Please rotate your device to landscape mode for a better experience.
Login

Marlies
GP: 41 | W: 19 | L: 18 | OTL: 4 | P: 42
GF: 131 | GA: 142 | PP%: 15.90% | PK%: 82.01%
GM : Joël Durocher | Morale : 90 | Team Overall : 54
Next Games #625 vs Twins

Game Center
Marlies
19-18-4, 42pts
3
2 Outlaws
23-14-3, 49pts
Team Stats
W1StreakW1
9-7-3Home Record14-3-3
10-11-1Home Record9-11-0
7-2-1Last 10 Games5-3-2
3.20Goals Per Game3.15
3.46Goals Against Per Game2.98
15.90%Power Play Percentage12.32%
82.01%Penalty Kill Percentage86.73%
Marlies
19-18-4, 42pts
2
1 Twins
17-18-5, 39pts
Team Stats
W1StreakL1
9-7-3Home Record11-7-2
10-11-1Home Record6-11-3
7-2-1Last 10 Games4-5-1
3.20Goals Per Game2.63
3.46Goals Against Per Game3.00
15.90%Power Play Percentage12.71%
82.01%Penalty Kill Percentage86.36%
Twins
17-18-5, 39pts
Day 50
Marlies
19-18-4, 42pts
Team Stats
L1StreakW1
11-7-2Home Record9-7-3
6-11-3Away Record10-11-1
4-5-1Last 10 Games7-2-1
2.63Goals Per Game3.20
3.00Goals Against Per Game3.20
12.71%Power Play Percentage15.90%
86.36%Penalty Kill Percentage82.01%
Goons
12-20-7, 31pts
Day 52
Marlies
19-18-4, 42pts
Team Stats
L4StreakW1
7-10-4Home Record9-7-3
5-10-3Away Record10-11-1
3-6-1Last 10 Games7-2-1
2.28Goals Per Game3.20
3.15Goals Against Per Game3.20
12.50%Power Play Percentage15.90%
87.88%Penalty Kill Percentage82.01%
Marlies
19-18-4, 42pts
Day 53
Supreme
26-12-1, 53pts
Team Stats
W1StreakW3
9-7-3Home Record10-9-1
10-11-1Away Record16-3-0
7-2-1Last 10 Games6-4-0
3.20Goals Per Game3.95
3.46Goals Against Per Game3.95
15.90%Power Play Percentage13.97%
82.01%Penalty Kill Percentage82.46%
Team Leaders
Marc StaalGoals
Marc Staal
7
Marc StaalAssists
Marc Staal
13
Marc StaalPoints
Marc Staal
20
Marc StaalPlus/Minus
Marc Staal
9

Team Stats
Goals For
131
3.20 GFG
Shots For
1464
35.71 Avg
Power Play Percentage
15.9%
31 GF
Offensive Zone Start
42.3%
Goals Against
142
3.46 GAA
Shots Against
1279
31.20 Avg
Penalty Kill Percentage
82.0%%
34 GA
Defensive Zone Start
39.1%
Team Info

General ManagerJoël Durocher
CoachManny Malhotra
DivisionDivision Ouest
ConferenceConference 1
Captain
Assistant #1
Assistant #2


Arena Info

Capacity3,000
Attendance2,671
Season Tickets300


Roster Info

Pro Team22
Farm Team24
Contract Limit46 / 50
Prospects69


Filter Tips
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
# Player Name C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPAgeContractSalary
1Valtteri Puustinen (R)X100.00574590805150405130445865658572090560261900,000$
2Andreas AthanasiouX100.0052459577635040473040546550907709055X03112,250,000$
3Jesse YlonenX100.00504589776750404530405055508471090530254900,000$
4Tim Washe (R)X100.005045957479504045304050575083700905302443,000,000$
5Alexander NylanderX100.00504590756950404530405055508774090530274900,000$
6Oskar LindblomX100.005045957763504045304050555087760905302912,800,000$
7Tyler BensonX100.00504595776050404530405055508572090520271850,000$
8Justin Richards (R)X100.00504595775950404530405055508573090520272775,000$
9Fredrik Karlstrom (R)X100.00504595766050404530405055508572090520273775,000$
10Chase Bradley (R)X100.00504595785250404530405055508370090520235900,000$
11Arnaud Durandeau (R)X100.005045957860504045304050555084740905202612,000,000$
12Hunter McKown (R)X100.00504595766050404530405055508069090520235900,000$
13Brandon Gignac (R)X100.00504595804850404530405055508675090520272775,000$
14Marc StaalX98.005045847672504045304050555097850905803811,200,000$
15Caleb JonesX100.005745927758524045304050565087750905702811,500,000$
16Mattias Norlinder (R)X100.00504595786050404530405055508370090560252900,000$
17Filip Roos (R)X100.00504595776350404530405055508574090560265800,000$
Scratches
1Lucas CondottaX100.00574595737550404730405461508774090550275800,000$
2German Rubtsov (R)X100.00504595795950404530405055508572090520272775,000$
TEAM AVERAGE99.8951459377625040463040515751867309054
Filter Tips
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
# Goalie Name CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SPAgeContractSalary
1Joel Blomqvist (R)100.0070507188707070707070708373090620234975,000$
2Hugo Alnefelt (R)100.0070404081656565656565658067090570243850,000$
3Michael Dipietro (R)100.0070404086656565656565658269090570265900,000$
Scratches
TEAM AVERAGE100.007043508567676767676767827009059
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Manny Malhotra65656565778286CAN4622,500,000$


Filter Tips
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
# Player Name Team NamePOSGP 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
1Marc StaalMarlies (TOR)D41713209340553349182714.29%4381819.97235281000000832139.39%3300000.4911000465
2Lucas CondottaMarlies (TOR)LW366814-2235397151143911.76%561217.01101130000221041.06%41400000.4603001535
3Jacob MoverareToronto Maple LeafsD2611112-78029275014352.00%2255221.2704424870000760029.55%4400000.4302000444
4Andreas AthanasiouMarlies (TOR)RW21369-88020483913227.69%435616.98033727000060048.78%28700000.5011000302
5Jesse YlonenMarlies (TOR)RW32268-71803628296256.90%1853116.6000000000010031.82%2200000.3001000154
Team Total or Average156194463-15915179207218651488.72%92287118.41310136021900001903142.88%80000000.4428001171820
Filter Tips
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
# Goalie Name Team NameGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3


Filter Tips
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
Player Name Team NamePOS Age Birthday Country Rookie Weight Height No Trade Available For Trade Acquired ByLast Trade DateForce Waivers Waiver Possible Contract Contract Signature DateForce UFA Emergency Recall Type Current Salary Salary RemainingSalary Cap Salary Cap Remaining Exclude from Salary Cap Salary Year 2Salary Year 3Salary Year 4Salary Year 5Salary Year 6Salary Year 7Salary Year 8Salary Year 9Salary Year 10Salary Cap Year 2Salary Cap Year 3Salary Cap Year 4Salary Cap Year 5Salary Cap Year 6Salary Cap Year 7Salary Cap Year 8Salary Cap Year 9Salary Cap Year 10No Trade Year 2No Trade Year 3No Trade Year 4No Trade Year 5No Trade Year 6No Trade Year 7No Trade Year 8No Trade Year 9No Trade Year 10Link
Alexander NylanderMarlies (TOR)LW271998-03-02SWENo192 Lbs6 ft1NoNoTrade2025-03-30NoNo42026-03-08FalseFalsePro & Farm900,000$491,667$0$0$No900,000$900,000$900,000$------900,000$900,000$900,000$------NoNoNo------
Andreas AthanasiouMarlies (TOR)RW311994-08-06CANNo190 Lbs6 ft2NoYesAssign ManuallyNoNo12026-03-08FalseFalsePro & Farm2,250,000$1,229,167$0$0$No---------------------------NHL Link
Arnaud DurandeauMarlies (TOR)LW261999-01-14CANYes185 Lbs6 ft0NoNoN/ANoNo12026-03-08FalseFalsePro & Farm2,000,000$1,092,593$0$0$No---------------------------
Brandon GignacMarlies (TOR)C271997-11-07CANYes170 Lbs5 ft11NoNoN/ANoNo22026-03-08FalseFalsePro & Farm775,000$423,380$0$0$No775,000$--------750,000$--------No--------NHL Link
Caleb JonesMarlies (TOR)D281997-06-06USANo194 Lbs6 ft1NoNoN/ANoNo12026-03-08FalseFalsePro & Farm1,500,000$819,444$0$0$No---------------------------NHL Link
Chase BradleyMarlies (TOR)LW232002-01-09USAYes180 Lbs5 ft11NoNoProspectNoNo52026-03-08FalseFalsePro & Farm900,000$491,667$0$0$No900,000$900,000$900,000$900,000$-----900,000$900,000$900,000$900,000$-----NoNoNoNo-----NHL Link
Filip RoosMarlies (TOR)D261999-01-05SWEYes190 Lbs6 ft4NoNoTrade2025-11-14NoNo52026-03-08FalseFalsePro & Farm800,000$437,037$0$0$No800,000$800,000$800,000$800,000$-----800,000$800,000$800,000$800,000$-----NoNoNoNo-----NHL Link
Fredrik KarlstromMarlies (TOR)C271998-01-12SWEYes200 Lbs6 ft3NoNoN/ANoNo32026-03-08FalseFalsePro & Farm775,000$423,380$0$0$No775,000$775,000$-------775,000$775,000$-------NoNo-------NHL Link
German RubtsovMarlies (TOR)C271998-06-27RUSYes178 Lbs6 ft2NoNoN/ANoNo22026-03-08FalseFalsePro & Farm775,000$423,380$0$0$No775,000$--------750,000$--------No--------
Hugo AlnefeltMarlies (TOR)G242001-06-04SWEYes177 Lbs6 ft2NoNoN/ANoNo32026-03-08FalseFalsePro & Farm850,000$464,352$0$0$No850,000$850,000$-------850,000$850,000$-------NoNo-------
Hunter McKownMarlies (TOR)C232002-08-18USAYes205 Lbs6 ft1NoNoTrade2025-03-20NoNo52026-03-08FalseFalsePro & Farm900,000$491,667$0$0$No900,000$900,000$900,000$900,000$-----900,000$900,000$900,000$900,000$-----NoNoNoNo-----NHL Link
Jesse YlonenMarlies (TOR)RW251999-10-03FINNo200 Lbs6 ft1NoNoTrade2025-03-20NoNo42026-03-08FalseFalsePro & Farm900,000$491,667$0$0$No900,000$900,000$900,000$------900,000$900,000$900,000$------NoNoNo------NHL Link
Joel BlomqvistMarlies (TOR)G232002-01-10FINYes200 Lbs6 ft3NoNoTrade2025-09-18NoNo42026-03-08FalseFalsePro & Farm975,000$532,639$0$0$No975,000$975,000$975,000$------975,000$975,000$975,000$------NoNoNo------NHL Link
Justin RichardsMarlies (TOR)C271998-03-17USAYes190 Lbs5 ft11NoNoN/ANoNo22026-03-08FalseFalsePro & Farm775,000$423,380$0$0$No775,000$--------750,000$--------No--------
Lucas CondottaMarlies (TOR)LW271997-11-06CANNo217 Lbs6 ft1NoNoN/ANoNo52026-03-08FalseFalsePro & Farm800,000$437,037$0$0$No800,000$800,000$800,000$800,000$-----800,000$800,000$800,000$800,000$-----NoNoNoNo-----NHL Link
Marc StaalMarlies (TOR)D381987-01-13CANNo208 Lbs6 ft4NoNoTrade2025-06-08NoNo12026-03-08FalseFalsePro & Farm1,200,000$655,556$0$0$No---------------------------NHL Link
Mattias NorlinderMarlies (TOR)D252000-04-12SWEYes185 Lbs6 ft0NoNoAssign ManuallyNoNo22026-03-08FalseFalsePro & Farm900,000$491,667$0$0$No900,000$--------900,000$--------No--------
Michael DipietroMarlies (TOR)G261999-06-09CANYes200 Lbs6 ft0NoNoTrade2025-03-20NoNo52026-03-08FalseFalsePro & Farm900,000$491,667$0$0$No900,000$900,000$900,000$900,000$-----900,000$900,000$900,000$900,000$-----NoNoNoNo-----NHL Link
Oskar LindblomMarlies (TOR)RW291996-08-15SWENo191 Lbs6 ft1NoNoN/ANoNo12026-03-08FalseFalsePro & Farm2,800,000$1,529,630$0$0$No---------------------------
Tim WasheMarlies (TOR)C242001-08-25USAYes215 Lbs6 ft3NoNoTrade2025-11-18NoNo42026-03-08FalseFalsePro & Farm3,000,000$1,638,889$0$0$No3,000,000$3,000,000$3,000,000$------3,000,000$3,000,000$3,000,000$------NoNoNo------NHL Link
Tyler BensonMarlies (TOR)RW271998-03-15CANNo190 Lbs6 ft0NoNoN/ANoNo12026-03-08FalseFalsePro & Farm850,000$464,352$0$0$No---------------------------
Valtteri PuustinenMarlies (TOR)RW261999-06-04FINYes183 Lbs5 ft9NoNoTrade2025-03-20NoNo12026-03-08FalseFalsePro & Farm900,000$491,667$0$0$No---------------------------NHL Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2226.64193 Lbs6 ft12.821,201,136$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
130014
230113
325113
415113
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
135131
2Marc Staal35131
330140
40050
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
155005
245005
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
155041
2Marc Staal45041
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
155041
245041
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
155140
2Marc Staal45140
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
15505055050
245050Marc Staal45050
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
155023
245023
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
155032
2Marc Staal45032
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Extra Forwards
Normal PowerPlayPenalty Kill
, , ,
Extra Defensemen
Normal PowerPlayPenalty Kill
, , ,
Penalty Shots
, , , ,
Goalie
#1 : , #2 :


Filter Tips
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
OverallHome Visitor
# VS Team 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 RI
1Bandits1010000024-2000000000001010000024-200.00024600454240632477459510303651618500.00%7185.71%0749149949.97%688138649.64%31065647.26%1001718995288484239
2Bayou11000000431000000000001100000043121.0004812004542406314774595103030613175240.00%40100.00%0749149949.97%688138649.64%31065647.26%1001718995288484239
3Chiwawa320000101156210000107341100000042261.000111829004542406116477459510307312375715213.33%9188.89%0749149949.97%688138649.64%31065647.26%1001718995288484239
4CoolFm1000010045-11000010045-10000000000010.500481200454240646477459510303082285360.00%000%0749149949.97%688138649.64%31065647.26%1001718995288484239
5Goons21001000624000000000002100100062441.000611170145424067247745951030421239478112.50%100100.00%0749149949.97%688138649.64%31065647.26%1001718995288484239
6Grizzlies21100000880110000006331010000025-320.500816240045424068947745951030802427498225.00%11281.82%0749149949.97%688138649.64%31065647.26%1001718995288484239
7Hunters11000000817110000008170000000000021.0008152300454240648477459510303388317342.86%20100.00%0749149949.97%688138649.64%31065647.26%1001718995288484239
8Husky11000000211000000000001100000021121.0002460045424063447745951030165831100.00%40100.00%0749149949.97%688138649.64%31065647.26%1001718995288484239
9Igloos2110000079-2110000005411010000025-320.5007142100454240677477459510306020216614214.29%7357.14%0749149949.97%688138649.64%31065647.26%1001718995288484239
10Outlaws412010001315-21100000041330201000914-540.50013213400454240613147745951030147485210826415.38%25484.00%0749149949.97%688138649.64%31065647.26%1001718995288484239
11Predateurs211000006511010000034-11100000031220.500612180045424067547745951030572016397228.57%8187.50%0749149949.97%688138649.64%31065647.26%1001718995288484239
12Raptors1010000037-41010000037-40000000000000.000369004542406274774595103040121418400.00%7357.14%0749149949.97%688138649.64%31065647.26%1001718995288484239
13Sags11000000532000000000001100000053221.0005914004542406324774595103018714193266.67%7185.71%0749149949.97%688138649.64%31065647.26%1001718995288484239
14Scorpions2010010048-4000000000002010010048-410.25048120045424066747745951030601616466116.67%8362.50%0749149949.97%688138649.64%31065647.26%1001718995288484239
15Smirnoff Ice1010000013-21010000013-20000000000000.0001230045424062547745951030197817100.00%4175.00%0749149949.97%688138649.64%31065647.26%1001718995288484239
16Snowbirds1010000034-1000000000001010000034-100.0003580045424064547745951030431214295120.00%7185.71%0749149949.97%688138649.64%31065647.26%1001718995288484239
17Spartans1010000026-4000000000001010000026-400.000246004542406304774595103042121224200.00%60100.00%0749149949.97%688138649.64%31065647.26%1001718995288484239
18Supreme11000000422110000004220000000000021.0004812004542406414774595103028121232500.00%50100.00%0749149949.97%688138649.64%31065647.26%1001718995288484239
19Thugs201000011013-31000000156-11010000057-210.2501018281045424068647745951030772214471400.00%20100.00%0749149949.97%688138649.64%31065647.26%1001718995288484239
20TigersCats2010100058-31010000015-41000100043120.500510150045424066147745951030782520491218.33%10370.00%0749149949.97%688138649.64%31065647.26%1001718995288484239
21Twins11000000211000000000001100000021121.00023500454240634477459510303541828400.00%8187.50%0749149949.97%688138649.64%31065647.26%1001718995288484239
22Vandals31100001880210000016511010000023-130.50081624004542406104477459510307218436210110.00%12283.33%0749149949.97%688138649.64%31065647.26%1001718995288484239
23Vipers20200000711-41010000058-31010000023-100.0007121900454240674477459510305715413417317.65%10370.00%0749149949.97%688138649.64%31065647.26%1001718995288484239
24Warriors11000000211110000002110000000000021.00024600454240636477459510301642144125.00%10100.00%0749149949.97%688138649.64%31065647.26%1001718995288484239
25Wolves2020000049-52020000049-50000000000000.0004812004542406514774595103090173046700.00%15473.33%0749149949.97%688138649.64%31065647.26%1001718995288484239
Total41151803212131142-111987001126867122711031006375-12420.51213124437511454240614644774595103012793514979561953115.90%1893482.01%0749149949.97%688138649.64%31065647.26%1001718995288484239
_Since Last GM Reset41151803212131142-111987001126867122711031006375-12420.51213124437511454240614644774595103012793514979561953115.90%1893482.01%0749149949.97%688138649.64%31065647.26%1001718995288484239
_Vs Conference146502100454237420010027225723020001820-2170.607458813301454240652047745951030410118151350651320.00%561082.14%0749149949.97%688138649.64%31065647.26%1001718995288484239
_Vs Division623010001620-4422000001012-22010100068-260.50016324800454240621147745951030193605712925416.00%26676.92%0749149949.97%688138649.64%31065647.26%1001718995288484239

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
4142W11312443751464127935149795611
All Games
GPWLOTWOTL SOWSOLGFGA
4115183212131142
Home Games
GPWLOTWOTL SOWSOLGFGA
198701126867
Visitor Games
GPWLOTWOTL SOWSOLGFGA
2271131006375
Last 10 Games
WLOTWOTL SOWSOL
621100
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
1953115.90%1893482.01%0
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
477459510304542406
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
749149949.97%688138649.64%31065647.26%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
1001718995288484239


Last Played Games
Filter Tips
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
DayGame Visitor Team Score Home Team Score ST OT SO RI Link
111Chiwawa2Marlies3WXXBox score
334Marlies5Outlaws7LBox score
444CoolFm5Marlies4LXBox score
561Predateurs4Marlies3LBox score
667Marlies3Snowbirds4LBox score
789Marlies3Predateurs1WBox score
999Marlies3Goons2WXBox score
10113Wolves5Marlies2LBox score
12133Vandals2Marlies4WBox score
13148Marlies1Outlaws5LBox score
14163Marlies5Sags3WBox score
15177Chiwawa1Marlies4WBox score
17192Marlies4Bayou3WBox score
18207Marlies3Scorpions6LBox score
19220Raptors7Marlies3LBox score
20238Supreme2Marlies4WBox score
22255Marlies2Vipers3LBox score
23268Warriors1Marlies2WBox score
24286Marlies5Thugs7LBox score
25293Marlies3Goons0WBox score
26310Thugs6Marlies5LXXBox score
27330Smirnoff Ice3Marlies1LBox score
28347TigersCats5Marlies1LBox score
30364Marlies2Igloos5LBox score
31371Marlies4TigersCats3WXBox score
32393Wolves4Marlies2LBox score
34411Marlies2Bandits4LBox score
35421Vandals3Marlies2LXXBox score
36443Hunters1Marlies8WBox score
37457Marlies2Vandals3LBox score
39469Marlies2Spartans6LBox score
40484Marlies1Scorpions2LXBox score
41490Igloos4Marlies5WBox score
42508Marlies2Husky1WBox score
43524Outlaws1Marlies4WBox score
44545Grizzlies3Marlies6WBox score
45557Marlies2Grizzlies5LBox score
46576Vipers8Marlies5LBox score
47588Marlies4Chiwawa2WBox score
48599Marlies3Outlaws2WXBox score
49611Marlies2Twins1WBox score
50625Twins-Marlies-
52646Goons-Marlies-
53661Marlies-Supreme-
54675Sags-Marlies-
55696Marlies-Snowbirds-
56705Marmots-Marlies-
57720Marlies-Raptors-
58736Scorpions-Marlies-
59746Marlies-CoolFm-
60764Husky-Marlies-
61778Marlies-Sags-
62791Marlies-Thugs-
64803Marlies-Twins-
65815Supreme-Marlies-
66836Xpress-Marlies-
68854Marlies-Smirnoff Ice-
69864Marlies-Warriors-
70876Bayou-Marlies-
71896Bandits-Marlies-
73918Marlies-Wolves-
74925Marlies-Farmers-
75935Snowbirds-Marlies-
76951Marlies-Hunters-
77960Barracudas-Marlies-
79990Chiwawa-Marlies-
801002Marlies-Barracudas-
811013Marlies-Xpress-
821023CoolFm-Marlies-
841052Raptors-Marlies-
861066Marlies-Barracudas-
871082Outlaws-Marlies-
901108Rockets-Marlies-
911128Marlies-Rockets-
921139Vipers-Marlies-
951166Farmers-Marlies-
971186Spartans-Marlies-
981193Marlies-Predateurs-
1011219Farmers-Marlies-
1021230Marlies-Bayou-
1061247Spartans-Marlies-
1071263Marlies-Marmots-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price4525
Attendance37,58013,173
Attendance PCT98.89%69.33%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
22 2671 - 89.04% 127,606$2,424,510$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Salaries CapCoaches Salaries
2,331,616$ 2,642,500$ 2,642,500$ 2,500,000$0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 1,197,335$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
2,807,327$ 59 47,616$ 2,809,344$




Marlies Players Stat Leaders (Regular Season)

# Player Name 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

Marlies Goalies Stat Leaders (Regular Season)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Marlies Career Team Stats

OverallHomeVisitor
Year 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

Marlies Players Stat Leaders (Play-Off)

# Player Name 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

Marlies Goalies Stat Leaders (Play-Off)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA