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Roadrunners
GP: 65 | W: 38 | L: 20 | OTL: 7 | P: 83
GF: 241 | GA: 221 | PP%: 26.71% | PK%: 79.31%
DG: Greg Vandersteen | Morale : 65 | Moyenne d’équipe : 58
Prochains matchs #716 vs Nordiks

Centre de jeu
Roadrunners
38-20-7, 83pts
3
FINAL
4 Aces
43-15-6, 92pts
Team Stats
L1SéquenceSOW2
21-10-1Fiche domicile23-9-0
17-10-6Fiche domicile20-6-6
3-5-2Derniers 10 matchs8-1-1
3.71Buts par match 3.77
3.40Buts contre par match 3.03
26.71%Pourcentage en avantage numérique25.56%
79.31%Pourcentage en désavantage numérique79.73%
Ice Bats
22-31-10, 54pts
4
FINAL
1 Roadrunners
38-20-7, 83pts
Team Stats
W1SéquenceL1
10-18-4Fiche domicile21-10-1
12-13-6Fiche domicile17-10-6
4-5-1Derniers 10 matchs3-5-2
4.14Buts par match 3.71
5.03Buts contre par match 3.40
26.67%Pourcentage en avantage numérique26.71%
75.00%Pourcentage en désavantage numérique79.31%
Nordiks
36-24-6, 78pts
Jour 141
Roadrunners
38-20-7, 83pts
Statistiques d’équipe
L1SéquenceL1
16-12-4Fiche domicile21-10-1
20-12-2Fiche visiteur17-10-6
5-3-210 derniers matchs3-5-2
5.26Buts par match 3.71
4.86Buts contre par match 3.71
20.95%Pourcentage en avantage numérique26.71%
73.58%Pourcentage en désavantage numérique79.31%
Roadrunners
38-20-7, 83pts
Jour 143
Butter Knives
27-28-7, 61pts
Statistiques d’équipe
L1SéquenceL1
21-10-1Fiche domicile16-13-3
17-10-6Fiche visiteur11-15-4
3-5-210 derniers matchs3-5-2
3.71Buts par match 4.77
3.40Buts contre par match 4.77
26.71%Pourcentage en avantage numérique21.32%
79.31%Pourcentage en désavantage numérique75.80%
Roadrunners
38-20-7, 83pts
Jour 145
Americiens
36-23-3, 75pts
Statistiques d’équipe
L1SéquenceW3
21-10-1Fiche domicile18-12-2
17-10-6Fiche visiteur18-11-1
3-5-210 derniers matchs6-3-1
3.71Buts par match 5.03
3.40Buts contre par match 5.03
26.71%Pourcentage en avantage numérique24.44%
79.31%Pourcentage en désavantage numérique71.52%
Meneurs d'équipe
Anthony ManthaButs
Anthony Mantha
28
Tyson JostPasses
Tyson Jost
49
Tyson JostPoints
Tyson Jost
73
Philippe MyersPlus/Moins
Philippe Myers
19
Akira SchmidVictoires
Akira Schmid
7
Akira SchmidPourcentage d’arrêts
Akira Schmid
0.842

Statistiques d’équipe
Buts pour
241
3.71 GFG
Tirs pour
1998
30.74 Avg
Pourcentage en avantage numérique
26.7%
39 GF
Début de zone offensive
40.6%
Buts contre
221
3.40 GAA
Tirs contre
2049
31.52 Avg
Pourcentage en désavantage numérique
79.3%%
30 GA
Début de la zone défensive
38.3%
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
1Ondrej PalatX100.00765591696974887050657062517874056660342500,000$
2Gustav NyquistX99.00615590676280916950676567638278074650363500,000$
3Nico Sturm (A)X100.00786692677567757177646166507472075640304500,000$
4Anthony ManthaX100.006869776384665470506170556373740756203142,000,000$
5Tyson JostX100.00696178666665627361645960506666076610273500,000$
6David GustafssonX100.00606997657062606867615361506464074590253500,000$
7Akil Thomas (R)X100.00737096636964566351565056506363073570263500,000$
8Nils AmanX100.00635493626460546953615056506062018570261500,000$
9Max JonesX100.00826166617863565650555057506563018560283500,000$
10Joey AndersonX100.00585099577464555150524964506870061550271500,000$
11Ville KoivunenX100.00505775545562555850665049506169018540224500,000$
12Philippe MyersX100.00796785607968636550575370556971074630292500,000$
13Zac JonesX100.00655977666871687050665168556264074630252500,000$
14Troy StecherX100.00626284616466796450545270557372045620312500,000$
15Matthew KesselX100.00655982607462586450555265556466074600252500,000$
16Artyom Levshunov (R)X100.00646077647557586550635059555156018580204500,000$
17Ian MitchellX100.00525692556851555750505161556365018550272500,000$
Rayé
1Oliver Kapanen (R)X100.00505593577061545257545056625557020530223500,000$
2Nikita Chibrikov (R)X100.00493590586050515050495348515765063510232500,000$
3Thomas BordeleauX100.00503589576350515050505050506362020510242500,000$
4Sam PoulinX100.00575885508150515250505050505859020510242500,000$
5John KlingbergX100.00506265576654555350505051567674040540332500,000$
MOYENNE D’ÉQUIPE99.9563588561706261625358545953666704958
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 Schmid100.0056626274504748484651506161020540252500,000$
Rayé
MOYENNE D’ÉQUIPE100.005662627450474848465150616102054
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)C652449734175901641914614812.57%20132620.4151318261030110533253.25%129200021.1024001727
2Anthony ManthaRoadrunners (UTA)RW65282856-85810107531865416115.05%8146622.563912171001013581448.33%18000000.7612002373
3Nico SturmRoadrunners (UTA)C65213354132801181391854812611.35%21114417.612682012900021184061.93%156800000.9413000245
4Brandt ClarkeUtah MammothD419415015280766161245014.75%5098924.1341014308102206801100.00%100001.0101000253
5David GustafssonRoadrunners (UTA)C65222749-3115241501905810911.58%13116217.8800007000051156.28%109100010.8413001313
6Gustav NyquistRoadrunners (UTA)RW4322244656027711556313014.19%1486720.1709916740001364434.62%5200011.0612000434
7Ondrej PalatRoadrunners (UTA)LW41232346-427578621553714814.84%1385020.759413286300037110254.87%11300011.0801010535
8Sam MalinskiUtah MammothD4883543108039638920458.99%64113323.6234722600003533233.33%1200000.7600000223
9Cutter GauthierUtah MammothLW352220421614059691714615212.87%1292926.5731418621012652038.18%5500010.9011000622
10Philippe MyersRoadrunners (UTA)D65830381936101304874195010.81%74124819.2035822840000891128.57%700000.6101101245
11Zac JonesRoadrunners (UTA)D6543337-14240101676132486.56%84132520.3923513320001571038.46%1300000.5611000122
12Akil ThomasRoadrunners (UTA)C6591120-14140718911828707.63%788013.55000000001131150.38%79000000.4500000032
13Matthew KesselRoadrunners (UTA)D6541519-1647582414417309.09%67117918.14202421000028000%100000.3211010010
14Troy StecherRoadrunners (UTA)D14410141601512166825.00%1931822.76112516000026000%000000.8800000120
15Joey AndersonRoadrunners (UTA)RW504101424023316117396.56%978915.7800016000001062.50%4000000.3500000000
16Max JonesRoadrunners (UTA)LW15336-3403041741117.65%228919.32101218000040062.50%1600000.4100000000
17Artyom LevshunovRoadrunners (UTA)D14066-31203348030%822716.250001100004000%000000.5300000010
18Ian MitchellRoadrunners (UTA)D14314-30071280337.50%1222916.4000000000013000%000000.3500000000
19Nikita ChibrikovRoadrunners (UTA)RW452241205111431414.29%251011.3400000000000056.00%2500000.1600000010
20Ben ChiarotUtah MammothD5123-740207831012.50%1311723.560223700008010%000000.5100000001
21Ville KoivunenRoadrunners (UTA)RW14022-400556360%117812.7300000000000045.45%1100000.2200000000
22Nils AmanRoadrunners (UTA)C141012201121350.00%0453.280000300002000%600000.4400000000
Statistiques d’équipe totales ou en moyenne913222405627935240114111641820529136412.20%5131721018.85386710522887723516779321955.47%527300060.73920125384345
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)227830.8424.74103800825190110.37582051101
Statistiques d’équipe totales ou en moyenne67381860.8943.293699012031910042196551831


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$11,667$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$11,667$No500,000$--------500,000$--------No--------Lien / Lien NHL
Anthony ManthaRoadrunners (UTA)RW311994-09-16CANNo234 Lbs6 ft5NoNoFree AgentNoNo42025-07-23FalseFalsePro & Farm2,000,000$200,000$46,667$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$11,667$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$11,667$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$11,667$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$11,667$No500,000$--------500,000$--------No--------Lien / Lien NHL
Joey AndersonRoadrunners (UTA)RW271998-06-19USANo207 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$11,667$No---------------------------Lien / Lien NHL
John KlingbergRoadrunners (UTA)D331992-08-14SWENo185 Lbs6 ft2NoNoAssign ManuallyNoNo22025-12-18FalseFalsePro & Farm500,000$50,000$11,667$No500,000$-----------------No--------Lien / Lien NHL
Matthew KesselRoadrunners (UTA)D252000-06-23USANo205 Lbs6 ft2NoNoAssign ManuallyNoNo22024-08-21FalseFalsePro & Farm500,000$50,000$11,667$No500,000$--------500,000$--------No--------Lien / Lien NHL
Max JonesRoadrunners (UTA)LW281998-02-17USANo216 Lbs6 ft3NoNoN/ANoNo32024-08-20FalseFalsePro & Farm500,000$50,000$11,667$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$11,667$No500,000$500,000$500,000$------500,000$500,000$500,000$------NoNoNo------Lien / Lien NHL
Nikita ChibrikovRoadrunners (UTA)RW232003-02-16RUSYes170 Lbs5 ft10NoNoTrade2025-06-25NoNo2FalseFalsePro & Farm500,000$50,000$11,667$No500,000$--------500,000$--------No--------Lien / Lien NHL
Nils AmanRoadrunners (UTA)C262000-02-07SWENo179 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$11,667$No---------------------------Lien / Lien NHL
Oliver KapanenRoadrunners (UTA)C222003-07-29SWEYes194 Lbs6 ft2NoNoFree AgentNoNo32025-07-25FalseFalsePro & Farm500,000$50,000$11,667$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$11,667$No500,000$--------500,000$--------No--------Lien / Lien NHL
Philippe MyersRoadrunners (UTA)D291997-01-25CANNo219 Lbs6 ft5NoNoN/ANoNo22024-08-20FalseFalsePro & Farm500,000$50,000$11,667$No500,000$--------500,000$--------No--------Lien / Lien NHL
Sam PoulinRoadrunners (UTA)RW242001-02-25CANNo227 Lbs6 ft2NoNoN/ANoNo22024-08-10FalseFalsePro & Farm500,000$50,000$11,667$No500,000$--------500,000$--------No--------Lien / Lien NHL
Thomas BordeleauRoadrunners (UTA)C242002-01-03USANo180 Lbs5 ft10NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$11,667$No500,000$--------500,000$--------No--------Lien / Lien NHL
Troy StecherRoadrunners (UTA)D311994-04-07CANNo184 Lbs5 ft10NoNoFree AgentNoNo22026-01-18FalseFalsePro & Farm500,000$50,000$11,667$No500,000$--------500,000$--------No--------Lien / Lien NHL
Tyson JostRoadrunners (UTA)C271998-03-14CANNo187 Lbs5 ft11NoNoN/ANoNo32024-08-20FalseFalsePro & Farm500,000$50,000$11,667$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$11,667$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$11,667$No500,000$--------500,000$--------No--------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2326.96196 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
1Aces21000001761110000004221000000134-130.750714210076847315506286457014448131027200.00%50100.00%01197213256.14%1126200956.05%621110956.00%170512251401436837437
2Admirals650001003221113200010014122330000001899110.917325890007684731518062864570144171433212113538.46%16475.00%01197213256.14%1126200956.05%621110956.00%170512251401436837437
3Americiens320001001376220000009271000010045-150.83313233600768473151086286457014411439546811327.27%50100.00%01197213256.14%1126200956.05%621110956.00%170512251401436837437
4Barons11000000532000000000001100000053221.000510150076847315326286457014434110112150.00%000%01197213256.14%1126200956.05%621110956.00%170512251401436837437
5Barracuda2110000078-11010000036-31100000042220.500714210076847315696286457014441116436116.67%20100.00%01197213256.14%1126200956.05%621110956.00%170512251401436837437
6Broncos611031002218430003000129331100100109190.7502243650076847315192628645701441474637908225.00%14378.57%01197213256.14%1126200956.05%621110956.00%170512251401436837437
7Bruins31100010811-31010000016-52100001075240.6678122000768473158862864570144752716579111.11%7271.43%01197213256.14%1126200956.05%621110956.00%170512251401436837437
8Butter Knives4220000016160321000009721010000079-240.50016294500768473151266286457014417765169511436.36%6350.00%01197213256.14%1126200956.05%621110956.00%170512251401436837437
9Canucks21000100770110000003211000010045-130.75071118007684731539628645701446920933200.00%2150.00%01197213256.14%1126200956.05%621110956.00%170512251401436837437
10Fighting Pandas6320001017134321000009633110001087180.667172744117684731516762864570144172462410820525.00%110100.00%11197213256.14%1126200956.05%621110956.00%170512251401436837437
11Firebirds541000002722543100000211741100000065180.800274976007684731519562864570144169392410214428.57%12466.67%21197213256.14%1126200956.05%621110956.00%170512251401436837437
12Griffins11000000642000000000001100000064221.000612180076847315376286457014445116235360.00%30100.00%01197213256.14%1126200956.05%621110956.00%170512251401436837437
13Ice Bats2010100046-21010000014-31000100032120.500461000768473156162864570144712115333133.33%40100.00%01197213256.14%1126200956.05%621110956.00%170512251401436837437
14Lions211000007521010000034-11100000041320.500711180076847315716286457014470218444250.00%3166.67%01197213256.14%1126200956.05%621110956.00%170512251401436837437
15Lynx411000021314-1211000008712000000257-240.500132437007684731513262864570144106331871100.00%9366.67%01197213256.14%1126200956.05%621110956.00%170512251401436837437
16Marlies21100000510-50000000000021100000510-520.500591400768473154562864570144561013387228.57%4250.00%01197213256.14%1126200956.05%621110956.00%170512251401436837437
17Nordiks31200000915-60000000000031200000915-620.33391726007684731591628645701441313922676350.00%10370.00%01197213256.14%1126200956.05%621110956.00%170512251401436837437
18Quacken2110000068-2110000003121010000037-420.5006101600768473154662864570144491212375120.00%5180.00%01197213256.14%1126200956.05%621110956.00%170512251401436837437
19Tomahawks2010100078-1100010006511010000013-220.500713200076847315456286457014481271834100.00%80100.00%01197213256.14%1126200956.05%621110956.00%170512251401436837437
20Wombats51301000121203120000010912010100023-140.4001219310076847315148628645701441413932871119.09%15286.67%01197213256.14%1126200956.05%621110956.00%170512251401436837437
21Wranglers211000001174110000007161010000046-220.5001120311076847315766286457014482201036500.00%4175.00%01197213256.14%1126200956.05%621110956.00%170512251401436837437
Total6530200642324122120321710041001231002333131002323118121-3830.6382414316722176847315199862864570144204959338212251463926.71%1453079.31%31197213256.14%1126200956.05%621110956.00%170512251401436837437
_Since Last GM Reset6530200642324122120321710041001231002333131002323118121-3830.6382414316722176847315199862864570144204959338212251463926.71%1453079.31%31197213256.14%1126200956.05%621110956.00%170512251401436837437
_Vs Conference4421120432216514421241370310093751820850122272693590.670165293458117684731513816286457014413283872668371052725.71%992376.77%31197213256.14%1126200956.05%621110956.00%170512251401436837437
_Vs Division2311504200997722136303100574710105201100423012320.69699181280007684731575262864570144673178131423511529.41%601378.33%21197213256.14%1126200956.05%621110956.00%170512251401436837437

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
6583L124143167219982049593382122521
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
6530206423241221
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3217104100123100
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3313102323118121
Derniers 10 matchs
WLOTWOTL SOWSOL
251101
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1463926.71%1453079.31%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
6286457014476847315
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
1197213256.14%1126200956.05%621110956.00%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
170512251401436837437


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
115582Firebirds6Roadrunners4LSommaire du match
119602Lions4Roadrunners3LSommaire du match
121612Roadrunners4Canucks5LXSommaire du match
123623Tomahawks5Roadrunners6WXSommaire du match
126641Roadrunners7Admirals3WSommaire du match
127648Barracuda6Roadrunners3LSommaire du match
130658Roadrunners4Marlies3WSommaire du match
132669Roadrunners7Butter Knives9LSommaire du match
133675Bruins6Roadrunners1LSommaire du match
135688Roadrunners3Quacken7LSommaire du match
137695Roadrunners3Aces4LXXSommaire du match
138699Ice Bats4Roadrunners1LSommaire du match
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
9 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,438,075$ 1,300,000$ 1,300,000$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
1,300,000$ 1,031,390$ 23 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 42 10,000$ 420,000$




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