Stars

GP: 76 | W: 61 | L: 10 | OTL: 5 | P: 127
GF: 263 | GA: 102 | PP%: 15.41% | PK%: 90.54%
DG: Mickael Lajeunesse | Morale : 97 | Moyenne d'Équipe : 63
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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 SP
1Dale WeiseXX100.008242807082737666566164656279725189660
2Devante Smith-PellyXX100.008341826379747061566264736573676382650
3Peter HollandX100.006338846579949363706261646275687089650
4T.J. HensickX100.005435956368787262736556575984745189620
5Nick LappinX100.005936926072846958585657595573674889600
6Nikita JevpalovsX100.006637875679939155575454565569656089600
7Nicholas MerkleyX100.005537876269868061706354565863627889600
8Zack MacEwenX100.006143845984777158625957595565635390600
9Isac Lundestrom (R)X100.005435936271746361726253645360628389600
10Stephen GiontaX100.005935936063726258675956645186763589600
11Linus Olund (R)X100.005735945571928854565352534963626378580
12Aaron LuchukX100.005035955657787255575453505463626368550
13Dylan McIlrathX100.007540795896856856305553724873677185660
14Chris BreenX100.008439835599878153305450614578705582650
15Philippe MyersX100.007839836391856861306258634863625489650
16Matt IrwinX100.008254796379695762306856645180722789640
17Kevin GravelX100.005636935989776358306153684972674689630
18Joe HickettsX100.005637885964897058305753684665635382620
19Timothy LiljegrenX100.006437896073857958305652615360628389620
Rayé
1Roope HintzX100.007438876886777267736665686764657231650
2Nikita Popugaev (R)X100.007935945596767054565253615461636419590
3Jonathan Dahlen (R)X100.005236926157918659635856526063627319580
4Cam Dineen (R)X100.005335945558918654305352515461637019570
MOYENNE D'ÉQUIPE100.00653888607782745952595661546966607562
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 SP
1Josef Korenar100.00797573747877797877797861655389730
2Spencer Martin100.00757270857473757473757467715289720
Rayé
1Martin Ouellette (R)100.00776563697675777675777675814520720
2Felix Sandstrom (R)100.00746462797372747372747363677520690
3Stuart Skinner (R)100.00716563887069717069717061657620680
MOYENNE D'ÉQUIPE100.0075686679747375747375746570604871
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Scott Gordon81788481847863USA5641,000,000$


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'ÉquipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Dale WeiseStars (Dal)LW/RW7645408558113152061233078622814.66%13167122.00691558280303724611249.73%37600001.02281111289
2Isac LundestromStars (Dal)C7624416547100241152084911211.54%10112514.81381127134000054164.05%127400001.1500000365
3Peter HollandStars (Dal)C7628346263260901232085616213.46%12151119.892352716700062277060.68%96900010.8238000948
4Nick LappinStars (Dal)RW762923524244084551705712517.06%8149519.6713132665310000008267.71%9600020.7000000556
5Nicholas MerkleyStars (Dal)RW76133447292353111115641918.33%15111514.6848121413600061711158.73%69300000.8411001135
6Philippe MyersStars (Dal)D7610314130102101146312058908.33%47158320.8361218752930111211100.00%000000.5200100220
7T.J. HensickStars (Dal)RW7616244024261040761544612310.39%6106314.00448251770002584062.16%7400000.7500100411
8Matt IrwinStars (Dal)D7663238298210127638233567.32%51130217.13347461760111224500.00%000000.5800002223
9Kevin GravelStars (Dal)D76431353724052534063310.00%49115015.140000120000149100.00%000000.6100000121
10Dylan McIlrathStars (Dal)D396263234411546337722447.79%3692023.613710451830110105100.00%000000.7000201025
11Stephen GiontaStars (Dal)C76725322118047103162291104.32%1495912.6305533159000002061.73%72900000.6700000021
12Devante Smith-PellyStars (Dal)LW/RW39141630302805546125398911.20%663916.40055381701012751162.16%11100010.9422000122
