Tucson Roadrunners
GP: 81 | W: 19 | L: 51 | OTL: 11 | P: 49
GF: 212 | GA: 326 | PP%: 16.90% | PK%: 75.36%
DG: Devon | Morale : 50 | Moyenne d’équipe : 57
Prochains matchs #1303 vs Lehigh Valley Phantoms
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Centre de jeu
Tucson Roadrunners
19-51-11, 49pts
5
FINAL
4 Abbotsford Canucks
29-41-11, 69pts
Team Stats
OTL1SéquenceL1
11-21-8Fiche domicile16-15-9
8-30-3Fiche domicile13-26-2
6-3-1Derniers 10 matchs4-4-2
2.62Buts par match 3.01
4.02Buts contre par match 3.79
16.90%Pourcentage en avantage numérique20.85%
75.36%Pourcentage en désavantage numérique76.71%
Charlotte Checkers
40-29-12, 92pts
4
FINAL
3 Tucson Roadrunners
19-51-11, 49pts
Team Stats
L1SéquenceOTL1
18-17-6Fiche domicile11-21-8
22-12-6Fiche domicile8-30-3
3-5-2Derniers 10 matchs6-3-1
3.49Buts par match 2.62
3.35Buts contre par match 4.02
18.01%Pourcentage en avantage numérique16.90%
77.36%Pourcentage en désavantage numérique75.36%
Lehigh Valley Phantoms
33-43-5, 71pts
2026-02-18
Tucson Roadrunners
19-51-11, 49pts
Statistiques d’équipe
W1SéquenceOTL1
21-19-1Fiche domicile11-21-8
12-24-4Fiche visiteur8-30-3
5-5-010 derniers matchs6-3-1
3.26Buts par match 2.62
3.73Buts contre par match 2.62
19.11%Pourcentage en avantage numérique16.90%
74.79%Pourcentage en désavantage numérique75.36%
Meneurs d'équipe
Buts
Jake Lucchini
27
Passes
Fabian Lysell
42
Points
Fabian Lysell
64
Milos KelemenPlus/Moins
Milos Kelemen
8
Victoires
Matt Villalta
13
Pourcentage d’arrêts
Oscar Dansk
0.893

Statistiques d’équipe
Buts pour
212
2.62 GFG
Tirs pour
2182
26.94 Avg
Pourcentage en avantage numérique
16.9%
48 GF
Début de zone offensive
37.2%
Buts contre
326
4.02 GAA
Tirs contre
2968
36.64 Avg
Pourcentage en désavantage numérique
75.4%%
85 GA
Début de la zone défensive
43.1%
Informations de l'équipe

Directeur généralDevon
DivisionDivision 1
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,788
Billets de saison0


Informations de la formation

Équipe Pro27
Équipe Mineure22
Limite contact 49 / 55
Espoirs14


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
1Cole Beaudoin (R)0X100.005552877075799568705965546846469550610193925,000$
2Jake Lucchini0XXX100.006454866866608461495857722554545050600301700,000$
3Oskar Steen0XX100.008345966865537764255055692556565950590271700,000$
4Milos Kelemen0XX100.006664666362798263505665606051517050590261700,000$
5Fabian Lysell (R)0XX100.0070647964627869645064616059474787505902252,999,999$
6Henrik Borgstrom13XXX100.007570947574646956705254665155555950590281700,000$
7Alan Quine26XX100.007671907573565657725651674860613550590321700,000$
8Nikita Grebenkin (R)0XX100.005451916875759560645356515958588050590223925,000$
9Jonah Gadjovich0X100.008899357478485862255456632564645950580262750,000$
10Gabriel Dumont0XX100.006868716569646660765660615852531750580341750,000$
11Rasmus Kupari0XXX100.007466847970626845635552594263647250570251700,000$
12Michal Teply (R)92X100.007871946271737654505351644847477750570241700,000$
13Taylor Fedun0X100.00737374657464715225454065376566450600371700,000$
14Ilya Solovyov0X100.008079786877737848253842634048487150590251700,000$
15Drew Helleson (R)0X100.007070856777707751254244643948487650590245775,000$
16Adam Wilsby0X100.007569876767767950253946634449497050590251700,000$
17Colton White0X100.007268876571636747253739643767675850580281700,000$
18Gavin Bayreuther0X100.006869726572545657255643643766663250580311700,000$
Rayé
1Martin Chromiak (R)0X100.006663896268687657505357635547477750570235875,000$
2John Quenneville0XX100.006968826471555658785656635453544950570291701,254$
3Patrick Khodorenko0X100.007573815974666755695648634646466350560262850,000$
4Jiri Felcman (R)0X100.005551866774586654665246504850509050530203925,000$
5Zach Nehring (R)0X100.005347776567618441493044454650509050480203925,000$
6Dylan MacKinnon (R)0X100.005651796372669540253736643850509050560203925,000$
MOYENNE D’ÉQUIPE100.00696581677165745548505162455454645058
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
1Matt Villalta0100.00564658656059566260593050506950570262750,000$
2Oscar Dansk0100.00484455815748505449493050503450530311700,000$
Rayé
1Jakub Skarek0100.00485164785548505448483049497050530252750,000$
MOYENNE D’ÉQUIPE100.0051475975575252575252305050585054
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Fabian LysellTucson Roadrunners (UTA)LW/RW812242640440108134225701649.78%21153218.925914462280000313235.35%9900000.8400000153
2Jake LucchiniTucson Roadrunners (UTA)C/LW/RW81273158-16200611191944816113.92%20152118.7898175121401131584241.54%60900000.7603000225
3Milos KelemenTucson Roadrunners (UTA)C/RW8126305683801491672048114912.75%15161219.914593616510171430237.80%138900000.6923000415
4Nils AmanUtah MammothC79203353-3114044219210751719.52%26152919.36712194623100021590141.26%151000000.6922000320
5Brett LeasonUtah MammothLW/RW5821295015180961492024913410.40%22121020.86538359600082037237.15%110900000.8337000454
6Henrik BorgstromTucson Roadrunners (UTA)C/LW/RW81112536-2020083118150411467.33%26128115.83178211310000400151.80%47100000.5600000111
7Radim SimekUtah MammothD75151833-347401935589254016.85%98148419.79641035198000140000%000100.4400000003
8Alan QuineTucson Roadrunners (UTA)C/LW8152833-406017214174451192.87%19130616.132810441880001680150.65%130500000.5100000002
9Taylor FedunTucson Roadrunners (UTA)D8152530-29660202616927477.25%134181122.37347322320220247110%000000.3300000200
10Oskar SteenTucson Roadrunners (UTA)C/RW75101929-32400145104164421256.10%23109314.5815610421012321030.84%10700000.5300000230
11Jonah GadjovichTucson Roadrunners (UTA)RW81171128-398802251331644811710.37%20117814.542133170113722033.73%8300000.4800000111
12Cole BeaudoinTucson Roadrunners (UTA)C81121527-27802078122431049.84%5149118.4214511390001353148.58%63400010.3602000100
13Ilya SolovyovTucson Roadrunners (UTA)D8171926-1112352194663224111.11%122172321.28347222390001222100%000000.3000000200
14Gavin BayreutherTucson Roadrunners (UTA)D8142226-164601015233142312.12%107139017.17000080112197100%000000.3700000021
15Nikita GrebenkinTucson Roadrunners (UTA)LW/RW81111526-4800612412537888.80%11157519.451231210310162821152.36%82500100.3313000020
16Colton WhiteTucson Roadrunners (UTA)D8131215-3832090457619283.95%102153018.90156302070001225000%000000.2000000000
17Adam WilsbyTucson Roadrunners (UTA)D7541014-135401223736122611.11%78119515.930225351011101010%000000.2300000001
18Drew HellesonTucson Roadrunners (UTA)D28257440147157913.33%272237.97022630000053000%000000.6300000011
19Gabriel DumontTucson Roadrunners (UTA)C/RW75246-6601120354165.71%21522.0300014000020057.14%2100000.7900000000
20Caden PriceUtah MammothD10066-600517154100%1424724.71022726000140000%000000.4900000000
21Rasmus KupariTucson Roadrunners (UTA)C/LW/RW71120204521250.00%1557.8700013000040046.15%1300000.7300000000
22Martin ChromiakTucson Roadrunners (UTA)RW7202-1001771328.57%1557.91202515000000040.00%5500000.7200000000
23Michal TeplyTucson Roadrunners (UTA)LW13011000101000%0100.83011030000100100.00%100001.8600000000
24Dylan MacKinnonTucson Roadrunners (UTA)D6101-4009220050.00%48213.760000000000000%000000.2400000000
25Patrick KhodorenkoTucson Roadrunners (UTA)C1000000120000%12222.6000002000050069.23%260000000000000
26John QuennevilleTucson Roadrunners (UTA)C/RW11000000001000%040.450000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne1492228401629-384703519271915237871517239.59%8992532216.9753881414592466459402372241543.76%825700210.50820000232527
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
1Matt VillaltaTucson Roadrunners (UTA)52133270.8913.8831394020318570230.55695223311
2Oscar DanskTucson Roadrunners (UTA)2861840.8934.0116932011310600110.66732835201
3Jake AllenUtah Mammoth10100.9154.0060004470000010000
Statistiques d’équipe totales ou en moyenne811951110.8923.924893603202964034128158512


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
Adam WilsbyTucson Roadrunners (UTA)D252000-07-08SWENo189 Lbs6 ft0NoNoAssign ManuallyNoNo12025-08-31FalseFalsePro & Farm700,000$0$0$No---------------------------Lien
Alan QuineTucson Roadrunners (UTA)C/LW321993-02-25ONTNo205 Lbs6 ft0NoNoAssign ManuallyNoNo12025-08-31FalseFalsePro & Farm700,000$0$0$No---------------------------Lien
Cole BeaudoinTucson Roadrunners (UTA)C192006-04-24CANYes209 Lbs6 ft2NoNoTrade2026-01-02NoNo32025-08-21FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien
Colton WhiteTucson Roadrunners (UTA)D281997-05-03ONTNo194 Lbs6 ft1NoNoAssign Manually2025-06-10NoNo12025-08-31FalseFalsePro & Farm700,000$0$0$No---------------------------Lien
Drew HellesonTucson Roadrunners (UTA)D242001-03-26USAYes211 Lbs6 ft3NoNoTrade2026-01-02NoNo52025-01-15FalseFalsePro & Farm775,000$0$0$No775,000$775,000$775,000$775,000$-----775,000$775,000$775,000$775,000$-----NoNoNoNo-----Lien
Dylan MacKinnonTucson Roadrunners (UTA)D202005-01-12CANYes196 Lbs6 ft2NoNoAssign ManuallyNoNo32025-08-21FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien
Fabian LysellTucson Roadrunners (UTA)LW/RW222003-01-19SWEYes177 Lbs5 ft10NoNoTrade2025-08-21NoNo52025-01-10FalseFalsePro & Farm2,999,999$0$0$No2,999,999$2,999,999$2,999,999$2,999,999$-----2,999,999$2,999,999$2,999,999$2,999,999$-----NoNoNoNo-----Lien
Gabriel DumontTucson Roadrunners (UTA)C/RW341990-10-06QUENo197 Lbs5 ft10NoNoAssign ManuallyNoNo12025-08-30FalseFalsePro & Farm750,000$0$0$No---------------------------Lien
Gavin BayreutherTucson Roadrunners (UTA)D311994-05-12USANo196 Lbs6 ft1NoNoAssign Manually2024-09-11NoNo12025-08-31FalseFalsePro & Farm700,000$0$0$No---------------------------Lien
Henrik BorgstromTucson Roadrunners (UTA)C/LW/RW281997-08-06FINNo201 Lbs6 ft3NoNoAssign ManuallyNoNo12025-08-31FalseFalsePro & Farm700,000$0$0$No---------------------------Lien
Ilya SolovyovTucson Roadrunners (UTA)D252000-07-20BELNo213 Lbs6 ft3NoNoAssign ManuallyNoNo12025-08-31FalseFalsePro & Farm700,000$0$0$No---------------------------Lien
Jake LucchiniTucson Roadrunners (UTA)C/LW/RW301995-09-05BCNo184 Lbs5 ft11NoNoAssign ManuallyNoNo12025-08-31FalseFalsePro & Farm700,000$0$0$No---------------------------Lien
Jakub SkarekTucson Roadrunners (UTA)G251999-11-10CZENo196 Lbs6 ft3NoNoAssign ManuallyNoNo22025-08-30FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien
Jiri FelcmanTucson Roadrunners (UTA)C202005-04-17CZEYes198 Lbs6 ft4NoNoAssign ManuallyNoNo32025-08-21FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien
John QuennevilleTucson Roadrunners (UTA)C/RW291996-04-16ABNo197 Lbs6 ft1NoNoAssign ManuallyNoNo12025-08-31FalseFalsePro & Farm701,254$0$0$No---------------------------Lien
Jonah GadjovichTucson Roadrunners (UTA)RW261998-10-12ONTNo204 Lbs6 ft2NoNoAssign ManuallyNoNo22025-08-30FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien / Lien NHL
Martin ChromiakTucson Roadrunners (UTA)RW232002-08-20SVKYes193 Lbs6 ft0NoNoAssign ManuallyNoNo52024-12-29FalseFalsePro & Farm875,000$0$0$No875,000$875,000$875,000$875,000$-----875,000$875,000$875,000$875,000$-----NoNoNoNo-----Lien
Matt VillaltaTucson Roadrunners (UTA)G261999-03-06ONTNo174 Lbs6 ft2NoNoAssign ManuallyNoNo22025-08-30FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien
Michal TeplyTucson Roadrunners (UTA)LW242001-05-27CZEYes192 Lbs6 ft3NoNoAssign ManuallyNoNo12025-08-31FalseFalsePro & Farm700,000$0$0$No---------------------------Lien
Milos KelemenTucson Roadrunners (UTA)C/RW261999-06-07SVKNo167 Lbs6 ft1NoNoAssign ManuallyNoNo12025-08-31FalseFalsePro & Farm700,000$0$0$No---------------------------Lien / Lien NHL
Nikita GrebenkinTucson Roadrunners (UTA)LW/RW222003-05-02RUSYes209 Lbs6 ft2NoNoAssign ManuallyNoNo32025-08-21FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien
Oscar DanskTucson Roadrunners (UTA)G311994-02-28SWENo206 Lbs6 ft3NoNoAssign ManuallyNoNo12025-08-30FalseFalsePro & Farm700,000$0$0$No---------------------------Lien
Oskar SteenTucson Roadrunners (UTA)C/RW271998-03-09SWENo190 Lbs5 ft9NoNoAssign ManuallyNoNo12025-08-31FalseFalsePro & Farm700,000$0$0$No---------------------------Lien / Lien NHL
Patrick KhodorenkoTucson Roadrunners (UTA)C261998-10-13USANo210 Lbs6 ft0NoNoTrade2026-01-19NoNo22024-12-29FalseFalsePro & Farm850,000$0$0$No850,000$--------850,000$--------No--------Lien
Rasmus KupariTucson Roadrunners (UTA)C/LW/RW252000-03-15FINNo194 Lbs6 ft2NoNoAssign Manually2025-01-27NoNo12025-08-31FalseFalsePro & Farm700,000$0$0$No---------------------------Lien / Lien NHL
Taylor FedunTucson Roadrunners (UTA)D371988-06-04ABNo200 Lbs6 ft1NoNoAssign ManuallyNoNo12025-08-31FalseFalsePro & Farm700,000$0$0$No---------------------------Lien
Zach NehringTucson Roadrunners (UTA)RW202005-03-07USAYes179 Lbs6 ft3NoNoAssign ManuallyNoNo32025-08-21FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2726.11196 Lbs6 ft11.96849,120$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jake LucchiniOskar Steen30122
2Fabian LysellCole BeaudoinMilos Kelemen30122
3Nikita GrebenkinHenrik BorgstromGabriel Dumont25122
4Alan QuineJonah Gadjovich15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Taylor Fedun30122
2Drew HellesonIlya Solovyov30122
3Adam WilsbyColton White25122
4Gavin Bayreuther15122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jake LucchiniOskar Steen60122
2Fabian LysellCole BeaudoinMilos Kelemen40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Taylor Fedun60122
2Drew HellesonIlya Solovyov40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Cole Beaudoin60122
2Jake LucchiniOskar Steen40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Taylor Fedun60122
2Drew HellesonIlya Solovyov40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
160122Taylor Fedun60122
2Cole Beaudoin40122Drew HellesonIlya Solovyov40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Cole Beaudoin60122
2Jake LucchiniOskar Steen40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Taylor Fedun60122
2Drew HellesonIlya Solovyov40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jake LucchiniOskar SteenTaylor Fedun
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jake LucchiniOskar SteenTaylor Fedun
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Nikita Grebenkin, Henrik Borgstrom, Alan QuineNikita Grebenkin, Henrik BorgstromAlan Quine
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Adam Wilsby, Colton White, Gavin BayreutherAdam WilsbyColton White, Gavin Bayreuther
Tirs de pénalité
, Cole Beaudoin, Jake Lucchini, Oskar Steen, Milos Kelemen
Gardien
#1 : Matt Villalta, #2 : Oscar Dansk
Lignes d’attaque personnalisées en prolongation
, Cole Beaudoin, Jake Lucchini, Oskar Steen, Milos Kelemen, Fabian Lysell, Fabian Lysell, Nikita Grebenkin, Henrik Borgstrom, Alan Quine, Gabriel Dumont
Lignes de défense personnalisées en prolongation
, Taylor Fedun, Drew Helleson, Ilya Solovyov, Adam Wilsby


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
1Abbotsford Canucks301001101315-21000010056-12010001089-130.5001323361069756110767247187084410033166714428.57%8275.00%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
2Bakersfield Condors30300000615-91010000014-320200000511-600.00061117006975611079724718708441232416771417.14%8362.50%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
3Belleville Senators21001000963110000004221000100054141.0009172600697561106872471870844682222529111.11%11281.82%11173249846.96%1304289345.07%556132541.96%1703112021496451055491
4Bridgeport Islanders210001005501000010023-11100000032130.750591400697561105372471870844661918337114.29%9188.89%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
5Calgary Wranglers30300000612-61010000023-12020000049-500.00061016006975611079724718708441283218641417.14%9188.89%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
6Charlotte Checkers2010010059-41000010034-11010000025-310.250581300697561107172471870844792818525120.00%9188.89%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
7Chicago Wolves61300200920-1151200200814-61010000016-540.33391524006975611016272471870844225503414018211.11%17382.35%11173249846.96%1304289345.07%556132541.96%1703112021496451055491
8Cleveland Monsters22000000945110000006241100000032141.0009152400697561106272471870844532114439333.33%7185.71%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
9Coachella Valley Firebirds20200000312-91010000016-51010000026-400.00035800697561104472471870844892420486233.33%10370.00%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
10Colorado Eagles2020000036-31010000012-11010000024-200.0003580069756110367247187084468232246000%11372.73%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
11Grand Rapids Griffins3010110079-2100010002112010010058-330.50071219006975611086724718708441314134731317.69%17382.35%11173249846.96%1304289345.07%556132541.96%1703112021496451055491
12Hartford Wolf Pack30200100811-32020000046-21000010045-110.16781422006975611083724718708447524286315213.33%140100.00%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
13Henderson Silver Knights2010010068-21000010034-11010000034-110.2506111700697561105172471870844702610426116.67%50100.00%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
14Hershey Bears20101000810-2100010005411010000036-320.5008152300697561105772471870844882224364250.00%12375.00%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
15Iowa Wild2020000058-31010000034-11010000024-200.00058130069756110647247187084482121650500.00%8187.50%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
16Laval Rocket20100001410-61010000005-51000000145-110.2504711006975611068724718708441073422628225.00%11372.73%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
17Lehigh Valley Phantoms11000000541000000000001100000054121.000591400697561103672471870844341510363133.33%5340.00%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
18Manitoba Moose4220000013130211000006602110000077040.500132639006975611012172471870844151404010314428.57%20290.00%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
19Milwaukee Admirals20200000510-51010000035-21010000025-300.000591400697561104372471870844851816604125.00%8275.00%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
20Ontario Reign40400000616-102020000039-62020000037-400.00061016206975611092724718708441103428871119.09%14471.43%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
21Providence Bruins40300100514-92010010049-52020000015-410.12551015006975611095724718708441173532881100.00%16756.25%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
22Rochester Americans21001000853110000004221000100043141.0008122000697561106572471870844791916489222.22%8275.00%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
23Rockford IceHogs20200000411-71010000026-41010000025-300.000461000697561103672471870844823335324125.00%11463.64%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
24San Diego Gulls30300000616-1020200000513-81010000013-200.00061218006975611058724718708441124626621000.00%13561.54%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
25San Jose Barracuda404000001019-92020000046-220200000613-700.00010192910697561109972471870844138473410513323.08%17664.71%11173249846.96%1304289345.07%556132541.96%1703112021496451055491
26Springfield Thunderbirds20101000810-2100010005411010000036-320.50081624006975611073724718708447620204212325.00%10550.00%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
27Syracuse Crunch22000000963110000004221100000054141.0009152400697561105872471870844712714429444.44%7185.71%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
28Texas Stars20100001710-31000000145-11010000035-210.2507132000697561106272471870844742616369111.11%8275.00%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
29Toronto Marlies2110000057-2110000005321010000004-420.500591400697561103972471870844762018497114.29%9188.89%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
30Utica Comets30300000514-91010000016-52020000048-400.0005914006975611074724718708441183336671000.00%18761.11%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
31Wilkes-Barre/Scranton Penguins302000101011-1100000104312020000068-220.333101828006975611092724718708449336306811218.18%15473.33%01173249846.96%1304289345.07%556132541.96%1703112021496451055491
Total81125105922212326-1144072103711104149-454153002211108177-69490.3022123785904069756110218272471870844296888470318732844816.90%3458575.36%41173249846.96%1304289345.07%556132541.96%1703112021496451055491
_Since Last GM Reset81125105922212326-1144072103711104149-454153002211108177-69490.3022123785904069756110218272471870844296888470318732844816.90%3458575.36%41173249846.96%1304289345.07%556132541.96%1703112021496451055491
_Vs Conference4192502410114157-4320411013105575-2021514011005982-23280.341114209323306975611010997247187084413644473669271422517.61%1834674.86%21173249846.96%1304289345.07%556132541.96%1703112021496451055491
_Vs Division22213001005979-201216001003038-81017000002941-1250.11459104163006975611061972471870844752220194486771316.88%972277.32%11173249846.96%1304289345.07%556132541.96%1703112021496451055491

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8149OTL121237859021822968884703187340
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8112515922212326
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
407213711104149
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
415302211108177
Derniers 10 matchs
WLOTWOTL SOWSOL
630100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2844816.90%3458575.36%4
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
7247187084469756110
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
1173249846.96%1304289345.07%556132541.96%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1703112021496451055491


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
2 - 2025-09-1216Manitoba Moose2Tucson Roadrunners3WSommaire du match
4 - 2025-09-1433Chicago Wolves3Tucson Roadrunners2LXSommaire du match
6 - 2025-09-1654Tucson Roadrunners3Abbotsford Canucks5LSommaire du match
7 - 2025-09-1762Tucson Roadrunners0Providence Bruins2LSommaire du match
9 - 2025-09-1977Tucson Roadrunners2San Jose Barracuda7LSommaire du match
10 - 2025-09-2089Chicago Wolves4Tucson Roadrunners1LSommaire du match
13 - 2025-09-23108Providence Bruins6Tucson Roadrunners2LSommaire du match
14 - 2025-09-24117Tucson Roadrunners4Manitoba Moose2WSommaire du match
17 - 2025-09-27139Tucson Roadrunners2Utica Comets3LSommaire du match
19 - 2025-09-29150Chicago Wolves2Tucson Roadrunners4WSommaire du match
22 - 2025-10-02167Ontario Reign5Tucson Roadrunners1LSommaire du match
24 - 2025-10-04186Tucson Roadrunners2Wilkes-Barre/Scranton Penguins3LSommaire du match
25 - 2025-10-05203Tucson Roadrunners1Ontario Reign3LSommaire du match
27 - 2025-10-07217San Jose Barracuda4Tucson Roadrunners3LSommaire du match
29 - 2025-10-09232Tucson Roadrunners3Bakersfield Condors4LSommaire du match
31 - 2025-10-11248Tucson Roadrunners3Calgary Wranglers6LSommaire du match
32 - 2025-10-12254Chicago Wolves3Tucson Roadrunners0LSommaire du match
35 - 2025-10-15276San Diego Gulls8Tucson Roadrunners2LSommaire du match
38 - 2025-10-18296Tucson Roadrunners4Hartford Wolf Pack5LXSommaire du match
39 - 2025-10-19308Rockford IceHogs6Tucson Roadrunners2LSommaire du match
42 - 2025-10-22330Calgary Wranglers3Tucson Roadrunners2LSommaire du match
44 - 2025-10-24346Tucson Roadrunners4Rochester Americans3WXSommaire du match
45 - 2025-10-25359Tucson Roadrunners3Cleveland Monsters2WSommaire du match
48 - 2025-10-28376Laval Rocket5Tucson Roadrunners0LSommaire du match
49 - 2025-10-29391Tucson Roadrunners2Utica Comets5LSommaire du match
50 - 2025-10-30405Hartford Wolf Pack3Tucson Roadrunners2LSommaire du match
52 - 2025-11-01425Tucson Roadrunners2Iowa Wild4LSommaire du match
54 - 2025-11-03439Abbotsford Canucks6Tucson Roadrunners5LXSommaire du match
56 - 2025-11-05457Utica Comets6Tucson Roadrunners1LSommaire du match
58 - 2025-11-07469Tucson Roadrunners2Coachella Valley Firebirds6LSommaire du match
60 - 2025-11-09486Tucson Roadrunners1Providence Bruins3LSommaire du match
61 - 2025-11-10502Tucson Roadrunners2Bakersfield Condors7LSommaire du match
62 - 2025-11-11512San Jose Barracuda2Tucson Roadrunners1LSommaire du match
64 - 2025-11-13533Tucson Roadrunners2Charlotte Checkers5LSommaire du match
66 - 2025-11-15542Manitoba Moose4Tucson Roadrunners3LSommaire du match
69 - 2025-11-18564Texas Stars5Tucson Roadrunners4LXXSommaire du match
70 - 2025-11-19581Tucson Roadrunners1Chicago Wolves6LSommaire du match
72 - 2025-11-21597Iowa Wild4Tucson Roadrunners3LSommaire du match
74 - 2025-11-23612Tucson Roadrunners4Laval Rocket5LXXSommaire du match
76 - 2025-11-25626Colorado Eagles2Tucson Roadrunners1LSommaire du match
79 - 2025-11-28649Syracuse Crunch2Tucson Roadrunners4WSommaire du match
80 - 2025-11-29664Tucson Roadrunners4San Jose Barracuda6LSommaire du match
82 - 2025-12-01676Tucson Roadrunners3Texas Stars5LSommaire du match
83 - 2025-12-02688Tucson Roadrunners2Rockford IceHogs5LSommaire du match
85 - 2025-12-04701Milwaukee Admirals5Tucson Roadrunners3LSommaire du match
87 - 2025-12-06720Tucson Roadrunners3Manitoba Moose5LSommaire du match
89 - 2025-12-08733Coachella Valley Firebirds6Tucson Roadrunners1LSommaire du match
91 - 2025-12-10754Grand Rapids Griffins1Tucson Roadrunners2WXSommaire du match
93 - 2025-12-12768Tucson Roadrunners3Henderson Silver Knights4LSommaire du match
95 - 2025-12-14780Tucson Roadrunners5Lehigh Valley Phantoms4WSommaire du match
97 - 2025-12-16793Bridgeport Islanders3Tucson Roadrunners2LXSommaire du match
99 - 2025-12-18808Tucson Roadrunners2Milwaukee Admirals5LSommaire du match
100 - 2025-12-19823San Diego Gulls5Tucson Roadrunners3LSommaire du match
103 - 2025-12-22843Tucson Roadrunners1San Diego Gulls3LSommaire du match
104 - 2025-12-23856Wilkes-Barre/Scranton Penguins3Tucson Roadrunners4WXXSommaire du match
107 - 2025-12-26881Tucson Roadrunners2Colorado Eagles4LSommaire du match
108 - 2025-12-27889Toronto Marlies3Tucson Roadrunners5WSommaire du match
110 - 2025-12-29912Tucson Roadrunners4Wilkes-Barre/Scranton Penguins5LSommaire du match
112 - 2025-12-31923Belleville Senators2Tucson Roadrunners4WSommaire du match
114 - 2026-01-02944Tucson Roadrunners3Hershey Bears6LSommaire du match
115 - 2026-01-03952Henderson Silver Knights4Tucson Roadrunners3LXSommaire du match
118 - 2026-01-06972Tucson Roadrunners1Calgary Wranglers3LSommaire du match
120 - 2026-01-08985Rochester Americans2Tucson Roadrunners4WSommaire du match
122 - 2026-01-101008Bakersfield Condors4Tucson Roadrunners1LSommaire du match
124 - 2026-01-121015Tucson Roadrunners0Toronto Marlies4LSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
126 - 2026-01-141037Tucson Roadrunners3Springfield Thunderbirds6LSommaire du match
128 - 2026-01-161049Providence Bruins3Tucson Roadrunners2LXSommaire du match
129 - 2026-01-171055Tucson Roadrunners3Grand Rapids Griffins4LXSommaire du match
131 - 2026-01-191075Tucson Roadrunners2Grand Rapids Griffins4LSommaire du match
132 - 2026-01-201086Chicago Wolves2Tucson Roadrunners1LXSommaire du match
135 - 2026-01-231107Tucson Roadrunners3Bridgeport Islanders2WSommaire du match
136 - 2026-01-241118Hartford Wolf Pack3Tucson Roadrunners2LSommaire du match
137 - 2026-01-251131Tucson Roadrunners2Ontario Reign4LSommaire du match
140 - 2026-01-281149Ontario Reign4Tucson Roadrunners2LSommaire du match
143 - 2026-01-311176Springfield Thunderbirds4Tucson Roadrunners5WXSommaire du match
144 - 2026-02-011183Tucson Roadrunners5Syracuse Crunch4WSommaire du match
145 - 2026-02-021198Tucson Roadrunners5Belleville Senators4WXSommaire du match
147 - 2026-02-041214Hershey Bears4Tucson Roadrunners5WXSommaire du match
151 - 2026-02-081241Cleveland Monsters2Tucson Roadrunners6WSommaire du match
152 - 2026-02-091248Tucson Roadrunners5Abbotsford Canucks4WXXSommaire du match
156 - 2026-02-131276Charlotte Checkers4Tucson Roadrunners3LXSommaire du match
161 - 2026-02-181303Lehigh Valley Phantoms-Tucson Roadrunners-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance74,82236,687
Assistance PCT93.53%91.72%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
1 2788 - 92.92% 40,406$1,616,227$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
23,818,236$ 22,926,252$ 22,926,252$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 23,818,236$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
40,406$ 3 141,520$ 424,560$




Tucson 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

Tucson 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

Tucson 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

Tucson 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

Tucson 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