- 43
- 33
- 7
- 34
- 31
- 11

### 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: **November 12, 2024 11:00** (2024-11-12 08:00 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 | 26.50 | 26.0833 | 4.8385 | 0.4167 | 0.1 | 26.1 ± 9.7 | |

MED_M | 25 | 26.0938 | 4.5248 | 1.0938 | 0.2 | 26.1 ± 9.0 | |

RNG_M | 36 | 28.0625 | 8.8880 | 7.9375 | 0.9 | 28.1 ± 17.8 | |

SUM_M | 159 | 156.5000 | 29.0310 | 2.5000 | 0.1 | 156.5 ± 58.1 | |

MINGAP_M | 1 | 1.3125 | 0.7042 | 0.3125 | 0.4 | 1.3 ± 1.4 | |

MAXGAP_M | 20 | 12.9375 | 5.2848 | 7.0625 | 1.3 | 12.9 ± 10.6 | |

SUM_A | 159 | 156.5000 | 29.0310 | 2.5000 | 0.1 | 156.5 ± 58.1 |

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: