## Latest Results – 2019-01-30

- 1
- 22
- 36
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- 59
- 41

### Results Details

January 30, 2019 00:00 (2019-01-30 05:00 show UTC)

New York Lotto

### Hot and Cold Numbers

View Hot, Cold and Overdue numbers for New York Lotto 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 NY Lotto Number Frequencies

### Next Draw

Next draw date is: **September 18, 2019 23:21** (2019-09-19 03:21 UTC). Follow our account in Twitter to be notified when fresh results and analysis are available. Use New York Lotto Numbers Generator to generate numbers for the next draw and test it using our New York Lotto Prediction System.

### Results Checker

Check your lottery ticket with New York Lotto Results Checker or browse New York Lotto 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 | 35.17 | 29.9906 | 6.5001 | 5.1761 | 0.8 | 30.0 ± 13.0 | |

MED_M | 30 | 30.0003 | 5.2330 | 0.0003 | 0.0 | 30.0 ± 10.5 | |

RNG_M | 58 | 43.0589 | 8.6841 | 14.9411 | 1.7 | 43.1 ± 17.4 | |

SUM_M | 211 | 179.9434 | 39.0004 | 31.0566 | 0.8 | 179.9 ± 78.0 | |

MINGAP_M | 5 | 2.1978 | 1.4286 | 2.8022 | 2.0 | 2.2 ± 2.9 | |

MAXGAP_M | 21 | 18.9201 | 6.3720 | 2.0799 | 0.3 | 18.9 ± 12.7 | |

SUM_A | 252 | 210.3168 | 41.8790 | 41.6832 | 1.0 | 210.3 ± 83.8 |

Check out detailed New York Lotto 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: