implemented linear regression with correlation and error metrics

hypotheses_modeling/21DaySlidingWorkAverage.csv

@@ -0,0 +1,336 @@
+"","TimeSinceAugFirst","slidingWorkAverage"
+"1",20,5563.95
+"2",21,5895.66666666667
+"3",22,6307.42857142857
+"4",23,6331.71428571429
+"5",24,6458.52380952381
+"6",25,6752.33333333333
+"7",26,6767.33333333333
+"8",27,6766.61904761905
+"9",28,6738.42857142857
+"10",29,6798.66666666667
+"11",30,6811.38095238095
+"12",31,6813.7619047619
+"13",32,6881.85714285714
+"14",33,6840.42857142857
+"15",34,6834.71428571429
+"16",35,6788.47619047619
+"17",36,6711.09523809524
+"18",37,6720.61904761905
+"19",38,6781.33333333333
+"20",39,6495.04761904762
+"21",40,6617.90476190476
+"22",41,6578.85714285714
+"23",42,6122.66666666667
+"24",43,5613.04761904762
+"25",44,5671
+"26",45,5383.2380952381
+"27",46,4878.52380952381
+"28",47,4872.90476190476
+"29",48,4874.33333333333
+"30",49,4910.85714285714
+"31",50,4796.80952380952
+"32",51,4867.42857142857
+"33",52,5067.90476190476
+"34",53,5234.04761904762
+"35",54,5216.19047619048
+"36",55,5235.47619047619
+"37",56,5313.09523809524
+"38",57,5416.90476190476
+"39",58,5454.90476190476
+"40",59,5578.47619047619
+"41",60,5850.80952380952
+"42",61,5744.38095238095
+"43",62,5768.66666666667
+"44",63,6210.71428571429
+"45",64,6592.95238095238
+"46",65,6613.90476190476
+"47",66,6986.7619047619
+"48",67,7557.09523809524
+"49",68,7567.71428571429
+"50",69,7583.42857142857
+"51",70,7640.33333333333
+"52",71,7712.38095238095
+"53",72,7741.19047619048
+"54",73,7612.85714285714
+"55",74,7466
+"56",75,7487.42857142857
+"57",76,7480.28571428571
+"58",77,7064.61904761905
+"59",78,6618.42857142857
+"60",79,6647.38095238095
+"61",80,6575.95238095238
+"62",81,5935.85714285714
+"63",82,6326.33333333333
+"64",83,7005.38095238095
+"65",84,6509.52380952381
+"66",85,6314.66666666667
+"67",86,6331
+"68",87,5901.95238095238
+"69",88,5370.85714285714
+"70",89,5633.80952380952
+"71",90,5935.52380952381
+"72",91,5317.66666666667
+"73",92,4865.38095238095
+"74",93,4682.7619047619
+"75",94,4640.61904761905
+"76",95,4585.61904761905
+"77",96,4604.66666666667
+"78",97,4592.52380952381
+"79",98,5018.95238095238
+"80",99,5509.19047619048
+"81",100,5545.38095238095
+"82",101,5570.52380952381
+"83",102,6642.42857142857
+"84",103,6281.95238095238
+"85",104,5579.19047619048
+"86",105,6177.7619047619
+"87",106,6478.2380952381
+"88",107,6441.33333333333
+"89",108,7018.95238095238
+"90",109,7771.09523809524
+"91",110,7487.42857142857
+"92",111,7168.57142857143
+"93",112,7570.95238095238
+"94",113,7856.38095238095
+"95",114,7973.7619047619
+"96",115,7617.33333333333
+"97",116,7176.85714285714
+"98",117,7260.66666666667
+"99",118,7479.2380952381
+"100",119,7162.33333333333
+"101",120,6722.57142857143
+"102",121,6734.71428571429
+"103",122,6630
+"104",123,6050.57142857143
+"105",124,6004.14285714286
+"106",125,6003.57142857143
+"107",126,5477.38095238095
+"108",127,4982.38095238095
+"109",128,4995.71428571429
+"110",129,4822.14285714286
+"111",130,4590
+"112",131,4634.28571428571
+"113",132,4634.28571428571
+"114",133,4787.61904761905
+"115",134,4950.19047619048
+"116",135,5018.52380952381
+"117",136,5628.90476190476
+"118",137,6380.04761904762
+"119",138,6255.7619047619
+"120",139,6037.19047619048
+"121",140,6435.90476190476
+"122",141,6408.04761904762
+"123",142,6788.90476190476
+"124",143,6869.19047619048
+"125",144,6356.95238095238
+"126",145,6463.14285714286
+"127",146,6653.61904761905
+"128",147,6511.71428571429
+"129",148,6512.95238095238
+"130",149,6397.71428571429
+"131",150,6617.2380952381
+"132",151,6094.85714285714
+"133",152,6766.28571428571
+"134",153,6873.19047619048
+"135",154,6273.19047619048
+"136",155,6500.61904761905
+"137",156,6401.80952380952
+"138",157,6452.2380952381
+"139",158,6449.42857142857
+"140",159,6518
+"141",160,6518
+"142",161,6399.7619047619
+"143",162,6653.19047619048
+"144",163,6260.19047619048
+"145",164,6179.2380952381
+"146",165,6804.2380952381
+"147",166,6751.14285714286
+"148",167,6560.66666666667
+"149",168,6990.90476190476
+"150",169,6975.14285714286
+"151",170,6970.14285714286
+"152",171,6734.80952380952
+"153",172,6583.04761904762
+"154",173,6174.2380952381
+"155",174,6067.33333333333
+"156",175,6419.2380952381
+"157",176,6005.47619047619
+"158",177,5965.57142857143
+"159",178,5539.04761904762
+"160",179,5201.80952380952
+"161",180,5306
+"162",181,5357.33333333333
+"163",182,4840.19047619048
+"164",183,4516.04761904762
+"165",184,4437.38095238095
+"166",185,4148.19047619048
+"167",186,3595.90476190476
+"168",187,3589
+"169",188,3614.71428571429
+"170",189,3615.90476190476
+"171",190,4194.09523809524
+"172",191,4347.19047619048
+"173",192,4576.33333333333
+"174",193,5244.28571428571
+"175",194,4937.38095238095
+"176",195,4937.38095238095
+"177",196,5191.42857142857
+"178",197,5533.57142857143
+"179",198,5683.71428571429
+"180",199,5955.38095238095
+"181",200,6318.57142857143
+"182",201,6214.85714285714
+"183",202,6167.80952380952
+"184",203,6524.47619047619
+"185",204,6826.14285714286
+"186",205,6846.95238095238
+"187",206,6975.66666666667
+"188",207,7325.80952380952
+"189",208,7488.04761904762
+"190",209,7584.71428571429
+"191",210,7458.04761904762
+"192",211,6931.52380952381
+"193",212,6847.33333333333
+"194",213,6665.90476190476
+"195",214,6637.09523809524
+"196",215,6637.09523809524
+"197",216,6637.09523809524
+"198",217,6707.80952380952
+"199",218,6657.04761904762
+"200",219,6630.80952380952
+"201",220,6465.09523809524
+"202",221,5746.7619047619
+"203",222,5677.71428571429
+"204",223,5673.42857142857
+"205",224,6052.2380952381
+"206",225,6061.28571428571
+"207",226,6100.90476190476
+"208",227,6407.80952380952
+"209",228,6582.80952380952
+"210",229,6400.09523809524
+"211",230,6277.71428571429
+"212",231,5974.61904761905
+"213",232,6039.85714285714
+"214",233,6138.61904761905
+"215",234,5793.95238095238
+"216",235,5185.61904761905
+"217",236,5185.61904761905
+"218",237,5185.61904761905
+"219",238,5011.33333333333
+"220",239,4762.33333333333
+"221",240,4749.28571428571
+"222",241,4999.7619047619
+"223",242,5391.90476190476
+"224",243,5391.90476190476
+"225",244,5391.90476190476
+"226",245,5236.42857142857
+"227",246,5204.09523809524
+"228",247,5067.57142857143
+"229",248,4865.90476190476
+"230",249,4221.85714285714
+"231",250,4196.14285714286
+"232",251,4287.33333333333
+"233",252,4549.61904761905
+"234",253,4529.61904761905
+"235",254,4321.95238095238
+"236",255,4376.2380952381
+"237",256,4534.95238095238
+"238",257,4642.28571428571
+"239",258,4867.95238095238
+"240",259,4410.66666666667
+"241",260,4181.7619047619
+"242",261,4132
+"243",262,3547.95238095238
+"244",263,3165.57142857143
+"245",264,3537.19047619048
+"246",265,3752.71428571429
+"247",266,3212
+"248",267,3017.04761904762
+"249",268,3013.47619047619
+"250",269,2987.04761904762
+"251",270,3462.28571428571
+"252",271,3469.42857142857
+"253",272,3391.09523809524
+"254",273,3847.14285714286
+"255",274,4045.71428571429
+"256",275,4249.85714285714
+"257",276,4280.47619047619
+"258",277,4291.42857142857
+"259",278,4184.09523809524
+"260",279,3958.42857142857
+"261",280,4075.47619047619
+"262",281,4352.66666666667
+"263",282,4394.80952380952
+"264",283,4441.95238095238
+"265",284,4476.2380952381
+"266",285,4435.66666666667
+"267",286,4468.14285714286
+"268",287,4414.09523809524
+"269",288,4349
+"270",289,4450.19047619048
+"271",290,4178.04761904762
+"272",291,3862.09523809524
+"273",292,3881.38095238095
+"274",293,3871.38095238095
+"275",294,3611.19047619048
+"276",295,3662.61904761905
+"277",296,3575.85714285714
+"278",297,3918.2380952381
+"279",298,4170.2380952381
+"280",299,4170.2380952381
+"281",300,4170.2380952381
+"282",301,4577.85714285714
+"283",302,4423.38095238095
+"284",303,4388.38095238095
+"285",304,4756.47619047619
+"286",305,4869.19047619048
+"287",306,4538.14285714286
+"288",307,4290.14285714286
+"289",308,4433.2380952381
+"290",309,4762.28571428571
+"291",310,4642.71428571429
+"292",311,4739.61904761905
+"293",312,4890.19047619048
+"294",313,4977.90476190476
+"295",314,5076.2380952381
+"296",315,4817.2380952381
+"297",316,4391.52380952381
+"298",317,4344.14285714286
+"299",318,4162.71428571429
+"300",319,4213.19047619048
+"301",320,4247.85714285714
+"302",321,4270.42857142857
+"303",322,4225.42857142857
+"304",323,4455.19047619048
+"305",324,4327.80952380952
+"306",325,4272.80952380952
+"307",326,4688.19047619048
+"308",327,4688.19047619048
+"309",328,4688.19047619048
+"310",329,5210.80952380952
+"311",330,5324.14285714286
+"312",331,5318.71428571429
+"313",332,5487.85714285714
+"314",333,5625.85714285714
+"315",334,5602.42857142857
+"316",335,5535.52380952381
+"317",336,5745.47619047619
+"318",337,6030.2380952381
+"319",338,5963.57142857143
+"320",339,5825
+"321",340,5540.95238095238
+"322",341,5506.28571428571
+"323",342,5496.09523809524
+"324",343,5394.66666666667
+"325",344,5061.95238095238
+"326",345,5061.2380952381
+"327",346,4868.61904761905
+"328",347,4190.04761904762
+"329",348,4192.90476190476
+"330",349,4192.90476190476
+"331",350,3631.2380952381
+"332",351,3369.09523809524
+"333",352,3366.2380952381
+"334",353,3131.38095238095
+"335",354,2723.52380952381

hypotheses_modeling/fatigue_total_sum.csv

@@ -0,0 +1,355 @@
+TimeSinceAugFirst,fatigueSum
+0,0.734457489003587
+1,0.485175472200728
+2,0.280474592899874
+3,0.852899672028512
+4,0.067718127997734
+5,0.387261248267282
+6,0.466815138124766
+7,0.763731947890889
+8,0.685512083480377
+9,0.895108656027463
+10,-0.061861871122328
+11,0.296321907390904
+12,0.623117762114496
+13,0.753829250795893
+14,0.217870344211225
+15,0.53926849046086
+16,0.734843942472552
+17,0.308469121871186
+18,0.167041135359123
+19,0.746267880340515
+20,0.622788652776368
+21,0.214320156058007
+22,0.050827857843934
+23,0.294246790332209
+24,0.186808624194322
+25,0.552767197321023
+26,0.78454170658556
+27,0.779419550851109
+28,0.798357373731036
+29,0.323129040463109
+30,0.145143808515553
+31,0.68487764162657
+32,0.539874793771553
+33,0.36321009791783
+34,0.489148204465833
+35,0.413236542977807
+36,0.395011893731417
+37,0.156837050771386
+38,-0.285558218459401
+39,-0.349698539921412
+40,-0.558765836143965
+41,0.785941194779244
+42,0.260825136166886
+43,0.175173324395181
+44,0.548662507988438
+45,0.252321231106257
+46,0.742763716938104
+47,0.529872511137736
+48,0.37042402851138
+49,0.162733394153363
+50,0.357107946620677
+51,0.012983087373205
+52,-0.038997965254495
+53,0.241085179931302
+54,0.27305103057282
+55,0.501283454971351
+56,0.352131554149897
+57,0.510308182531921
+58,0.408416961411701
+59,-0.38225962517156
+60,0.111784933841739
+61,0.610578265741467
+62,0.563836579606691
+63,0.387038159139884
+64,0.17691474265164
+65,-0.158440974403251
+66,-0.127808846886789
+67,0.16767510337051
+68,0.232412554117885
+69,-0.034039586741236
+70,0.369219132420847
+71,0.055166081100634
+72,-0.15914007575716
+73,-0.143815705049808
+74,0.309931292450968
+75,0.481718700637843
+76,0.542695985663472
+77,-0.592609862606928
+78,-0.087871760090222
+79,0.323133612277408
+80,0.145926738048549
+81,0.266068498675575
+82,0.112895006227449
+83,0.11774653805839
+84,0.289982558620813
+85,0.156268777724842
+86,0.336960194430492
+87,0.211568516622687
+88,0.405654888856629
+89,-0.080651094767532
+90,-0.989503212930113
+91,-0.618589483268202
+92,-0.106354633315225
+93,-0.036704167015262
+94,-0.199061758628498
+95,-0.165391404949047
+96,0.465559713151923
+97,0.553712364147757
+98,0.10718598664192
+99,-0.176520319237606
+100,-0.012471746839114
+101,0.009238546030446
+102,0.031210965670768
+103,0.306981488185374
+104,0.326512806301329
+105,0.389789945787445
+106,0.163338392510265
+107,0.43041006311016
+108,0.064529621280754
+109,-0.056642839331862
+110,0.360810616073057
+111,0.674486235636005
+112,0.203177618350165
+113,0.016482187327924
+114,0.645937951499796
+115,-0.635636762766677
+116,0.054267298726349
+117,0.197678247905769
+118,-0.037744729883124
+119,0.510184386241254
+120,0.456725618316876
+121,0.36942720222611
+122,-0.305694272607688
+123,-1.09191169102099
+124,-0.726910533417431
+125,-0.43884728739089
+126,0.029939288546349
+127,-0.061371102729405
+128,-0.245528132438078
+129,0.009470765956943
+130,-0.341784370603988
+131,-0.049919365357729
+132,0.097143172058972
+133,-0.011342193521127
+134,0.080421703207904
+135,-0.129004417719117
+136,-0.270859696160466
+137,-0.708904646451948
+138,-0.229009026264089
+139,-0.181424438959781
+140,-0.026564683920245
+141,0.219065484118407
+142,-0.530439085926495
+143,-0.739993065212586
+144,-0.078144247328314
+145,0.281806254987051
+146,0.106323312617401
+147,0.461051503524687
+148,-0.194960844877302
+149,-1.0323471479209
+150,-0.221708749633043
+151,-0.146094771209489
+152,-0.769845305708576
+153,-0.006930021908459
+154,-0.104647283728296
+155,-0.012381788872799
+156,-0.19121232166827
+157,-0.671529527201817
+158,-0.616394224498445
+159,-0.073943182938408
+160,0.057147640203543
+161,-0.346330630873381
+162,-0.08655944015928
+163,-0.408202837238968
+164,-1.28901633269902
+165,-1.06200969217439
+166,-0.239078707352407
+167,-0.069592861351456
+168,-0.47050097438462
+169,-1.02350760409975
+170,-0.382414735756562
+171,-0.091983676112389
+172,0.016194125135445
+173,0.208557925296051
+174,0.382631435594289
+175,0.054618860565352
+176,0.392539314443691
+177,0.407308177079325
+178,0.5361087576086
+179,-0.559118537823889
+180,-0.041279425806623
+181,-0.811977779328337
+182,-0.673110139192779
+183,-0.647190032646896
+184,-0.264055759125838
+185,0.2137206708926
+186,0.169532929678205
+187,0.572823128029248
+188,0.504138498108557
+189,-0.025148663593221
+190,0.243256165168842
+191,-0.028600242158836
+192,-0.470973085298726
+193,-0.404980167324132
+194,0.192687307444004
+195,0.249123463461409
+196,-0.094501395021819
+197,0.330171642369123
+198,0.303808916345168
+199,-0.225895188174485
+200,-0.337185144362268
+201,0.184560773992318
+202,0.105945063048639
+203,-0.268263490373093
+204,-0.630585558331497
+205,-0.458206840787744
+206,-0.498158052976791
+207,-0.029702307826457
+208,-0.067979765277485
+209,-0.656925656525055
+210,-0.457529274865099
+211,-0.271352185811345
+212,-1.11655632791675
+213,-0.611166931446556
+214,-0.610527376526797
+215,0.034382530133085
+216,-0.141318464945944
+217,0.004511261469066
+218,-0.164492395019851
+219,-0.056862211997474
+220,0.010261586762043
+221,0.101082024613018
+222,0.372300796539504
+223,-0.145874961700409
+224,0.060726106209981
+225,-0.371059412216481
+226,-0.370670092221636
+227,0.083119527458891
+228,-0.058338986929759
+229,0.3362958277405
+230,0.519265121699177
+231,0.169683826619216
+232,0.077486840441911
+233,-0.474364612134558
+234,-0.247702269140266
+235,-0.659595488129965
+236,0.262402593762269
+237,-0.277905669965979
+238,-0.073857678558781
+239,0.053602846962544
+240,-0.606205677585295
+241,-0.624053318548306
+242,-0.605867224210048
+243,-0.252954297674564
+244,-0.101338569851228
+245,0.133299355850543
+246,0.416469635541468
+247,-0.48865392999333
+248,0.145411566109825
+250,-0.727338523179393
+251,0.124104120321982
+252,0.276748683294634
+253,0.793381770905604
+254,0.643063414197272
+255,1.04989185847975
+256,0.164337667404437
+257,0.158175420900341
+258,-0.376784412957032
+259,-1.13446825563484
+260,-0.682110266582935
+261,0.03890579636218
+262,0.250705347616431
+263,0.63083548881295
+264,-0.381185476545982
+265,-2.09473205252048
+266,-1.08423548600842
+267,-1.00435109992827
+268,-0.96922353115861
+269,-0.845113477539493
+270,-0.542326267460438
+271,-0.154289023678556
+272,-0.47818347594847
+273,-0.306186227227698
+274,0.130165587788887
+275,-0.534607431666707
+276,-0.024108562029165
+277,0.441356603857835
+278,0.835974252393425
+279,0.504743612581526
+280,0.608084130261808
+281,0.354286698358717
+282,0.149098455139156
+283,0.362866649040982
+284,0.585107099551978
+285,-0.238849557858286
+286,-1.29316205044401
+287,-0.514971003845922
