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### Results Details

January 15, 2022 00:00 (2022-01-14 21:00 GMT) / 41817

Gosloto 5/36

### Hot and Cold Numbers

View Hot, Cold and Overdue numbers for Gosloto 5/36 based on latest 4 weeks, 12 weeks, half a year, year to date or last 10 draws, last 30 draws, last 50 draws, last 100 draws.

You can also find detailed number statistcs in Russia Gosloto 5/36 Number Frequencies

### Next Draw

Next draw date is: **January 19, 2022 12:00** (2022-01-19 09:00 GMT). Follow our account in Twitter to be notified when fresh results and analysis are available. Use Gosloto 5/36 Numbers Generator to generate numbers for the next draw and test it using our Gosloto 5/36 Prediction System.

### Results Checker

Check your lottery ticket with Gosloto 5/36 Results Checker or browse Gosloto 5/36 Recent Results.

## Results Analysis

Click on the feature code to view feature chart.

Code | Value | Predicted Correctly | Statistics after draw | Deviation | xSSD | Prediction for next draw | |
---|---|---|---|---|---|---|---|

MEAN | SSD | ||||||

MEAN_M | 16 | 15.8303 | 3.6409 | 0.1697 | 0.0 | 15.8 ± 7.3 | |

MED_M | 17 | 16.5070 | 2.4796 | 0.4930 | 0.2 | 16.5 ± 5.0 | |

RNG_M | 32 | 28.6810 | 4.8276 | 3.3190 | 0.7 | 28.7 ± 9.7 | |

SUM_M | 96 | 94.9821 | 21.8456 | 1.0179 | 0.0 | 95.0 ± 43.7 | |

MINGAP_M | 2 | 1.3397 | 0.9294 | 0.6603 | 0.7 | 1.3 ± 1.9 | |

MAXGAP_M | 12 | 12.9409 | 4.0779 | 0.9409 | 0.2 | 12.9 ± 8.2 | |

SUM_A | 96 | 94.9821 | 21.8456 | 1.0179 | 0.0 | 95.0 ± 43.7 |

Check out detailed Gosloto 5/36 Predictions page

### Analysis Explanation

After each draw we calculate values for a number of features we analyze for the game. Each feature is a random value itself and we calculate statistics for them. We calculate expected value (**MEAN**) and sample standard deviation (**SSD**). more info

Also for each value we present how current result is correlate with feature statistics. **Deviation** is the absolute value of the result and mean difference. **xSSD** is deviation to SSD ratio.

xSSD shows to what area of bell shaped curve the result belongs. Assuming that each feature is distributed under normal distribution law the following is true: 68% of results lies within MEAN±SSD interval, 95% – MEAN±2*SSD and 99.7% of all results within MEAN±3*SSD (see illustration below):

Feature codes are as following: