- 19
- 7
- 21
- 13
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- 4

### Results Details

May 15, 2024 23:45 (2024-05-15 20:45 GMT) / 109560

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: **May 29, 2024 18:00** (2024-05-29 15:00 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 | 13.17 | 15.8525 | 3.6431 | 2.6859 | 0.7 | 15.9 ± 7.3 | |

MED_M | 12.50 | 16.5101 | 2.4713 | 4.0101 | 1.6 | 16.5 ± 4.9 | |

RNG_M | 17 | 28.6806 | 4.8112 | 11.6806 | 2.4 | 28.7 ± 9.6 | |

SUM_M | 79 | 95.1153 | 21.8585 | 16.1153 | 0.7 | 95.1 ± 43.7 | |

MINGAP_M | 2 | 1.3410 | 0.9288 | 0.6590 | 0.7 | 1.3 ± 1.9 | |

MAXGAP_M | 6 | 12.9370 | 4.0651 | 6.9370 | 1.7 | 12.9 ± 8.1 | |

SUM_A | 79 | 95.1153 | 21.8585 | 16.1153 | 0.7 | 95.1 ± 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: