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Heat
GP: 5 | W: 1 | L: 4
GF: 15 | GA: 19 | PP%: 12.50% | PK%: 70.59%
DG: Steve Landry | Morale : 13 | Moyenne d’équipe : 65
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Centre de jeu
Heat
1-4-0, 2pts
5
FINAL
2 Griffins
16-7-0, 32pts
Team Stats
OTL1StreakW3
0-3-0Home Record8-2-0
1-1-0Away Record8-5-0
1-3-1Last 10 Games8-2-0
3.00Buts par match 4.13
3.80Buts contre par match 3.17
12.50%Pourcentage en avantage numérique28.41%
70.59%Pourcentage en désavantage numérique84.29%
Griffins
16-7-0, 32pts
3
FINAL
2 Heat
1-4-0, 2pts
Team Stats
W3StreakOTL1
8-2-0Home Record0-3-0
8-5-0Away Record1-1-0
8-2-0Last 10 Games1-3-1
4.13Buts par match 3.00
3.17Buts contre par match 3.80
28.41%Pourcentage en avantage numérique12.50%
84.29%Pourcentage en désavantage numérique70.59%
Meneurs d'équipe
Buts
Matthew Nieto
4
Passes
Victor Rask
4
Points
Matthew Nieto
7
Plus/Moins
Barclay Goodrow
3
Victoires
Michael Hutchinson
1
Pourcentage d’arrêts
Vitek Vanecek
0.941

Statistiques d’équipe
Buts pour
15
3.00 GFG
Tirs pour
178
35.60 Avg
Pourcentage en avantage numérique
12.5%
2 GF
Début de zone offensive
38.0%
Buts contre
19
3.80 GAA
Tirs contre
174
34.80 Avg
Pourcentage en désavantage numérique
70.6%%
5 GA
Début de la zone défensive
39.3%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance2,989
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 NietoX100.007328797077817975748072647268633872720251950,000$
2Evgeny Svechnikov (R)X100.006932866886767772757088527054465874710212900,000$
3Philip VaroneX100.007124717273757875797672626673652954710271900,000$
4Victor Rask (R)X100.007234787376747573767179637660504457710242950,000$
5Peter Cehlarik (R)X100.006744797165727172737470597048465262680223800,000$
6Ryan SpoonerX100.006431757374737369757868616653483659680251850,000$
7Barclay Goodrow (R)X100.007629737168676868656971706446503874670241850,000$
8Nico Sturm (R)X100.006429877175777663717356686848494969670221500,000$
9Chris BrownX100.006342807369707263605682536950502960660261750,000$
10Jesper Bratt (R)X100.006047706963716768716967557041427153640191500,000$
11Tage Thompson (R)X100.005532836762756251626949595744436574590201500,000$
12Mathieu BrodeurX100.007228856872747472487157775969542559710271850,000$
13Rasmus Andersson (R)X100.007137828165667281427965725455476057710212950,000$
14Frank Corrado (R)X100.006940736976757473577059686057503949680243800,000$
15Petteri Lindbohm (R)X100.005839746164666972456670675547523734650241600,000$
16Dominik Masin (R)X100.006431846567626853296042755046445359630213600,000$
17Brandon Hickey (R)X100.006227825960596050336642764943434250620212600,000$
18Christian Jaros (R)X100.006529756260595660326744705043444731620213600,000$
Rayé
1Eric Karlsson (R)X100.008033726777666862636471615447474162650233650,000$
2Ryan Donato (R)X100.007237736278647065716473476543435321640211600,000$
3Vladislav Kamenev (R)X100.006928714971656767585774567143435421610211600,000$
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$
8Trevor Carrick (R)X100.006038748063647475397455654146473521660231600,000$
9John Gilmour (R)X100.006932756661746673507156645647493420650242700,000$
10Erik Brannstrom (R)X100.004829676944426982338057673340408557600182500,000$
11Darren Raddysh (R)X100.006124906356666045446635653749455520600212500,000$
MOYENNE D’ÉQUIPE100.00643377666868686657686361594947494665
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 Hutchinson100.00727874737673737877697265632674740271975,000$
2Vitek Vanecek100.00626867585871765156746144445174620212600,000$
Rayé
1Collin Delia (R)100.00715263706855495761536641416120580231500,000$
MOYENNE D’ÉQUIPE100.0068666867676666626565665049465665
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)LW5437-1601072471716.67%611122.25112415101160046.67%1540001.2600000100
2Rasmus AnderssonHeat (Cal)D5235-12098187611.11%1213527.07112215000115000.00%034000.7400000010
3Victor RaskHeat (Cal)C5145-280813183145.56%410320.65022115000000046.53%14422000.9700000000
4Philip VaroneHeat (Cal)C52242401211114718.18%49418.820002110000130054.43%7911000.8500000010
5Evgeny SvechnikovHeat (Cal)RW5112-22062157116.67%210320.70000215000001044.44%905000.3900000000
6Frank CorradoHeat (Cal)D3112-1404740025.00%06220.810000600003000.00%002000.6400000000
7Mathieu BrodeurHeat (Cal)D5202-2203562133.33%1312124.37000114000013000.00%016000.3300000001
8Peter CehlarikHeat (Cal)LW51123206581912.50%17414.9500000000030050.00%220000.5300000000
9Ryan SpoonerHeat (Cal)C50220004215320.00%15611.3600000000010050.00%2200000.7000000000
10Jesper BrattHeat (Cal)LW5022-1008893120.00%07214.4800001100005000.00%021000.5500000000
11Tage ThompsonHeat (Cal)RW5022-200324180.00%1489.700000000000000.00%101000.8300000000
12Barclay GoodrowHeat (Cal)RW510130011461716.67%39519.120000110000150050.00%632000.2100000000
13Brandon HickeyHeat (Cal)D5011-200843010.00%35711.430000100006000.00%302000.3500000000
14Dominik MasinHeat (Cal)D5011-1006112430.00%612124.20000011011012000.00%006000.1700000000
15Petteri LindbohmHeat (Cal)D5011320555020.00%37715.520000000006000.00%032000.2600000000
16Nico SturmHeat (Cal)C5011-2002716390.00%0469.3700000000000025.00%1220000.4300000000
17Chris BrownHeat (Cal)C5000020433100.00%05811.78000000000200100.00%210000.00%00000000
18Christian JarosHeat (Cal)D5000200767120.00%37014.180000000000000.00%001000.00%00000000
19Erik BrannstromHeat (Cal)D2000-200024210.00%23718.960000400000000.00%000000.00%00000000
Statistiques d’équipe totales ou en moyenne90152540-6340116112178501128.43%64155017.222461213711221061047.80%2952435000.5200000121
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)51310.8853.70292001815776000.00%050000
2Vitek VanecekHeat (Cal)10000.9412.7322001179000.00%005000
Statistiques d’équipe totales ou en moyenne61310.8913.6231500191748500055000


