Harvard
GP: 82 | W: 29 | L: 48 | T: 3 | P: 63
GF: 264 | GA: 301 | PP%: 19.29% | PK%: 76.72%
GM : Marcel | Morale : 31 | Team Overall : 64
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

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
1Ron SutterX99.008270576871797972687568746655663338680312554,500$
2Jim SandlakX100.007868506381777769626864776161675534670282400,000$
3Brent FedykX99.006146787072747473647374706848446140670272575,000$
4Mikko MakelaX99.005741826575676767616971696759684653650292250,000$
5Josef BeranekX100.005339817272707275687573617138407452650252470,000$
6Ronnie SternX100.008376386574747662636563796247416052640273429,000$
7Craig JohnsonX100.005948677272676867657368666432328942630232225,000$
8Jozef StumpelX100.005948686778687070657367666431339721630222500,000$
9Niklas AnderssonX100.004937827569656872647267606232328921630233386,000$
10Reid SimpsonX100.006960546777687166656658795538387550630251480,000$
11Stu GrimsonX100.009890305981747660586345794352524720620291395,000$
12Pat PeakeX100.005544797170616466656861676041419620610213220,000$
13Jeff NortonX100.006551676575697064627352765041354829630292225,000$
14Janne Laukkanen (R)X100.005745787172666768627258725335288243620241280,000$
15Ryan McGill (R)X100.008265556674646455546442784035357636620251387,000$
16Todd ReirdenX100.006347726480686864606852745019289033610233359,000$
17Cory Cross (R)X100.006865446281676755525845764336419020610233380,000$
18Jan Vopat (R)X100.005644796274596057586541733931339819580213300,000$
Scratches
1Matthew Barnaby (R)X100.008276456674656654536054755228339820590212350,000$
TEAM AVERAGE99.84675663677569706562685972564041743463
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 SP
1Vincent Riendeau100.00717883808071758477777352525411720
2Wendell Young100.00658674727068728073697173763321710
Scratches
1Milan Hnilicka100.00677475737168758175696727319720660
TEAM AVERAGE100.0068797775746974827572705153611770
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Michel Therrien71707072738388CAN31295,000$


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
1Ron SutterHarvard (BOS)C75244165-23148202842132124614611.32%18176623.551223355531402263094151.90%234100000.7400112645
2J. J. DaigneaultBruinsD73134659-3434051103118316911.02%97175724.08112132773211232303010.00%000000.6700000221
3Jason AllisonBruinsC77243357-9220681772036214911.82%17142118.45710174721910152102156.34%126200000.8000000161
4Brent FedykHarvard (BOS)RW76223153-2314047842004713411.00%7144018.95817256833300031365148.70%15400010.7400000313
5Janne LaukkanenHarvard (BOS)D7913385113205997115357511.30%78163220.6691221833080000259110.00%000000.6200000212
6Dimitri YushkevichBruinsD70133750-211395174112114327111.40%94157022.4391120732571123210200.00%000000.6400010143
7Tim TaylorBruinsC47132841111002914314746868.84%14105422.43311144718831472202153.29%80500000.7800000212
8Mikko MakelaHarvard (BOS)LW81172441-1860970139349812.23%7120614.8981018292501121362049.02%10200000.6800000023
9Reid SimpsonHarvard (BOS)LW791622381056107867118437913.56%497312.330221159000040042.00%5000000.7800110103
10Ronnie SternHarvard (BOS)RW82122335-11122019478109317111.01%9101612.4005571280110321049.52%10500000.6900004132
11Josef BeranekHarvard (BOS)C82161733-10601079113267714.16%184910.371129620000402052.91%66900000.7800000111
12Jeff NortonHarvard (BOS)D7642731-1780133676425616.25%67155420.4531013412970110199100.00%000000.4000000001
13Jim SandlakHarvard (BOS)RW65161430-166016961106368215.09%8104416.07257382520110916145.90%12200000.5700000231
