# Request for TC of perfect predictions

**URL:** <https://forum.numer.ai/t/request-for-tc-of-perfect-predictions/6060>\
**Category:** Tournament\
**Created:** [January 22, 2023, 11:43pm UTC](https://forum.numer.ai/t/request-for-tc-of-perfect-predictions/6060 "2023-01-22T23:43:20Z")\
**Posts on this page:** 1\
**Showing post:** 2

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**Author:** ![nyuton](https://yyz1.discourse-cdn.com/flex009/user_avatar/forum.numer.ai/nyuton/32/687_2.png) [@nyuton](https://forum.numer.ai/u/nyuton)\
**Post date:** [January 23, 2023, 9:27am UTC](https://forum.numer.ai/t/request-for-tc-of-perfect-predictions/6060/2 "2023-01-23T09:27:15Z")

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The perfect prediction is, if you hit the exact right ranking! It must have a good TC 🙂

But here is a good (?) description on how to estimate TC:

> [@How to estimate TC with the numerai meta model data](http://forum.numer.ai/t/how-to-estimate-tc-with-the-numerai-meta-model-data/6032):
>
> Hi, TC is a metric that shows, how much your model improves the meta model. That means that ensembling the predictions of my model with the metamodel should improve the meta model metrics like corr and sharpe. The fund also picks trades from the stocks, where the metamodel has the most confidence (top/bottom 200). With that in mind, we can estimate the (past) TC of a model with the following script: validation[‘my\_prediction’] = my\_model.predict(validation[features]) mm = pd.read\_parquet(‘…

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