diff --git a/docs/backtesting.md b/docs/backtesting.md
index 837fcfa3b..34c5f1fbe 100644
--- a/docs/backtesting.md
+++ b/docs/backtesting.md
@@ -201,6 +201,8 @@ Since backtesting lacks some detailed information about what happens within a ca
 Taking these assumptions, backtesting tries to mirror real trading as closely as possible. However, backtesting will **never** replace running a strategy in dry-run mode.
 Also, keep in mind that past results don't guarantee future success.
 
+In addition to the above assumptions, strategy authors should carefully read the [Common Mistakes](strategy-customization.md#common-mistakes-when-developing-strategies) section, to avoid using data in backtesting which is not available in real market conditions.
+
 ### Further backtest-result analysis
 
 To further analyze your backtest results, you can [export the trades](#exporting-trades-to-file).
diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md
index ca76071af..ab7dcfc30 100644
--- a/docs/strategy-customization.md
+++ b/docs/strategy-customization.md
@@ -60,8 +60,7 @@ file as reference.**
 !!! Warning Using future data
     Since backtesting passes the full time interval to the `populate_*()` methods, the strategy author
     needs to take care to avoid having the strategy utilize data from the future.
-    Samples for usage of future data are `dataframe.shift(-1)`, `dataframe.resample("1h")` (this uses the left border of the interval, so moves data from an hour to the start of the hour).
-    They all use data which is not available during regular operations, so these strategies will perform well during backtesting, but will fail / perform badly in dry-runs.
+    Some common patterns for this are listed in the [Common Mistakes](#common-mistakes-when-developing-strategies) section of this document.
 
 ### Customize Indicators
 
@@ -399,10 +398,10 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
 
 Printing more than a few rows is also possible (simply use  `print(dataframe)` instead of `print(dataframe.tail())`), however not recommended, as that will be very verbose (~500 lines per pair every 5 seconds).
 
-### Where is the default strategy?
+### Where can i find a strategy template?
 
-The default buy strategy is located in the file
-[freqtrade/default_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/strategy/default_strategy.py).
+The strategy template is located in the file
+[user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/sample_strategy.py).
 
 ### Specify custom strategy location
 
@@ -412,6 +411,18 @@ If you want to use a strategy from a different directory you can pass `--strateg
 freqtrade --strategy AwesomeStrategy --strategy-path /some/directory
 ```
 
+### Common mistakes when developing strategies
+
+Backtesting analyzes the whole time-range at once for performance reasons. Because of this, strategy authors need to make sure that strategies do not look-ahead into the future.
+This is a common pain-point, which can cause huge differences between backtesting and dry/live run methods, since they all use data which is not available during dry/live runs, so these strategies will perform well during backtesting, but will fail / perform badly in real conditions.
+
+The following lists some common patterns which should be avoided to prevent frustration:
+
+- don't use `shift(-1)`. This uses data from the future, which is not available.
+- don't use `.iloc[-1]` or any other absolute position in the dataframe, this will be different between dry-run and backtesting.
+- don't use `dataframe['volume'].mean()`. This uses the full DataFrame for backtesting, including data from the future. Use `dataframe['volume'].rolling(<window>).mean()` instead
+- don't use `.resample('1h')`. This uses the left border of the interval, so moves data from an hour to the start of the hour. Use `.resample('1h', label='right')` instead.
+
 ### Further strategy ideas
 
 To get additional Ideas for strategies, head over to our [strategy repository](https://github.com/freqtrade/freqtrade-strategies). Feel free to use them as they are - but results will depend on the current market situation, pairs used etc. - therefore please backtest the strategy for your exchange/desired pairs first, evaluate carefully, use at your own risk.