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Roadrunners
GP: 28 | W: 20 | L: 7 | OTL: 1 | P: 41
GF: 109 | GA: 82 | PP%: 29.41% | PK%: 86.15%
DG: Greg Vandersteen | Morale : 68 | Moyenne d’équipe : 59
Prochains matchs #305 vs Fighting Pandas

Centre de jeu
Americiens
16-8-1, 33pts
1
FINAL
7 Roadrunners
20-7-1, 41pts
Team Stats
L2SéquenceL1
9-5-0Fiche domicile11-2-0
7-3-1Fiche domicile9-5-1
7-3-0Derniers 10 matchs7-2-1
4.84Buts par match 3.89
4.40Buts contre par match 2.93
28.07%Pourcentage en avantage numérique29.41%
76.81%Pourcentage en désavantage numérique86.15%
Roadrunners
20-7-1, 41pts
2
FINAL
7 Nordiks
16-12-1, 33pts
Team Stats
L1SéquenceW2
11-2-0Fiche domicile6-7-0
9-5-1Fiche domicile10-5-1
7-2-1Derniers 10 matchs6-4-0
3.89Buts par match 5.59
2.93Buts contre par match 5.07
29.41%Pourcentage en avantage numérique29.31%
86.15%Pourcentage en désavantage numérique71.95%
Fighting Pandas
14-9-4, 32pts
Jour 61
Roadrunners
20-7-1, 41pts
Statistiques d’équipe
OTL1SéquenceL1
6-4-4Fiche domicile11-2-0
8-5-0Fiche visiteur9-5-1
4-3-310 derniers matchs7-2-1
4.33Buts par match 3.89
3.78Buts contre par match 3.89
31.37%Pourcentage en avantage numérique29.41%
83.13%Pourcentage en désavantage numérique86.15%
Lynx
17-10-0, 34pts
Jour 65
Roadrunners
20-7-1, 41pts
Statistiques d’équipe
W2SéquenceL1
9-5-0Fiche domicile11-2-0
8-5-0Fiche visiteur9-5-1
6-4-010 derniers matchs7-2-1
4.63Buts par match 3.89
3.59Buts contre par match 3.89
30.51%Pourcentage en avantage numérique29.41%
91.18%Pourcentage en désavantage numérique86.15%
Roadrunners
20-7-1, 41pts
Jour 67
Nordiks
16-12-1, 33pts
Statistiques d’équipe
L1SéquenceW2
11-2-0Fiche domicile6-7-0
9-5-1Fiche visiteur10-5-1
7-2-110 derniers matchs6-4-0
3.89Buts par match 5.59
2.93Buts contre par match 5.59
29.41%Pourcentage en avantage numérique29.31%
86.15%Pourcentage en désavantage numérique71.95%
Meneurs d'équipe
Ondrej PalatButs
Ondrej Palat
18
Brandt ClarkePasses
Brandt Clarke
29
Brandt ClarkePoints
Brandt Clarke
36
Brandt ClarkePlus/Moins
Brandt Clarke
9
Jet GreavesVictoires
Jet Greaves
19
Jet GreavesPourcentage d’arrêts
Jet Greaves
0.909

Statistiques d’équipe
Buts pour
109
3.89 GFG
Tirs pour
913
32.61 Avg
Pourcentage en avantage numérique
29.4%
20 GF
Début de zone offensive
41.5%
Buts contre
82
2.93 GAA
Tirs contre
894
31.93 Avg
Pourcentage en désavantage numérique
86.2%%
9 GA
Début de la zone défensive
38.2%
Informations de l'équipe

Directeur généralGreg Vandersteen
EntraîneurDave Semenko
DivisionMetropolitan
ConférenceEastern Conference
Capitaine
Assistant #1Gustav Nyquist
Assistant #2Nico Sturm


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro26
Équipe Mineure19
Limite contact 45 / 50
Espoirs37


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
1Cutter Gauthier (R)X98.00685687727374927150707264545459078660212500,000$
2Gustav Nyquist (A)X100.00615590676280916850666468638177084650363500,000$
3Nico Sturm (A)X100.00776691677567757077636067507371081640304500,000$
4Anthony ManthaX99.006769776384665469505969566372730776103142,000,000$
5Tyson JostX100.00696177666665627160625660506565080600273500,000$
6David GustafssonX100.00606996657062606867605262506363079590253500,000$
7Akil Thomas (R)X100.00737096636964566351564958506262076570253500,000$
8Joey AndersonX100.00595099577464555250525064506769078550271500,000$
9Nikita Chibrikov (R)X100.00493590586050515050495349515664076510222500,000$
10Brandt ClarkeX100.00586171737370907450735572565862082660221500,000$
11Sam MalinskiX100.00665789636769886750615472566768081640273500,000$
12Philippe MyersX100.00796785607968636450555169556870082630282500,000$
13Zac JonesX100.00655977656771686950655068556163078620252500,000$
14Matthew KesselX100.00655982607462586350545166556365076600252500,000$
15John KlingbergX100.00506265576654555350505051567674048540331500,000$
Rayé
1Ondrej PalatXS1755591696974886950647063517774074650342500,000$
2Nils AmanX100.00635493626460546953615056506062022570251500,000$
3Max JonesX100.00816166617863565650555058506462020560273500,000$
4Ville KoivunenX100.00505775545562555850665050506169022540224500,000$
5Oliver Kapanen (R)X100.00505593577061545257545056625557022530223500,000$
6Thomas BordeleauX100.00503589576350515050505050506362022510232500,000$
7Sam PoulinX100.00575885508150515250505050505859022510242500,000$
8Artyom Levshunov (R)X100.00646077647557586550635059555156022580204500,000$
9Ian MitchellX100.00525692556851555750505061556365022550262500,000$
MOYENNE D’ÉQUIPE99.8863588562706364635359546054646505959
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
1Jet Greaves (R)98.0079657270716564706776506066078670243500,000$
2Akira Schmid100.0056626274505050505051506060080550252500,000$
Rayé
MOYENNE D’ÉQUIPE99.006864677261585760596450606307961
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dave Semenko8787878787501CAN616500,000$


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
1Brandt ClarkeRoadrunners (UTA)D28729369220544241133817.07%3166723.8447112157011050000%000001.0800000231
2Cutter GauthierRoadrunners (UTA)LW28161531514044561413712311.35%974126.4831417521012512038.10%4200000.8411000401
3Gustav NyquistRoadrunners (UTA)RW281615318401535112367114.29%950718.120661557000004233.33%2700011.2211000332
4Ondrej PalatRoadrunners (UTA)LW2718133102354432102199217.65%650918.88831124480002408264.00%2500011.2200010534
5David GustafssonRoadrunners (UTA)C281115265401473102245410.78%450518.0500003000030158.76%56500001.0300000213
6Tyson JostRoadrunners (UTA)C2862026515538597315528.22%854019.31191013500000330054.00%58700000.9600001210
7Anthony ManthaRoadrunners (UTA)RW28149231355422381215817.28%261521.991347480002281151.56%6400000.7500001132
8Sam MalinskiRoadrunners (UTA)D28320234201936449236.82%4564623.112241444000237110%100000.7100000012
9Nico SturmRoadrunners (UTA)C2861622916052607023568.57%853519.130116540001602062.50%76000000.8200000004
10Philippe MyersRoadrunners (UTA)D28314179221060162772311.11%3152218.641341548000044000%000000.6500101112
11Zac JonesRoadrunners (UTA)D2811213-16043301516116.67%3754119.340112700012010100.00%200000.4800000020
12Joey AndersonRoadrunners (UTA)RW2826852019183411235.88%747216.8600014000000057.69%2600000.3400000000
13Matthew KesselRoadrunners (UTA)D28156-51803513129128.33%3548517.350000200004000%000000.2500000000
14Akil ThomasRoadrunners (UTA)C281450002228339173.03%12318.2500000000000051.98%22700000.4300000010
15Ben ChiarotUtah MammothD5123-740207831012.50%1311723.560223700008010%000000.5100000001
16Nikita ChibrikovRoadrunners (UTA)RW282020201491322.22%22258.0400000000000037.50%800000.1800000010
17Max JonesRoadrunners (UTA)LW1011100421020%099.6500000000000050.00%200002.0700000000
Statistiques d’équipe totales ou en moyenne425108196304481892552653490525366811.93%248787518.532038581384881121038419857.23%233600020.7722113202022
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
1Jet GreavesRoadrunners (UTA)2819710.9092.90165401808830111.0002280320
2Akira SchmidRoadrunners (UTA)11000.9001.67360011000000028000
Statistiques d’équipe totales ou en moyenne2920710.9092.881690018189301122828320


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 Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Plafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Akil ThomasRoadrunners (UTA)C252000-01-02CANYes195 Lbs6 ft0NoNoFree AgentNoNo32024-09-04FalseFalsePro & Farm500,000$50,000$33,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Akira SchmidRoadrunners (UTA)G252000-05-12CHENo190 Lbs6 ft5NoNoTrade2024-11-08NoNo2FalseFalsePro & Farm500,000$50,000$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Anthony ManthaRoadrunners (UTA)RW311994-09-16CANNo234 Lbs6 ft5NoNoFree AgentNoNo42025-07-23FalseFalsePro & Farm2,000,000$200,000$134,444$No2,000,000$2,000,000$2,000,000$------2,000,000$2,000,000$2,000,000$------NoNoNo------Lien / Lien NHL
Artyom LevshunovRoadrunners (UTA)D202005-10-28BLRYes208 Lbs6 ft2NoNoFree AgentNoNo42025-07-25FalseFalsePro & Farm500,000$50,000$33,611$No500,000$500,000$500,000$------500,000$500,000$500,000$------NoNoNo------Lien / Lien NHL
Brandt ClarkeRoadrunners (UTA)D222003-02-09CANNo200 Lbs6 ft2NoNoTrade2024-08-13NoNo1FalseFalsePro & Farm500,000$50,000$33,611$No---------------------------Lien / Lien NHL
Cutter GauthierRoadrunners (UTA)LW212004-01-19SWEYes201 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
David GustafssonRoadrunners (UTA)C252000-04-11SWENo196 Lbs6 ft2NoNoN/ANoNo32024-08-13FalseFalsePro & Farm500,000$50,000$33,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Gustav NyquistRoadrunners (UTA)RW361989-09-01SWENo180 Lbs5 ft11NoNoFree AgentNoNo32025-08-10FalseFalsePro & Farm500,000$50,000$33,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Ian MitchellRoadrunners (UTA)D261999-01-18CANNo192 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Jet GreavesRoadrunners (UTA)G242001-03-30CANYes190 Lbs6 ft0NoNoN/ANoNo32024-08-25FalseFalsePro & Farm500,000$50,000$33,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Joey AndersonRoadrunners (UTA)RW271998-06-19USANo207 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$33,611$No---------------------------Lien / Lien NHL
John KlingbergRoadrunners (UTA)D331992-08-14SWENo185 Lbs6 ft2NoNoAssign ManuallyNoNo12025-11-23FalseFalsePro & Farm500,000$0$0$No---------------------------Lien / Lien NHL
Matthew KesselRoadrunners (UTA)D252000-06-23USANo205 Lbs6 ft2NoNoAssign ManuallyNoNo22024-08-21FalseFalsePro & Farm500,000$50,000$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Max JonesRoadrunners (UTA)LW271998-02-17USANo216 Lbs6 ft3NoNoN/ANoNo32024-08-20FalseFalsePro & Farm500,000$50,000$33,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Nico SturmRoadrunners (UTA)C301995-05-03DEUNo209 Lbs6 ft3NoNoFree AgentNoNo42025-07-23FalseFalsePro & Farm500,000$50,000$33,611$No500,000$500,000$500,000$------500,000$500,000$500,000$------NoNoNo------Lien / Lien NHL
Nikita ChibrikovRoadrunners (UTA)RW222003-02-16RUSYes170 Lbs5 ft10NoNoTrade2025-06-25NoNo2FalseFalsePro & Farm500,000$50,000$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Nils AmanRoadrunners (UTA)C252000-02-07SWENo179 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$33,611$No---------------------------Lien / Lien NHL
Oliver KapanenRoadrunners (UTA)C222003-07-29SWEYes194 Lbs6 ft2NoNoFree AgentNoNo32025-07-25FalseFalsePro & Farm500,000$50,000$33,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Ondrej PalatRoadrunners (UTA)LW341991-03-28CZENo194 Lbs6 ft0NoNoAssign ManuallyNoNo22024-08-21FalseFalsePro & Farm500,000$50,000$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Philippe MyersRoadrunners (UTA)D281997-01-25CANNo219 Lbs6 ft5NoNoN/ANoNo22024-08-20FalseFalsePro & Farm500,000$50,000$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Sam MalinskiRoadrunners (UTA)D271998-07-27USANo190 Lbs5 ft11NoNoFree AgentNoNo32024-10-07FalseFalsePro & Farm500,000$50,000$33,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Sam PoulinRoadrunners (UTA)RW242001-02-25CANNo227 Lbs6 ft2NoNoN/ANoNo22024-08-10FalseFalsePro & Farm500,000$50,000$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Thomas BordeleauRoadrunners (UTA)C232002-01-03USANo180 Lbs5 ft10NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Tyson JostRoadrunners (UTA)C271998-03-14CANNo187 Lbs5 ft11NoNoN/ANoNo32024-08-20FalseFalsePro & Farm500,000$50,000$33,611$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Ville KoivunenRoadrunners (UTA)RW222003-06-13FINNo161 Lbs5 ft11NoNoFree AgentNoNo42025-07-25FalseFalsePro & Farm500,000$50,000$33,611$No500,000$500,000$500,000$------500,000$500,000$500,000$------NoNoNo------Lien / Lien NHL
Zac JonesRoadrunners (UTA)D252000-10-18USANo190 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$33,611$No500,000$--------500,000$--------No--------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2626.00196 Lbs6 ft12.46557,692$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Cutter GauthierNico SturmGustav Nyquist40122
2Tyson JostAnthony Mantha30122
3David GustafssonJoey Anderson20122
4Cutter GauthierAkil ThomasNikita Chibrikov10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brandt Clarke40122
2Sam MalinskiPhilippe Myers30122
3Zac JonesMatthew Kessel20122
4Brandt Clarke10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Cutter GauthierNico SturmGustav Nyquist60122
2Tyson JostAnthony Mantha40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brandt Clarke60122
2Sam MalinskiPhilippe Myers40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Nico SturmCutter Gauthier60122
2Tyson Jost40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brandt Clarke60122
2Sam MalinskiPhilippe Myers40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Nico Sturm60122Brandt Clarke60122
2Tyson Jost40122Sam MalinskiPhilippe Myers40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Nico SturmCutter Gauthier60122
2Tyson Jost40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Brandt Clarke60122
2Sam MalinskiPhilippe Myers40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Cutter GauthierNico SturmGustav NyquistBrandt Clarke
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Cutter GauthierNico SturmGustav NyquistBrandt Clarke
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Anthony Mantha, Tyson Jost, David GustafssonAnthony Mantha, Tyson JostAnthony Mantha
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Philippe Myers, Zac Jones, Matthew KesselPhilippe MyersPhilippe Myers, Zac Jones
Tirs de pénalité
Gustav Nyquist, Cutter Gauthier, , Nico Sturm, Anthony Mantha
Gardien
#1 : Jet Greaves, #2 : Akira Schmid


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
1Aces11000000422110000004220000000000021.0004812004038266262952943179186411100.00%20100.00%054596256.65%51188657.67%28146959.91%759546575184358192
2Admirals330000001385220000008531100000053261.000132336004038266892952943179982418577114.29%9277.78%054596256.65%51188657.67%28146959.91%759546575184358192
3Americiens210001001165110000007161000010045-130.750111930004038266672952943179792852488337.50%40100.00%054596256.65%51188657.67%28146959.91%759546575184358192
4Barracuda11000000422000000000001100000042221.00048120040382664429529431791632184125.00%000%054596256.65%51188657.67%28146959.91%759546575184358192
5Broncos4110200017134200020009722110000086260.7501733500040382661332952943179972618566233.33%7185.71%054596256.65%51188657.67%28146959.91%759546575184358192
6Bruins10000010431000000000001000001043121.00046100040382662429529431792396173133.33%3166.67%054596256.65%51188657.67%28146959.91%759546575184358192
7Butter Knives1010000023-11010000023-10000000000000.0002460040382663529529431795120631300.00%20100.00%054596256.65%51188657.67%28146959.91%759546575184358192
8Fighting Pandas21100000431110000003031010000013-220.500461011403826654295294317961144447228.57%20100.00%054596256.65%51188657.67%28146959.91%759546575184358192
9Firebirds33000000181442200000012931100000065161.00018335100403826614929529431791253110759333.33%5260.00%154596256.65%51188657.67%28146959.91%759546575184358192
10Griffins11000000642000000000001100000064221.0006121800403826637295294317945116235360.00%30100.00%054596256.65%51188657.67%28146959.91%759546575184358192
11Ice Bats10001000321000000000001000100032121.000358004038266352952943179275913000%20100.00%054596256.65%51188657.67%28146959.91%759546575184358192
12Nordiks21100000811-30000000000021100000811-320.50081624004038266592952943179792516424375.00%7357.14%054596256.65%51188657.67%28146959.91%759546575184358192
13Quacken11000000312110000003120000000000021.000358004038266262952943179157614300.00%20100.00%054596256.65%51188657.67%28146959.91%759546575184358192
14Tomahawks1010000013-2000000000001010000013-200.00012300403826618295294317945171020100.00%40100.00%054596256.65%51188657.67%28146959.91%759546575184358192
15Wombats3020100046-21010000023-12010100023-120.3334610004038266742952943179822724564125.00%110100.00%054596256.65%51188657.67%28146959.91%759546575184358192
16Wranglers11000000716110000007160000000000021.000713200040382664329529431793310619300.00%20100.00%054596256.65%51188657.67%28146959.91%759546575184358192
Total2815704110109822713920200057322515650211052502410.7321091993081140382669132952943179894263197544682029.41%65986.15%154596256.65%51188657.67%28146959.91%759546575184358192
_Since Last GM Reset2815704110109822713920200057322515650211052502410.7321091993081140382669132952943179894263197544682029.41%65986.15%154596256.65%51188657.67%28146959.91%759546575184358192
_Vs Conference1995031107356171062020004328159330111030282270.711731302031140382666252952943179616179138384471327.66%43686.05%154596256.65%51188657.67%28146959.91%759546575184358192
_Vs Division14730300058451374102000312477320100027216200.71458107165004038266482295294317944711976267311032.26%35585.71%154596256.65%51188657.67%28146959.91%759546575184358192

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2841L110919930891389426319754411
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
28157411010982
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
139220005732
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
156521105250
Derniers 10 matchs
WLOTWOTL SOWSOL
422110
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
682029.41%65986.15%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
29529431794038266
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
54596256.65%51188657.67%28146959.91%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
759546575184358192


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
25Firebirds3Roadrunners5WSommaire du match
414Roadrunners0Wombats2LSommaire du match
729Broncos5Roadrunners6WXSommaire du match
1147Butter Knives3Roadrunners2LSommaire du match
1362Roadrunners6Nordiks4WSommaire du match
1569Wombats3Roadrunners2LSommaire du match
1676Roadrunners2Broncos3LSommaire du match
1889Roadrunners6Firebirds5WSommaire du match
2099Roadrunners5Admirals3WSommaire du match
21105Fighting Pandas0Roadrunners3WSommaire du match
25119Roadrunners1Fighting Pandas3LSommaire du match
26127Admirals2Roadrunners3WSommaire du match
28134Roadrunners2Wombats1WXSommaire du match
31146Firebirds6Roadrunners7WSommaire du match
33157Roadrunners4Barracuda2WSommaire du match
35170Admirals3Roadrunners5WSommaire du match
38182Roadrunners6Broncos3WSommaire du match
40191Aces2Roadrunners4WSommaire du match
42199Roadrunners4Americiens5LXSommaire du match
44207Roadrunners4Bruins3WXXSommaire du match
46217Wranglers1Roadrunners7WSommaire du match
48230Roadrunners1Tomahawks3LSommaire du match
49238Broncos2Roadrunners3WXSommaire du match
52251Roadrunners3Ice Bats2WXSommaire du match
53261Roadrunners6Griffins4WSommaire du match
54264Quacken1Roadrunners3WSommaire du match
57280Americiens1Roadrunners7WSommaire du match
59292Roadrunners2Nordiks7LSommaire du match
61305Fighting Pandas-Roadrunners-
65321Lynx-Roadrunners-
67330Roadrunners-Nordiks-
69343Butter Knives-Roadrunners-
71352Roadrunners-Lions-
73364Butter Knives-Roadrunners-
76379Firebirds-Roadrunners-
79393Roadrunners-Marlies-
81404Roadrunners-Lynx-
82412Fighting Pandas-Roadrunners-
84425Roadrunners-Admirals-
86434Broncos-Roadrunners-
89447Canucks-Roadrunners-
91454Roadrunners-Bruins-
93465Roadrunners-Lynx-
95471Roadrunners-Fighting Pandas-
97479Roadrunners-Barons-
98485Admirals-Roadrunners-
100500Wombats-Roadrunners-
102513Roadrunners-Wranglers-
104521Americiens-Roadrunners-
106533Roadrunners-Broncos-
108544Roadrunners-Fighting Pandas-
109550Wombats-Roadrunners-
112568Lynx-Roadrunners-
115582Firebirds-Roadrunners-
119602Lions-Roadrunners-
121612Roadrunners-Canucks-
123623Tomahawks-Roadrunners-
126641Roadrunners-Admirals-
127648Barracuda-Roadrunners-
130658Roadrunners-Marlies-
132669Roadrunners-Butter Knives-
133675Bruins-Roadrunners-
135688Roadrunners-Quacken-
137695Roadrunners-Aces-
138699Ice Bats-Roadrunners-
141716Nordiks-Roadrunners-
143728Roadrunners-Butter Knives-
145732Roadrunners-Americiens-
146741Bruins-Roadrunners-
149758Marlies-Roadrunners-
152778Barons-Roadrunners-
153783Roadrunners-Barracuda-
155790Roadrunners-Firebirds-
158806Nordiks-Roadrunners-
160815Roadrunners-Wombats-
163828Ice Bats-Roadrunners-
164835Roadrunners-Firebirds-
168851Barons-Roadrunners-
169857Roadrunners-Barracuda-
171864Roadrunners-Wombats-
173874Marlies-Roadrunners-
178897Griffins-Roadrunners-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
28 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
628,898$ 1,450,000$ 1,400,000$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
1,400,000$ 461,960$ 26 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 121 10,833$ 1,310,793$




Roadrunners Leaders statistiques des joueurs (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

Roadrunners 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

Roadrunners 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

Roadrunners Leaders statistiques des joueurs (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

Roadrunners 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