoHeat (Cal)D241993-01-01Yes195 Lbs6 ft0NoNoNo3Pro & Farm800,000$0$0$No850,000$900,000$
Ivan ChekhovichHeat (Cal)LW181999-01-01Yes187 Lbs5 ft10NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Jesper BrattHeat (Cal)LW191998-01-01Yes185 Lbs5 ft10NoNoNo1Pro & Farm500,000$0$0$NoLien
John GilmourHeat (Cal)D241993-01-01Yes185 Lbs6 ft0NoNoNo2Pro & Farm700,000$0$0$No800,000$Lien
Mathieu BrodeurHeat (Cal)D271990-01-01No215 Lbs6 ft6NoNoNo1Pro & Farm850,000$0$0$No
Matthew NietoHeat (Cal)LW251992-01-01No190 Lbs5 ft11NoNoNo1Pro & Farm950,000$0$0$No
Michael HutchinsonHeat (Cal)G271990-01-01No202 Lbs6 ft3NoNoNo1Pro & Farm975,000$0$0$No
Nico SturmHeat (Cal)C221995-01-01Yes207 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$NoLien
Peter CehlarikHeat (Cal)LW221995-01-01Yes185 Lbs6 ft2NoNoNo3Pro & Farm800,000$0$0$No850,000$900,000$Lien
Petteri LindbohmHeat (Cal)D241993-01-01Yes209 Lbs6 ft3NoNoNo1Pro & Farm600,000$0$0$NoLien
Philip VaroneHeat (Cal)C271990-01-01No185 Lbs5 ft10NoNoNo1Pro & Farm900,000$0$0$No
Radim ZohornaHeat (Cal)LW211996-01-01Yes229 Lbs6 ft6NoNoNo1Pro & Farm500,000$0$0$NoLien
Rasmus AnderssonHeat (Cal)D211996-01-01Yes214 Lbs6 ft1NoNoNo2Pro & Farm950,000$0$0$No1,500,000$Lien
Ryan DonatoHeat (Cal)C211996-01-01Yes193 Lbs6 ft0NoNoNo1Pro & Farm600,000$0$0$NoLien
Ryan SpoonerHeat (Cal)C251992-01-01No181 Lbs5 ft11NoNoNo1Pro & Farm850,000$0$0$No
Skyler Brind'AmourHeat (Cal)C181999-01-01Yes185 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Tage ThompsonHeat (Cal)RW201997-01-01Yes218 Lbs6 ft7NoNoNo1Pro & Farm500,000$0$0$NoLien
Taylor RaddyshHeat (Cal)RW191998-01-01Yes198 Lbs6 ft3NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Trevor CarrickHeat (Cal)D231994-01-01Yes171 Lbs6 ft1NoNoNo1Pro & Farm600,000$0$0$NoLien
Victor RaskHeat (Cal)C241993-01-01Yes200 Lbs6 ft2NoNoNo2Pro & Farm950,000$0$0$No1,300,000$
Vitek VanecekHeat (Cal)G211996-01-01No190 Lbs5 ft11NoNoNo2Pro & Farm600,000$0$0$No600,000$Lien
Vladislav KamenevHeat (Cal)C211996-01-01Yes194 Lbs6 ft2NoNoNo1Pro & Farm600,000$0$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3222.25198 Lbs6 ft11.66677,344$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Matthew NietoVictor RaskEvgeny Svechnikov40122
2Peter CehlarikPhilip VaroneBarclay Goodrow30122
3Jesper BrattVladislav KamenevChris Brown20122
4Brandon HickeyRyan DonatoTage Thompson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mathieu BrodeurRasmus Andersson40122
2Dominik MasinErik Brannstrom30122
3Petteri LindbohmChristian Jaros20122
4Dominik MasinRasmus Andersson10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Matthew NietoVictor RaskEvgeny Svechnikov60122
2Jesper BrattPhilip VaroneBarclay Goodrow40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mathieu BrodeurRasmus Andersson60122
2Dominik MasinErik Brannstrom40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Philip VaroneBarclay Goodrow60122
2Brandon HickeyJesper Bratt40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mathieu BrodeurRasmus Andersson60122
2Dominik MasinPetteri Lindbohm40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Philip Varone60122Mathieu BrodeurRasmus Andersson60122
2Victor Rask40122Dominik MasinPetteri Lindbohm40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Victor RaskMatthew Nieto60122
2Philip VaroneEvgeny Svechnikov40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mathieu BrodeurRasmus Andersson60122
2Dominik MasinErik Brannstrom40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Matthew NietoVictor RaskEvgeny SvechnikovMathieu BrodeurRasmus Andersson
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Matthew NietoVictor RaskEvgeny SvechnikovMathieu BrodeurRasmus Andersson
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Philip Varone, Jesper Bratt, Barclay GoodrowPeter Cehlarik, Tage ThompsonMatthew Nieto
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Dominik Masin, Erik Brannstrom, Petteri LindbohmErik BrannstromDominik Masin, Petteri Lindbohm
Tirs de pénalité
Victor Rask, Matthew Nieto, Evgeny Svechnikov, Jesper Bratt, Philip Varone
Gardien
#1 : Michael Hutchinson, #2 : Vitek Vanecek


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
1Admirals3210000014113110000007432110000077040.6671423370011210210022105926867831559222206212433.33%10370.00%1942177453.10%937176053.24%673132450.83%172095716767631466729
2Barracuda30200001913-42010000169-31010000034-110.1679142300112102100221069268678315510933247310220.00%11554.55%0942177453.10%937176053.24%673132450.83%172095716767631466729
3Bears21100000812-4110000006331010000029-720.5008132100112102100225892686783155801612487228.57%6183.33%0942177453.10%937176053.24%673132450.83%172095716767631466729
4Comets20100100911-21000010067-11010000034-110.2509162500112102100226592686783155712020524250.00%10190.00%0942177453.10%937176053.24%673132450.83%172095716767631466729
5Condors412010001516-11010000045-1311010001111040.50015264100112102100221259268678315513046349012433.33%17570.59%0942177453.10%937176053.24%673132450.83%172095716767631466729
6Crunch21000010853100000104311100000042241.0008122000112102100226792686783155551710453266.67%50100.00%0942177453.10%937176053.24%673132450.83%172095716767631466729
7Devils2110000011110110000006421010000057-220.50011172800112102100226692686783155691124442150.00%12191.67%1942177453.10%937176053.24%673132450.83%172095716767631466729
8Eagles20200000616-101010000047-31010000029-700.0006121800112102100227892686783155712815438337.50%5340.00%0942177453.10%937176053.24%673132450.83%172095716767631466729
9Griffins3200100013852100100010731100000031261.000132235001121021002292926867831559026206610550.00%10190.00%0942177453.10%937176053.24%673132450.83%172095716767631466729
10Icehogs412001001923-4210001001413120200000510-530.37519304900112102100221289268678315513745378113538.46%17664.71%2942177453.10%937176053.24%673132450.83%172095716767631466729
11Little Stars21100000101001010000035-21100000075220.50010172700112102100225992686783155672414419111.11%7528.57%2942177453.10%937176053.24%673132450.83%172095716767631466729
12Marlies633000002830-2312000001216-4321000001614260.5002844720011210210022204926867831551826671145301136.67%33487.88%1942177453.10%937176053.24%673132450.83%172095716767631466729
13Monsters302000101117-61010000028-62010001099020.333111728001121021002291926867831559137149012216.67%7271.43%0942177453.10%937176053.24%673132450.83%172095716767631466729
14Moose3300000015871100000031222000000127561.000152237001121021002292926867831558035266014214.29%13376.92%1942177453.10%937176053.24%673132450.83%172095716767631466729
15Penguins3120000012102211000009631010000034-120.3331218300011210210022112926867831558743126610330.00%6183.33%1942177453.10%937176053.24%673132450.83%172095716767631466729
16Phantoms6320000129245312000001415-132000001159670.5832951800011210210022194926867831551765970156411126.83%35780.00%0942177453.10%937176053.24%673132450.83%172095716767631466729
17Punishers330000001064110000003212200000074361.0001016260011210210022100926867831559219166315320.00%8187.50%0942177453.10%937176053.24%673132450.83%172095716767631466729
18Rampage210010001055100010005411100000051441.00010162600112102100225892686783155642216475360.00%8187.50%0942177453.10%937176053.24%673132450.83%172095716767631466729
19Reign1016000303338-55120002018162504000101522-780.40033508300112102100223189268678315531810511521641819.51%531277.36%2942177453.10%937176053.24%673132450.83%172095716767631466729
20Rocket310000201284210000107431000001054161.00012152700112102100221009268678315510226145715320.00%7357.14%0942177453.10%937176053.24%673132450.83%172095716767631466729
21Senators3100001114131210000109721000000156-150.8331422360011210210022999268678315510138226811327.27%11645.45%0942177453.10%937176053.24%673132450.83%172095716767631466729
22Sound Tigers2020000037-41010000024-21010000013-200.0003360011210210022679268678315570256404125.00%30100.00%0942177453.10%937176053.24%673132450.83%172095716767631466729
23Thunderbirds21100000651110000004221010000023-120.500610160011210210022669268678315551268389111.11%40100.00%0942177453.10%937176053.24%673132450.83%172095716767631466729
24Wolfpack2110000067-11010000024-21100000043120.5006814001121021002276926867831557318842400.00%40100.00%0942177453.10%937176053.24%673132450.83%172095716767631466729
25Wolves3210000014104211000006421100000086240.667142438001121021002211192686783155943039579111.11%13284.62%0942177453.10%937176053.24%673132450.83%172095716767631466729
Total80313303283325324140151502251166160640161801032159164-5890.5563255188430011210210022263792686783155255283766717903108326.77%3157376.83%11942177453.10%937176053.24%673132450.83%172095716767631466729
_Since Last GM Reset80313303283325324140151502251166160640161801032159164-5890.5563255188430011210210022263792686783155255283766717903108326.77%3157376.83%11942177453.10%937176053.24%673132450.83%172095716767631466729
_Vs Conference511820021732122093259901141106105126911010321061042580.5692123365480011210210022165492686783155160853846711642216027.15%2245774.55%7942177453.10%937176053.24%673132450.83%172095716767631466729
_Vs Division22711000319092-21136000204447-311450001146451210.477901452350011210210022716926867831556762302565171123026.79%1212380.99%3942177453.10%937176053.24%673132450.83%172095716767631466729

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8089W132551884326372552837667179000
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8031333283325324
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4015152251166160
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4016181032159164
Derniers 10 matchs
WLOTWOTL SOWSOL
530101
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3108326.77%3157376.83%11
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
9268678315511210210022
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
942177453.10%937176053.24%673132450.83%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
172095716767631466729


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
1 - 2022-10-276Heat2Reign3ALR1Sommaire du match
5 - 2022-10-3125Reign2Heat3BWXXSommaire du match
7 - 2022-11-0239Reign1Heat2BWXXR1Sommaire du match
9 - 2022-11-0448Heat4Phantoms5ALXXSommaire du match
10 - 2022-11-0551Heat3Reign4ALR1Sommaire du match
13 - 2022-11-0868Phantoms5Heat4BLSommaire du match
16 - 2022-11-1183Heat6Marlies2AWSommaire du match
19 - 2022-11-1498Heat4Condors2AWSommaire du match
20 - 2022-11-15103Marlies7Heat2BLSommaire du match
23 - 2022-11-18124Reign7Heat6BLR1Sommaire du match
25 - 2022-11-20136Senators5Heat6BWXXSommaire du match
26 - 2022-11-21144Heat3Reign5ALR1Sommaire du match
31 - 2022-11-26166Heat4Condors3AWXSommaire du match
33 - 2022-11-28175Griffins6Heat7BWXSommaire du match
36 - 2022-12-01191Heat4Icehogs8ALSommaire du match
38 - 2022-12-03202Barracuda4Heat2BLSommaire du match
43 - 2022-12-08222Little Stars5Heat3BLSommaire du match
45 - 2022-12-10236Heat2Eagles9ALSommaire du match
47 - 2022-12-12247Condors5Heat4BLSommaire du match
49 - 2022-12-14253Heat1Icehogs2ALSommaire du match
51 - 2022-12-16264Heat3Monsters2AWXXSommaire du match
53 - 2022-12-18272Heat8Marlies6AWSommaire du match
55 - 2022-12-20282Admirals4Heat7BWSommaire du match
58 - 2022-12-23295Heat7Phantoms3AWSommaire du match
60 - 2022-12-25305Marlies5Heat8BWSommaire du match
62 - 2022-12-27318Heat5Rocket4AWXXSommaire du match
64 - 2022-12-29328Heat5Senators6ALXXSommaire du match
66 - 2022-12-31335Moose1Heat3BWSommaire du match
69 - 2023-01-03357Phantoms4Heat9BWSommaire du match
71 - 2023-01-05369Heat5Rampage1AWSommaire du match
73 - 2023-01-07378Heat1Sound Tigers3ALSommaire du match
75 - 2023-01-09386Marlies4Heat2BLSommaire du match
77 - 2023-01-11396Heat5Moose3AWSommaire du match
79 - 2023-01-13410Heat4Punishers3AWSommaire du match
81 - 2023-01-15415Phantoms6Heat1BLSommaire du match
84 - 2023-01-18432Heat5Devils7ALSommaire du match
85 - 2023-01-19438Reign1Heat4BWR1Sommaire du match
88 - 2023-01-22454Heat3Punishers1AWSommaire du match
90 - 2023-01-24464Punishers2Heat3BWSommaire du match
92 - 2023-01-26479Heat3Penguins4ALSommaire du match
94 - 2023-01-28490Sound Tigers4Heat2BLSommaire du match
99 - 2023-02-02515Rampage4Heat5BWXSommaire du match
101 - 2023-02-04527Heat8Wolves6AWSommaire du match
104 - 2023-02-07538Heat4Wolfpack3AWSommaire du match
105 - 2023-02-08545Rocket3Heat4BWXXSommaire du match
109 - 2023-02-12568Comets7Heat6BLXSommaire du match
112 - 2023-02-15586Heat3Griffins1AWSommaire du match
114 - 2023-02-17594Crunch3Heat4BWXXSommaire du match
118 - 2023-02-21616Bears3Heat6BWSommaire du match
120 - 2023-02-23621Heat3Barracuda4ALSommaire du match
122 - 2023-02-25633Heat6Monsters7ALSommaire du match
124 - 2023-02-27643Monsters8Heat2BLSommaire du match
126 - 2023-03-01650Heat3Condors6ALSommaire du match
128 - 2023-03-03667Thunderbirds2Heat4BWSommaire du match
130 - 2023-03-05678Heat3Reign7ALR1Sommaire du match
132 - 2023-03-07687Heat7Moose4AWSommaire du match
134 - 2023-03-09699Reign5Heat3BLR1Sommaire du match
136 - 2023-03-11711Heat3Comets4ALSommaire du match
138 - 2023-03-13723Eagles7Heat4BLSommaire du match
141 - 2023-03-16737Heat2Marlies6ALSommaire du match
143 - 2023-03-18748Heat4Crunch2AWSommaire du match
144 - 2023-03-19753Griffins1Heat3BWSommaire du match
149 - 2023-03-24777Devils4Heat6BWSommaire du match
153 - 2023-03-28801Wolfpack4Heat2BLSommaire du match
155 - 2023-03-30806Heat2Bears9ALSommaire du match
159 - 2023-04-03827Wolves1Heat4BWSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
162 - 2023-04-06837Heat4Reign3AWXXR1Sommaire du match
165 - 2023-04-09852Wolves3Heat2BLSommaire du match
166 - 2023-04-10862Heat6Admirals4AWSommaire du match
169 - 2023-04-13878Heat7Little Stars5AWSommaire du match
170 - 2023-04-14884Icehogs8Heat7BLXSommaire du match
175 - 2023-04-19905Rocket1Heat3BWSommaire du match
180 - 2023-04-24928Icehogs5Heat7BWSommaire du match
182 - 2023-04-26938Heat2Thunderbirds3ALSommaire du match
185 - 2023-04-29956Senators2Heat3BWSommaire du match
187 - 2023-05-01966Heat1Admirals3ALSommaire du match
192 - 2023-05-06985Barracuda5Heat4BLXXSommaire du match
196 - 2023-05-101005Penguins2Heat7BWSommaire du match
202 - 2023-05-161024Penguins4Heat2BLSommaire du match
203 - 2023-05-171030Heat4Phantoms1AWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance75,24637,504
Assistance PCT94.06%93.76%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2819 - 93.96% 83,900$3,355,981$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,941,967$ 2,167,500$ 1,875,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
10,522$ 2,112,184$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 14,405$ 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