From 152bd1d78956ae1625077e8e1efbcd93a9573041 Mon Sep 17 00:00:00 2001
From: jamieveitch <jvveitch@gmail.com>
Date: Mon, 6 Mar 2023 22:25:09 +0000
Subject: [PATCH] introduced ranked beta

---
 Pipfile                     |    2 +
 Pipfile.lock                | 1226 +++++++++++++++++++++++------------
 analysis/preprocess.py      |   42 +-
 analysis/ranked.py          |   91 +++
 database/elo.csv            |   14 +
 database/mongo.py           |    7 +-
 database/timeseries_elo.csv |   14 +
 legacy/elo.py               |   20 +-
 spreadsheet/webapp.py       |    5 +-
 9 files changed, 960 insertions(+), 461 deletions(-)
 create mode 100644 analysis/ranked.py
 create mode 100644 database/elo.csv
 create mode 100644 database/timeseries_elo.csv

diff --git a/Pipfile b/Pipfile
index b6a6495..9086f96 100644
--- a/Pipfile
+++ b/Pipfile
@@ -10,6 +10,8 @@ tqdm = "*"
 jupyter = "*"
 pandas = "==1.4.2"
 streamlit-aggrid = "*"
+matplotlib = "*"
+scikit-learn = "*"
 
 [dev-packages]
 
diff --git a/Pipfile.lock b/Pipfile.lock
index 3e59e7a..85a78e7 100644
--- a/Pipfile.lock
+++ b/Pipfile.lock
@@ -1,7 +1,7 @@
 {
     "_meta": {
         "hash": {
-            "sha256": "512c27b12a3a2a914980d02045e430a4d531879559dc6abc1edec856ca5de859"
+            "sha256": "2498b5bc551eb437dd5c21b479e5e309d65e846add21fbaa51ccc15e52d285fc"
         },
         "pipfile-spec": 6,
         "requires": {
@@ -18,11 +18,11 @@
     "default": {
         "altair": {
             "hashes": [
-                "sha256:0c724848ae53410c13fa28be2b3b9a9dcb7b5caa1a70f7f217bd663bb419935a",
-                "sha256:d87d9372e63b48cd96b2a6415f0cf9457f50162ab79dc7a31cd7e024dd840026"
+                "sha256:39399a267c49b30d102c10411e67ab26374156a84b1aeb9fcd15140429ba49c5",
+                "sha256:8b45ebeaf8557f2d760c5c77b79f02ae12aee7c46c27c06014febab6f849bc87"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==4.2.0"
+            "version": "==4.2.2"
         },
         "anyio": {
             "hashes": [
@@ -92,11 +92,11 @@
         },
         "attrs": {
             "hashes": [
-                "sha256:29adc2665447e5191d0e7c568fde78b21f9672d344281d0c6e1ab085429b22b6",
-                "sha256:86efa402f67bf2df34f51a335487cf46b1ec130d02b8d39fd248abfd30da551c"
+                "sha256:29e95c7f6778868dbd49170f98f8818f78f3dc5e0e37c0b1f474e3561b240836",
+                "sha256:c9227bfc2f01993c03f68db37d1d15c9690188323c067c641f1a35ca58185f99"
             ],
-            "markers": "python_version >= '3.5'",
-            "version": "==22.1.0"
+            "markers": "python_version >= '3.6'",
+            "version": "==22.2.0"
         },
         "backcall": {
             "hashes": [
@@ -107,19 +107,19 @@
         },
         "beautifulsoup4": {
             "hashes": [
-                "sha256:58d5c3d29f5a36ffeb94f02f0d786cd53014cf9b3b3951d42e0080d8a9498d30",
-                "sha256:ad9aa55b65ef2808eb405f46cf74df7fcb7044d5cbc26487f96eb2ef2e436693"
+                "sha256:0e79446b10b3ecb499c1556f7e228a53e64a2bfcebd455f370d8927cb5b59e39",
+                "sha256:bc4bdda6717de5a2987436fb8d72f45dc90dd856bdfd512a1314ce90349a0106"
             ],
             "markers": "python_version >= '3.6'",
-            "version": "==4.11.1"
+            "version": "==4.11.2"
         },
         "bleach": {
             "hashes": [
-                "sha256:085f7f33c15bd408dd9b17a4ad77c577db66d76203e5984b1bd59baeee948b2a",
-                "sha256:0d03255c47eb9bd2f26aa9bb7f2107732e7e8fe195ca2f64709fcf3b0a4a085c"
+                "sha256:1a1a85c1595e07d8db14c5f09f09e6433502c51c595970edc090551f0db99414",
+                "sha256:33c16e3353dbd13028ab4799a0f89a83f113405c766e9c122df8a06f5b85b3f4"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==5.0.1"
+            "version": "==6.0.0"
         },
         "blinker": {
             "hashes": [
@@ -131,11 +131,11 @@
         },
         "cachetools": {
             "hashes": [
-                "sha256:6a94c6402995a99c3970cc7e4884bb60b4a8639938157eeed436098bf9831757",
-                "sha256:f9f17d2aec496a9aa6b76f53e3b614c965223c061982d434d160f930c698a9db"
+                "sha256:13dfddc7b8df938c21a940dfa6557ce6e94a2f1cdfa58eb90c805721d58f2c14",
+                "sha256:429e1a1e845c008ea6c85aa35d4b98b65d6a9763eeef3e37e92728a12d1de9d4"
             ],
             "markers": "python_version ~= '3.7'",
-            "version": "==5.2.0"
+            "version": "==5.3.0"
         },
         "certifi": {
             "hashes": [
@@ -216,11 +216,97 @@
         },
         "charset-normalizer": {
             "hashes": [
-                "sha256:5a3d016c7c547f69d6f81fb0db9449ce888b418b5b9952cc5e6e66843e9dd845",
-                "sha256:83e9a75d1911279afd89352c68b45348559d1fc0506b054b346651b5e7fee29f"
-            ],
-            "markers": "python_version >= '3.6'",
-            "version": "==2.1.1"
+                "sha256:00d3ffdaafe92a5dc603cb9bd5111aaa36dfa187c8285c543be562e61b755f6b",
+                "sha256:024e606be3ed92216e2b6952ed859d86b4cfa52cd5bc5f050e7dc28f9b43ec42",
+                "sha256:0298eafff88c99982a4cf66ba2efa1128e4ddaca0b05eec4c456bbc7db691d8d",
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+            ],
+            "markers": "python_full_version >= '3.6.0'",
+            "version": "==3.0.1"
         },
         "click": {
             "hashes": [
@@ -238,36 +324,97 @@
             "markers": "python_version >= '3.6'",
             "version": "==0.1.2"
         },
-        "commonmark": {
+        "contourpy": {
+            "hashes": [
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@@ -287,11 +434,11 @@
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@@ -315,6 +462,14 @@
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@@ -332,11 +487,11 @@
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@@ -348,27 +503,27 @@
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@@ -379,11 +534,11 @@
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@@ -408,6 +563,14 @@
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@@ -434,51 +597,51 @@
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@@ -490,57 +653,196 @@
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@@ -550,20 +852,28 @@
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@@ -1009,33 +1335,46 @@
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+                "sha256:75243e422e85a62f0ab7953dc315452a56b2c6a7e7d1a3c3109ac3cc57ed6b47",
+                "sha256:7877264aa851c19404b1bb9dbe6eed21ea0c13698be1eda3784aab3036d1c861",
+                "sha256:81f99fb1224d36eb91557afec8cdc2264e856f3464500b55749020ce4c848ef2",
+                "sha256:8539216173135e9e89f6b1cc392e74e6b935b91e8c76106cf50e7a02ab02efe5",
+                "sha256:85456f0d8f3268eecd63dede3b99d5bd8d3b306310c37d4c15141111d22baeaf",
+                "sha256:866eabf7c1315ef2e93e34230db7cbf672e0d7c626b37c11f7e870c8612c3dcc",
+                "sha256:926236ca003aec70574754f39703528947211a406f5c6c8b3e50eca04a9e87fc",
+                "sha256:930e6ad4f2eaac31a3d0c2130619d25db754b267487ebc186c6ad18af2a74018",
+                "sha256:94f0a7289d0f5c80807c37ebb404205e7deb737e8763eb176f4770839ee2a287",
+                "sha256:9a2d5e419bd39a1edb6cdd326d831f0120ddb9b1ff397e7d73541bf393294973",
+                "sha256:9ca6db34b26c4d3e9b0728841ec9aa39484eee272caa97972ec8c8e231b20c7e",
+                "sha256:9f72ea279b2941a5203e935a4588b9ba8a48aeb9a926d9dfa1986278bd362cb8",
+                "sha256:a0e7ef9ac807db50b4eb6f534c5dcc22f998f5dae920cc28873d2c1d080a4fc9",
+                "sha256:a1cd4a95f176cdc0ee0a82d49d5830f13ae6015d89decbf834c273bc33eeb3d3",
+                "sha256:a9c464cc508177c09a5a6122b67f978f20e2954a21362bf095a0da4647e3e908",
+                "sha256:ac97e7d647d5519bcef48dd8d3d331f72975afa5c4496c95f6e854686f45e2d9",
+                "sha256:af1fbfb7ad6ac0009ccee33c90a1d303431c7fb594335eb97760988727a37577",
+                "sha256:b055a1cddf8035966ad13aa51edae5dc8f1bba0b5d5e06f7a843d8b83dc9b66b",
+                "sha256:b6f75b4b8574f3a8a0d6b4b52606fc75b82cb4391471be48ab0b8677c82f9ed4",
+                "sha256:b90bb8dfbbd138558f1f284fecfe328f7653616ff9a972433a00711d9475d1a9",
+                "sha256:be05504af0619d1cffa500af1e0ede69fb683f301003851f5993b5247cc2c576",
+                "sha256:c21a5f4e54a807df5afdef52b6d24ec1580153a6bcf0607f70a6e1d9fa74c5c3",
+                "sha256:c48f257da280b3be6c94e05bd575eddb1373419dbb1a72c3ce64e88f29d1cd6d",
+                "sha256:cac602e02341eaaf4edfd3e29bd3fdef672e61d4e6dfe5c1d065172aee00acee",
+                "sha256:ccb3e1a863222afdbda42b7ca8ac8569959593d7abd44f5a709177d6fa27d266",
+                "sha256:e1081d7030a1229c8ff90120346fb7599b54f552e98fcea5170544e7c6725aab",
+                "sha256:e14df47c1265356715d3d66e90282a645ebc077b70b3806cf47efcb7d1d630cb",
+                "sha256:e4bba04ea779a3d7ef25a821bb63fd0939142c88e7813e5bd9c6265a20c523a2",
+                "sha256:e99629a976809fe102ef73e856cf4b2660acd82a412a51e80ba2215e523dfd0a",
+                "sha256:f330a1a2c7f89fd4b0aa4dcb7bf50243bf1c8da9a2f1efc31daf57a2046b31f2",
+                "sha256:f3f96d452e9580cb961ece2e5a788e64abaecb1232a80e61deffb28e105ff84a",
+                "sha256:fc7c1421c5b1c916acf3128bf3cc7ea7f5018b58c69a6866d70c14190e600ce9"
             ],
             "markers": "python_version >= '3.6'",
-            "version": "==24.0.1"
+            "version": "==25.0.0"
         },
         "qtconsole": {
             "hashes": [
@@ -1219,17 +1561,18 @@
         },
         "requests": {
             "hashes": [
-                "sha256:7c5599b102feddaa661c826c56ab4fee28bfd17f5abca1ebbe3e7f19d7c97983",
-                "sha256:8fefa2a1a1365bf5520aac41836fbee479da67864514bdb821f31ce07ce65349"
+                "sha256:64299f4909223da747622c030b781c0d7811e359c37124b4bd368fb8c6518baa",
+                "sha256:98b1b2782e3c6c4904938b84c0eb932721069dfdb9134313beff7c83c2df24bf"
             ],
             "markers": "python_version >= '3.7' and python_version < '4'",
-            "version": "==2.28.1"
+            "version": "==2.28.2"
         },
         "rfc3339-validator": {
             "hashes": [
                 "sha256:138a2abdf93304ad60530167e51d2dfb9549521a836871b88d7f4695d0022f6b",
                 "sha256:24f6ec1eda14ef823da9e36ec7113124b39c04d50a4d3d3a3c2859577e7791fa"
             ],
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'",
             "version": "==0.1.4"
         },
         "rfc3986-validator": {
@@ -1237,15 +1580,70 @@
                 "sha256:2f235c432ef459970b4306369336b9d5dbdda31b510ca1e327636e01f528bfa9",
                 "sha256:3d44bde7921b3b9ec3ae4e3adca370438eccebc676456449b145d533b240d055"
             ],
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'",
             "version": "==0.1.1"
         },
         "rich": {
             "hashes": [
-                "sha256:a4eb26484f2c82589bd9a17c73d32a010b1e29d89f1604cd9bf3a2097b81bb5e",
-                "sha256:ba3a3775974105c221d31141f2c116f4fd65c5ceb0698657a11e9f295ec93fd0"
+                "sha256:125d96d20c92b946b983d0d392b84ff945461e5a06d3867e9f9e575f8697b67f",
+                "sha256:8aa57747f3fc3e977684f0176a88e789be314a99f99b43b75d1e9cb5dc6db9e9"
+            ],
+            "markers": "python_version >= '3.7'",
+            "version": "==13.3.1"
+        },
+        "scikit-learn": {
+            "hashes": [
+                "sha256:479aedd0abedbda6b8b4529145fe4cd8622f69f726a72cef8f75548a93eeb1e1",
+                "sha256:54731e2c2fbff40da6d76cbb9022ace5f44a4020a10bd5cd92107e86882bad15",
+                "sha256:5523e21ab2b4d52b2bd41bedd335dbe8f3c1b5f6dd7c9c001b2e17ec9818af8d",
+                "sha256:559f66e12f93b34c8c85c0a5728c3b8af98f04eb12f2c9ee18ea3c82c3d2fad1",
+                "sha256:5a8111f3c7a314017ebf90d6feab861c11d1ca14f3dbafb39abcc31aa4c54ba6",
+                "sha256:5b2c5d9930ced2b7821ad936b9940706ccb5471d89b8a516bb641cec87257d1c",
+                "sha256:61bb9c654b5d2e6cdd4b1c7e6048fc66270c1682bda1b0f7d2726fdae09010f4",
+                "sha256:70fa30d146b7e9d0c256e73e271b3e17f23123b7c4adcbde1a385031adf59090",
+                "sha256:a9abf17d177df54e529154f26acfd42930e19117d045e8a9a8e893ca82dd94ec",
+                "sha256:bed9f75763bd392c094bf474c7ab75a01d68b15146ea7a20c0f9ff6fb3063dad",
+                "sha256:c722f3446ad8c4f1a93b2399fe1a188635b94709a3f25e6f4d61efbe75fe8eaa",
+                "sha256:c9285275a435d1f8f47bbe3500346ab9ead2499e0e090518404d318ea90d1c1c",
+                "sha256:cba0c7c6bf1493f8ce670bab69f9317874826ee838988de377ae355abd4d74cf",
+                "sha256:d00e46a2a7fce6e118ed0f4c6263785bf6c297a94ffd0cd7b32455043c508cc8",
+                "sha256:d8bcd303dd982494842a3f482f844d539484c6043b4eed896b43ea8e5f609a21",
+                "sha256:da0e2d50a8435ea8dc5cd21f1fc1a45d329bae03dcca92087ebed859d22d184e",
+                "sha256:dbb7831b2308c67bb6dd83c5ea3cdaf8e8cafd2de4000b93d78bb689126bd2cf",
+                "sha256:dc838b5a4057c55ba81b82316ea8bf443af445f96eb21500b0e40618017e0923",
+                "sha256:dcfab6a19b236194af88771d8e6e778a60c3339248ab0018696ebf2b7c8bed4b",
+                "sha256:e0ee4d4d32c94e082344308528f7b3c9294b60ab19c84eb37a2d9c88bdffd9d1",
+                "sha256:fbf8a5c893c9b4b99bcc7ed8fb3e8500957a113f4101860386d06635520f7cfb"
             ],
-            "markers": "python_version < '4' and python_full_version >= '3.6.3'",
-            "version": "==12.6.0"
+            "index": "pypi",
+            "version": "==1.2.1"
+        },
+        "scipy": {
+            "hashes": [
+                "sha256:0490dc499fe23e4be35b8b6dd1e60a4a34f0c4adb30ac671e6332446b3cbbb5a",
+                "sha256:0ab2a58064836632e2cec31ca197d3695c86b066bc4818052b3f5381bfd2a728",
+                "sha256:151f066fe7d6653c3ffefd489497b8fa66d7316e3e0d0c0f7ff6acca1b802809",
+                "sha256:16ba05d3d1b9f2141004f3f36888e05894a525960b07f4c2bfc0456b955a00be",
+                "sha256:27e548276b5a88b51212b61f6dda49a24acf5d770dff940bd372b3f7ced8c6c2",
+                "sha256:2ad449db4e0820e4b42baccefc98ec772ad7818dcbc9e28b85aa05a536b0f1a2",
+                "sha256:2f9ea0a37aca111a407cb98aa4e8dfde6e5d9333bae06dfa5d938d14c80bb5c3",
+                "sha256:38bfbd18dcc69eeb589811e77fae552fa923067fdfbb2e171c9eac749885f210",
+                "sha256:3afcbddb4488ac950ce1147e7580178b333a29cd43524c689b2e3543a080a2c8",
+                "sha256:42ab8b9e7dc1ebe248e55f54eea5307b6ab15011a7883367af48dd781d1312e4",
+                "sha256:441cab2166607c82e6d7a8683779cb89ba0f475b983c7e4ab88f3668e268c143",
+                "sha256:4bd0e3278126bc882d10414436e58fa3f1eca0aa88b534fcbf80ed47e854f46c",
+                "sha256:4df25a28bd22c990b22129d3c637fd5c3be4b7c94f975dca909d8bab3309b694",
+                "sha256:5cd7a30970c29d9768a7164f564d1fbf2842bfc77b7d114a99bc32703ce0bf48",
+                "sha256:6e4497e5142f325a5423ff5fda2fff5b5d953da028637ff7c704378c8c284ea7",
+                "sha256:6faf86ef7717891195ae0537e48da7524d30bc3b828b30c9b115d04ea42f076f",
+                "sha256:954ff69d2d1bf666b794c1d7216e0a746c9d9289096a64ab3355a17c7c59db54",
+                "sha256:9b878c671655864af59c108c20e4da1e796154bd78c0ed6bb02bc41c84625686",
+                "sha256:b901b423c91281a974f6cd1c36f5c6c523e665b5a6d5e80fcb2334e14670eefd",
+                "sha256:c8b3cbc636a87a89b770c6afc999baa6bcbb01691b5ccbbc1b1791c7c0a07540",
+                "sha256:e096b062d2efdea57f972d232358cb068413dc54eec4f24158bcbb5cb8bddfd8"
+            ],
+            "markers": "python_version < '3.12' and python_version >= '3.8'",
+            "version": "==1.10.0"
         },
         "semver": {
             "hashes": [
@@ -1288,11 +1686,11 @@
         },
         "soupsieve": {
             "hashes": [
-                "sha256:3b2503d3c7084a42b1ebd08116e5f81aadfaea95863628c80a3b774a11b7c759",
-                "sha256:fc53893b3da2c33de295667a0e19f078c14bf86544af307354de5fcf12a3f30d"
+                "sha256:49e5368c2cda80ee7e84da9dbe3e110b70a4575f196efb74e51b94549d921955",
+                "sha256:e28dba9ca6c7c00173e34e4ba57448f0688bb681b7c5e8bf4971daafc093d69a"
             ],
-            "markers": "python_version >= '3.6'",
-            "version": "==2.3.2.post1"
+            "markers": "python_version >= '3.7'",
+            "version": "==2.4"
         },
         "stack-data": {
             "hashes": [
@@ -1325,6 +1723,14 @@
             "markers": "python_version >= '3.7'",
             "version": "==0.17.1"
         },
+        "threadpoolctl": {
+            "hashes": [
+                "sha256:8b99adda265feb6773280df41eece7b2e6561b772d21ffd52e372f999024907b",
+                "sha256:a335baacfaa4400ae1f0d8e3a58d6674d2f8828e3716bb2802c44955ad391380"
+            ],
+            "markers": "python_version >= '3.6'",
+            "version": "==3.1.0"
+        },
         "tinycss2": {
             "hashes": [
                 "sha256:2b80a96d41e7c3914b8cda8bc7f705a4d9c49275616e886103dd839dfc847847",
@@ -1376,19 +1782,19 @@
         },
         "traitlets": {
             "hashes": [
-                "sha256:57ba2ba951632eeab9388fa45f342a5402060a5cc9f0bb942f760fafb6641581",
-                "sha256:fde8f62c05204ead43c2c1b9389cfc85befa7f54acb5da28529d671175bb4108"
+                "sha256:9e6ec080259b9a5940c797d58b613b5e31441c2257b87c2e795c5228ae80d2d8",
+                "sha256:f6cde21a9c68cf756af02035f72d5a723bf607e862e7be33ece505abf4a3bad9"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==5.7.1"
+            "version": "==5.9.0"
         },
         "typing-extensions": {
             "hashes": [
-                "sha256:1511434bb92bf8dd198c12b1cc812e800d4181cfcb867674e0f8279cc93087aa",
-                "sha256:16fa4864408f655d35ec496218b85f79b3437c829e93320c7c9215ccfd92489e"
+                "sha256:5cb5f4a79139d699607b3ef622a1dedafa84e115ab0024e0d9c044a9479ca7cb",
+                "sha256:fb33085c39dd998ac16d1431ebc293a8b3eedd00fd4a32de0ff79002c19511b4"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==4.4.0"
+            "version": "==4.5.0"
         },
         "tzdata": {
             "hashes": [
@@ -1415,11 +1821,11 @@
         },
         "urllib3": {
             "hashes": [
-                "sha256:47cc05d99aaa09c9e72ed5809b60e7ba354e64b59c9c173ac3018642d8bb41fc",
-                "sha256:c083dd0dce68dbfbe1129d5271cb90f9447dea7d52097c6e0126120c521ddea8"
+                "sha256:076907bf8fd355cde77728471316625a4d2f7e713c125f51953bb5b3eecf4f72",
+                "sha256:75edcdc2f7d85b137124a6c3c9fc3933cdeaa12ecb9a6a959f22797a0feca7e1"
             ],
             "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4, 3.5'",
-            "version": "==1.26.13"
+            "version": "==1.26.14"
         },
         "validators": {
             "hashes": [
@@ -1430,10 +1836,10 @@
         },
         "wcwidth": {
             "hashes": [
-                "sha256:beb4802a9cebb9144e99086eff703a642a13d6a0052920003a230f3294bbe784",
-                "sha256:c4d647b99872929fdb7bdcaa4fbe7f01413ed3d98077df798530e5b04f116c83"
+                "sha256:795b138f6875577cd91bba52baf9e445cd5118fd32723b460e30a0af30ea230e",
+                "sha256:a5220780a404dbe3353789870978e472cfe477761f06ee55077256e509b156d0"
             ],
-            "version": "==0.2.5"
+            "version": "==0.2.6"
         },
         "webcolors": {
             "hashes": [
@@ -1451,27 +1857,27 @@
         },
         "websocket-client": {
             "hashes": [
-                "sha256:d6b06432f184438d99ac1f456eaf22fe1ade524c3dd16e661142dc54e9cba574",
-                "sha256:d6e8f90ca8e2dd4e8027c4561adeb9456b54044312dba655e7cae652ceb9ae59"
+                "sha256:3f09e6d8230892547132177f575a4e3e73cfdf06526e20cc02aa1c3b47184d40",
+                "sha256:cdf5877568b7e83aa7cf2244ab56a3213de587bbe0ce9d8b9600fc77b455d89e"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==1.4.2"
+            "version": "==1.5.1"
         },
         "widgetsnbextension": {
             "hashes": [
-                "sha256:44c69f18237af0f610557d6c1c7ef76853f5856a0e604c0a517f2320566bb775",
-                "sha256:fa0e840719ec95dd2ec85c3a48913f1a0c29d323eacbcdb0b29bfed0cc6da678"
+                "sha256:003f716d930d385be3fd9de42dd9bf008e30053f73bddde235d14fbeaeff19af",
+                "sha256:eaaaf434fb9b08bd197b2a14ffe45ddb5ac3897593d43c69287091e5f3147bf7"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==4.0.4"
+            "version": "==4.0.5"
         },
         "zipp": {
             "hashes": [
-                "sha256:83a28fcb75844b5c0cdaf5aa4003c2d728c77e05f5aeabe8e95e56727005fbaa",
-                "sha256:a7a22e05929290a67401440b39690ae6563279bced5f314609d9d03798f56766"
+                "sha256:23f70e964bc11a34cef175bc90ba2914e1e4545ea1e3e2f67c079671883f9cb6",
+                "sha256:e8b2a36ea17df80ffe9e2c4fda3f693c3dad6df1697d3cd3af232db680950b0b"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==3.11.0"
+            "version": "==3.13.0"
         }
     },
     "develop": {}
diff --git a/analysis/preprocess.py b/analysis/preprocess.py
index 95fc770..49bb040 100644
--- a/analysis/preprocess.py
+++ b/analysis/preprocess.py
@@ -17,19 +17,6 @@ def remove_uneven_teams(games: pd.DataFrame) -> pd.Index:
     return valid_games
 
 
-def remove_no_damage_rounds(games: pd.DataFrame) -> pd.Index:
-    """
-    get the list of games that have had damage dealt in all rounds
-    :param games:   all data stored in the mongo database
-    :return:        the list of games that have had damage dealt in all rounds
-    """
-    damage_dealt = get_damage_dealt(games=games)
-    min_damage_dealt = damage_dealt.groupby('matchID').min()
-    valid_games = min_damage_dealt[min_damage_dealt != 0].index
-
-    return valid_games
-
-
 def remove_non_highlander(games: pd.DataFrame) -> pd.Index:
     """
     remove all games that weren't playing highlander in any round
@@ -49,36 +36,21 @@ def preprocess(games: pd.DataFrame) -> pd.DataFrame:
     :param games:   all data stored in the mongo database
     :return:        the list of games that should be used for ranking
     """
+
     ranked_games: pd.DataFrame = games[
-        games['ranked'] &
-        games['rebalance'] &
-        ~games['perfectKits'] &
-        ~games['isPreRelease'].replace(np.nan, True)
+        ~games.perfectKits &
+        games.rebalance &
+        (games["kit1"] != "Spectate") &
+        (games.matchTimestamp > "2023-03-01")
     ].copy()
 
     has_even_teams = remove_uneven_teams(games=ranked_games)
-    has_damage = remove_no_damage_rounds(games=ranked_games)
     has_highlander = remove_non_highlander(games=ranked_games)
 
     ranked_games.set_index('matchID', inplace=True)
-    ranked_games = ranked_games.loc[has_even_teams.intersection(has_damage).intersection(has_highlander)]
-    ranked_games = games.copy().set_index('matchID')
+    ranked_games = ranked_games.loc[has_even_teams.intersection(has_highlander)]
 
     recent_names = player_names(games=ranked_games)
     ranked_games['name'] = ranked_games['uid'].replace(recent_names)
 
-    ranked_games.drop(
-        columns=[
-            '_id',
-            'uid',
-            'serverName',
-            'ranked',
-            'rebalance',
-            'perfectKits',
-            'isPreRelease',
-            'version'
-        ],
-        inplace=True
-    )
-
-    return ranked_games
+    return ranked_games.reset_index()
diff --git a/analysis/ranked.py b/analysis/ranked.py
new file mode 100644
index 0000000..3b23e8e
--- /dev/null
+++ b/analysis/ranked.py
@@ -0,0 +1,91 @@
+import itertools
+import pandas as pd
+
+
+def get_result(elo, p1, p2) -> float:
+    """
+    :param p1: the elo of player 1
+    :param p2: the elo of player 2
+    :return: the expected result of player 1
+    """
+    p2 = elo[p2]
+    p1 = elo[p1]
+
+    exponent = (p2 - p1) / 400.0
+    return 1 / ((10.0 ** exponent) + 1)
+
+
+def update_elo(game_round: pd.DataFrame, k: int, g: int) -> pd.Series:
+    """
+    update the elo for each player in the game round
+    :param game_round:      the game round to update the elo for
+    :param elo:             the current elo for each player
+    :param k:               the k factor for the elo
+    :param g:               the g factor for the elo
+    :return:                the updated elo for each player
+    """
+    try:
+        elo = pd.read_csv("database/elo.csv", index_col=0).squeeze()
+    except FileNotFoundError:
+        elo = pd.Series(dtype=float, name="2023-03-01")
+
+    if game_round.matchTimestamp.unique()[0] < elo.name:
+        print("outdated game round")
+        return elo
+
+    winners = game_round[game_round['result'] == "Win"]["name"].unique().tolist()
+    losers = game_round[game_round['result'] == "Loss"]["name"].unique().tolist()
+
+    for player in winners + losers:
+        if player not in elo.index:
+            elo[player] = 1000
+
+    expected_results = pd.DataFrame(columns=winners, index=losers)
+    expected_results = expected_results.apply(
+        lambda winner: winner.index.to_series().apply(lambda loser: get_result(elo, winner.name, loser))
+    )
+    loser_elo = expected_results.apply(lambda loser: (k * g)*(loser - 1), axis=1).mean(axis=1)
+    winner_elo = expected_results.apply(lambda winner: (k * g) * (1 - winner)).mean()
+
+    elo = elo.add(winner_elo, fill_value=0.0)
+    elo = elo.add(loser_elo, fill_value=0.0)
+
+    elo = elo.rename(game_round.matchTimestamp.unique()[0])
+    elo.to_csv("database/elo.csv")
+
+    try:
+        timeseries_elo = pd.read_csv("database/timeseries_elo.csv", index_col=0)
+        timeseries_elo = pd.concat([timeseries_elo, elo], axis=1)
+    except FileNotFoundError:
+        timeseries_elo = elo
+
+    timeseries_elo.to_csv("database/timeseries_elo.csv")
+
+    return elo
+
+
+def trigger_update(games: pd.DataFrame) -> None:
+    """
+    :param games:
+    :return:
+    """
+    try:
+        elo = pd.read_csv("database/elo.csv", index_col=0).squeeze()
+    except FileNotFoundError:
+        elo = pd.Series(dtype=float, name="2023-03-01")
+
+    games = games[games['matchTimestamp'] > elo.name]
+    chronological_matches = games.sort_values("matchTimestamp", ascending=True).matchID.unique()
+
+    for match in chronological_matches:
+
+        match_played = games[games["matchID"] == match]
+        rounds = match_played["round"].sort_values(ascending=True).unique()
+
+        for round_played in rounds:
+            update_elo(
+                match_played[match_played["round"] == round_played],
+                k=32,
+                g=1
+            )
+
diff --git a/database/elo.csv b/database/elo.csv
new file mode 100644
index 0000000..1c54d20
--- /dev/null
+++ b/database/elo.csv
@@ -0,0 +1,14 @@
+,2023-03-06 01:55:26
+DustShelter_Inc,1001.5317741589588
+Fun13us,1101.588475146853
+L1GHTMAN2k,968.8683288311493
+MrBlaBlak,948.42744492315
+TTVbiohaZard1324,899.4598874131813
+Test97point3,1031.1316711688498
+TragicRAT55,1077.872539483852
+dsnvacation,979.9420269562636
+lexvi1,1038.8063425633643
+pon47k,938.89203628405
+sparkyfan236,1043.5106348693398
+spooksi,986.4583569874478
+zerytoe,983.5104812135404
diff --git a/database/mongo.py b/database/mongo.py
index 900dad9..a9346bd 100644
--- a/database/mongo.py
+++ b/database/mongo.py
@@ -4,7 +4,8 @@
 import datetime
 import pandas as pd
 import numpy as np
-from tqdm import tqdm
+
+from analysis.utilities import player_names
 
