- 20
- 40
- 39
- 42
- 27
- 2

### Results Details

### Hot and Cold Numbers

View Hot, Cold and Overdue numbers for Gosloto 6/45 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 6/45 Number Frequencies

### Next Draw

Next draw date is: **May 28, 2023 23:00** (2023-05-28 20:00 GMT). Follow our account in Twitter to be notified when fresh results and analysis are available. Use Gosloto 6/45 Numbers Generator to generate numbers for the next draw and test it using our Gosloto 6/45 Prediction System.

### Results Checker

Check your lottery ticket with Gosloto 6/45 Results Checker or browse Gosloto 6/45 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 | 28.33 | 23.0597 | 5.0229 | 5.2737 | 1.0 | 23.1 ± 10.0 | |

MED_M | 22 | 22.9847 | 4.0127 | 0.9847 | 0.2 | 23.0 ± 8.0 | |

RNG_M | 40 | 32.8137 | 6.8732 | 7.1863 | 1.0 | 32.8 ± 13.7 | |

SUM_M | 170 | 138.3581 | 30.1372 | 31.6419 | 1.0 | 138.4 ± 60.3 | |

MINGAP_M | 1 | 1.7501 | 1.0087 | 0.7501 | 0.7 | 1.8 ± 2.0 | |

MAXGAP_M | 18 | 14.3680 | 4.8901 | 3.6320 | 0.7 | 14.4 ± 9.8 | |

SUM_A | 170 | 138.3581 | 30.1372 | 31.6419 | 1.0 | 138.4 ± 60.3 |

Check out detailed Gosloto 6/45 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: