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Roadrunners
GP: 53 | W: 35 | L: 13 | OTL: 5 | P: 75
GF: 195 | GA: 159 | PP%: 25.81% | PK%: 81.42%
DG: Greg Vandersteen | Morale : 74 | Moyenne d’équipe : 58
Prochains matchs #582 vs Firebirds

Centre de jeu
Wombats
26-17-8, 60pts
4
FINAL
8 Roadrunners
35-13-5, 75pts
Team Stats
W2SéquenceL1
12-12-3Fiche domicile20-5-1
14-5-5Fiche domicile15-8-4
7-3-0Derniers 10 matchs5-3-2
4.16Buts par match 3.68
3.86Buts contre par match 3.00
21.60%Pourcentage en avantage numérique25.81%
87.88%Pourcentage en désavantage numérique81.42%
Lynx
31-19-1, 63pts
6
FINAL
4 Roadrunners
35-13-5, 75pts
Team Stats
L1SéquenceL1
15-11-1Fiche domicile20-5-1
16-8-0Fiche domicile15-8-4
5-5-0Derniers 10 matchs5-3-2
4.00Buts par match 3.68
3.57Buts contre par match 3.00
31.82%Pourcentage en avantage numérique25.81%
85.19%Pourcentage en désavantage numérique81.42%
Firebirds
20-32-2, 42pts
Jour 115
Roadrunners
35-13-5, 75pts
Statistiques d’équipe
L2SéquenceL1
11-14-1Fiche domicile20-5-1
9-18-1Fiche visiteur15-8-4
0-9-110 derniers matchs5-3-2
4.00Buts par match 3.68
4.63Buts contre par match 3.68
19.35%Pourcentage en avantage numérique25.81%
76.07%Pourcentage en désavantage numérique81.42%
Lions
23-30-0, 46pts
Jour 119
Roadrunners
35-13-5, 75pts
Statistiques d’équipe
OTW1SéquenceL1
14-12-0Fiche domicile20-5-1
9-18-0Fiche visiteur15-8-4
4-6-010 derniers matchs5-3-2
4.77Buts par match 3.68
5.17Buts contre par match 3.68
21.37%Pourcentage en avantage numérique25.81%
73.10%Pourcentage en désavantage numérique81.42%
Roadrunners
35-13-5, 75pts
Jour 121
Canucks
25-22-7, 57pts
Statistiques d’équipe
L1SéquenceOTL1
20-5-1Fiche domicile14-8-4
15-8-4Fiche visiteur11-14-3
5-3-210 derniers matchs4-4-2
3.68Buts par match 4.07
3.00Buts contre par match 4.07
25.81%Pourcentage en avantage numérique30.83%
81.42%Pourcentage en désavantage numérique78.33%
Meneurs d'équipe
Ondrej PalatButs
Ondrej Palat
19
Tyson JostPasses
Tyson Jost
39
Tyson JostPoints
Tyson Jost
56
Philippe MyersPlus/Moins
Philippe Myers
19
Akira SchmidVictoires
Akira Schmid
4
Akira SchmidPourcentage d’arrêts
Akira Schmid
0.873

Statistiques d’équipe
Buts pour
195
3.68 GFG
Tirs pour
1677
31.64 Avg
Pourcentage en avantage numérique
25.8%
32 GF
Début de zone offensive
41.7%
Buts contre
159
3.00 GAA
Tirs contre
1658
31.28 Avg
Pourcentage en désavantage numérique
81.4%%
21 GA
Début de la zone défensive
38.2%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro23
Équipe Mineure20
Limite contact 43 / 50
Espoirs44


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
1Gustav NyquistX100.00615590676280916850666468638177080650363500,000$
2Ondrej PalatX100.00755591696974886950647063517774060650342500,000$
3Nico Sturm (A)X100.00786692677567757177636167507472081640304500,000$
4Anthony ManthaX100.006869776384665470506069556373740806203142,000,000$
5Tyson JostX100.00696178666665627260635860506666082610273500,000$
6David GustafssonX100.00606997657062606867605261506464080590253500,000$
7Akil Thomas (R)X100.00737096636964566351565057506363079570263500,000$
8Nils AmanX100.00635493626460546953615056506062022570251500,000$
9Max JonesX100.00816166617863565650555058506462023560273500,000$
10Joey AndersonX100.00585099577464555150525064506769066550271500,000$
11Ville KoivunenX100.00505775545562555850665050506169020540224500,000$
12Philippe MyersX100.00796785607968636550565370556971081630292500,000$
13Zac JonesX100.00655977666871687050655168556264080630252500,000$
14Troy StecherX100.00626284616466796350535070557372046620312500,000$
15Matthew KesselX100.00655982607462586350545166556466080600252500,000$
16Artyom Levshunov (R)X100.00646077647557586550635059555156023580204500,000$
17Ian MitchellX100.00525692556851555750505161556365023550272500,000$
Rayé
1Oliver Kapanen (R)X100.00505593577061545257545056625557020530223500,000$
2Nikita Chibrikov (R)X100.00493590586050515050495348515765075510222500,000$
3Thomas BordeleauX100.00503589576350515050505050506362020510242500,000$
4Sam PoulinX100.00575885508150515250505050505859020510242500,000$
5John KlingbergX100.00506265576654555350505051567674052540332500,000$
MOYENNE D’ÉQUIPE100.0063588561706261625357545953666705458
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
1Akira Schmid100.0056626274504950504951506060073540252500,000$
Rayé
MOYENNE D’ÉQUIPE100.005662627450495050495150606007354
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
1Tyson JostRoadrunners (UTA)C5317395614175801281523712211.18%17109420.654121622860110532153.77%103400011.0213001526
2Brandt ClarkeUtah MammothD419415015280766161245014.75%5098924.1341014308102206801100.00%100001.0101000253
3Nico SturmRoadrunners (UTA)C5319284713220991181634011711.66%1999918.861451811400021034061.86%137400000.9402000235
4Sam MalinskiUtah MammothD4883543108039638920458.99%64113323.6234722600003533233.33%1200000.7600000223
5Cutter GauthierUtah MammothLW352220421614059691714615212.87%1292926.5731418621012652038.18%5500010.9011000622
6Anthony ManthaRoadrunners (UTA)RW53192140253595421484412712.84%5121923.00371014831013421247.85%16300000.6611001262
7David GustafssonRoadrunners (UTA)C53182240-24022123167479310.78%11100719.0000006000051156.24%93700010.7913000313
8Gustav NyquistRoadrunners (UTA)RW311718356401642122408413.93%1057318.510771560000054333.33%3000011.2211000333
9Ondrej PalatRoadrunners (UTA)LW29191534023548351102610317.27%655619.19831124490002438259.46%3700011.2200010534
10Philippe MyersRoadrunners (UTA)D5372431193210963861164111.48%5697118.3334719690000641128.57%700000.6400101224
11Zac JonesRoadrunners (UTA)D5332225-518084544425366.82%61106920.181125150001311038.46%1300000.4700000121
12Akil ThomasRoadrunners (UTA)C537916-124058729424617.45%571313.4600000000121151.07%60900000.4500000032
13Matthew KesselRoadrunners (UTA)D5331114-733565323312209.09%5493017.5710125000010000%100000.3000010010
14Joey AndersonRoadrunners (UTA)RW38371042021244715326.38%963716.7700016000001063.89%3600000.3100000000
15Nikita ChibrikovRoadrunners (UTA)RW452241205111431414.29%251011.3400000000000056.00%2500000.1600000010
16Ben ChiarotUtah MammothD5123-740207831012.50%1311723.560223700008010%000000.5100000001
17Max JonesRoadrunners (UTA)LW31237209341325.00%04916.5000001000000066.67%300001.2100000000
18Troy StecherRoadrunners (UTA)D2022100243020%34623.280000100004000%000000.8600000000
19Artyom LevshunovRoadrunners (UTA)D2022140314000%23316.760000000000000%000001.1900000000
20Ian MitchellRoadrunners (UTA)D21011000430033.33%03417.130000000001000%000000.5800000000
21Ville KoivunenRoadrunners (UTA)RW2011-200011020%12613.18000000000000100.00%100000.7600000000
22Nils AmanRoadrunners (UTA)C2000000010000%052.960000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne70917632349975274308979331499423111411.74%4001365019.2531558619371523514565291555.95%433800050.73512123333639
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 GreavesUtah Mammoth45311030.9132.7326600112113910310.72711450730
2Akira SchmidRoadrunners (UTA)104320.8733.77525003325901100851101
Statistiques d’équipe totales ou en moyenne55351350.9072.903186011541650042115351831


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)C262000-01-02CANYes195 Lbs6 ft0NoNoFree AgentNoNo32024-09-04FalseFalsePro & Farm500,000$50,000$18,333$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$18,333$No500,000$--------500,000$--------No--------Lien / Lien NHL
Anthony ManthaRoadrunners (UTA)RW311994-09-16CANNo234 Lbs6 ft5NoNoFree AgentNoNo42025-07-23FalseFalsePro & Farm2,000,000$200,000$73,333$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$18,333$No500,000$500,000$500,000$------500,000$500,000$500,000$------NoNoNo------Lien / Lien NHL
David GustafssonRoadrunners (UTA)C252000-04-11SWENo196 Lbs6 ft2NoNoN/ANoNo32024-08-13FalseFalsePro & Farm500,000$50,000$18,333$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$18,333$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Ian MitchellRoadrunners (UTA)D271999-01-18CANNo192 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$18,333$No500,000$--------500,000$--------No--------Lien / Lien NHL
Joey AndersonRoadrunners (UTA)RW271998-06-19USANo207 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$18,333$No---------------------------Lien / Lien NHL
John KlingbergRoadrunners (UTA)D331992-08-14SWENo185 Lbs6 ft2NoNoAssign ManuallyNoNo22025-12-18FalseFalsePro & Farm500,000$0$0$No500,000$-----------------No--------Lien / Lien NHL
Matthew KesselRoadrunners (UTA)D252000-06-23USANo205 Lbs6 ft2NoNoAssign ManuallyNoNo22024-08-21FalseFalsePro & Farm500,000$50,000$18,333$No500,000$--------500,000$--------No--------Lien / Lien NHL
Max JonesRoadrunners (UTA)LW271998-02-17USANo216 Lbs6 ft3NoNoN/ANoNo32024-08-20FalseFalsePro & Farm500,000$50,000$18,333$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$18,333$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$18,333$No500,000$--------500,000$--------No--------Lien / Lien NHL
Nils AmanRoadrunners (UTA)C252000-02-07SWENo179 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$18,333$No---------------------------Lien / Lien NHL
Oliver KapanenRoadrunners (UTA)C222003-07-29SWEYes194 Lbs6 ft2NoNoFree AgentNoNo32025-07-25FalseFalsePro & Farm500,000$50,000$18,333$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$18,333$No500,000$--------500,000$--------No--------Lien / Lien NHL
Philippe MyersRoadrunners (UTA)D291997-01-25CANNo219 Lbs6 ft5NoNoN/ANoNo22024-08-20FalseFalsePro & Farm500,000$50,000$18,333$No500,000$--------500,000$--------No--------Lien / Lien NHL
Sam PoulinRoadrunners (UTA)RW242001-02-25CANNo227 Lbs6 ft2NoNoN/ANoNo22024-08-10FalseFalsePro & Farm500,000$50,000$18,333$No500,000$--------500,000$--------No--------Lien / Lien NHL
Thomas BordeleauRoadrunners (UTA)C242002-01-03USANo180 Lbs5 ft10NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$18,333$No500,000$--------500,000$--------No--------Lien / Lien NHL
Troy StecherRoadrunners (UTA)D311994-04-07CANNo184 Lbs5 ft10NoNoFree AgentNoNo22026-01-18FalseFalsePro & Farm500,000$50,000$18,333$No500,000$--------500,000$--------No--------Lien / Lien NHL
Tyson JostRoadrunners (UTA)C271998-03-14CANNo187 Lbs5 ft11NoNoN/ANoNo32024-08-20FalseFalsePro & Farm500,000$50,000$18,333$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$18,333$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$18,333$No500,000$--------500,000$--------No--------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2326.83196 Lbs6 ft12.52565,217$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Ondrej PalatNico SturmGustav Nyquist40122
2Max JonesTyson JostAnthony Mantha30122
3Ondrej PalatDavid GustafssonJoey Anderson20122
4Gustav NyquistAkil ThomasVille Koivunen10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Philippe MyersTroy Stecher40122
2Zac JonesMatthew Kessel30122
3Artyom LevshunovIan Mitchell20122
4Philippe MyersTroy Stecher10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Ondrej PalatNico SturmGustav Nyquist60122
2Max JonesTyson JostAnthony Mantha40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Philippe MyersTroy Stecher60122
2Zac JonesMatthew Kessel40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Ondrej PalatGustav Nyquist60122
2Nico SturmAnthony Mantha40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Philippe MyersTroy Stecher60122
2Zac JonesMatthew Kessel40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Ondrej Palat60122Philippe MyersTroy Stecher60122
2Gustav Nyquist40122Zac JonesMatthew Kessel40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Ondrej PalatGustav Nyquist60122
2Nico SturmAnthony Mantha40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Philippe MyersTroy Stecher60122
2Zac JonesMatthew Kessel40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ondrej PalatNico SturmGustav NyquistPhilippe MyersTroy Stecher
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ondrej PalatNico SturmGustav NyquistPhilippe MyersTroy Stecher
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Nils Aman, David Gustafsson, Akil ThomasNils Aman, David GustafssonAkil Thomas
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Artyom Levshunov, Ian Mitchell, Zac JonesArtyom LevshunovIan Mitchell, Zac Jones
Tirs de pénalité
Ondrej Palat, Gustav Nyquist, Nico Sturm, Anthony Mantha, Tyson Jost
Gardien
#1 : Akira Schmid, #2 :


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
1Aces11000000422110000004220000000000021.000481200636857102652854758133186411100.00%20100.00%01010180256.05%943165157.12%49387056.67%141210161123354681359
2Admirals5400010025187320001001412222000000116590.900254570006368571015452854758133146322610013538.46%13376.92%01010180256.05%943165157.12%49387056.67%141210161123354681359
3Americiens320001001376220000009271000010045-150.83313233600636857101085285475813311439546811327.27%50100.00%01010180256.05%943165157.12%49387056.67%141210161123354681359
4Barons11000000532000000000001100000053221.000510150063685710325285475813334110112150.00%000%01010180256.05%943165157.12%49387056.67%141210161123354681359
5Barracuda11000000422000000000001100000042221.0004812006368571044528547581331632184125.00%000%01010180256.05%943165157.12%49387056.67%141210161123354681359
6Broncos611031002218430003000129331100100109190.7502243650063685710192528547581331474637908225.00%14378.57%01010180256.05%943165157.12%49387056.67%141210161123354681359
7Bruins21000010752000000000002100001075241.0007101700636857106752854758133461710347114.29%4175.00%01010180256.05%943165157.12%49387056.67%141210161123354681359
8Butter Knives32100000972321000009720000000000040.6679162500636857108752854758133128518678225.00%3166.67%01010180256.05%943165157.12%49387056.67%141210161123354681359
9Canucks11000000321110000003210000000000021.00035800636857101552854758133307013100.00%000%01010180256.05%943165157.12%49387056.67%141210161123354681359
10Fighting Pandas6320001017134321000009633110001087180.667172744116368571016752854758133172462410820525.00%110100.00%11010180256.05%943165157.12%49387056.67%141210161123354681359
11Firebirds440000002316733000000171161100000065181.00023426500636857101705285475813314935208811327.27%10280.00%21010180256.05%943165157.12%49387056.67%141210161123354681359
12Griffins11000000642000000000001100000064221.000612180063685710375285475813345116235360.00%30100.00%01010180256.05%943165157.12%49387056.67%141210161123354681359
13Ice Bats10001000321000000000001000100032121.00035800636857103552854758133275913000%20100.00%01010180256.05%943165157.12%49387056.67%141210161123354681359
14Lions11000000413000000000001100000041321.00046100063685710285285475813340134262150.00%110.00%01010180256.05%943165157.12%49387056.67%141210161123354681359
15Lynx411000021314-1211000008712000000257-240.500132437006368571013252854758133106331871100.00%9366.67%01010180256.05%943165157.12%49387056.67%141210161123354681359
16Marlies1010000017-6000000000001010000017-600.000123006368571024528547581332632164125.00%110.00%01010180256.05%943165157.12%49387056.67%141210161123354681359
17Nordiks31200000915-60000000000031200000915-620.33391726006368571091528547581331313922676350.00%10370.00%01010180256.05%943165157.12%49387056.67%141210161123354681359
18Quacken11000000312110000003120000000000021.00035800636857102652854758133157614300.00%20100.00%01010180256.05%943165157.12%49387056.67%141210161123354681359
19Tomahawks1010000013-2000000000001010000013-200.0001230063685710185285475813345171020100.00%40100.00%01010180256.05%943165157.12%49387056.67%141210161123354681359
20Wombats51301000121203120000010912010100023-140.4001219310063685710148528547581331413932871119.09%15286.67%01010180256.05%943165157.12%49387056.67%141210161123354681359
21Wranglers211000001174110000007161010000046-220.5001120311063685710765285475813382201036500.00%4175.00%01010180256.05%943165157.12%49387056.67%141210161123354681359
Total532813053221951593626175031001056936271180222290900750.708195349544216368571016775285475813316584803049811243225.81%1132181.42%31010180256.05%943165157.12%49387056.67%141210161123354681359
_Since Last GM Reset532813053221951593626175031001056936271180222290900750.708195349544216368571016775285475813316584803049811243225.81%1132181.42%31010180256.05%943165157.12%49387056.67%141210161123354681359
_Vs Conference391990432214211725221350310088632517640122254540550.70514225139311636857101249528547581331175341231729942324.47%851681.18%31010180256.05%943165157.12%49387056.67%141210161123354681359
_Vs Division21104042008868201262031005341129420110035278300.71488161249006368571070152854758133628163121388481429.17%551081.82%21010180256.05%943165157.12%49387056.67%141210161123354681359

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
5375L11953495441677165848030498121
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
5328135322195159
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
26175310010569
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
2711822229090
Derniers 10 matchs
WLOTWOTL SOWSOL
430210
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1243225.81%1132181.42%3
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
5285475813363685710
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
1010180256.05%943165157.12%49387056.67%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
141210161123354681359


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 Pandas2Roadrunners4WSommaire du match
65321Lynx1Roadrunners4WSommaire du match
67330Roadrunners1Nordiks4LSommaire du match
69343Butter Knives1Roadrunners3WSommaire du match
71352Roadrunners4Lions1WSommaire du match
73364Butter Knives3Roadrunners4WSommaire du match
76379Firebirds2Roadrunners5WSommaire du match
79393Roadrunners1Marlies7LSommaire du match
81404Roadrunners1Lynx2LXXSommaire du match
82412Fighting Pandas4Roadrunners2LSommaire du match
84425Roadrunners6Admirals3WSommaire du match
86434Broncos2Roadrunners3WXSommaire du match
89447Canucks2Roadrunners3WSommaire du match
91454Roadrunners3Bruins2WSommaire du match
93465Roadrunners4Lynx5LXXSommaire du match
95471Roadrunners3Fighting Pandas2WXXSommaire du match
97479Roadrunners5Barons3WSommaire du match
98485Admirals7Roadrunners6LXSommaire du match
100500Wombats2Roadrunners0LSommaire du match
102513Roadrunners4Wranglers6LSommaire du match
104521Americiens1Roadrunners2WSommaire du match
106533Roadrunners2Broncos3LXSommaire du match
108544Roadrunners4Fighting Pandas2WSommaire du match
109550Wombats4Roadrunners8WSommaire du match
112568Lynx6Roadrunners4LSommaire du match
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-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
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
15 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,198,075$ 1,300,000$ 1,250,000$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
1,250,000$ 863,066$ 23 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 66 10,000$ 660,000$




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