diff --git a/corpus/README.md b/corpus/README.md
index b1cb4fb..48dce88 100644
--- a/corpus/README.md
+++ b/corpus/README.md
@@ -36,12 +36,14 @@ The model compiler derives each single-byte encoding's case-folding byte map
 through iconv, applies the detector's whitespace normalization, and emits 64
 sorted detector-ready trigrams into `src/encoding/models/generated.ts`. It also
 learns Laplace-smoothed high-byte distributions from the training split. The
-evaluator uses byte likelihood to rank candidates whose trigram hit rates are
-statistically competitive at a 95% margin. `models:evaluate` reports every
-held-out test document, while `models:verify` checks reproducibility and fails if
-any encoding or language result is incorrect. A different encoding label is
-accepted only when both encodings decode the actual held-out bytes identically;
-the report distinguishes these byte-equivalent results from exact matches.
-CP949 is excluded because its
-multibyte recogniser requires character frequency data rather than byte
-trigrams.
+compiler evaluator and library runtime share the normalization, trigram,
+byte-likelihood, confidence, candidate-prefiltering, and tie-breaking
+implementation in `src/encoding/sbcs-scoring.ts`. Candidates whose trigram hit
+rates are statistically competitive at a 95% margin are ranked by byte
+likelihood and deterministic encoding-family preferences. `models:evaluate`
+reports every held-out test document, while `models:verify` checks
+reproducibility and fails if any encoding or language result is incorrect. A
+different encoding label is accepted only when both encodings decode the actual
+held-out bytes identically; the report distinguishes these byte-equivalent
+results from exact matches. CP949 is excluded because its multibyte recogniser
+requires character frequency data rather than byte trigrams.
diff --git a/corpus/model-evaluation.json b/corpus/model-evaluation.json
index 013725c..3021440 100644
--- a/corpus/model-evaluation.json
+++ b/corpus/model-evaluation.json
@@ -1,11 +1,11 @@
 {
   "summary": {
     "tests": 66,
-    "encodingExact": 44,
-    "encodingEquivalent": 22,
+    "encodingExact": 46,
+    "encodingEquivalent": 20,
     "encodingCorrect": 66,
     "languageCorrect": 66,
-    "topScoreTies": 34
+    "topScoreTies": 37
   },
   "confusion": {
     "CP850": {
@@ -21,8 +21,7 @@
       "IBM866": 1
     },
     "ISO-8859-1": {
-      "ISO-8859-1": 8,
-      "ISO-8859-15": 2
+      "ISO-8859-1": 10
     },
     "ISO-8859-10": {
       "ISO-8859-10": 1
@@ -80,8 +79,7 @@
       "windows-1251": 1
     },
     "windows-1252": {
-      "ISO-8859-1": 8,
-      "ISO-8859-15": 2
+      "ISO-8859-1": 10
     },
     "windows-1253": {
       "ISO-8859-7": 1
@@ -116,8 +114,8 @@
       },
       "predicted": {
         "encoding": "CP850",
-        "confidence": 73,
         "language": "de",
+        "confidence": 73,
         "byteLogLikelihood": -3.169712077519,
         "hits": 53,
         "total": 216,
@@ -131,35 +129,35 @@
       "candidates": [
         {
           "encoding": "CP850",
-          "confidence": 73,
           "language": "de",
+          "confidence": 73,
           "byteLogLikelihood": -3.169712077519,
           "hits": 53,
           "total": 216,
           "hitRate": 0.24537037037037038
         },
         {
-          "encoding": "ISO-8859-1",
-          "confidence": 72,
+          "encoding": "windows-1252",
           "language": "de",
+          "confidence": 72,
           "byteLogLikelihood": -5.003946305945,
           "hits": 52,
           "total": 215,
           "hitRate": 0.24186046511627907
         },
         {
-          "encoding": "windows-1252",
-          "confidence": 72,
+          "encoding": "ISO-8859-15",
           "language": "de",
+          "confidence": 72,
           "byteLogLikelihood": -5.003946305945,
           "hits": 52,
           "total": 215,
           "hitRate": 0.24186046511627907
         },
         {
-          "encoding": "ISO-8859-15",
-          "confidence": 72,
+          "encoding": "ISO-8859-1",
           "language": "de",
+          "confidence": 72,
           "byteLogLikelihood": -5.003946305945,
           "hits": 52,
           "total": 215,
@@ -167,8 +165,8 @@
         },
         {
           "encoding": "macintosh",
-          "confidence": 70,
           "language": "de",
+          "confidence": 70,
           "byteLogLikelihood": -5.003946305945,
           "hits": 51,
           "total": 216,
@@ -176,8 +174,8 @@
         },
         {
           "encoding": "ISO-8859-14",
-          "confidence": 22,
           "language": "cy",
+          "confidence": 22,
           "byteLogLikelihood": -4.912654885736,
           "hits": 16,
           "total": 215,
@@ -185,8 +183,8 @@
         },
         {
           "encoding": "ISO-8859-2",
-          "confidence": 13,
           "language": "ro",
+          "confidence": 13,
           "byteLogLikelihood": -5.176149732574,
           "hits": 10,
           "total": 215,
@@ -194,8 +192,8 @@
         },
         {
           "encoding": "ISO-8859-9",
-          "confidence": 13,
           "language": "tr",
+          "confidence": 13,
           "byteLogLikelihood": -5.075173815234,
           "hits": 10,
           "total": 215,
@@ -203,80 +201,26 @@
         },
         {
           "encoding": "windows-1250",
-          "confidence": 13,
           "language": "ro",
-          "byteLogLikelihood": -5.176149732574,
-          "hits": 10,
-          "total": 215,
-          "hitRate": 0.046511627906976744
-        },
-        {
-          "encoding": "windows-1254",
           "confidence": 13,
-          "language": "tr",
-          "byteLogLikelihood": -5.075173815234,
+          "byteLogLikelihood": -5.176149732574,
           "hits": 10,
           "total": 215,
           "hitRate": 0.046511627906976744
         },
         {
           "encoding": "windows-1257",
-          "confidence": 11,
           "language": "lv",
-          "byteLogLikelihood": -5.19295685089,
-          "hits": 8,
-          "total": 215,
-          "hitRate": 0.037209302325581395
-        },
-        {
-          "encoding": "ISO-8859-4",
           "confidence": 11,
-          "language": "lv",
           "byteLogLikelihood": -5.19295685089,
           "hits": 8,
           "total": 215,
           "hitRate": 0.037209302325581395
         },
-        {
-          "encoding": "ISO-8859-16",
-          "confidence": 11,
-          "language": "ro",
-          "byteLogLikelihood": -5.220355825078,
-          "hits": 8,
-          "total": 215,
-          "hitRate": 0.037209302325581395
-        },
-        {
-          "encoding": "windows-1258",
-          "confidence": 6,
-          "language": "vi",
-          "byteLogLikelihood": -5.172849867117,
-          "hits": 5,
-          "total": 215,
-          "hitRate": 0.023255813953488372
-        },
-        {
-          "encoding": "ISO-8859-3",
-          "confidence": 5,
-          "language": "mt",
-          "byteLogLikelihood": -5.105945473901,
-          "hits": 4,
-          "total": 215,
-          "hitRate": 0.018604651162790697
-        },
-        {
-          "encoding": "CP852",
-          "confidence": 5,
-          "language": "pl",
-          "byteLogLikelihood": -5.087596335232,
-          "hits": 4,
-          "total": 216,
-          "hitRate": 0.018518518518518517
-        },
         {
           "encoding": "ISO-8859-10",
-          "confidence": 4,
           "language": "is",
+          "confidence": 4,
           "byteLogLikelihood": -4.97295762689,
           "hits": 3,
           "total": 215,
@@ -284,138 +228,12 @@
         },
         {
           "encoding": "ISO-8859-13",
-          "confidence": 2,
           "language": "lt",
+          "confidence": 2,
           "byteLogLikelihood": -5.00843944931,
           "hits": 2,
           "total": 215,
           "hitRate": 0.009302325581395349
-        },
-        {
-          "encoding": "ISO-8859-5",
-          "confidence": 0,
-          "language": "ru",
-          "byteLogLikelihood": -6.099525732258,
-          "hits": 0,
-          "total": 215,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-6",
-          "confidence": 0,
-          "language": "ar",
-          "byteLogLikelihood": -5.729917997667,
-          "hits": 0,
-          "total": 215,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-7",
-          "confidence": 0,
-          "language": "el",
-          "byteLogLikelihood": -5.542674768484,
-          "hits": 0,
-          "total": 215,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-8",
-          "confidence": 0,
-          "language": "he",
-          "byteLogLikelihood": -5.504753627871,
-          "hits": 0,
-          "total": 215,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-1251",
-          "confidence": 0,
-          "language": "ru",
-          "byteLogLikelihood": -6.219881518497,
-          "hits": 0,
-          "total": 215,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-1253",
-          "confidence": 0,
-          "language": "el",
-          "byteLogLikelihood": -5.542674768484,
-          "hits": 0,
-          "total": 215,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-1255",
-          "confidence": 0,
-          "language": "he",
-          "byteLogLikelihood": -5.504753627871,
-          "hits": 0,
-          "total": 215,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-1256",
-          "confidence": 0,
-          "language": "ar",
-          "byteLogLikelihood": -5.511862527725,
-          "hits": 0,
-          "total": 215,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-874",
-          "confidence": 0,
-          "language": "th",
-          "byteLogLikelihood": -5.737138560752,
-          "hits": 0,
-          "total": 215,
-          "hitRate": 0
-        },
-        {
-          "encoding": "KOI8-R",
-          "confidence": 0,
-          "language": "ru",
-          "byteLogLikelihood": -6.692083742507,
-          "hits": 0,
-          "total": 215,
-          "hitRate": 0
-        },
-        {
-          "encoding": "KOI8-U",
-          "confidence": 0,
-          "language": "uk",
-          "byteLogLikelihood": -6.650279048587,
-          "hits": 0,
-          "total": 215,
-          "hitRate": 0
-        },
-        {
-          "encoding": "IBM866",
-          "confidence": 0,
-          "language": "ru",
-          "byteLogLikelihood": -5.695189876932,
-          "hits": 0,
-          "total": 216,
-          "hitRate": 0
-        },
-        {
-          "encoding": "IBM855",
-          "confidence": 0,
-          "language": "ru",
-          "byteLogLikelihood": -5.428281637736,
-          "hits": 0,
-          "total": 216,
-          "hitRate": 0
-        },
-        {
-          "encoding": "x-mac-cyrillic",
-          "confidence": 0,
-          "language": "uk",
-          "byteLogLikelihood": -5.621314697937,
-          "hits": 0,
-          "total": 216,
-          "hitRate": 0
         }
       ]
     },
@@ -426,8 +244,8 @@
       },
       "predicted": {
         "encoding": "CP850",
-        "confidence": 61,
         "language": "es",
+        "confidence": 61,
         "byteLogLikelihood": -3.834657935767,
         "hits": 41,
         "total": 200,
@@ -441,8 +259,8 @@
       "candidates": [
         {
           "encoding": "CP850",
-          "confidence": 61,
           "language": "es",
+          "confidence": 61,
           "byteLogLikelihood": -3.834657935767,
           "hits": 41,
           "total": 200,
@@ -450,8 +268,8 @@
         },
         {
           "encoding": "ISO-8859-1",
-          "confidence": 58,
           "language": "es",
+          "confidence": 58,
           "byteLogLikelihood": -4.948759890378,
           "hits": 39,
           "total": 199,
@@ -459,8 +277,8 @@
         },
         {
           "encoding": "windows-1252",
-          "confidence": 58,
           "language": "es",
+          "confidence": 58,
           "byteLogLikelihood": -4.948759890378,
           "hits": 39,
           "total": 199,
@@ -468,8 +286,8 @@
         },
         {
           "encoding": "macintosh",
-          "confidence": 58,
           "language": "es",
+          "confidence": 58,
           "byteLogLikelihood": -4.948759890378,
           "hits": 39,
           "total": 199,
@@ -477,8 +295,8 @@
         },
         {
           "encoding": "ISO-8859-15",
-          "confidence": 58,
           "language": "es",
+          "confidence": 58,
           "byteLogLikelihood": -4.948759890378,
           "hits": 39,
           "total": 199,
@@ -486,215 +304,44 @@
         },
         {
           "encoding": "windows-1257",
-          "confidence": 25,
           "language": "lv",
-          "byteLogLikelihood": -5.19295685089,
-          "hits": 17,
-          "total": 199,
-          "hitRate": 0.08542713567839195
-        },
-        {
-          "encoding": "ISO-8859-4",
           "confidence": 25,
-          "language": "lv",
           "byteLogLikelihood": -5.19295685089,
           "hits": 17,
           "total": 199,
           "hitRate": 0.08542713567839195
         },
-        {
-          "encoding": "ISO-8859-13",
-          "confidence": 19,
-          "language": "lt",
-          "byteLogLikelihood": -5.123963979403,
-          "hits": 13,
-          "total": 199,
-          "hitRate": 0.06532663316582915
-        },
         {
           "encoding": "ISO-8859-14",
-          "confidence": 16,
           "language": "cy",
+          "confidence": 16,
           "byteLogLikelihood": -4.912654885736,
           "hits": 11,
           "total": 199,
           "hitRate": 0.05527638190954774
         },
-        {
-          "encoding": "ISO-8859-2",
-          "confidence": 15,
-          "language": "ro",
-          "byteLogLikelihood": -5.176149732574,
-          "hits": 10,
-          "total": 199,
-          "hitRate": 0.05025125628140704
-        },
-        {
-          "encoding": "windows-1250",
-          "confidence": 15,
-          "language": "ro",
-          "byteLogLikelihood": -5.176149732574,
-          "hits": 10,
-          "total": 199,
-          "hitRate": 0.05025125628140704
-        },
         {
           "encoding": "ISO-8859-16",
-          "confidence": 15,
           "language": "ro",
+          "confidence": 15,
           "byteLogLikelihood": -4.952116173006,
           "hits": 10,
           "total": 199,
           "hitRate": 0.05025125628140704
         },
         {
-          "encoding": "ISO-8859-9",
-          "confidence": 7,
-          "language": "tr",
-          "byteLogLikelihood": -5.075173815234,
-          "hits": 5,
+          "encoding": "windows-874",
+          "language": "th",
+          "confidence": 0,
+          "byteLogLikelihood": -4.61627103998,
+          "hits": 0,
           "total": 199,
-          "hitRate": 0.02512562814070352
-        },
-        {
-          "encoding": "windows-1254",
-          "confidence": 7,
-          "language": "tr",
-          "byteLogLikelihood": -5.075173815234,
-          "hits": 5,
-          "total": 199,
-          "hitRate": 0.02512562814070352
-        },
-        {
-          "encoding": "windows-1258",
-          "confidence": 7,
-          "language": "vi",
-          "byteLogLikelihood": -5.497168225293,
-          "hits": 5,
-          "total": 199,
-          "hitRate": 0.02512562814070352
-        },
-        {
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-          "confidence": 7,
-          "language": "pl",
-          "byteLogLikelihood": -5.087596335232,
-          "hits": 5,
-          "total": 200,
-          "hitRate": 0.025
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-        {
-          "encoding": "ISO-8859-10",
-          "confidence": 4,
-          "language": "is",
-          "byteLogLikelihood": -5.204006687077,
-          "hits": 3,
-          "total": 199,
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-          "confidence": 0,
-          "language": "ru",
-          "byteLogLikelihood": -6.692083742507,
-          "hits": 0,
-          "total": 199,
-          "hitRate": 0
-        },
-        {
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-          "confidence": 0,
-          "language": "ar",
-          "byteLogLikelihood": -6.113682179832,
-          "hits": 0,
-          "total": 199,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-7",
-          "confidence": 0,
-          "language": "el",
-          "byteLogLikelihood": -6.120297418951,
-          "hits": 0,
-          "total": 199,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-8",
-          "confidence": 0,
-          "language": "he",
-          "byteLogLikelihood": -5.932245187448,
-          "hits": 0,
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-          "hitRate": 0
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-        {
-          "encoding": "windows-1251",
-          "confidence": 0,
-          "language": "ru",
-          "byteLogLikelihood": -6.692083742507,
-          "hits": 0,
-          "total": 199,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-1253",
-          "confidence": 0,
-          "language": "el",
-          "byteLogLikelihood": -6.120297418951,
-          "hits": 0,
-          "total": 199,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-1255",
-          "confidence": 0,
-          "language": "he",
-          "byteLogLikelihood": -5.932245187448,
-          "hits": 0,
-          "total": 199,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-1256",
-          "confidence": 0,
-          "language": "ar",
-          "byteLogLikelihood": -6.113682179832,
-          "hits": 0,
-          "total": 199,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-874",
-          "confidence": 0,
-          "language": "th",
-          "byteLogLikelihood": -4.61627103998,
-          "hits": 0,
-          "total": 199,
-          "hitRate": 0
-        },
-        {
-          "encoding": "KOI8-R",
-          "confidence": 0,
-          "language": "ru",
-          "byteLogLikelihood": -6.692083742507,
-          "hits": 0,
-          "total": 199,
-          "hitRate": 0
-        },
-        {
-          "encoding": "KOI8-U",
-          "confidence": 0,
-          "language": "uk",
-          "byteLogLikelihood": -6.351652470383,
-          "hits": 0,
-          "total": 199,
-          "hitRate": 0
+          "hitRate": 0
         },
         {
           "encoding": "IBM866",
-          "confidence": 0,
           "language": "ru",
+          "confidence": 0,
           "byteLogLikelihood": -3.374008967132,
           "hits": 0,
           "total": 200,
@@ -702,26 +349,17 @@
         },
         {
           "encoding": "IBM855",
-          "confidence": 0,
           "language": "sr",
+          "confidence": 0,
           "byteLogLikelihood": -4.64715417232,
           "hits": 0,
           "total": 200,
           "hitRate": 0
         },
-        {
-          "encoding": "x-mac-cyrillic",
-          "confidence": 0,
-          "language": "uk",
-          "byteLogLikelihood": -6.650279048587,
-          "hits": 0,
-          "total": 199,
-          "hitRate": 0
-        },
         {
           "encoding": "ISO-8859-3",
-          "confidence": 0,
           "language": "mt",
+          "confidence": 0,
           "byteLogLikelihood": -4.759371883621,
           "hits": 0,
           "total": 199,
@@ -736,8 +374,8 @@
       },
       "predicted": {
         "encoding": "CP850",
-        "confidence": 77,
         "language": "fr",
+        "confidence": 77,
         "byteLogLikelihood": -2.06619631493,
         "hits": 59,
         "total": 228,
@@ -751,35 +389,35 @@
       "candidates": [
         {
           "encoding": "CP850",
-          "confidence": 77,
           "language": "fr",
+          "confidence": 77,
           "byteLogLikelihood": -2.06619631493,
           "hits": 59,
           "total": 228,
           "hitRate": 0.25877192982456143
         },
         {
-          "encoding": "ISO-8859-1",
-          "confidence": 75,
+          "encoding": "windows-1252",
           "language": "fr",
+          "confidence": 75,
           "byteLogLikelihood": -5.010635294096,
           "hits": 56,
           "total": 224,
           "hitRate": 0.25
         },
         {
-          "encoding": "windows-1252",
-          "confidence": 75,
+          "encoding": "ISO-8859-15",
           "language": "fr",
+          "confidence": 75,
           "byteLogLikelihood": -5.010635294096,
           "hits": 56,
           "total": 224,
           "hitRate": 0.25
         },
         {
-          "encoding": "ISO-8859-15",
-          "confidence": 75,
+          "encoding": "ISO-8859-1",
           "language": "fr",
+          "confidence": 75,
           "byteLogLikelihood": -5.010635294096,
           "hits": 56,
           "total": 224,
@@ -787,8 +425,8 @@
         },
         {
           "encoding": "macintosh",
-          "confidence": 71,
           "language": "fr",
+          "confidence": 71,
           "byteLogLikelihood": -5.010635294096,
           "hits": 54,
           "total": 228,
@@ -796,8 +434,8 @@
         },
         {
           "encoding": "ISO-8859-2",
-          "confidence": 12,
           "language": "ro",
+          "confidence": 12,
           "byteLogLikelihood": -5.176149732574,
           "hits": 9,
           "total": 224,
@@ -805,62 +443,26 @@
         },
         {
           "encoding": "windows-1250",
-          "confidence": 12,
           "language": "ro",
-          "byteLogLikelihood": -5.176149732574,
-          "hits": 9,
-          "total": 224,
-          "hitRate": 0.04017857142857143
-        },
-        {
-          "encoding": "ISO-8859-10",
-          "confidence": 12,
-          "language": "is",
-          "byteLogLikelihood": -5.204006687077,
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-          "hitRate": 0.005649717514124294
-        },
-        {
-          "encoding": "ISO-8859-1",
-          "confidence": 0,
-          "language": "sv",
-          "byteLogLikelihood": -4.665227236998,
-          "hits": 0,
-          "total": 177,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-2",
-          "confidence": 0,
-          "language": "cs",
-          "byteLogLikelihood": -4.845647442888,
-          "hits": 0,
-          "total": 177,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-5",
-          "confidence": 0,
-          "language": "ru",
-          "byteLogLikelihood": -4.975257565806,
-          "hits": 0,
-          "total": 175,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-6",
-          "confidence": 0,
-          "language": "ar",
-          "byteLogLikelihood": -4.847464468096,
-          "hits": 0,
-          "total": 127,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-7",
-          "confidence": 0,
-          "language": "el",
-          "byteLogLikelihood": -4.148248171081,
-          "hits": 0,
-          "total": 177,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-9",
-          "confidence": 0,
-          "language": "tr",
-          "byteLogLikelihood": -4.950903003627,
-          "hits": 0,
-          "total": 177,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-1250",
-          "confidence": 0,
-          "language": "cs",
-          "byteLogLikelihood": -4.845647442888,
-          "hits": 0,
-          "total": 177,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-1252",
-          "confidence": 0,
-          "language": "sv",
-          "byteLogLikelihood": -4.665227236998,
-          "hits": 0,
-          "total": 177,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-1253",
-          "confidence": 0,
-          "language": "el",
-          "byteLogLikelihood": -4.148248171081,
-          "hits": 0,
-          "total": 177,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-1254",
-          "confidence": 0,
-          "language": "tr",
-          "byteLogLikelihood": -4.950903003627,
-          "hits": 0,
-          "total": 177,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-1257",
-          "confidence": 0,
-          "language": "lv",
-          "byteLogLikelihood": -4.61521723683,
-          "hits": 0,
-          "total": 177,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-1258",
-          "confidence": 0,
-          "language": "vi",
-          "byteLogLikelihood": -4.899487478125,
-          "hits": 0,
-          "total": 173,
-          "hitRate": 0
+          "byteLogLikelihood": -3.941595102268,
+          "hits": 2,
+          "total": 167,
+          "hitRate": 0.011976047904191617
         },
         {
-          "encoding": "windows-874",
-          "confidence": 0,
-          "language": "th",
-          "byteLogLikelihood": -5.446015416921,
-          "hits": 0,
-          "total": 85,
-          "hitRate": 0
+          "encoding": "ISO-8859-14",
+          "language": "cy",
+          "confidence": 1,
+          "byteLogLikelihood": -4.724449359889,
+          "hits": 1,
+          "total": 177,
+          "hitRate": 0.005649717514124294
         },
         {
-          "encoding": "IBM866",
+          "encoding": "ISO-8859-1",
+          "language": "sv",
           "confidence": 0,
-          "language": "ru",
-          "byteLogLikelihood": -5.05026366488,
+          "byteLogLikelihood": -4.665227236998,
           "hits": 0,
-          "total": 169,
+          "total": 177,
           "hitRate": 0
         },
         {
-          "encoding": "macintosh",
+          "encoding": "ISO-8859-7",
+          "language": "el",
           "confidence": 0,
-          "language": "es",
-          "byteLogLikelihood": -4.944169511699,
+          "byteLogLikelihood": -4.148248171081,
           "hits": 0,
-          "total": 151,
+          "total": 177,
           "hitRate": 0
         },
         {
-          "encoding": "ISO-8859-3",
+          "encoding": "windows-1252",
+          "language": "sv",
           "confidence": 0,
-          "language": "mt",
-          "byteLogLikelihood": -4.904224209153,
+          "byteLogLikelihood": -4.665227236998,
           "hits": 0,
-          "total": 175,
+          "total": 177,
           "hitRate": 0
         },
         {
-          "encoding": "ISO-8859-4",
+          "encoding": "windows-1253",
+          "language": "el",
           "confidence": 0,
-          "language": "lv",
-          "byteLogLikelihood": -4.79659105312,
+          "byteLogLikelihood": -4.148248171081,
           "hits": 0,
           "total": 177,
           "hitRate": 0
         },
         {
-          "encoding": "ISO-8859-10",
+          "encoding": "windows-1257",
+          "language": "lv",
           "confidence": 0,
-          "language": "is",
-          "byteLogLikelihood": -4.939249573759,
+          "byteLogLikelihood": -4.61521723683,
           "hits": 0,
           "total": 177,
           "hitRate": 0
         },
         {
           "encoding": "ISO-8859-13",
-          "confidence": 0,
           "language": "lt",
+          "confidence": 0,
           "byteLogLikelihood": -4.66408545306,
           "hits": 0,
           "total": 177,
@@ -20223,39 +8548,12 @@
         },
         {
           "encoding": "ISO-8859-15",
-          "confidence": 0,
           "language": "fr",
-          "byteLogLikelihood": -4.760478683076,
-          "hits": 0,
-          "total": 177,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-16",
           "confidence": 0,
-          "language": "ro",
-          "byteLogLikelihood": -4.97522262578,
+          "byteLogLikelihood": -4.760478683076,
           "hits": 0,
           "total": 177,
           "hitRate": 0
-        },
-        {
-          "encoding": "CP850",
-          "confidence": 0,
-          "language": "es",
-          "byteLogLikelihood": -4.948759890378,
-          "hits": 0,
-          "total": 137,
-          "hitRate": 0
-        },
-        {
-          "encoding": "CP852",
-          "confidence": 0,
-          "language": "pl",
-          "byteLogLikelihood": -5.083005956553,
-          "hits": 0,
-          "total": 156,
-          "hitRate": 0
         }
       ]
     },
@@ -20266,8 +8564,8 @@
       },
       "predicted": {
         "encoding": "x-mac-cyrillic",
-        "confidence": 32,
         "language": "uk",
+        "confidence": 32,
         "byteLogLikelihood": -3.34369756932,
         "hits": 19,
         "total": 177,
@@ -20281,8 +8579,8 @@
       "candidates": [
         {
           "encoding": "x-mac-cyrillic",
-          "confidence": 32,
           "language": "uk",
+          "confidence": 32,
           "byteLogLikelihood": -3.34369756932,
           "hits": 19,
           "total": 177,
@@ -20290,26 +8588,17 @@
         },
         {
           "encoding": "windows-1251",
-          "confidence": 17,
           "language": "ru",
+          "confidence": 17,
           "byteLogLikelihood": -3.606822645813,
           "hits": 10,
           "total": 176,
           "hitRate": 0.056818181818181816
         },
-        {
-          "encoding": "IBM855",
-          "confidence": 5,
-          "language": "sr",
-          "byteLogLikelihood": -5.830774318921,
-          "hits": 3,
-          "total": 163,
-          "hitRate": 0.018404907975460124
-        },
         {
           "encoding": "ISO-8859-8",
-          "confidence": 3,
           "language": "he",
+          "confidence": 3,
           "byteLogLikelihood": -4.062591421695,
           "hits": 2,
           "total": 165,
@@ -20317,98 +8606,35 @@
         },
         {
           "encoding": "windows-1255",
-          "confidence": 3,
           "language": "he",
+          "confidence": 3,
           "byteLogLikelihood": -4.062591421695,
           "hits": 2,
           "total": 165,
           "hitRate": 0.012121212121212121
         },
-        {
-          "encoding": "KOI8-R",
-          "confidence": 3,
-          "language": "ru",
-          "byteLogLikelihood": -6.397907632883,
-          "hits": 2,
-          "total": 169,
-          "hitRate": 0.011834319526627219
-        },
-        {
-          "encoding": "ISO-8859-6",
-          "confidence": 2,
-          "language": "ar",
-          "byteLogLikelihood": -4.990380473945,
-          "hits": 1,
-          "total": 119,
-          "hitRate": 0.008403361344537815
-        },
-        {
-          "encoding": "KOI8-U",
-          "confidence": 1,
-          "language": "uk",
-          "byteLogLikelihood": -6.341901231006,
-          "hits": 1,
-          "total": 175,
-          "hitRate": 0.005714285714285714
-        },
         {
           "encoding": "ISO-8859-1",
-          "confidence": 0,
           "language": "it",
-          "byteLogLikelihood": -4.629500955096,
-          "hits": 0,
-          "total": 169,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-2",
           "confidence": 0,
-          "language": "cs",
-          "byteLogLikelihood": -4.739775351774,
+          "byteLogLikelihood": -4.629500955096,
           "hits": 0,
           "total": 169,
           "hitRate": 0
         },
-        {
-          "encoding": "ISO-8859-5",
-          "confidence": 0,
-          "language": "ru",
-          "byteLogLikelihood": -4.989983227843,
-          "hits": 0,
-          "total": 171,
-          "hitRate": 0
-        },
         {
           "encoding": "ISO-8859-7",
-          "confidence": 0,
           "language": "el",
-          "byteLogLikelihood": -4.300043808736,
-          "hits": 0,
-          "total": 169,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-9",
           "confidence": 0,
-          "language": "tr",
-          "byteLogLikelihood": -4.951345660734,
+          "byteLogLikelihood": -4.300043808736,
           "hits": 0,
           "total": 169,
           "hitRate": 0
         },
-        {
-          "encoding": "windows-1250",
-          "confidence": 0,
-          "language": "cs",
-          "byteLogLikelihood": -4.739775351774,
-          "hits": 0,
-          "total": 170,
-          "hitRate": 0
-        },
         {
           "encoding": "windows-1252",
-          "confidence": 0,
           "language": "it",
+          "confidence": 0,
           "byteLogLikelihood": -4.629500955096,
           "hits": 0,
           "total": 170,
@@ -20416,107 +8642,35 @@
         },
         {
           "encoding": "windows-1253",
-          "confidence": 0,
           "language": "el",
+          "confidence": 0,
           "byteLogLikelihood": -4.300043808736,
           "hits": 0,
           "total": 169,
           "hitRate": 0
         },
-        {
-          "encoding": "windows-1254",
-          "confidence": 0,
-          "language": "tr",
-          "byteLogLikelihood": -4.951345660734,
-          "hits": 0,
-          "total": 170,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-1256",
-          "confidence": 0,
-          "language": "ar",
-          "byteLogLikelihood": -5.607550779971,
-          "hits": 0,
-          "total": 155,
-          "hitRate": 0
-        },
         {
           "encoding": "windows-1257",
-          "confidence": 0,
           "language": "lv",
+          "confidence": 0,
           "byteLogLikelihood": -4.60874799529,
           "hits": 0,
           "total": 169,
           "hitRate": 0
         },
-        {
-          "encoding": "windows-1258",
-          "confidence": 0,
-          "language": "vi",
-          "byteLogLikelihood": -4.777030248466,
-          "hits": 0,
-          "total": 164,
-          "hitRate": 0
-        },
-        {
-          "encoding": "windows-874",
-          "confidence": 0,
-          "language": "th",
-          "byteLogLikelihood": -5.197321748228,
-          "hits": 0,
-          "total": 83,
-          "hitRate": 0
-        },
-        {
-          "encoding": "IBM866",
-          "confidence": 0,
-          "language": "ru",
-          "byteLogLikelihood": -5.100977296295,
-          "hits": 0,
-          "total": 167,
-          "hitRate": 0
-        },
-        {
-          "encoding": "macintosh",
-          "confidence": 0,
-          "language": "es",
-          "byteLogLikelihood": -4.948759890378,
-          "hits": 0,
-          "total": 139,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-3",
-          "confidence": 0,
-          "language": "mt",
-          "byteLogLikelihood": -5.035218126431,
-          "hits": 0,
-          "total": 164,
-          "hitRate": 0
-        },
         {
           "encoding": "ISO-8859-4",
-          "confidence": 0,
           "language": "lv",
+          "confidence": 0,
           "byteLogLikelihood": -4.726279355538,
           "hits": 0,
           "total": 169,
           "hitRate": 0
         },
-        {
-          "encoding": "ISO-8859-10",
-          "confidence": 0,
-          "language": "is",
-          "byteLogLikelihood": -4.876716873437,
-          "hits": 0,
-          "total": 175,
-          "hitRate": 0
-        },
         {
           "encoding": "ISO-8859-13",
-          "confidence": 0,
           "language": "lt",
+          "confidence": 0,
           "byteLogLikelihood": -4.669220995205,
           "hits": 0,
           "total": 169,
@@ -20524,48 +8678,12 @@
         },
         {
           "encoding": "ISO-8859-14",
-          "confidence": 0,
           "language": "cy",
-          "byteLogLikelihood": -4.725687554138,
-          "hits": 0,
-          "total": 175,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-15",
-          "confidence": 0,
-          "language": "fr",
-          "byteLogLikelihood": -4.753004092615,
-          "hits": 0,
-          "total": 175,
-          "hitRate": 0
-        },
-        {
-          "encoding": "ISO-8859-16",
           "confidence": 0,
-          "language": "ro",
-          "byteLogLikelihood": -5.030920483462,
+          "byteLogLikelihood": -4.725687554138,
           "hits": 0,
           "total": 175,
           "hitRate": 0
-        },
-        {
-          "encoding": "CP850",
-          "confidence": 0,
-          "language": "es",
-          "byteLogLikelihood": -4.948759890378,
-          "hits": 0,
-          "total": 137,
-          "hitRate": 0
-        },
-        {
-          "encoding": "CP852",
-          "confidence": 0,
-          "language": "pl",
-          "byteLogLikelihood": -5.087596335232,
-          "hits": 0,
-          "total": 152,
-          "hitRate": 0
         }
       ]
     }
diff --git a/package.json b/package.json
index a3e54c5..1cb77cb 100644
--- a/package.json
+++ b/package.json
@@ -16,9 +16,9 @@
     "build": "rm -rf lib/* && tsc -p tsconfig.build.json",
     "corpus:build": "node scripts/build-corpus.mjs",
     "corpus:verify": "node scripts/verify-corpus.mjs",
-    "models:build": "node scripts/build-models.mjs",
-    "models:evaluate": "node scripts/evaluate-models.mjs",
-    "models:verify": "node scripts/verify-models.mjs",
+    "models:build": "tsx scripts/build-models.mjs",
+    "models:evaluate": "tsx scripts/evaluate-models.mjs",
+    "models:verify": "tsx scripts/verify-models.mjs",
     "benchmark": "tsx scripts/benchmark.mjs",
     "validate": "tsx scripts/validate.mjs",
     "format": "prettier --write \"**/*.{ts,json,md,mjs}\"",
diff --git a/scripts/model-utils.mjs b/scripts/model-utils.mjs
index f9e9f15..e068aa9 100644
--- a/scripts/model-utils.mjs
+++ b/scripts/model-utils.mjs
@@ -2,6 +2,11 @@ import { spawnSync } from 'node:child_process';
 import { mkdirSync, readFileSync, writeFileSync } from 'node:fs';
 import { dirname, join, resolve } from 'node:path';
 import { fileURLToPath } from 'node:url';
+import {
+  prepareSBCSModels,
+  scoreSBCS,
+  trigrams,
+} from '../src/encoding/sbcs-scoring.ts';
 
 const root = resolve(dirname(fileURLToPath(import.meta.url)), '..');
 const corpus = join(root, 'corpus');
@@ -90,30 +95,6 @@ function byteMapFor(encoding) {
   return byteMap;
 }
 
-function normalizedBytes(buffer, byteMap) {
-  const normalized = [];
-  let ignoreSpace = false;
-  for (const byte of buffer) {
-    const mapped = byteMap[byte];
-    if (mapped !== 0) {
-      if (!(mapped === 0x20 && ignoreSpace)) normalized.push(mapped);
-      ignoreSpace = mapped === 0x20;
-    }
-  }
-  normalized.push(0x20);
-  return normalized;
-}
-
-function trigrams(buffer, byteMap) {
-  const values = [];
-  let trigram = 0;
-  for (const byte of normalizedBytes(buffer, byteMap)) {
-    trigram = ((trigram << 8) + byte) & 0xffffff;
-    values.push(trigram);
-  }
-  return values;
-}
-
 function detectorNgrams(buffers, byteMap) {
   const counts = new Map();
   for (const buffer of buffers) {
@@ -160,43 +141,6 @@ function highByteDistribution(buffers) {
   };
 }
 
-function byteLogLikelihood(buffer, distribution) {
-  const counts = new Map(distribution.counts);
-  const denominator = distribution.total + 128;
-  let highBytes = 0;
-  let likelihood = 0;
-  for (const byte of buffer) {
-    if (byte >= 0x80) {
-      likelihood += Math.log(((counts.get(byte) ?? 0) + 1) / denominator);
-      highBytes += 1;
-    }
-  }
-  return highBytes === 0
-    ? Number.NEGATIVE_INFINITY
-    : Number((likelihood / highBytes).toFixed(12));
-}
-
-function ngramScore(buffer, byteMap, modelNgrams) {
-  const known = new Set(modelNgrams);
-  const values = trigrams(buffer, byteMap);
-  const hits = values.filter((trigram) => known.has(trigram)).length;
-  const rawPercent = hits / values.length;
-  return {
-    confidence: rawPercent > 0.33 ? 98 : Math.floor(rawPercent * 300),
-    hits,
-    total: values.length,
-    hitRate: rawPercent,
-  };
-}
-
-function statisticallyCompetitive(best, candidate) {
-  const variance =
-    (best.hitRate * (1 - best.hitRate)) / best.total +
-    (candidate.hitRate * (1 - candidate.hitRate)) / candidate.total;
-  const margin = 1.96 * Math.sqrt(variance);
-  return best.hitRate - candidate.hitRate <= margin;
-}
-
 function decodedText(buffer, encodingName) {
   const encoding = manifest.encodings.find(
     (candidate) => candidate.name === encodingName,
@@ -215,21 +159,6 @@ function byteEquivalent(buffer, leftEncoding, rightEncoding) {
   }
 }
 
-const equivalentEncodingFamilies = [
-  ['ISO-8859-1', 'ISO-8859-15', 'windows-1252'],
-  ['ISO-8859-2', 'windows-1250'],
-  ['ISO-8859-7', 'windows-1253'],
-  ['ISO-8859-8', 'windows-1255'],
-  ['ISO-8859-9', 'windows-1254'],
-  ['ISO-8859-13', 'windows-1257'],
-];
-
-function encodingFamily(name) {
-  return (
-    equivalentEncodingFamilies.find((family) => family.includes(name)) ?? [name]
-  );
-}
-
 function compileSingleByteModels() {
   const models = [];
   for (const encoding of manifest.encodings) {
@@ -262,78 +191,14 @@ function compileSingleByteModels() {
 }
 
 function evaluate(models) {
+  const preparedModels = prepareSBCSModels(models);
   const tests = corpusIndex.filter(
     (row) => row.split === 'test' && row.encoding !== 'CP949',
   );
   const results = tests.map((test) => {
     const buffer = readFileSync(join(generatedCorpus, test.path));
-    const candidates = models.map((model) => {
-      const languageScores = model.languages.map((language) => ({
-        language: language.language,
-        ...ngramScore(buffer, model.byteMap, language.ngrams),
-        byteLogLikelihood: byteLogLikelihood(buffer, language.highBytes),
-      }));
-      const confidenceScore = Math.max(
-        ...languageScores.map((score) => score.confidence),
-      );
-      const confidenceLanguages = languageScores.filter(
-        (score) => score.confidence === confidenceScore,
-      );
-      confidenceLanguages.sort(
-        (left, right) => right.byteLogLikelihood - left.byteLogLikelihood,
-      );
-      const confidenceLanguage = confidenceLanguages[0];
-      return {
-        encoding: model.encoding,
-        confidence: confidenceScore,
-        language: confidenceLanguage.language,
-        byteLogLikelihood: confidenceLanguage.byteLogLikelihood,
-        hits: confidenceLanguage.hits,
-        total: confidenceLanguage.total,
-        hitRate: confidenceLanguage.hitRate,
-      };
-    });
-    candidates.sort((left, right) => right.confidence - left.confidence);
-    const strongest = candidates[0];
-    const competitive = candidates.filter((candidate) =>
-      statisticallyCompetitive(strongest, candidate),
-    );
-    const competitiveEncodings = new Set(
-      competitive.map((candidate) => candidate.encoding),
-    );
-    competitive.sort(
-      (left, right) =>
-        right.byteLogLikelihood - left.byteLogLikelihood ||
-        right.confidence - left.confidence,
-    );
-    const remaining = candidates.filter(
-      (candidate) => !competitiveEncodings.has(candidate.encoding),
-    );
-    candidates.splice(0, candidates.length, ...competitive, ...remaining);
-    const strongestPrediction = candidates[0];
-    const strongestFamily = encodingFamily(strongestPrediction.encoding);
-    const equivalentLanguageCandidates = candidates.filter(
-      (candidate) =>
-        strongestFamily.includes(candidate.encoding) &&
-        byteEquivalent(
-          buffer,
-          strongestPrediction.encoding,
-          candidate.encoding,
-        ),
-    );
-    equivalentLanguageCandidates.sort(
-      (left, right) =>
-        manifest.encodings.findIndex(
-          (encoding) => encoding.name === left.encoding,
-        ) -
-        manifest.encodings.findIndex(
-          (encoding) => encoding.name === right.encoding,
-        ),
-    );
-    const predicted = {
-      ...strongestPrediction,
-      language: equivalentLanguageCandidates[0].language,
-    };
+    const candidates = scoreSBCS(buffer, preparedModels);
+    const predicted = candidates[0];
     const encodingExact = predicted.encoding === test.encoding;
     const encodingEquivalent =
       !encodingExact &&
diff --git a/src/encoding/sbcs-scoring.test.ts b/src/encoding/sbcs-scoring.test.ts
new file mode 100644
index 0000000..a509527
--- /dev/null
+++ b/src/encoding/sbcs-scoring.test.ts
@@ -0,0 +1,78 @@
+import fs from 'fs';
+import path from 'path';
+import { describe, expect, it } from 'vitest';
+import type { Context } from '.';
+import { generatedSBCSModels } from './models/generated';
+import type { GeneratedSBCSModel } from './models/types';
+import { analyseGeneratedSBCS } from './sbcs';
+import { prepareSBCSModels, scoreSBCS, trigrams } from './sbcs-scoring';
+
+const preparedModels = prepareSBCSModels(
+  generatedSBCSModels as readonly GeneratedSBCSModel[],
+);
+
+function context(input: Uint8Array): Context {
+  const byteStats = Array<number>(256).fill(0);
+  for (const byte of input) byteStats[byte] += 1;
+  return {
+    byteStats,
+    c1Bytes: input.some((byte) => byte >= 0x80 && byte <= 0x9f),
+    rawInput: input,
+    rawLen: input.length,
+    inputBytes: input,
+    inputLen: input.length,
+  };
+}
+
+describe('shared SBCS scoring', () => {
+  it('normalizes ignored bytes and repeated spaces before scoring trigrams', () => {
+    const byteMap = Array.from({ length: 256 }, (_, byte) => byte);
+    byteMap[0x27] = 0;
+
+    expect(
+      trigrams(new Uint8Array([0x41, 0x20, 0x20, 0x27, 0x42]), byteMap),
+    ).toEqual([0x41, 0x4120, 0x412042, 0x204220]);
+  });
+
+  it.each([
+    new Uint8Array(),
+    new Uint8Array([0x41]),
+    new Uint8Array([0xff]),
+    new Uint8Array([0xc3]),
+    new Uint8Array([0x00, 0xff, 0x80, 0x00]),
+  ])('returns deterministic finite confidence scores for %j', (input) => {
+    const first = scoreSBCS(input, preparedModels);
+    const second = scoreSBCS(input, preparedModels);
+
+    expect(second).toEqual(first);
+    expect(first.length).toBeGreaterThan(0);
+    expect(
+      first.every(
+        ({ confidence }) =>
+          Number.isFinite(confidence) && confidence >= 0 && confidence <= 100,
+      ),
+    ).toBe(true);
+  });
+
+  it('keeps the runtime wrapper aligned with the shared scorer on the corpus', () => {
+    const corpusRoot = path.join(__dirname, '../../corpus/generated');
+    const corpusIndex = JSON.parse(
+      fs.readFileSync(path.join(corpusRoot, 'index.json'), 'utf8'),
+    ) as { encoding: string; path: string }[];
+    const rows = corpusIndex.filter(({ encoding }) => encoding !== 'CP949');
+
+    for (const row of rows) {
+      const input = fs.readFileSync(path.join(corpusRoot, row.path));
+      const raw = scoreSBCS(input, preparedModels).find(
+        ({ confidence }) => confidence > 0,
+      );
+      const runtime = analyseGeneratedSBCS(context(input))[0];
+
+      expect(runtime, row.path).toEqual({
+        name: raw?.encoding,
+        lang: raw?.language,
+        confidence: raw ? raw.confidence / 100 : undefined,
+      });
+    }
+  });
+});
diff --git a/src/encoding/sbcs-scoring.ts b/src/encoding/sbcs-scoring.ts
new file mode 100644
index 0000000..d192928
--- /dev/null
+++ b/src/encoding/sbcs-scoring.ts
@@ -0,0 +1,304 @@
+import type { EncodingName } from '../match';
+import type {
+  GeneratedSBCSLanguage,
+  GeneratedSBCSModel,
+  HighByteDistribution,
+} from './models/types';
+
+const N_GRAM_MASK = 0xffffff;
+// Byte distributions are cheap and sufficiently discriminative to exclude
+// most encodings before the more expensive n-gram pass. The corpus needs 11
+// candidates to preserve full-result accuracy; keep one additional candidate
+// as headroom for unseen inputs.
+const MAX_SBCS_CANDIDATES = 12;
+
+export interface SBCSScore {
+  readonly confidence: number;
+  readonly hitRate: number;
+  readonly hits: number;
+  readonly total: number;
+}
+
+export interface SBCSCandidate extends SBCSScore {
+  readonly encoding: EncodingName;
+  readonly language: string;
+  readonly byteLogLikelihood: number;
+}
+
+interface RankedSBCSCandidate extends SBCSCandidate {
+  readonly modelIndex: number;
+}
+
+interface PreparedSBCSLanguage {
+  readonly model: GeneratedSBCSLanguage;
+  readonly highByteLogProbabilities: Float64Array;
+}
+
+export interface PreparedSBCSModel {
+  readonly model: GeneratedSBCSModel;
+  readonly modelIndex: number;
+  readonly languages: readonly PreparedSBCSLanguage[];
+  readonly ngramLanguageIndexes: ReadonlyMap<number, readonly number[]>;
+}
+
+type HighByteCounts = readonly (readonly [number, number])[];
+
+const equivalentEncodingFamilies = [
+  ['ISO-8859-1', 'ISO-8859-15', 'windows-1252'],
+  ['ISO-8859-2', 'windows-1250'],
+  ['ISO-8859-7', 'windows-1253'],
+  ['ISO-8859-8', 'windows-1255'],
+  ['ISO-8859-9', 'windows-1254'],
+  ['ISO-8859-13', 'windows-1257'],
+] as const;
+
+function scanTrigrams(
+  input: Uint8Array,
+  byteMap: readonly number[],
+  record: (value: number) => void,
+): number {
+  let ignoreSpace = false;
+  let ngram = 0;
+  let total = 0;
+
+  const append = (mapped: number) => {
+    ngram = ((ngram << 8) + mapped) & N_GRAM_MASK;
+    total += 1;
+    record(ngram);
+  };
+
+  for (const byte of input) {
+    const mapped = byteMap[byte];
+    if (mapped !== 0) {
+      if (!(mapped === 0x20 && ignoreSpace)) append(mapped);
+      ignoreSpace = mapped === 0x20;
+    }
+  }
+
+  append(0x20);
+  return total;
+}
+
+export function trigrams(
+  input: Uint8Array,
+  byteMap: readonly number[],
+): number[] {
+  const values: number[] = [];
+  scanTrigrams(input, byteMap, (value) => values.push(value));
+  return values;
+}
+
+export function statisticallyCompetitive(
+  best: SBCSScore,
+  candidate: SBCSScore,
+): boolean {
+  const variance =
+    (best.hitRate * (1 - best.hitRate)) / best.total +
+    (candidate.hitRate * (1 - candidate.hitRate)) / candidate.total;
+  return best.hitRate - candidate.hitRate <= 1.96 * Math.sqrt(variance);
+}
+
+function highByteCounts(input: Uint8Array): HighByteCounts {
+  const counts = new Uint32Array(128);
+  for (const byte of input) {
+    if (byte >= 0x80) counts[byte - 0x80] += 1;
+  }
+
+  const result: [number, number][] = [];
+  counts.forEach((count, index) => {
+    if (count > 0) result.push([index + 0x80, count]);
+  });
+  return result;
+}
+
+function highByteLogProbabilities(distribution: HighByteDistribution) {
+  const counts = new Map(distribution.counts);
+  const denominator = distribution.total + 128;
+  return Float64Array.from({ length: 128 }, (_, index) =>
+    Math.log(((counts.get(index + 0x80) ?? 0) + 1) / denominator),
+  );
+}
+
+function ngramLanguageIndexes(model: GeneratedSBCSModel) {
+  const indexes = new Map<number, number[]>();
+  model.languages.forEach((language, languageIndex) => {
+    for (const ngram of new Set(language.ngrams)) {
+      const languageIndexes = indexes.get(ngram) ?? [];
+      languageIndexes.push(languageIndex);
+      indexes.set(ngram, languageIndexes);
+    }
+  });
+  return indexes;
+}
+
+export function prepareSBCSModels(
+  models: readonly GeneratedSBCSModel[],
+): readonly PreparedSBCSModel[] {
+  return models.map((model, modelIndex) => ({
+    model,
+    modelIndex,
+    languages: model.languages.map((language) => ({
+      model: language,
+      highByteLogProbabilities: highByteLogProbabilities(language.highBytes),
+    })),
+    ngramLanguageIndexes: ngramLanguageIndexes(model),
+  }));
+}
+
+function byteLogLikelihood(
+  counts: HighByteCounts,
+  logProbabilities: Float64Array,
+) {
+  let highBytes = 0;
+  let likelihood = 0;
+
+  for (const [byte, count] of counts) {
+    likelihood += logProbabilities[byte - 0x80] * count;
+    highBytes += count;
+  }
+
+  return highBytes === 0
+    ? Number.NEGATIVE_INFINITY
+    : Number((likelihood / highBytes).toFixed(12));
+}
+
+function modelByteLogLikelihood(
+  counts: HighByteCounts,
+  prepared: PreparedSBCSModel,
+) {
+  let best = Number.NEGATIVE_INFINITY;
+  for (const language of prepared.languages) {
+    best = Math.max(
+      best,
+      byteLogLikelihood(counts, language.highByteLogProbabilities),
+    );
+  }
+  return best;
+}
+
+function candidate(
+  input: Uint8Array,
+  counts: HighByteCounts,
+  prepared: PreparedSBCSModel,
+  hits: Uint32Array,
+): RankedSBCSCandidate {
+  hits.fill(0, 0, prepared.languages.length);
+  const total = scanTrigrams(input, prepared.model.byteMap, (value) => {
+    for (const languageIndex of prepared.ngramLanguageIndexes.get(value) ??
+      []) {
+      hits[languageIndex] += 1;
+    }
+  });
+
+  let bestIndex = 0;
+  let bestConfidence = -1;
+  let bestByteLogLikelihood = Number.NEGATIVE_INFINITY;
+  let bestHitRate = 0;
+
+  for (let index = 0; index < prepared.languages.length; index += 1) {
+    const hitRate = hits[index] / total;
+    const confidence = hitRate > 0.33 ? 98 : Math.floor(hitRate * 300);
+    const likelihood = byteLogLikelihood(
+      counts,
+      prepared.languages[index].highByteLogProbabilities,
+    );
+    if (
+      confidence > bestConfidence ||
+      (confidence === bestConfidence && likelihood > bestByteLogLikelihood)
+    ) {
+      bestIndex = index;
+      bestConfidence = confidence;
+      bestByteLogLikelihood = likelihood;
+      bestHitRate = hitRate;
+    }
+  }
+
+  return {
+    encoding: prepared.model.encoding,
+    language: prepared.languages[bestIndex].model.language,
+    confidence: bestConfidence,
+    byteLogLikelihood: bestByteLogLikelihood,
+    hits: hits[bestIndex],
+    total,
+    hitRate: bestHitRate,
+    modelIndex: prepared.modelIndex,
+  };
+}
+
+function family(name: EncodingName) {
+  return equivalentEncodingFamilies.find((value) =>
+    value.includes(name as never),
+  );
+}
+
+function familyPreference(
+  left: SBCSCandidate,
+  right: SBCSCandidate,
+  c1Bytes: boolean,
+) {
+  const leftFamily = family(left.encoding);
+  if (!leftFamily || leftFamily !== family(right.encoding)) return 0;
+  const preferred =
+    leftFamily[0] === 'ISO-8859-13' || c1Bytes
+      ? [...leftFamily].reverse()
+      : [...leftFamily];
+  return (
+    preferred.indexOf(left.encoding as never) -
+    preferred.indexOf(right.encoding as never)
+  );
+}
+
+export function scoreSBCS(
+  input: Uint8Array,
+  preparedModels: readonly PreparedSBCSModel[],
+  c1Bytes = input.some((byte) => byte >= 0x80 && byte <= 0x9f),
+): SBCSCandidate[] {
+  if (preparedModels.length === 0) return [];
+
+  const counts = highByteCounts(input);
+  const hits = new Uint32Array(
+    Math.max(...preparedModels.map((model) => model.languages.length)),
+  );
+  const models =
+    counts.length === 0
+      ? preparedModels
+      : preparedModels
+          .map((model) => ({
+            model,
+            likelihood: modelByteLogLikelihood(counts, model),
+          }))
+          .sort(
+            (left, right) =>
+              right.likelihood - left.likelihood ||
+              left.model.modelIndex - right.model.modelIndex,
+          )
+          .slice(0, MAX_SBCS_CANDIDATES)
+          .map(({ model }) => model);
+  const candidates = models.map((model) =>
+    candidate(input, counts, model, hits),
+  );
+  candidates.sort(
+    (left, right) =>
+      right.confidence - left.confidence || left.modelIndex - right.modelIndex,
+  );
+
+  const strongest = candidates[0];
+  const competitive = candidates.filter((value) =>
+    statisticallyCompetitive(strongest, value),
+  );
+  const competitiveNames = new Set(competitive.map((value) => value.encoding));
+  competitive.sort(
+    (left, right) =>
+      familyPreference(left, right, c1Bytes) ||
+      right.byteLogLikelihood - left.byteLogLikelihood ||
+      right.confidence - left.confidence ||
+      left.modelIndex - right.modelIndex,
+  );
+  const remaining = candidates.filter(
+    (value) => !competitiveNames.has(value.encoding),
+  );
+
+  return [...competitive, ...remaining].map(
+    ({ modelIndex: _modelIndex, ...value }) => value,
+  );
+}
diff --git a/src/encoding/sbcs.ts b/src/encoding/sbcs.ts
index 3e79e99..bc45362 100644
--- a/src/encoding/sbcs.ts
+++ b/src/encoding/sbcs.ts
@@ -1,267 +1,23 @@
 import type { Match } from '../match';
 import type { Context } from '.';
 import { generatedSBCSModels } from './models/generated';
-import type {
-  GeneratedSBCSLanguage,
-  GeneratedSBCSModel,
-  HighByteDistribution,
-} from './models/types';
+import type { GeneratedSBCSModel } from './models/types';
+import { prepareSBCSModels, scoreSBCS } from './sbcs-scoring';
 
-const N_GRAM_MASK = 0xffffff;
-// Byte distributions are cheap and sufficiently discriminative to exclude
-// most encodings before the more expensive n-gram pass. The corpus needs 11
-// candidates to preserve full-result accuracy; keep one additional candidate
-// as headroom for unseen inputs.
-const MAX_SBCS_CANDIDATES = 12;
-
-interface Score {
-  confidence: number;
-  hitRate: number;
-  hits: number;
-  total: number;
-}
-
-interface Candidate extends Match, Score {
-  byteLogLikelihood: number;
-}
-
-interface PreparedSBCSLanguage {
-  readonly model: GeneratedSBCSLanguage;
-  readonly highByteLogProbabilities: Float64Array;
-}
-
-interface PreparedSBCSModel {
-  readonly model: GeneratedSBCSModel;
-  readonly languages: readonly PreparedSBCSLanguage[];
-  readonly ngramLanguageMasks: ReadonlyMap<number, number>;
-}
-
-type HighByteCounts = readonly (readonly [number, number])[];
-
-function highByteLogProbabilities(distribution: HighByteDistribution) {
-  const counts = new Map(distribution.counts);
-  const denominator = distribution.total + 128;
-  return Float64Array.from({ length: 128 }, (_, index) =>
-    Math.log(((counts.get(index + 0x80) ?? 0) + 1) / denominator),
-  );
-}
-
-function ngramLanguageMasks(model: GeneratedSBCSModel) {
-  const masks = new Map<number, number>();
-  model.languages.forEach((language, languageIndex) => {
-    for (const ngram of new Set(language.ngrams)) {
-      masks.set(ngram, (masks.get(ngram) ?? 0) | (1 << languageIndex));
-    }
-  });
-  return masks;
-}
-
-const preparedSBCSModels: readonly PreparedSBCSModel[] = (
-  generatedSBCSModels as readonly GeneratedSBCSModel[]
-).map((model) => ({
-  model,
-  languages: model.languages.map((language) => ({
-    model: language,
-    highByteLogProbabilities: highByteLogProbabilities(language.highBytes),
-  })),
-  ngramLanguageMasks: ngramLanguageMasks(model),
-}));
-const maxLanguagesPerModel = Math.max(
-  ...preparedSBCSModels.map((model) => model.languages.length),
+const preparedSBCSModels = prepareSBCSModels(
+  generatedSBCSModels as readonly GeneratedSBCSModel[],
 );
 
-const equivalentEncodingFamilies = [
-  ['ISO-8859-1', 'ISO-8859-15', 'windows-1252'],
-  ['ISO-8859-2', 'windows-1250'],
-  ['ISO-8859-7', 'windows-1253'],
-  ['ISO-8859-8', 'windows-1255'],
-  ['ISO-8859-9', 'windows-1254'],
-  ['ISO-8859-13', 'windows-1257'],
-] as const;
-
-function family(name: Match['name']) {
-  return equivalentEncodingFamilies.find((value) =>
-    value.includes(name as never),
-  );
-}
-
-function familyPreference(left: Candidate, right: Candidate, c1Bytes: boolean) {
-  const leftFamily = family(left.name);
-  if (!leftFamily || leftFamily !== family(right.name)) return 0;
-  const preferred =
-    leftFamily[0] === 'ISO-8859-13' || c1Bytes
-      ? [...leftFamily].reverse()
-      : [...leftFamily];
-  return (
-    preferred.indexOf(left.name as never) -
-    preferred.indexOf(right.name as never)
-  );
-}
-
-function ngramHits(
-  input: Uint8Array,
-  prepared: PreparedSBCSModel,
-  hits: Uint32Array,
-): number {
-  hits.fill(0, 0, prepared.languages.length);
-  const byteMap = prepared.model.byteMap;
-  let ignoreSpace = false;
-  let ngram = 0;
-  let total = 0;
-
-  const record = (value: number) => {
-    let languageMask = prepared.ngramLanguageMasks.get(value) ?? 0;
-    while (languageMask !== 0) {
-      const languageBit = languageMask & -languageMask;
-      hits[31 - Math.clz32(languageBit)] += 1;
-      languageMask ^= languageBit;
-    }
-  };
-
-  for (let inputIndex = 0; inputIndex < input.length; inputIndex += 1) {
-    const byte = input[inputIndex];
-    const mapped = byteMap[byte];
-    if (mapped !== 0) {
-      if (!(mapped === 0x20 && ignoreSpace)) {
-        ngram = ((ngram << 8) + mapped) & N_GRAM_MASK;
-        total += 1;
-        record(ngram);
-      }
-      ignoreSpace = mapped === 0x20;
-    }
-  }
-
-  ngram = ((ngram << 8) + 0x20) & N_GRAM_MASK;
-  total += 1;
-  record(ngram);
-  return total;
-}
-
-function byteLogLikelihood(
-  highByteCounts: HighByteCounts,
-  logProbabilities: Float64Array,
-) {
-  let highBytes = 0;
-  let likelihood = 0;
-
-  for (const [byte, count] of highByteCounts) {
-    likelihood += logProbabilities[byte - 0x80] * count;
-    highBytes += count;
-  }
-
-  return highBytes === 0 ? Number.NEGATIVE_INFINITY : likelihood / highBytes;
-}
-
-function modelByteLogLikelihood(
-  highByteCounts: HighByteCounts,
-  prepared: PreparedSBCSModel,
-) {
-  let best = Number.NEGATIVE_INFINITY;
-  for (const language of prepared.languages) {
-    best = Math.max(
-      best,
-      byteLogLikelihood(highByteCounts, language.highByteLogProbabilities),
-    );
-  }
-  return best;
-}
-
-function candidate(
-  input: Uint8Array,
-  highByteCounts: HighByteCounts,
-  prepared: PreparedSBCSModel,
-  hits: Uint32Array,
-): Candidate {
-  const { model, languages: preparedLanguages } = prepared;
-  const total = ngramHits(input, prepared, hits);
-  let bestIndex = 0;
-  let bestConfidence = -1;
-  let bestByteLogLikelihood = Number.NEGATIVE_INFINITY;
-  let bestHitRate = 0;
-
-  for (let index = 0; index < preparedLanguages.length; index += 1) {
-    const hitRate = hits[index] / total;
-    const confidence = hitRate > 0.33 ? 98 : Math.floor(hitRate * 300);
-    const likelihood = byteLogLikelihood(
-      highByteCounts,
-      preparedLanguages[index].highByteLogProbabilities,
-    );
-    if (
-      confidence > bestConfidence ||
-      (confidence === bestConfidence && likelihood > bestByteLogLikelihood)
-    ) {
-      bestIndex = index;
-      bestConfidence = confidence;
-      bestByteLogLikelihood = likelihood;
-      bestHitRate = hitRate;
-    }
-  }
-
-  return {
-    name: model.encoding,
-    lang: preparedLanguages[bestIndex].model.language,
-    confidence: bestConfidence,
-    byteLogLikelihood: bestByteLogLikelihood,
-    hits: hits[bestIndex],
-    total,
-    hitRate: bestHitRate,
-  };
-}
-
-function statisticallyCompetitive(best: Score, value: Score) {
-  const variance =
-    (best.hitRate * (1 - best.hitRate)) / best.total +
-    (value.hitRate * (1 - value.hitRate)) / value.total;
-  return best.hitRate - value.hitRate <= 1.96 * Math.sqrt(variance);
-}
-
 export function analyseGeneratedSBCS(context: Context): Match[] {
-  const highByteCounts: [number, number][] = [];
-  for (let byte = 0x80; byte <= 0xff; byte += 1) {
-    const count = context.byteStats[byte];
-    if (count > 0) highByteCounts.push([byte, count]);
-  }
-  const hits = new Uint32Array(maxLanguagesPerModel);
-  const models =
-    highByteCounts.length === 0
-      ? preparedSBCSModels
-      : preparedSBCSModels
-          .map((model, index) => ({
-            model,
-            index,
-            likelihood: modelByteLogLikelihood(highByteCounts, model),
-          }))
-          .sort(
-            (left, right) =>
-              right.likelihood - left.likelihood || left.index - right.index,
-          )
-          .slice(0, MAX_SBCS_CANDIDATES)
-          .map(({ model }) => model);
-  const candidates = models.map((model) =>
-    candidate(context.inputBytes, highByteCounts, model, hits),
-  );
-  candidates.sort((left, right) => right.confidence - left.confidence);
-
-  const strongest = candidates[0];
-  const competitive = candidates.filter((value) =>
-    statisticallyCompetitive(strongest, value),
-  );
-  const competitiveNames = new Set(competitive.map((value) => value.name));
-  competitive.sort(
-    (left, right) =>
-      familyPreference(left, right, context.c1Bytes) ||
-      right.byteLogLikelihood - left.byteLogLikelihood ||
-      right.confidence - left.confidence,
-  );
-  const remaining = candidates.filter(
-    (value) => !competitiveNames.has(value.name),
-  );
-
   let confidenceCeiling = 1;
-  return [...competitive, ...remaining]
+  return scoreSBCS(context.inputBytes, preparedSBCSModels, context.c1Bytes)
     .filter((value) => value.confidence > 0)
-    .map(({ name, lang, confidence }) => {
+    .map(({ encoding, language, confidence }) => {
       confidenceCeiling = Math.min(confidenceCeiling, confidence / 100);
-      return { name, lang, confidence: confidenceCeiling };
+      return {
+        name: encoding,
+        lang: language,
+        confidence: confidenceCeiling,
+      };
     });
 }