Update S5 methodology

backends/redoubt/tokens.py

@@ -79,7 +79,13 @@ def _do_calculate(self, config: SeasonConfig, dry_run: bool = False):
               and build_time <  to_timestamp({config.start_time}) - interval '14 day' -- end of the S4 season
               order by thd.address, build_time desc
             ), tvl_prior_start as (
-              select symbol, sum(tvl_ton) as start_tvl from tvl_prior_start_all
+              select symbol, sum(tvl_ton) as start_tvl,
+              (
+                select rate from ton_usd_rates 
+                where build_time < to_timestamp({config.start_time}) - interval '14 day' 
+                order by build_time desc limit 1
+              ) * sum(tvl_ton) as start_tvl_usd
+              from tvl_prior_start_all
               group by 1
             ), current_tvl as (
               -- TVL during the season
@@ -116,6 +122,7 @@ def _do_calculate(self, config: SeasonConfig, dry_run: bool = False):
             prizes,
             url, boost_link,
             coalesce(start_tvl, 0) as start_tvl,
+            coalesce(start_tvl_usd, 0) as start_tvl_usd,
             coalesce(last_tvl.tvl, 0) as last_tvl,
             coalesce(100 * coalesce(price_change, 0), 0) as price_delta,
             coalesce(price_before, 0) as price_before,
@@ -148,6 +155,7 @@ def _do_calculate(self, config: SeasonConfig, dry_run: bool = False):
                     results[row['symbol']].metrics[ProjectStat.TOKEN_IS_MEME] = row['is_meme']
                     results[row['symbol']].metrics[ProjectStat.TOKEN_HAS_BOOST] = row['has_boost']
                     results[row['symbol']].metrics[ProjectStat.TOKEN_START_TVL] = int(row['start_tvl'])
+                    results[row['symbol']].metrics[ProjectStat.TOKEN_START_TVL_USD] = int(row['start_tvl_usd'])
                     results[row['symbol']].metrics[ProjectStat.TOKEN_LAST_TVL] = int(row['last_tvl'])
                     results[row['symbol']].metrics[ProjectStat.TOKEN_PRICE_BEFORE] = float(row['price_before'])
                     results[row['symbol']].metrics[ProjectStat.TOKEN_PRICE_AFTER] = float(row['price_after'])

models/results.py

@@ -16,8 +16,10 @@ class ProjectStat:
     APP_ONCHAIN_UAW = 'onchain_uaw'
     APP_ONCHAIN_MEDIAN_TX = 'onchain_median_tx'
 
+    TOKEN_TVL_CATEGORY = 'token_tvl_category'
     TOKEN_TVL_CHANGE = 'token_tvl_change'
     TOKEN_START_TVL = 'token_start_tvl'
+    TOKEN_START_TVL_USD = 'token_start_tvl_usd'
     TOKEN_LAST_TVL = 'token_last_tvl'
     TOKEN_PRICE_BEFORE = 'token_price_before'
     TOKEN_PRICE_AFTER = 'token_price_after'

seasons/tokens_models.py

@@ -29,18 +29,38 @@ def calculate(self, metrics: List[ProjectStat]):
 
 
 """
-Token leaderboard score model, launched since S5. The only metrics is price change
+Token leaderboard score model, launched since S5
+30% - base TVL Delta weight
+40% - base New holders weight
+30% - base Price change (normalised on sqrt(TVL)) weight
 """
 class TokenLeaderboardModelV5(ScoreModel):
     def __init__(self):
         super().__init__()
         self.params[ScoreModel.PARAM_TOKEN_MIN_VALUE_FOR_NEW_HOLDER] = 1.0 # 1 TON
+        self.tvl_category = {
+            "10M – 20M": {"low": 10_000_000, "high": None, "coefficient": 1},
+            "5M – 10M": {"low": 5_000_000, "high": 10_000_000, "coefficient": 0.8},
+            "2M – 5M": {"low": 2_000_000, "high": 5_000_000, "coefficient": 0.6},
+            "1M – 2M": {"low": 1_000_000, "high": 2_000_000, "coefficient": 0.5},
+            "500K – 1M": {"low": 500_000, "high": 1_000_000, "coefficient": 0.4},
+            "100K – 500K": {"low": None, "high": 500_000, "coefficient": 0.3},
+        }
+
+    def get_tvl_category(self, tvl_value) -> str:
+        for category_name, limits in self.tvl_category.items():
+            if (not limits["low"] or tvl_value > limits["low"]) and (not limits["high"] or tvl_value <= limits["high"]):
+                return category_name
 
     def calculate(self, metrics: List[ProjectStat]):
-        MIN_TVL = 14106 # $100,000 nominated in TON
         for project in metrics:
             logger.info(f"Calculating score for {project}")
-            project.score = project.metrics[ProjectStat.TOKEN_LAST_TVL] - \
-                            max(MIN_TVL, project.metrics[ProjectStat.TOKEN_START_TVL])
+            project.metrics[ProjectStat.TOKEN_TVL_CATEGORY] = self.get_tvl_category(project.metrics[ProjectStat.TOKEN_START_TVL_USD])
+            price_change_weight = 30 * self.tvl_category[project.metrics[ProjectStat.TOKEN_TVL_CATEGORY]]["coefficient"]
+            tvl_change_weight = 30 + (30 - price_change_weight) * 3 / 7
+            new_holders_weight = 40 + (30 - price_change_weight) * 4 / 7
+            project.score = new_holders_weight * self.normalized_max(project, ProjectStat.TOKEN_NEW_USERS_WITH_MIN_AMOUNT, metrics) + \
+                            tvl_change_weight * self.normalized_min_max(project, ProjectStat.TOKEN_TVL_CHANGE, metrics) + \
+                            price_change_weight * self.normalized_min_max(project, ProjectStat.TOKEN_PRICE_CHANGE_NORMED, metrics)
 
         return sorted(metrics, key=lambda m: m.score, reverse=True)