+288,-0.130605271784348
+289,0.054601023159174
+290,0.712654053152515
+291,0.345411091599797
+292,0.590827647093801
+293,0.226175565336716
+294,0.066456432118622
+295,-0.244109627769699
+296,-0.668607818640876
+297,-0.892753779097629
+298,-0.864450623997139
+299,-0.052629105168991
+300,0.097879540271865
+301,0.068861223343318
+302,0.201303180551096
+303,-0.343311264954187
+304,-0.149597988654366
+305,0.1591975667215
+306,-0.128030046827757
+307,-0.881761347390814
+308,0.110911445153907
+309,-0.059481544970226
+310,0.248261046579106
+311,0.217829171777561
+312,-0.168769117743194
+313,-0.734302536254684
+314,-1.23366692589506
+315,-0.425009478665031
+316,-0.236956665438271
+317,-0.135287941133465
+318,-0.214676104364952
+319,-0.246512442890127
+320,0.020016985976053
+321,-0.561102012471304
+322,-0.258337553328078
+323,-0.360201383670261
+324,-0.676758179307032
+325,-1.22326716932596
+326,-0.552498077877283
+327,-0.05938292421172
+328,-0.230174146084735
+329,-0.178125732975686
+330,-0.782218150988738
+331,-0.902771605320945
+332,-0.83417758585907
+333,-0.623742294718358
+334,0.029100211618237
+335,-0.276998463243979
+336,-0.495616972912957
+337,-0.16842928848014
+338,-0.215205592767
+339,-0.400929404850442
+340,0.001421286489176
+341,0.247646162510804
+342,-0.019832667817069
+343,0.41449646066539
+344,0.305217583351337
+345,0.260375893221019
+346,0.643585606257478
+347,0.587502564497385
+348,0.933368991653645
+349,0.562934043178896
+350,0.582213233197938
+351,0.550560856980579
+352,0.598280595137412
+353,0.739698209165581
+354,0.066689402177346

hypotheses_modeling/team_regressions.py

@@ -1,4 +1,32 @@
 from sklearn import linear_model
+import pandas as pd
+from sklearn.metrics import mean_squared_error, r2_score
 
-reg = linear_model.LinearRegression()
-reg
+
+def k_days_into_future_regression(X, y, k, n0):
+  col = "TimeSinceAugFirst"
+  inp = []
+  out = []
+  for day in y[col][n0 - 1:]:
+    prev = day - k
+    xprev = X[X[col] == prev].drop(columns=[col]).to_numpy()[0, :]
+    yt = y[y[col] == day].drop(columns=[col]).to_numpy()[0, :]
+    inp.append(xprev)
+    out.append(yt)
+  regr = linear_model.LinearRegression()
+  regr.fit(inp, out)
+  predictions = regr.predict(inp)
+  mse = mean_squared_error(out, predictions)/(len(out) - 2)
+  r2 = r2_score(out, predictions)
+  return regr.intercept_, regr.coef_, r2, mse
+
+
+def main():
+  fatigueSums = pd.read_csv("fatigue_total_sum.csv")
+  workMovingAverage21 = pd.read_csv("21DaySlidingWorkAverage.csv", index_col=0)
+  performance = pd.read_csv("time_series_days_ranked.csv", index_col=0)
+  print(k_days_into_future_regression(workMovingAverage21, fatigueSums, 0, 21))
+
+
+if __name__ == "__main__":
+  main()

hypotheses_modeling/time_series_days_ranked.csv

@@ -0,0 +1,18 @@
+,Date,DailyElo
+0,121,0.0
+1,122,-3.714599999999998
+2,178,0.04346000000000028
+3,179,2.1916710000000013
+4,180,0.0
+5,255,0.0
+6,256,0.0
+7,257,-2.520374784999996
+8,263,-2.0880156214999985
+9,264,-1.7032140593500005
+10,284,-0.6130256153877235
+11,285,2.620463284090865
+12,311,-2.076954630427971
+13,312,1.0960590427574828
+14,313,1.8954531384817344
+15,353,-0.2940921753664384
+16,354,-1.8646829578297937