## Latest Results – 2019-07-16

- 10
- 1
- 6
- 14
- 21
- 1

### Results Details

### 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 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: **July 16, 2019 18:00** (2019-07-16 15:00 UTC). 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 | 8.83 | 15.8093 | 3.6059 | 6.9759 | 1.9 | 15.8 ± 7.2 | |

MED_M | 11 | 16.4708 | 2.5036 | 5.4708 | 2.2 | 16.5 ± 5.0 | |

RNG_M | 20 | 28.6746 | 4.8699 | 8.6746 | 1.8 | 28.7 ± 9.7 | |

SUM_M | 53 | 94.8555 | 21.6352 | 41.8555 | 1.9 | 94.9 ± 43.3 | |

MINGAP_M | 0 | 1.3267 | 0.8941 | 1.3267 | 1.5 | 1.3 ± 1.8 | |

MAXGAP_M | 7 | 12.9523 | 4.1235 | 5.9523 | 1.4 | 13.0 ± 8.2 | |

SUM_A | 53 | 94.8555 | 21.6352 | 41.8555 | 1.9 | 94.9 ± 43.3 |

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: