diff --git a/README.md b/README.md
index ba841211..26ef1e25 100644
--- a/README.md
+++ b/README.md
@@ -36,7 +36,7 @@ Provider | API | Versions
 ![bigquery](logos/bigquery.png?raw=true "BigQuery Client API")| `bigquery` | `3.4.1`
 ![pandas](logos/pandas.svg?raw=true "Pandas DataFrame API")| `pandas`| `2.0.2`, `1.5.x`, `1.4.x`
 ![duckdb](logos/duckdb.png?raw=true "DuckDB API")|`duckdb` | `0.10.2`,~~`0.9.2`~~,~~`0.8.0`~~, ~~`0.7.1`~~
-![polars](logos/polars.svg?raw=true "Polars API")|`polars`| `0.19.6`
+![polars](logos/polars.svg?raw=true "Polars API")|`polars`| `1.0.0`,~~`0.19.6`~~
 ![daft](logos/daft.png?raw=true "Daft API")|`daft`| `0.2.24`, ~~`0.2.19`~~
 
  <sub>Logos are trademarks of their own brands.</sub>
diff --git a/cuallee/polars_validation.py b/cuallee/polars_validation.py
index f8cb0ff2..b50de0b1 100644
--- a/cuallee/polars_validation.py
+++ b/cuallee/polars_validation.py
@@ -113,7 +113,7 @@ def has_pattern(self, rule: Rule, dataframe: pl.DataFrame) -> Union[bool, int]:
         """Conformance on column values to regular expression threshold"""
         return Compute._result(
             dataframe.select(
-                operator.gt(pl.col(rule.column).str.count_match(rule.value), 0).cast(
+                operator.gt(pl.col(rule.column).str.count_matches(rule.value), 0).cast(
                     pl.Int8
                 )
             )
diff --git a/pyproject.toml b/pyproject.toml
index 20c357d2..8862fb93 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -48,7 +48,7 @@ duckdb = [
   "duckdb==1.0.0"
 ]
 polars = [
-  "polars>=0.19.6"
+  "polars>=1.0.0"
 ]
 test = [
   "pytest",
diff --git a/test/unit/polars_dataframe/test_has_mean.py b/test/unit/polars_dataframe/test_has_mean.py
index 02174824..8b79bde4 100644
--- a/test/unit/polars_dataframe/test_has_mean.py
+++ b/test/unit/polars_dataframe/test_has_mean.py
@@ -21,7 +21,7 @@ def test_negative(check: Check):
 @pytest.mark.parametrize("extra_value", [4, 4.0], ids=("int", "float"))
 def test_values(check: Check, extra_value):
     check.has_mean("id", extra_value)
-    df = pl.DataFrame({"id": [0, 1, 2, 3, 14] + [extra_value]})
+    df = pl.DataFrame({"id": [0, 1, 2, 3, 14] + [extra_value]}, strict=False)
     result = check.validate(df).select(pl.col("status")) == "PASS"
     assert all(result.to_series().to_list())