documented findings

findings/r2correlation.txt

@@ -0,0 +1,4 @@
+Document Linear Relationship
+7 day moving average team workload - normalized team fatigue: 0.0006
+21 day moving average team workload - normalized team fatigue: 0.0024
+

hypotheses_modeling/slidingWorkAverageSevenDay.csv

@@ -0,0 +1,350 @@
+"","TimeSinceAugFirst","slidingWorkAverage"
+"1",6,3340
+"2",7,4662.14285714286
+"3",8,5407.85714285714
+"4",9,5460.71428571429
+"5",10,5780.71428571429
+"6",11,6050
+"7",12,6225.71428571429
+"8",13,6240.71428571429
+"9",14,6057.14285714286
+"10",15,6055.71428571429
+"11",16,6022.71428571429
+"12",17,6087
+"13",18,6871.28571428571
+"14",19,6693.42857142857
+"15",20,6793.42857142857
+"16",21,6967.71428571429
+"17",22,7458.71428571429
+"18",23,7511.71428571429
+"19",24,7507.85714285714
+"20",25,7335.71428571429
+"21",26,7382.85714285714
+"22",27,7265.71428571429
+"23",28,7190.42857142857
+"24",29,6881.57142857143
+"25",30,6899.71428571429
+"26",31,6846.42857142857
+"27",32,6438.57142857143
+"28",33,6445
+"29",34,6445
+"30",35,6207.28571428571
+"31",36,5793
+"32",37,5750.42857142857
+"33",38,5989.71428571429
+"34",39,5710.85714285714
+"35",40,6025.85714285714
+"36",41,6025.85714285714
+"37",42,4970.28571428571
+"38",43,4164.57142857143
+"39",44,4362.85714285714
+"40",45,3313.57142857143
+"41",46,2486.14285714286
+"42",47,2147.85714285714
+"43",48,2152.14285714286
+"44",49,3555
+"45",50,4432.85714285714
+"46",51,4489
+"47",52,5900.42857142857
+"48",53,7505.14285714286
+"49",54,7474.85714285714
+"50",55,7528.42857142857
+"51",56,7414
+"52",57,7653.28571428571
+"53",58,7512.85714285714
+"54",59,7521.42857142857
+"55",60,7561.14285714286
+"56",61,7610.42857142857
+"57",62,7625.42857142857
+"58",63,7663.14285714286
+"59",64,7692.71428571429
+"60",65,7839.85714285714
+"61",66,7538.42857142857
+"62",67,7605
+"63",68,7617.85714285714
+"64",69,7596.42857142857
+"65",70,7843.85714285714
+"66",71,7791.14285714286
+"67",72,7870.85714285714
+"68",73,7778.71428571429
+"69",74,7231.85714285714
+"70",75,7234
+"71",76,7219
+"72",77,5686.85714285714
+"73",78,4371.42857142857
+"74",79,4231.42857142857
+"75",80,4410.71428571429
+"76",81,2970.71428571429
+"77",82,4127.14285714286
+"78",83,6200.71428571429
+"79",84,5997.85714285714
+"80",85,6781.42857142857
+"81",86,6890.71428571429
+"82",87,5516.42857142857
+"83",88,5910
+"84",89,5540.28571428571
+"85",90,4386.85714285714
+"86",91,4268.28571428571
+"87",92,3443.28571428571
+"88",93,2926.14285714286
+"89",94,3994.71428571429
+"90",95,4876.14285714286
+"91",96,4146.57142857143
+"92",97,3190
+"93",98,4790.71428571429
+"94",99,6302.85714285714
+"95",100,6819.28571428571
+"96",101,7200.42857142857
+"97",102,9141.14285714286
+"98",103,9159
+"99",104,9160.71428571429
+"100",105,9474.28571428571
+"101",106,9688.57142857143
+"102",107,9578.57142857143
+"103",108,9861.71428571429
+"104",109,9296
+"105",110,9156.71428571429
+"106",111,9155
+"107",112,8447.85714285714
+"108",113,7577.71428571429
+"109",114,7523.42857142857
+"110",115,5789.85714285714
+"111",116,3093.42857142857
+"112",117,3466.28571428571
+"113",118,4122
+"114",119,3564.85714285714
+"115",120,2901.42857142857
+"116",121,3102.14285714286
+"117",122,4238.42857142857
+"118",123,5762.28571428571
+"119",124,5389.42857142857
+"120",125,4733.71428571429
+"121",126,4419.42857142857
+"122",127,4468
+"123",128,4361.57142857143
+"124",129,4438.14285714286
+"125",130,4914.28571428571
+"126",131,5047.14285714286
+"127",132,5047.14285714286
+"128",133,6378.57142857143
+"129",134,7481.14285714286
+"130",135,7591.85714285714
+"131",136,8210.14285714286
+"132",137,8463.57142857143
+"133",138,8330.71428571429
+"134",139,8330.71428571429
+"135",140,8509.71428571429
+"136",141,7275
+"137",142,8413.28571428571
+"138",143,7959.28571428571
+"139",144,5693
+"140",145,6011.57142857143
+"141",146,6583
+"142",147,4646.85714285714
+"143",148,4782.71428571429
+"144",149,3188
+"145",150,3682.28571428571
+"146",151,4128
+"147",152,5956.57142857143
+"148",153,5705.85714285714
+"149",154,5663
+"150",155,7444.14285714286
+"151",156,7604.14285714286
+"152",157,7715.14285714286
+"153",158,9527.28571428571
+"154",159,7585.85714285714
+"155",160,7265.14285714286
+"156",161,8889.42857142857
+"157",162,7732.71428571429
+"158",163,7988.42857142857
+"159",164,7140.28571428571
+"160",165,6757.42857142857
+"161",166,6711
+"162",167,6711
+"163",168,6420.28571428571
+"164",169,5748.57142857143
+"165",170,5317.85714285714
+"166",171,5349
+"167",172,3464.42857142857
+"168",173,4225.85714285714
+"169",174,4225.85714285714
+"170",175,3948
+"171",176,4535.14285714286
+"172",177,4590.42857142857
+"173",178,4127.85714285714
+"174",179,5383.57142857143
+"175",180,4981.14285714286
+"176",181,5135.14285714286
+"177",182,4152.28571428571
+"178",183,3264.42857142857
+"179",184,3403.85714285714
+"180",185,2967.71428571429
+"181",186,1939.71428571429
+"182",187,1560
+"183",188,1483.14285714286
+"184",189,2747.42857142857
+"185",190,4782.71428571429
+"186",191,5047.28571428571
+"187",192,6633.42857142857
+"188",193,8409.57142857143
+"189",194,8271
+"190",195,8193.85714285714
+"191",196,8674.57142857143
+"192",197,8553.57142857143
+"193",198,8600
+"194",199,8265
+"195",200,8606.42857142857
+"196",201,8813.57142857143
+"197",202,8826.42857142857
+"198",203,8151.42857142857
+"199",204,7142.14285714286
+"200",205,6893.57142857143
+"201",206,6028.57142857143
+"202",207,4961.42857142857
+"203",208,5379.57142857143
+"204",209,5733.85714285714
+"205",210,5548.14285714286
+"206",211,5098.85714285714
+"207",212,5048.42857142857
+"208",213,5704.14285714286
+"209",214,6343.42857142857
+"210",215,5718.14285714286
+"211",216,5351
+"212",217,6423.85714285714
+"213",218,7730.14285714286
+"214",219,7950.42857142857
+"215",220,7662.57142857143
+"216",221,5935.42857142857
+"217",222,5935.42857142857
+"218",223,5935.42857142857
+"219",224,6184.71428571429
+"220",225,5354.85714285714
+"221",226,5303.85714285714
+"222",227,5856.71428571429
+"223",228,7469.57142857143
+"224",229,7546.71428571429
+"225",230,7546.71428571429
+"226",231,5315.28571428571
+"227",232,5034.57142857143
+"228",233,5161.57142857143
+"229",234,3862.57142857143
+"230",235,2151.85714285714
+"231",236,2074.71428571429
+"232",237,2074.71428571429
+"233",238,3534
+"234",239,3897.57142857143
+"235",240,3782.42857142857
+"236",241,5280
+"237",242,6554.28571428571
+"238",243,6554.28571428571
+"239",244,6554.28571428571
+"240",245,6860
+"241",246,6680.14285714286
+"242",247,6258.71428571429
+"243",248,5455.14285714286
+"244",249,3959.42857142857
+"245",250,3959.42857142857
+"246",251,4233
+"247",252,3254.85714285714
+"248",253,3011.14285714286
+"249",254,2924.71428571429
+"250",255,2393.57142857143
+"251",256,3091.14285714286
+"252",257,3413.14285714286
+"253",258,3816.57142857143
+"254",259,3117.14285714286
+"255",260,2854
+"256",261,3212.57142857143
+"257",262,2795.14285714286
+"258",263,2446.14285714286
+"259",264,3239
+"260",265,3208.57142857143
+"261",266,3264
+"262",267,3186
+"263",268,2903.14285714286
+"264",269,3772.42857142857
+"265",270,4849.57142857143
+"266",271,3756.14285714286
+"267",272,3148.14285714286
+"268",273,5160.28571428571
+"269",274,6097.14285714286
+"270",275,6633.85714285714
+"271",276,6273.85714285714
+"272",277,5578.57142857143
+"273",278,5557.14285714286
+"274",279,5518.57142857143
+"275",280,3802.14285714286
+"276",281,3774.85714285714
+"277",282,3647.42857142857
+"278",283,3279.57142857143
+"279",284,3000.57142857143
+"280",285,3993.71428571429
+"281",286,4737.71428571429
+"282",287,4279.85714285714
+"283",288,3175
+"284",289,3069.28571428571
+"285",290,2980.71428571429
+"286",291,3007.14285714286
+"287",292,2093.28571428571
+"288",293,1357.85714285714
+"289",294,2751.57142857143
+"290",295,4038
+"291",296,4010.85714285714
+"292",297,5494.42857142857
+"293",298,6503
+"294",299,6423.71428571429
+"295",300,6415.14285714286
+"296",301,6702.14285714286
+"297",302,6057.14285714286
+"298",303,6085
+"299",304,5794.28571428571
+"300",305,5097.42857142857
+"301",306,5097.42857142857
+"302",307,5097.42857142857
+"303",308,3846
+"304",309,4191.71428571429
+"305",310,3832.28571428571
+"306",311,2930.14285714286
+"307",312,3070.14285714286
+"308",313,3412.57142857143
+"309",314,3716.14285714286
+"310",315,3903.57142857143
+"311",316,2925.71428571429
+"312",317,3115.14285714286
+"313",318,3763.71428571429
+"314",319,4472
+"315",320,4233.57142857143
+"316",321,3997.71428571429
+"317",322,4926.71428571429
+"318",323,6248.14285714286
+"319",324,6036
+"320",325,6124.57142857143
+"321",326,6522.42857142857
+"322",327,6418.42857142857
+"323",328,6350.71428571429
+"324",329,6802.14285714286
+"325",330,6798.57142857143
+"326",331,6805
+"327",332,6575.28571428571
+"328",333,5883.14285714286
+"329",334,6155.28571428571
+"330",335,6258.14285714286
+"331",336,5507.57142857143
+"332",337,5044
+"333",338,5049.71428571429
+"334",339,4775.14285714286
+"335",340,4217.28571428571
+"336",341,3945.14285714286
+"337",342,3879.42857142857
+"338",343,3874.28571428571
+"339",344,3343.28571428571
+"340",345,3329
+"341",346,3255.42857142857
+"342",347,2469.71428571429
+"343",348,2478.28571428571
+"344",349,2441.14285714286
+"345",350,1511.85714285714
+"346",351,1720
+"347",352,1720
+"348",353,1363.57142857143
+"349",354,1483.57142857143

hypotheses_modeling/team_regressions.py

@@ -32,7 +32,6 @@ def k_days_into_future_regression(X, y, k, n0):
 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))