unique

Author: UnravelSports [JB]

README.md

@@ -18,9 +18,9 @@ This package currently supports:
 - ⚽ 🏈 [**Polars DataFrame Conversion**](#polars-dataframes) 
 - ⚽ 🏈 [**Graph Neural Network**](#graph-neural-networks) Training, Graph Conversion and Prediction <small>
   [[🔗 Bekkers & Sahasrabudhe (2023)](https://arxiv.org/pdf/2411.17450)]</small>
-- ⚽ [**Pressing Intensity**](#pressing-intensity) 
+- ⚽ [**Pressing Intensity**](#⚽-pressing-intensity) 
   <small>[[🔗 Bekkers (2024)](https://arxiv.org/pdf/2501.04712)]</small>
-- ⚽ [**Formation and Position Identification (EFPI)**](#pressing-intensity) 
+- ⚽ [**Formation and Position Identification (EFPI)**](#⚽-formation-and-position-identification) 
   <small>[[🔗 Bekkers (2025)](https://arxiv.org/pdf/2506.23843)]</small>
 
 🌀 Features
@@ -87,7 +87,7 @@ converter = SoccerGraphConverter(
 
 ---
 
-### **Pressing Intensity**
+### ⚽ **Pressing Intensity**
 
 Compute [**Pressing Intensity**](https://arxiv.org/abs/2501.04712) for a whole game (or segment) of Soccer tracking data.
 
@@ -116,7 +116,7 @@ model.fit(
 
 ---
 
-### **Formation and Position Identification**
+### ⚽ **Formation and Position Identification**
 
 Compute [Elastic Formation and Position Identification, **EFPI**](https://arxiv.org/pdf/2506.23843) for individual frames, possessions, periods or specific time intervals for Soccer.
 
@@ -137,6 +137,8 @@ model.fit(
 )
 ```
 
+![Elastic Formation and Position Identification Example](assets/efpi.png)
+
 ⌛ ***More to come soon...!***
 
 🌀 Quick Start
@@ -234,6 +236,20 @@ If you use this repository for any educational purposes, research, project etc.,
 </details>
 <br>
 
+📎 [Bekkers, J. (2025). EFPI: Elastic Formation and Position Identification in Football (Soccer) using Template Matching and Linear Assignment. arXiv preprint arXiv:2506.23843.](https://arxiv.org/pdf/2506.23843)
+<details>
+<summary>BibTex</summary>
+<pre>
+@article{bekkers2025efpi,
+  title={EFPI: Elastic Formation and Position Identification in Football (Soccer) using Template Matching and Linear Assignment},
+  author={Bekkers, Joris},
+  journal={arXiv preprint arXiv:2506.23843},
+  year={2025}
+}
+</pre>
+</details>
+<br>
+
 🌀 Social Media
 ----
 [<img alt="alt_text" width="40px" src="https://upload.wikimedia.org/wikipedia/commons/c/ca/LinkedIn_logo_initials.png"/>](https://www.linkedin.com/in/joris-bekkers-33138288/)

unravel/soccer/dataset/kloppy_polars.py

@@ -716,7 +716,9 @@ def load(
         if self._infer_goalkeepers:
             df = self.__infer_goalkeepers(df)
 
-        self.data = df
+        self.data = df.unique(
+            [Column.OBJECT_ID, Column.FRAME_ID, Column.PERIOD_ID]
+        ).sort([Column.FRAME_ID, Column.PERIOD_ID, Column.OBJECT_ID])
         return self
 
     def add_dummy_labels(