13Zack MacEwenStars (Dal)C7613132619471567771183911111.02%1592012.11000000112594156.73%34900000.5700003231
14Timothy LiljegrenStars (Dal)D76620263427555406726458.96%51134617.72145311310221198200.00%000000.3900001042
15Chris BreenStars (Dal)D39517223342070173692813.89%3086122.09459221860220118000.00%000000.5100000310
16Roope HintzStars (Dal)LW157815522036335993911.86%028318.8704411431011380063.79%29000001.0602000032
17Nikita JevpalovsStars (Dal)RW76951413140703679244711.39%86558.63000223000000059.65%5700000.4300000320
18Jonathan DahlenStars (Dal)LW1544848071132112412.50%123915.99213644000001050.00%1400000.6701000002
19Joe HickettsStars (Dal)D39055300131313160.00%62075.3200034011023000.00%000000.4800000000
20Aaron LuchukStars (Dal)C3911212011240225.00%0912.35000011124800052.38%8400000.4400000000
21Nikita PopugaevStars (Dal)LW151120140186174125.88%115110.1100002000070185.71%700000.2600000010
22Cam DineenStars (Dal)D151010000552720.00%317811.9210144400003100.00%000000.1100000000
23Linus OlundStars (Dal)C43011000436010.00%1972.260003140001140066.67%1500000.2100000000
Stats d'équipe Total ou en Moyenne128624943268155671385125712172245647158511.09%3831957315.22529214453527006101634201954960.57%513800040.70822519485353
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
1Josef KorenarStars (Dal)76611050.9351.2946052179915130110.917247601034
Stats d'équipe Total ou en Moyenne76611050.9351.2946052179915130110.917247601034


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 Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Aaron LuchukStars (Dal)C221997-04-04No180 Lbs5 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Cam DineenStars (Dal)D211998-06-19Yes183 Lbs5 ft1NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien
Chris BreenStars (Dal)D301989-06-29No226 Lbs6 ft7NoNoNo1Pro & Farm300,000$0$0$NoLien
Dale WeiseStars (Dal)LW/RW301988-08-05No206 Lbs6 ft2NoNoNo2Pro & Farm936,481$0$0$No936,481$Lien
Devante Smith-PellyStars (Dal)LW/RW271992-06-14No223 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$0$0$NoLien
Dylan McIlrathStars (Dal)D271992-04-20No236 Lbs6 ft5NoNoNo4Pro & Farm963,777$0$0$No963,777$963,777$963,777$Lien
Felix SandstromStars (Dal)G221997-01-12Yes191 Lbs6 ft2NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Isac LundestromStars (Dal)C191999-11-06Yes187 Lbs6 ft0NoNoNo4Pro & Farm900,000$0$0$No900,000$900,000$900,000$Lien
Joe HickettsStars (Dal)D231996-05-04No180 Lbs5 ft8NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Jonathan DahlenStars (Dal)LW211997-12-20Yes176 Lbs5 ft1NoNoNo4Pro & Farm900,000$0$0$No900,000$900,000$900,000$Lien
Josef KorenarStars (Dal)G211998-01-31No185 Lbs6 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Kevin GravelStars (Dal)D271992-03-06No211 Lbs6 ft4NoNoNo1Pro & Farm973,000$0$0$NoLien
Linus OlundStars (Dal)C221997-06-05Yes185 Lbs6 ft0NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Martin OuelletteStars (Dal)G271991-12-30Yes160 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$NoLien
Matt IrwinStars (Dal)D311987-11-29No207 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$0$0$NoLien
Nicholas MerkleyStars (Dal)RW221997-05-23No194 Lbs5 ft10NoNoNo3Pro & Farm900,000$0$0$No900,000$900,000$Lien
Nick LappinStars (Dal)RW261992-11-01No175 Lbs6 ft1NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Nikita JevpalovsStars (Dal)RW241994-09-09No210 Lbs6 ft1NoNoNo1Pro & Farm300,000$0$0$NoLien
Nikita PopugaevStars (Dal)LW201998-11-20Yes217 Lbs6 ft6NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Peter HollandStars (Dal)C281991-01-14No193 Lbs6 ft2NoNoNo3Pro & Farm915,775$0$0$No915,775$915,775$Lien
Philippe MyersStars (Dal)D221997-01-25No210 Lbs6 ft5NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Roope HintzStars (Dal)LW221996-11-17No215 Lbs6 ft3NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Spencer MartinStars (Dal)G241995-06-08No210 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$NoLien
Stephen GiontaStars (Dal)C351983-10-09No177 Lbs5 ft7NoNoNo1Pro & Farm300,000$0$0$NoLien
Stuart SkinnerStars (Dal)G201998-11-01Yes206 Lbs6 ft4NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien
T.J. HensickStars (Dal)RW331985-12-10No190 Lbs5 ft10NoNoNo1Pro & Farm498,888$0$0$NoLien
Timothy LiljegrenStars (Dal)D201999-04-30No192 Lbs6 ft0NoNoNo4Pro & Farm900,000$0$0$No900,000$900,000$900,000$Lien
Zack MacEwenStars (Dal)C221996-07-08No205 Lbs6 ft3NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2824.57198 Lbs6 ft02.64570,997$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Dale WeisePeter HollandDevante Smith-Pelly40122
2Nick LappinStephen GiontaT.J. Hensick30122
3Dale WeiseZack MacEwenNick Lappin20122
4Peter HollandIsac LundestromNicholas Merkley10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dylan McIlrathChris Breen40122
2Philippe MyersMatt Irwin30122
3Kevin GravelTimothy Liljegren20122
4Joe HickettsDylan McIlrath10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Dale WeisePeter HollandDevante Smith-Pelly60122
2Nick LappinStephen GiontaT.J. Hensick40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dylan McIlrathChris Breen60122
2Philippe MyersMatt Irwin40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Dale WeisePeter Holland60122
2Devante Smith-PellyT.J. Hensick40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dylan McIlrathChris Breen60122
2Philippe MyersMatt Irwin40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Dale Weise60122Dylan McIlrathChris Breen60122
2Peter Holland40122Philippe MyersMatt Irwin40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Dale WeisePeter Holland60122
2Devante Smith-PellyT.J. Hensick40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dylan McIlrathChris Breen60122
2Philippe MyersMatt Irwin40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Dale WeisePeter HollandDevante Smith-PellyDylan McIlrathChris Breen
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Dale WeisePeter HollandDevante Smith-PellyDylan McIlrathChris Breen
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nikita Jevpalovs, Linus Olund, Aaron LuchukNikita Jevpalovs, Linus OlundAaron Luchuk
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Kevin Gravel, Timothy Liljegren, Joe HickettsKevin GravelTimothy Liljegren, Joe Hicketts
Tirs de Pénalité
Dale Weise, Peter Holland, Devante Smith-Pelly, T.J. Hensick, Nick Lappin
Gardien
#1 : Josef Korenar, #2 : Spencer Martin


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
LigueDomicileVisiteur
# 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
1Admirals84200101211834110010179-2431000001495100.6252139600010682671020374179479339188418516044715.91%35585.71%01456244559.55%1158203856.82%628105759.41%216916011536508905484
2Barracuda20100010440100000103211010000012-120.5004610001068267103374179479339431132349111.11%16193.75%01456244559.55%1158203856.82%628105759.41%216916011536508905484
3Condors22000000826110000003121100000051441.00081523001068267108274179479339411317338225.00%60100.00%01456244559.55%1158203856.82%628105759.41%216916011536508905484
4Griffins8800000039102944000000194154400000020614161.00039701090210682671025374179479339106296212235822.86%24483.33%21456244559.55%1158203856.82%628105759.41%216916011536508905484
5Gulls22000000413110000002021100000021141.0004812011068267105374179479339321331331417.14%120100.00%01456244559.55%1158203856.82%628105759.41%216916011536508905484
6Heat22000000312110000002111100000010141.000369011068267107274179479339441183610220.00%40100.00%01456244559.55%1158203856.82%628105759.41%216916011536508905484
7IceHogs880000005244844000000273244400000025124161.000529314505106826710381741794793391283842172401025.00%200100.00%11456244559.55%1158203856.82%628105759.41%216916011536508905484
8Moose880000004373644000000193164400000024420161.00043801230210682671033074179479339145385514132412.50%25196.00%21456244559.55%1158203856.82%628105759.41%216916011536508905484
9Rampage14830011135221375000101201197330001015114200.71435589302106826710362741794793393269614225179810.13%60788.33%11456244559.55%1158203856.82%628105759.41%216916011536508905484
10Reign2200000014410110000007341100000071641.0001427410010682671010774179479339229293510550.00%9188.89%01456244559.55%1158203856.82%628105759.41%216916011536508905484
11Roadrunners42100010862210000105322110000033060.7508142200106826710104741794793396525516119210.53%19478.95%01456244559.55%1158203856.82%628105759.41%216916011536508905484
Total7653100236226310216138273012321264878382670113013754831270.836263466729117106826710234274179479339151441576313643705715.41%3173090.54%61456244559.55%1158203856.82%628105759.41%216916011536508905484
13Wild822011201716141101010642411001101112-1110.6881725421110682671018374179479339193539812926311.54%43588.37%01456244559.55%1158203856.82%628105759.41%216916011536508905484
14Wolves8510101015784310000064242001010936140.8751525400310682671017974179479339181381111574449.09%44295.45%01456244559.55%1158203856.82%628105759.41%216916011536508905484
_Since Last GM Reset7653100236226310216138273012321264878382670113013754831270.836263466729117106826710234274179479339151441576313643705715.41%3173090.54%61456244559.55%1158203856.82%628105759.41%216916011536508905484
_Vs Conference583980234219080110292030121290375329195011301004357950.819190331521114106826710171574179479339120731956510602864415.38%2362390.25%41456244559.55%1158203856.82%628105759.41%216916011536508905484

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
76127OTL1263466729234215144157631364117
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7653102362263102
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
38273123212648
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
38267113013754
Derniers 10 Matchs
WLOTWOTL SOWSOL
700210
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3705715.41%3173090.54%6
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
74179479339106826710
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
1456244559.55%1158203856.82%628105759.41%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
216916011536508905484


Derniers Match 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 - 2019-09-045Griffins2Stars6WSommaire du Match
4 - 2019-09-0519Admirals2Stars3WSommaire du Match
10 - 2019-09-1139Stars4Wild3WXXSommaire du Match
11 - 2019-09-1250Stars4IceHogs1WSommaire du Match
15 - 2019-09-1665Stars4Griffins1WSommaire du Match
17 - 2019-09-1878Wild1Stars0LSommaire du Match
18 - 2019-09-1991Wild0Stars1WSommaire du Match
24 - 2019-09-25113Wolves2Stars1LSommaire du Match
25 - 2019-09-26127Barracuda2Stars3WXXSommaire du Match
31 - 2019-10-02151Stars7Reign1WSommaire du Match
32 - 2019-10-03166Stars5Condors1WSommaire du Match
39 - 2019-10-10201Rampage1Stars3WSommaire du Match
40 - 2019-10-11208Stars4Rampage1WSommaire du Match
43 - 2019-10-14220Moose1Stars4WSommaire du Match
45 - 2019-10-16231IceHogs1Stars7WSommaire du Match
52 - 2019-10-23273Stars2Rampage1WSommaire du Match
53 - 2019-10-24287Rampage4Stars3LXXSommaire du Match
54 - 2019-10-25295Stars0Rampage1LSommaire du Match
59 - 2019-10-30314Stars1Admirals2LSommaire du Match
60 - 2019-10-31325Stars4Griffins3WSommaire du Match
61 - 2019-11-01336Stars1Wolves0WSommaire du Match
64 - 2019-11-04345Admirals2Stars1LXSommaire du Match
66 - 2019-11-06357Admirals3Stars2LXXSommaire du Match
71 - 2019-11-11388Wild1Stars2WXXSommaire du Match
73 - 2019-11-13398Stars5Admirals3WSommaire du Match
74 - 2019-11-14407Stars7IceHogs0WSommaire du Match
77 - 2019-11-17422Stars3Wolves2WXSommaire du Match
80 - 2019-11-20444Rampage1Stars2WSommaire du Match
81 - 2019-11-21460Stars2Rampage3LSommaire du Match
86 - 2019-11-26474Rampage0Stars4WSommaire du Match
88 - 2019-11-28496Reign3Stars7WSommaire du Match
89 - 2019-11-29502Stars2Rampage0WSommaire du Match
94 - 2019-12-04526Moose1Stars5WSommaire du Match
95 - 2019-12-05541Moose1Stars5WSommaire du Match
99 - 2019-12-09557Condors1Stars3WSommaire du Match
101 - 2019-12-11569IceHogs0Stars8WSommaire du Match
102 - 2019-12-12583Wild2Stars3WXSommaire du Match
106 - 2019-12-16604Stars2Gulls1WSommaire du Match
108 - 2019-12-18614Stars1Barracuda2LSommaire du Match
109 - 2019-12-19628Stars1Heat0WSommaire du Match
111 - 2019-12-21642Stars0Roadrunners2LSommaire du Match
113 - 2019-12-23651Stars3Roadrunners1WSommaire du Match
115 - 2019-12-25664Heat1Stars2WSommaire du Match
116 - 2019-12-26680Gulls0Stars2WSommaire du Match
121 - 2019-12-31682Griffins1Stars3WSommaire du Match
127 - 2020-01-06721Stars2Admirals1WSommaire du Match
130 - 2020-01-09742Stars3Moose2WSommaire du Match
131 - 2020-01-10750Stars7Moose1WSommaire du Match
133 - 2020-01-12759Stars6IceHogs0WSommaire du Match
136 - 2020-01-15777Roadrunners1Stars2WXXSommaire du Match
137 - 2020-01-16790Roadrunners2Stars3WSommaire du Match
140 - 2020-01-19807Stars1Wild3LSommaire du Match
142 - 2020-01-21814Stars2Wolves1WXXSommaire du Match
143 - 2020-01-22820Stars8Griffins2WSommaire du Match
145 - 2020-01-24844Stars3Wolves0WSommaire du Match
148 - 2020-01-27853Admirals2Stars1LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29863Wolves1Stars2WSommaire du Match
151 - 2020-01-30877Wolves1Stars2WSommaire du Match
154 - 2020-02-02889Stars6Admirals3WSommaire du Match
155 - 2020-02-03891Stars4Griffins0WSommaire du Match
158 - 2020-02-06919Stars3Rampage4LSommaire du Match
159 - 2020-02-07929Rampage1Stars4WSommaire du Match
162 - 2020-02-10940Stars5Moose0WSommaire du Match
164 - 2020-02-12951Stars9Moose1WSommaire du Match
166 - 2020-02-14970Stars8IceHogs0WSommaire du Match
169 - 2020-02-17982Griffins0Stars5WSommaire du Match
171 - 2020-02-19990Wolves0Stars1WSommaire du Match
172 - 2020-02-201004Griffins1Stars5WSommaire du Match
176 - 2020-02-241024Moose0Stars5WSommaire du Match
178 - 2020-02-261034Stars4Wild3WSommaire du Match
179 - 2020-02-271046Stars2Wild3LXSommaire du Match
185 - 2020-03-041080IceHogs0Stars6WSommaire du Match
186 - 2020-03-051094IceHogs2Stars6WSommaire du Match
190 - 2020-03-091110Rampage1Stars2WSommaire du Match
192 - 2020-03-111124Stars2Rampage1WXXSommaire du Match
193 - 2020-03-121138Rampage3Stars2LXSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,167,279$ 159,880$ 21,320$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 167,271$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 5,979$ 0$




LigueDomicileVisiteur
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
14765310023622631021613827301232126487838267011301375483127263466729117106826710234274179479339151441576313643705715.41%3173090.54%61456244559.55%1158203856.82%628105759.41%216916011536508905484
Total Saison Régulière765310023622631021613827301232126487838267011301375483127263466729117106826710234274179479339151441576313643705715.41%3173090.54%61456244559.55%1158203856.82%628105759.41%216916011536508905484