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 BrattRyan SpoonerChris Brown20122
4Brandon HickeyNico SturmTage Thompson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dominik MasinRasmus Andersson40122
2Mathieu BrodeurFrank Corrado30122
3Petteri LindbohmChristian Jaros20122
4Mathieu BrodeurRasmus 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 MasinFrank Corrado40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Philip VaroneBarclay Goodrow60122
2Brandon HickeyJesper Bratt40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dominik MasinRasmus Andersson60122
2Mathieu BrodeurFrank Corrado40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Philip Varone60122Dominik MasinRasmus Andersson60122
2Victor Rask40122Mathieu BrodeurFrank Corrado40122
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 MasinFrank Corrado40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Matthew NietoVictor RaskEvgeny SvechnikovDominik MasinRasmus 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, Frank Corrado, Petteri LindbohmFrank CorradoDominik 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
1Griffins514000001519-430300000711-42110000088020.20015254000483017842685612174643411616212.50%17570.59%15711250.89%5311645.69%316746.27%11465109489144
Total514000001519-430300000711-42110000088020.20015254000483017842685612174643411616212.50%17570.59%15711250.89%5311645.69%316746.27%11465109489144
_Since Last GM Reset514000001519-430300000711-42110000088020.20015254000483017842685612174643411616212.50%17570.59%15711250.89%5311645.69%316746.27%11465109489144
_Vs Conference514000001519-430300000711-42110000088020.20015254000483017842685612174643411616212.50%17570.59%15711250.89%5311645.69%316746.27%11465109489144

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
52OTL1152540178174643411600
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
51400001519
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3030000711
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
211000088
Derniers 10 matchs
WLOTWOTL SOWSOL
130100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
16212.50%17570.59%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
426856124830
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
5711250.89%5311645.69%316746.27%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
11465109489144


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 - 2022-10-273Griffins3Heat2BLSommaire du match
2 - 2022-10-2811Griffins5Heat3BLSommaire du match
3 - 2022-10-2919Heat3Griffins6ALSommaire du match
4 - 2022-10-3027Heat5Griffins2AWSommaire du match
5 - 2022-10-3135Griffins3Heat2BLXSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance6,0002,968
Assistance PCT100.00%98.93%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
37 2989 - 99.64% 89,082$267,246$3000100

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

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