14Craig JohnsonHarvard (BOS)LW82101424-5100186811119549.01%47909.640225561122941048.54%10300000.6100000000
15Ryan McGillHarvard (BOS)D6351520010801793733122715.15%60103616.461231284000089010.00%000000.3900000111
16Todd ReirdenHarvard (BOS)D5641115920038382171019.05%4489415.98000423000091000.00%000000.3400000001
17Niklas AnderssonHarvard (BOS)LW5121214-7004385017394.00%461912.151349122000100045.00%10000000.4500000000
18Cory CrossHarvard (BOS)D31145-55007514101610.00%2546915.15000117000029000.00%000000.2100000000
19Jan VopatHarvard (BOS)D14314-321517551360.00%721215.1600015000032000.00%000000.3800000000
20Jozef StumpelHarvard (BOS)C53033200234213180.00%43005.67000180002480046.86%27100000.2000000000
21Matthew BarnabyHarvard (BOS)RW31011-32604816132130.00%32989.6300002000000043.75%6400000.0700000000
22Pat PeakeHarvard (BOS)C131010001350420.00%0493.7700000000030043.10%5800000.4100000000
23Stu GrimsonHarvard (BOS)LW12000-140840100.00%1484.0800008000080044.00%2500000.0000000000
Team Total or Average1368229442671-13296260169516082027557137211.30%5732200816.097514522061833248111932245429852.14%623100010.6100236232930
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
1Vincent RiendeauHarvard (BOS)68234110.8583.9734902223116310100.0000685320
2Wendell YoungHarvard (BOS)296810.8882.98120700605350200.00001448200
3Milan HnilickaHarvard (BOS)60110.9022.6222900101020000.0000029000
Team Total or Average103295030.8673.6749282230122680300.00008282520


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 Rookie Weight Height No Trade Available For Trade Force Waivers Contract Type Current Salary Salary 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 10Link
Brent FedykHarvard (BOS)RW271994-02-09 9:08:37 PMNo186 Lbs6 ft1NoNoNo2Pro & Farm575,000$57,500$423$No575,000$
Cory CrossHarvard (BOS)D231998-02-09 9:08:37 PMYes219 Lbs6 ft5NoNoNo3Pro & Farm380,000$38,000$279$No380,000$380,000$
Craig JohnsonHarvard (BOS)LW231998-02-09 9:08:37 PMNo197 Lbs6 ft2NoNoNo2Pro & Farm225,000$22,500$165$No225,000$
Jan VopatHarvard (BOS)D212000-02-09 9:08:37 PMYes207 Lbs6 ft0NoNoNo3Pro & Farm300,000$30,000$221$No300,000$300,000$
Janne LaukkanenHarvard (BOS)D241997-02-09 9:08:37 PMYes180 Lbs6 ft0NoNoNo1Pro & Farm280,000$28,000$206$No
Jeff NortonHarvard (BOS)D291992-02-09 9:08:37 PMNo195 Lbs6 ft2NoNoNo2Pro & Farm225,000$22,500$165$No225,000$
Jim SandlakHarvard (BOS)RW281993-02-09 9:08:37 PMNo219 Lbs6 ft4NoNoNo2Pro & Farm400,000$40,000$294$No400,000$
Josef BeranekHarvard (BOS)C251996-02-09 9:08:37 PMNo195 Lbs6 ft2NoNoNo2Pro & Farm470,000$47,000$346$No470,000$
Jozef StumpelHarvard (BOS)C221999-02-09 9:08:37 PMNo216 Lbs6 ft3NoNoNo2Pro & Farm500,000$50,000$368$No500,000$
Matthew BarnabyHarvard (BOS)RW212000-02-09 9:08:37 PMYes195 Lbs6 ft1NoNoNo2Pro & Farm350,000$35,000$257$No350,000$
Mikko MakelaHarvard (BOS)LW291992-02-09 9:08:37 PMNo200 Lbs6 ft2NoNoNo2Pro & Farm250,000$25,000$184$No250,000$
Milan HnilickaHarvard (BOS)G221999-02-09 9:08:37 PMNo180 Lbs6 ft0NoNoNo2Pro & Farm270,000$27,000$199$No270,000$
Niklas AnderssonHarvard (BOS)LW231998-02-09 9:08:37 PMNo175 Lbs5 ft9NoNoNo3Pro & Farm386,000$38,600$284$No386,000$386,000$
Pat PeakeHarvard (BOS)C212000-02-09 9:08:37 PMNo190 Lbs6 ft1NoNoNo3Pro & Farm220,000$22,000$162$No220,000$220,000$
Reid SimpsonHarvard (BOS)LW251996-02-09 9:08:37 PMNo210 Lbs6 ft1NoNoNo1Pro & Farm480,000$48,000$353$No
Ron SutterHarvard (BOS)C311990-02-09 9:08:37 PMNo180 Lbs6 ft0NoNoNo2Pro & Farm554,500$55,450$408$No554,500$
Ronnie SternHarvard (BOS)RW271994-02-09 9:08:37 PMNo195 Lbs6 ft0NoNoNo3Pro & Farm429,000$42,900$315$No429,000$429,000$
Ryan McGillHarvard (BOS)D251996-02-09 9:08:37 PMYes197 Lbs6 ft2NoNoNo1Pro & Farm387,000$38,700$285$No
Stu GrimsonHarvard (BOS)LW291992-02-09 9:08:37 PMNo230 Lbs6 ft5NoNoNo1Pro & Farm395,000$39,500$290$No
Todd ReirdenHarvard (BOS)D231998-02-09 9:08:37 PMNo220 Lbs6 ft5NoNoNo3Pro & Farm359,000$35,900$264$No359,000$359,000$
Vincent RiendeauHarvard (BOS)G281993-02-09 9:08:37 PMNo181 Lbs5 ft10NoNoNo3Pro & Farm985,000$98,500$724$No985,000$985,000$
Wendell YoungHarvard (BOS)G311990-02-09 9:08:37 PMNo182 Lbs5 ft9NoNoNo2Pro & Farm750,000$75,000$551$No750,000$
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2225.32198 Lbs6 ft12.14416,841$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Mikko MakelaRon SutterBrent Fedyk35122
2Reid SimpsonJosef BeranekJim Sandlak30122
3Craig JohnsonJozef StumpelRonnie Stern20122
4Niklas AnderssonPat PeakeRon Sutter15122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Jeff NortonJanne Laukkanen35122
2Ryan McGillCory Cross30122
3Todd ReirdenJan Vopat20122
4Jeff NortonJanne Laukkanen15122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Mikko MakelaRon SutterBrent Fedyk60122
2Reid SimpsonJosef BeranekJim Sandlak40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Jeff NortonJanne Laukkanen60122
2Ryan McGillCory Cross40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Ron SutterBrent Fedyk60122
2Jim SandlakMikko Makela40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Jeff NortonJanne Laukkanen60122
2Ryan McGillCory Cross40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Ron Sutter60122Jeff NortonJanne Laukkanen60122
2Brent Fedyk40122Ryan McGillCory Cross40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Ron SutterBrent Fedyk60122
2Jim SandlakMikko Makela40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Jeff NortonJanne Laukkanen60122
2Ryan McGillCory Cross40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Mikko MakelaRon SutterBrent FedykJeff NortonJanne Laukkanen
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Mikko MakelaRon SutterBrent FedykJeff NortonJanne Laukkanen
Extra Forwards
Normal PowerPlayPenalty Kill
Stu Grimson, Ronnie Stern, Craig JohnsonStu Grimson, Ronnie SternCraig Johnson
Extra Defensemen
Normal PowerPlayPenalty Kill
Todd Reirden, Jan Vopat, Ryan McGillTodd ReirdenJan Vopat, Ryan McGill
Penalty Shots
Ron Sutter, Brent Fedyk, Jim Sandlak, Mikko Makela, Josef Beranek
Goalie
#1 : Vincent Riendeau, #2 : Wendell Young


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
OverallHomeVisitor
# 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
1Ailes Rouges624000001422-820200000411-7422000001011-140.33314264000105768121747497277909172338310837616.22%32778.13%11517284553.32%1432276951.72%749139953.54%1954130619166421070530
2As624000001618-230300000715-83210000093640.33316284401105768121527497277909179378313937718.92%34682.35%01517284553.32%1432276951.72%749139953.54%1954130619166421070530
3Banshees624000001925-631200000610-4312000001315-240.3331936550010576812146749727790918242841282129.52%31970.97%01517284553.32%1432276951.72%749139953.54%1954130619166421070530
4Canadiens86200000332310422000001315-24400000020812120.7503358910010576812263749727790919357109187711216.90%48981.25%11517284553.32%1432276951.72%749139953.54%1954130619166421070530
5Chiefs9350100028253513010001716142200000119280.444285280011057681225774972779092337110316340922.50%451077.78%21517284553.32%1432276951.72%749139953.54%1954130619166421070530
6Citadelles615000002128-720200000611-5413000001517-220.16721375800105768121607497277909186576610835411.43%31680.65%11517284553.32%1432276951.72%749139953.54%1954130619166421070530
7Croque-Morts522100001819-132010000141042020000049-550.50018325000105768121277497277909137514311122418.18%18572.22%01517284553.32%1432276951.72%749139953.54%1954130619166421070530
8Isotopes513001001419-530200100913-42110000056-130.30014264000105768121387497277909121425010023417.39%23482.61%01517284553.32%1432276951.72%749139953.54%1954130619166421070530
9Pacifiques de la route514000001621-5312000001210220200000411-720.20016294500105768121257497277909178446710215533.33%301066.67%11517284553.32%1432276951.72%749139953.54%1954130619166421070530
10Riverman623010002423121100000990412010001514160.500244569001057681219374972779091414359148341235.29%19573.68%01517284553.32%1432276951.72%749139953.54%1954130619166421070530
11Snipers732101002526-14111010015141321000001012-280.57125467100105768121727497277909196548112623730.43%35780.00%11517284553.32%1432276951.72%749139953.54%1954130619166421070530
12Spoonman's817000001930-11413000001217-540400000713-620.125193453001057681220274972779092295411821465913.85%561475.00%11517284553.32%1432276951.72%749139953.54%1954130619166421070530
13Wolves513100001722-531200000910-120110000812-430.3001731480010576812166749727790912135409628621.43%19668.42%01517284553.32%1432276951.72%749139953.54%1954130619166421070530
Total82274832200264301-3741112521200133161-2841162311000131140-9630.384264480744021057681222757497277909226862098617304518719.29%4219876.72%81517284553.32%1432276951.72%749139953.54%1954130619166421070530
_Since Last GM Reset82304802200264301-3741112521200133161-28411923-21000131140-9660.402264480744021057681222757497277909226862098617304518719.29%4219876.72%81517284553.32%1432276951.72%749139953.54%1954130619166421070530
_Vs Conference42142601100134150-1621514011006382-19219120000071683310.36913424337701105768121166749727790911443235309002554015.69%2345277.78%51517284553.32%1432276951.72%749139953.54%1954130619166421070530
_Vs Division25101401000807821348010004248-612660000038308220.44080144224011057681272274972779096551823305641763017.05%1493377.85%41517284553.32%1432276951.72%749139953.54%1954130619166421070530

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
8263L326448074422752268620986173002
All Games
GPWLOTWOTL TGFGA
822748223264301
Home Games
GPWLOTWOTL TGFGA
411125122133161
Visitor Games
GPWLOTWOTL TGFGA
411623101131140
Last 10 Games
WLOTWOTL T
37000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
4518719.29%4219876.72%8
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
749727790910576812
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
1517284553.32%1432276951.72%749139953.54%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
1954130619166421070530


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
1 - 2020-09-216Snipers5Harvard5TXBoxScore
2 - 2020-09-229Harvard7Riverman3WBoxScore
4 - 2020-09-2417Harvard3Citadelles6LBoxScore
5 - 2020-09-2524Harvard0Spoonman's1LBoxScore
6 - 2020-09-2628Chiefs2Harvard3WXBoxScore
7 - 2020-09-2734Harvard2Chiefs0WBoxScore
9 - 2020-09-2940Spoonman's4Harvard3LBoxScore
10 - 2020-09-3051Harvard3Ailes Rouges1WBoxScore
11 - 2020-10-0153Canadiens3Harvard1LBoxScore
13 - 2020-10-0361Harvard9Canadiens2WBoxScore
15 - 2020-10-0570Chiefs5Harvard4LBoxScore
17 - 2020-10-0778Harvard2Snipers7LBoxScore
19 - 2020-10-0983As5Harvard4LBoxScore
21 - 2020-10-1192Harvard3Ailes Rouges4LBoxScore
23 - 2020-10-1397Pacifiques de la route4Harvard2LBoxScore
25 - 2020-10-15104Harvard6Canadiens3WBoxScore
27 - 2020-10-17111Wolves4Harvard1LBoxScore
29 - 2020-10-19119Harvard3Canadiens2WBoxScore
31 - 2020-10-21125Harvard1Ailes Rouges5LBoxScore
33 - 2020-10-23131Wolves4Harvard3LBoxScore
35 - 2020-10-25140Ailes Rouges5Harvard1LBoxScore
37 - 2020-10-27147Harvard5Banshees6LBoxScore
39 - 2020-10-29152Harvard2Pacifiques de la route5LBoxScore
41 - 2020-10-31159Canadiens3Harvard5WBoxScore
42 - 2020-11-01168Pacifiques de la route2Harvard8WBoxScore
44 - 2020-11-03176Wolves2Harvard5WBoxScore
46 - 2020-11-05182Harvard3Snipers2WBoxScore
47 - 2020-11-06189Chiefs6Harvard3LBoxScore
49 - 2020-11-08198Harvard1Chiefs2LBoxScore
50 - 2020-11-09203Harvard6Wolves6TXBoxScore
52 - 2020-11-11209Chiefs1Harvard6WBoxScore
53 - 2020-11-12217Snipers1Harvard5WBoxScore
55 - 2020-11-14226Harvard2Wolves6LBoxScore
57 - 2020-11-16233Harvard1As2LBoxScore
58 - 2020-11-17237Croque-Morts3Harvard5WBoxScore
59 - 2020-11-18243Harvard2Isotopes4LBoxScore
61 - 2020-11-20250Citadelles6Harvard4LBoxScore
63 - 2020-11-22261Harvard2Chiefs3LBoxScore
65 - 2020-11-24266Croque-Morts3Harvard5WBoxScore
66 - 2020-11-25273Harvard2Croque-Morts4LBoxScore
67 - 2020-11-26280Riverman7Harvard3LBoxScore
68 - 2020-11-27289Croque-Morts4Harvard4TXBoxScore
71 - 2020-11-30297Harvard8Citadelles4WBoxScore
72 - 2020-12-01303As3Harvard1LBoxScore
73 - 2020-12-02306Harvard4As0WBoxScore
74 - 2020-12-03311Harvard3Spoonman's4LBoxScore
75 - 2020-12-04319Harvard2Croque-Morts5LBoxScore
76 - 2020-12-05325Isotopes5Harvard3LBoxScore
78 - 2020-12-07334Banshees5Harvard2LBoxScore
79 - 2020-12-08344Harvard5Snipers3WBoxScore
80 - 2020-12-09345Harvard2Riverman5LBoxScore
82 - 2020-12-11352Isotopes5Harvard4LBoxScore
84 - 2020-12-13362Canadiens3Harvard4WBoxScore
86 - 2020-12-15367Harvard2Citadelles3LBoxScore
88 - 2020-12-17375Isotopes3Harvard2LXBoxScore
90 - 2020-12-19380Harvard4Banshees3WBoxScore
92 - 2020-12-21391Riverman2Harvard6WBoxScore
94 - 2020-12-23395Harvard1Spoonman's2LBoxScore
96 - 2020-12-25404As7Harvard2LBoxScore
98 - 2020-12-27409Harvard2Riverman3LBoxScore
100 - 2020-12-29416Harvard2Pacifiques de la route6LBoxScore
101 - 2020-12-30421Snipers4Harvard3LXBoxScore
103 - 2021-01-01434Chiefs2Harvard1LBoxScore
104 - 2021-01-02439Harvard2Canadiens1WBoxScore
106 - 2021-01-04446Spoonman's3Harvard4WBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
109 - 2021-01-07454Harvard6Chiefs4WBoxScore
110 - 2021-01-08461Spoonman's4Harvard3LBoxScore
111 - 2021-01-09464Harvard3Spoonman's6LBoxScore
113 - 2021-01-11471Harvard4Riverman3WXBoxScore
114 - 2021-01-12477Ailes Rouges6Harvard3LBoxScore
115 - 2021-01-13484Harvard4Banshees6LBoxScore
116 - 2021-01-14487Harvard3Ailes Rouges1WBoxScore
117 - 2021-01-15492Pacifiques de la route4Harvard2LBoxScore
119 - 2021-01-17504Spoonman's6Harvard2LBoxScore
121 - 2021-01-19516Snipers4Harvard2LBoxScore
122 - 2021-01-20521Harvard3Isotopes2WBoxScore
123 - 2021-01-21528Harvard4As1WBoxScore
124 - 2021-01-22532Citadelles5Harvard2LBoxScore
127 - 2021-01-25542Banshees1Harvard2WBoxScore
128 - 2021-01-26549Harvard2Citadelles4LBoxScore
130 - 2021-01-28558Banshees4Harvard2LBoxScore
135 - 2021-02-02573Canadiens6Harvard3LBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price3515
Attendance00
Attendance PCT0.00%0.00%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
0 0 - 0.00% 0$0$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
1,161,610$ 917,050$ 917,050$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
917,050$ 1,161,610$ 22 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 1 7,442$ 7,442$




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