- 14
- 7
- 25
- 1
- 20
- 33

### 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: **September 11, 2024 11:00** (2024-09-11 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 | 16.67 | 23.0505 | 5.0127 | 6.3838 | 1.3 | 23.1 ± 10.0 | |

MED_M | 17 | 22.9832 | 4.0264 | 5.9832 | 1.5 | 23.0 ± 8.1 | |

RNG_M | 32 | 32.8285 | 6.8648 | 0.8285 | 0.1 | 32.8 ± 13.7 | |

SUM_M | 100 | 138.3030 | 30.0761 | 38.3030 | 1.3 | 138.3 ± 60.2 | |

MINGAP_M | 5 | 1.7512 | 1.0153 | 3.2488 | 3.2 | 1.8 ± 2.0 | |

MAXGAP_M | 8 | 14.3682 | 4.8617 | 6.3682 | 1.3 | 14.4 ± 9.7 | |

SUM_A | 100 | 138.3030 | 30.0761 | 38.3030 | 1.3 | 138.3 ± 60.2 |

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: