diff --git a/dist/habitrpg-shared.js b/dist/habitrpg-shared.js
index a6b307b39b..b309e768e9 100644
--- a/dist/habitrpg-shared.js
+++ b/dist/habitrpg-shared.js
@@ -63,7 +63,7 @@ process.chdir = function (dir) {
 };
 
 },{}],3:[function(require,module,exports){
-var global=typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {};/**
+var global=self;/**
  * @license
  * Lo-Dash 2.4.1 (Custom Build) <http://lodash.com/>
  * Build: `lodash modern -o ./dist/lodash.js`
@@ -12059,69 +12059,66 @@ var process=require("__browserify_process");(function() {
       */
 
       autoAllocate: function() {
-        var diff, ideal, preference, suggested;
-        switch (user.preferences.allocationMode) {
-          case "flat":
-            suggested = Math.min(user.stats.str, user.stats.int, user.stats.con, user.stats.per);
-            if (user.stats.int === suggested) {
-              return "int";
-            } else if (user.stats.per === suggested) {
-              return "per";
-            } else if (user.stats.str === suggested) {
-              return "str";
-            } else {
-              return "con";
-            }
-            break;
-          case "classbased":
-            ideal = [user.stats.lvl / 7 * 3, user.stats.lvl / 7 * 2, user.stats.lvl / 7, user.stats.lvl / 7];
-            switch (user.stats["class"]) {
-              case "wizard":
-                preference = ["int", "per", "con", "str"];
-                break;
-              case "rogue":
-                preference = ["per", "str", "int", "con"];
-                break;
-              case "healer":
-                preference = ["con", "int", "str", "per"];
-                break;
-              default:
-                preference = ["str", "con", "per", "int"];
-            }
-            diff = [user.stats[preference[0]] - ideal[0], user.stats[preference[1]] - ideal[1], user.stats[preference[2]] - ideal[2], user.stats[preference[3]] - ideal[3]];
-            suggested = _.findIndex(diff, (function(val) {
-              if (val === _.min(diff)) {
-                return true;
+        return user.stats[(function() {
+          var diff, ideal, preference, suggested;
+          switch (user.preferences.allocationMode) {
+            case "flat":
+              switch (Math.min(user.stats.str, user.stats.int, user.stats.con, user.stats.per)) {
+                case user.stats.int:
+                  return "int";
+                case user.stats.per:
+                  return "per";
+                case user.stats.str:
+                  return "str";
+                default:
+                  return "con";
               }
-            }));
-            if (suggested === -1) {
-              return "str";
-            } else {
-              return preference[suggested];
-            }
-            break;
-          case "taskbased":
-            suggested = _.findKey(user.stats.training, (function(val) {
-              if (val === _.max(user.stats.training)) {
-                return val;
+              break;
+            case "classbased":
+              ideal = [user.stats.lvl / 7 * 3, user.stats.lvl / 7 * 2, user.stats.lvl / 7, user.stats.lvl / 7];
+              preference = (function() {
+                switch (user.stats["class"]) {
+                  case "wizard":
+                    return ["int", "per", "con", "str"];
+                  case "rogue":
+                    return ["per", "str", "int", "con"];
+                  case "healer":
+                    return ["con", "int", "str", "per"];
+                  default:
+                    return ["str", "con", "per", "int"];
+                }
+              })();
+              diff = [user.stats[preference[0]] - ideal[0], user.stats[preference[1]] - ideal[1], user.stats[preference[2]] - ideal[2], user.stats[preference[3]] - ideal[3]];
+              suggested = _.findIndex(diff, (function(val) {
+                if (val === _.min(diff)) {
+                  return true;
+                }
+              }));
+              if (~suggested) {
+                return preference[suggested];
+              } else {
+                return "str";
               }
-            }));
-            user.stats.training.str = 0;
-            user.stats.training.int = 0;
-            user.stats.training.con = 0;
-            user.stats.training.per = 0;
-            if (suggested === void 0) {
+            case "taskbased":
+              suggested = _.findKey(user.stats.training, (function(val) {
+                if (val === _.max(user.stats.training)) {
+                  return val;
+                }
+              }));
+              _.merge(user.stats.training, {
+                str: 0,
+                int: 0,
+                con: 0,
+                per: 0
+              });
+              return suggested || "str";
+            default:
               return "str";
-            } else {
-              return suggested;
-            }
-            break;
-          default:
-            return "str";
-        }
+          }
+        })()]++;
       },
       updateStats: function(stats) {
-        var suggested, tnl;
+        var tnl;
         if (stats.hp <= 0) {
           return user.stats.hp = 0;
         }
@@ -12140,8 +12137,7 @@ var process=require("__browserify_process");(function() {
               user.stats.lvl++;
               tnl = api.tnl(user.stats.lvl);
               if (user.preferences.automaticAllocation) {
-                suggested = user.fns.autoAllocate();
-                user.stats[suggested]++;
+                user.fns.autoAllocate();
               } else {
                 user.stats.points = user.stats.lvl - (user.stats.con + user.stats.str + user.stats.per + user.stats.int);
               }
diff --git a/script/index.coffee b/script/index.coffee
index fcc336e390..eb8c6c95f5 100644
--- a/script/index.coffee
+++ b/script/index.coffee
@@ -1006,41 +1006,36 @@ api.wrap = (user) ->
       {update} if aggregated changes, pass in userObj as update. otherwise commits will be made immediately
     ###
     autoAllocate: ->
-      switch user.preferences.allocationMode
-        when "flat"
-          suggested = Math.min(user.stats.str, user.stats.int, user.stats.con, user.stats.per)
-          if user.stats.int is suggested # In case of ties, favor INT first, to get the next point sooner
-            return "int"
-          else if user.stats.per is suggested # Then favor PER, it's a god stat
-            return "per"
-          else if user.stats.str is suggested # Then favor STR, everyone loves crits
-            return "str"
-          else
-            return "con" # CON, the unsexiest of attributes
-        when "classbased"
-          # Attributes get 3:2:1:1 per 7 levels.
-          ideal = [(user.stats.lvl / 7 * 3), (user.stats.lvl / 7 * 2), (user.stats.lvl / 7), (user.stats.lvl / 7)]
-          # Primary, secondary etc. attributes aren't explicitly defined, so hardcode them. In order as above
-          switch user.stats.class
-            when "wizard" then preference = ["int", "per", "con", "str"]
-            when "rogue" then preference = ["per", "str", "int", "con"]
-            when "healer" then preference = ["con", "int", "str", "per"]
-            else preference = ["str", "con", "per", "int"]
-          # Get the difference between the ideal attribute spread according to level, and the user's current spread.
-          diff = [(user.stats[preference[0]]-ideal[0]),(user.stats[preference[1]]-ideal[1]),(user.stats[preference[2]]-ideal[2]),(user.stats[preference[3]]-ideal[3])]
-          suggested = _.findIndex(diff, ((val) -> if val is _.min(diff) then true)) # Returns the index of the first attribute that's furthest behind the ideal
-          if suggested is -1 then return "str" else return preference[suggested] # If _.findIndex failed, we'd get a -1...
-        when "taskbased"
-          suggested = _.findKey(user.stats.training, ((val) -> if val is _.max(user.stats.training) then val)) # Returns the stat that's been trained up the most this level
-          # FIXME Reset training for this level. Tried _.each but couldn't get it to take.
-          user.stats.training.str = 0
-          user.stats.training.int = 0
-          user.stats.training.con = 0
-          user.stats.training.per = 0
-          if suggested is undefined then return "str" else return suggested # Failed _.findkey gives undefined
-          # tallies = _.reduce user.tasks, ((m,v)-> m[v.attribute or 'str'] += v.value;m), {str:0,int:0,con:0,per:0}
-          # suggested = _.reduce tallies, ((m,v,k)-> if v>tallies[m] then k else m), 'str'
-        else return "str" # if all else fails, dump into STR
+      user.stats[(->
+        switch user.preferences.allocationMode
+          when "flat"
+            switch Math.min(user.stats.str, user.stats.int, user.stats.con, user.stats.per)
+              when user.stats.int then "int" # In case of ties, favor INT first, to get the next point sooner
+              when user.stats.per then "per" # Then favor PER, it's a god stat
+              when user.stats.str then "str" # Then favor STR, everyone loves crits
+              else                     "con" # CON, the unsexiest of attributes
+          when "classbased"
+            # Attributes get 3:2:1:1 per 7 levels.
+            ideal = [(user.stats.lvl / 7 * 3), (user.stats.lvl / 7 * 2), (user.stats.lvl / 7), (user.stats.lvl / 7)]
+            # Primary, secondary etc. attributes aren't explicitly defined, so hardcode them. In order as above
+            preference = switch user.stats.class
+              when "wizard" then ["int", "per", "con", "str"]
+              when "rogue"  then ["per", "str", "int", "con"]
+              when "healer" then ["con", "int", "str", "per"]
+              else               ["str", "con", "per", "int"]
+            # Get the difference between the ideal attribute spread according to level, and the user's current spread.
+            diff = [(user.stats[preference[0]]-ideal[0]),(user.stats[preference[1]]-ideal[1]),(user.stats[preference[2]]-ideal[2]),(user.stats[preference[3]]-ideal[3])]
+            suggested = _.findIndex(diff, ((val) -> if val is _.min(diff) then true)) # Returns the index of the first attribute that's furthest behind the ideal
+            return if ~suggested then preference[suggested] else "str"  # If _.findIndex failed, we'd get a -1...
+          when "taskbased"
+            suggested = _.findKey(user.stats.training, ((val) -> if val is _.max(user.stats.training) then val)) # Returns the stat that's been trained up the most this level
+            # Reset training for this level.
+            _.merge user.stats.training, {str:0,int:0,con:0,per:0}
+            return suggested or "str" # Failed _.findkey gives undefined
+            # tallies = _.reduce user.tasks, ((m,v)-> m[v.attribute or 'str'] += v.value;m), {str:0,int:0,con:0,per:0}
+            # suggested = _.reduce tallies, ((m,v,k)-> if v>tallies[m] then k else m), 'str'
+          else "str" # if all else fails, dump into STR
+      )()]++
 
     updateStats: (stats) ->
       # Game Over
@@ -1067,8 +1062,7 @@ api.wrap = (user) ->
 
             # Auto-allocate a point, or give them a new manual point
             if user.preferences.automaticAllocation
-              suggested = user.fns.autoAllocate()
-              user.stats[suggested]++
+              user.fns.autoAllocate()
             else
               # add new allocatable points. We could do user.stats.points++, but this does a fail-safe just in case
               user.stats.points = user.stats.lvl - (user.stats.con + user.stats.str + user.stats.per + user.stats.int);
diff --git a/tests/simulations/autoAllocate.coffee b/tests/simulations/autoAllocate.coffee
new file mode 100644
index 0000000000..f722557753
--- /dev/null
+++ b/tests/simulations/autoAllocate.coffee
@@ -0,0 +1,72 @@
+###
+1) clone the repo
+2) npm install
+3) coffee ./tests/math_samples.coffee
+
+Current results at https://gist.github.com/lefnire/8049676
+###
+
+shared = require '../../script/index.coffee'
+_ = require 'lodash'
+$w = (s)->s.split(' ')
+
+id = shared.uuid()
+user =
+  stats:
+      class: 'warrior'
+      lvl:1, hp:50, gp:0, exp:10
+      per:0, int:0, con:0, str:0
+      buffs: {per:0, int:0, con:0, str:0}
+      training: {int:0,con:0,per:0,str:0}
+  preferences: automaticAllocation: false
+  party: quest: key:'evilsanta', progress: {up:0,down:0}
+  achievements: {}
+  items:
+    eggs: {}
+    hatchingPotions: {}
+    food: {}
+    gear:
+      equipped:
+        weapon: 'weapon_warrior_4'
+        armor:  'armor_warrior_4'
+        shield: 'shield_warrior_4'
+        head:   'head_warrior_4'
+  habits: [{value:1,type:'habit'}]
+  dailys: []
+  todos: []
+  rewards: []
+
+modes =
+  flat: _.cloneDeep user
+  classbased_warrior: _.cloneDeep user
+  classbased_rogue: _.cloneDeep user
+  classbased_wizard: _.cloneDeep user
+  classbased_healer: _.cloneDeep user
+  taskbased: _.cloneDeep user
+
+modes.classbased_warrior.stats.class = 'warrior'
+modes.classbased_rogue.stats.class = 'rogue'
+modes.classbased_wizard.stats.class = 'wizard'
+modes.classbased_healer.stats.class = 'healer'
+
+_.each $w('flat classbased_warrior classbased_rogue classbased_wizard classbased_healer taskbased'), (mode) ->
+  _.merge modes[mode].preferences,
+    automaticAllocation: true
+    allocationMode: if mode.indexOf('classbased') is 0 then 'classbased' else mode
+  shared.wrap(modes[mode])
+
+console.log "\n\n================================================"
+console.log "New Simulation"
+console.log "================================================\n\n"
+
+
+_.times [20], (lvl) ->
+  console.log ("[lvl #{lvl}]\n--------------\n")
+  _.each $w('flat classbased_warrior classbased_rogue classbased_wizard classbased_healer taskbased'), (mode) ->
+    u = modes[mode] #local var
+    u.stats.exp = shared.tnl(lvl)+1 # level up
+    u.habits[0].attribute = u.fns.randomVal({str:'str',int:'int',per:'per',con:'con'})
+    u.ops.score {params:{id:u.habits[0].id},direction:'up'}
+    u.fns.updateStats(u.stats) # trigger stats update
+    str = mode + (if mode is 'taskbased' then " (#{u.habits[0].attribute})" else "")
+    console.log str, _.pick(u.stats, $w 'per int con str')
\ No newline at end of file
diff --git a/tests/math_samples.coffee b/tests/simulations/passive_active_attrs.coffee
similarity index 99%
rename from tests/math_samples.coffee
rename to tests/simulations/passive_active_attrs.coffee
index 96ce6e22bd..5f8060bd3e 100644
--- a/tests/math_samples.coffee
+++ b/tests/simulations/passive_active_attrs.coffee
@@ -6,7 +6,7 @@
 Current results at https://gist.github.com/lefnire/8049676
 ###
 
-shared = require '../script/index.coffee'
+shared = require '../../script/index.coffee'
 _ = require 'lodash'
 
 id = shared.uuid()