 
 def load_database() -> pd.DataFrame:
@@ -15,11 +16,11 @@ def load_database() -> pd.DataFrame:
         os.environ["LIGHTHOUSE_MONGO_KEY"],
         tlsAllowInvalidCertificates=True
     )
-    games = pd.DataFrame(list(tqdm(client["ranking"].ranking.find())))
+    games = pd.DataFrame(list(client["ranking"].ranking.find()))
     games["team"] = games["team"].replace([2, 3], ["imc", "militia"])
 
     games['matchTimestamp'] = games['matchTimestamp'].apply(
-        lambda date: str(datetime.datetime.fromtimestamp(date).date())
+        lambda date: str(datetime.datetime.fromtimestamp(date))
     )
 
     return games
diff --git a/database/timeseries_elo.csv b/database/timeseries_elo.csv
new file mode 100644
index 0000000..095b0d8
--- /dev/null
+++ b/database/timeseries_elo.csv
@@ -0,0 +1,14 @@
+,2023-03-01 00:45:01,2023-03-01 00:45:01.1,2023-03-01 00:45:01.2,2023-03-01 01:05:12,2023-03-01 01:05:12.1,2023-03-01 01:05:12.2,2023-03-01 01:12:51,2023-03-01 01:12:51.1,2023-03-01 01:12:51.2,2023-03-01 01:12:51.3,2023-03-01 01:12:51.4,2023-03-01 01:22:37,2023-03-01 01:22:37.1,2023-03-01 01:22:37.2,2023-03-01 01:22:37.3,2023-03-01 01:22:37.4,2023-03-01 01:41:51,2023-03-01 01:41:51.1,2023-03-01 01:41:51.2,2023-03-01 01:41:51.3,2023-03-01 01:48:46,2023-03-01 01:58:00,2023-03-01 01:58:00.1,2023-03-01 01:58:00.2,2023-03-01 02:04:44,2023-03-01 02:04:44.1,2023-03-01 02:04:44.2,2023-03-01 02:10:50,2023-03-01 02:10:50.1,2023-03-01 02:10:50.2,2023-03-01 02:15:50,2023-03-01 02:15:50.1,2023-03-01 02:15:50.2,2023-03-01 02:15:50.3,2023-03-01 02:15:50.4,2023-03-01 02:25:01,2023-03-01 02:25:01.1,2023-03-01 02:25:01.2,2023-03-01 02:25:01.3,2023-03-01 02:25:01.4,2023-03-01 19:41:11,2023-03-01 19:41:11.1,2023-03-01 19:41:11.2,2023-03-01 19:41:11.3,2023-03-01 19:41:11.4,2023-03-01 19:52:00,2023-03-01 19:52:00.1,2023-03-01 19:52:00.2,2023-03-01 19:58:17,2023-03-01 19:58:17.1,2023-03-01 19:58:17.2,2023-03-03 18:39:47,2023-03-03 18:39:47.1,2023-03-03 18:39:47.2,2023-03-03 18:46:56,2023-03-03 18:46:56.1,2023-03-03 18:46:56.2,2023-03-03 18:46:56.3,2023-03-03 18:46:56.4,2023-03-03 18:56:56,2023-03-03 18:56:56.1,2023-03-03 18:56:56.2,2023-03-03 18:56:56.3,2023-03-03 19:06:37,2023-03-03 19:06:37.1,2023-03-03 19:06:37.2,2023-03-03 19:06:37.3,2023-03-03 19:13:56,2023-03-03 19:13:56.1,2023-03-03 19:13:56.2,2023-03-04 12:24:20,2023-03-04 12:24:20.1,2023-03-04 12:24:20.2,2023-03-04 12:31:11,2023-03-04 12:31:11.1,2023-03-04 12:31:11.2,2023-03-04 17:58:04,2023-03-04 18:24:11,2023-03-04 18:24:11.1,2023-03-04 18:24:11.2,2023-03-04 18:24:11.3,2023-03-04 18:24:11.4,2023-03-05 14:47:55,2023-03-05 14:47:55.1,2023-03-05 14:47:55.2,2023-03-05 14:54:18,2023-03-05 14:54:18.1,2023-03-05 14:54:18.2,2023-03-05 14:59:34,2023-03-05 14:59:34.1,2023-03-05 14:59:34.2,2023-03-05 14:59:34.3,2023-03-05 17:46:07,2023-03-05 17:46:07.1,2023-03-05 17:46:07.2,2023-03-05 17:46:07.3,2023-03-05 17:46:07.4,2023-03-05 17:57:40,2023-03-05 17:57:40.1,2023-03-05 17:57:40.2,2023-03-05 17:57:40.3,2023-03-05 17:57:40.4,2023-03-05 18:13:40,2023-03-05 18:13:40.1,2023-03-05 18:13:40.2,2023-03-05 18:13:40.3,2023-03-06 00:53:28,2023-03-06 00:53:28.1,2023-03-06 00:53:28.2,2023-03-06 00:53:28.3,2023-03-06 01:03:16,2023-03-06 01:03:16.1,2023-03-06 01:03:16.2,2023-03-06 01:10:33,2023-03-06 01:10:33.1,2023-03-06 01:10:33.2,2023-03-06 01:10:33.3,2023-03-06 01:10:33.4,2023-03-06 01:21:55,2023-03-06 01:21:55.1,2023-03-06 01:21:55.2,2023-03-06 01:28:25,2023-03-06 01:28:25.1,2023-03-06 01:28:25.2,2023-03-06 01:28:25.3,2023-03-06 01:36:54,2023-03-06 01:36:54.1,2023-03-06 01:36:54.2,2023-03-06 01:48:12,2023-03-06 01:48:12.1,2023-03-06 01:48:12.2,2023-03-06 01:55:26,2023-03-06 01:55:26.1,2023-03-06 01:55:26.2,2023-03-06 01:55:26
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diff --git a/legacy/elo.py b/legacy/elo.py
index 1ae34fa..32e5014 100644
--- a/legacy/elo.py
+++ b/legacy/elo.py
@@ -2,7 +2,6 @@
 from sklearn.linear_model import LogisticRegression
 from typing import List, Tuple
 
-from utilities import convert_uid_index
 import itertools
 
 import warnings
@@ -48,6 +47,7 @@ def process_match(self, match: pd.DataFrame):
         :param match: the match that has been played
         :return:
         """
+        match.set_index("round", inplace=True)
 
         for round_played in match.index.unique():
             try:
@@ -56,7 +56,7 @@ def process_match(self, match: pd.DataFrame):
                 print('could not process match at time {} round {}'.format(match.matchTimestamp, round_played))
                 print(e)
 
-        match_played = pd.Series(1, index=match['uid'].unique())
+        match_played = pd.Series(1, index=match['name'].unique())
         self.matches_played = self.matches_played.add(match_played, fill_value=0)
 
         self.historical_rankings = pd.concat(
@@ -70,13 +70,13 @@ def process_round(self, game_round: pd.DataFrame):
         :return: the elo changes to make
         """
 
-        winners = game_round[game_round.result == 'Win'].set_index('uid')
-        losers = game_round[game_round.result == 'Loss'].set_index('uid')
+        winners = game_round[game_round.result == 'Win'].set_index('name')
+        losers = game_round[game_round.result == 'Loss'].set_index('name')
 
-        for player in game_round['uid'].unique():
+        for player in game_round['name'].unique():
             self.check_player(player)
 
-        elo_gained = pd.Series(0, index=game_round['uid'].unique())
+        elo_gained = pd.Series(0, index=game_round['name'].unique())
 
         for winner, loser in list(itertools.product(winners.index.values, losers.index.values)):
 
@@ -84,7 +84,7 @@ def process_round(self, game_round: pd.DataFrame):
             prob_loss = self.lr.predict_proba(losers.loc[loser][features].values.reshape(-1, 1).T)[0][0]
 
             win_gain, lose_loss = self.update_elo(
-                winner, loser, prob_win/len(winners.index.values), prob_loss/len(winners.index.values)
+                winner, loser, prob_win, prob_loss
             )
 
             elo_gained[winner] += win_gain
@@ -121,14 +121,14 @@ def get_top_10(self) -> pd.DataFrame:
         """
         top = self.elo[self.matches_played > self.min_matches].nlargest(10)
 
-        return convert_uid_index(top.copy(), self.games)
+        return top.copy()
 
     def get_player_elo(self, player_gt: str) -> float:
         """
         :param player_gt: the player to get elo rating for
         :return: the elo rating of the player
         """
-        player_id = self.games[self.games.name == player_gt].uid.unique()[0]
+        player_id = self.games[self.games.name == player_gt].name.unique()[0]
 
         return self.elo.loc[player_id]
 
@@ -159,7 +159,7 @@ def plot_player_elo(self, player_gts: List[str] = None):
         """
         :param player_gts: the list of players to plot for
         """
-        plot_data = convert_uid_index(self.historical_rankings.copy(), self.games).T
+        plot_data = self.historical_rankings.copy().T
 
         if player_gts is not None:
             plot_data[player_gts].plot(figsize=(20, 10))
diff --git a/spreadsheet/webapp.py b/spreadsheet/webapp.py
index b704dec..7d25945 100644
--- a/spreadsheet/webapp.py
+++ b/spreadsheet/webapp.py
@@ -39,10 +39,9 @@ def view_data() -> None:
     """
     @st.cache
     def load_game_data() -> pd.DataFrame:
-        return load_database()
+        return get_game_type(preprocess(load_database()))
 
-    ranked_games = preprocess(load_game_data())
-    ranked_games = get_game_type(ranked_games)
+    ranked_games = load_game_data()
 
     start_date, end_date = st.columns(2)