Skip to content

HKJC Guru is an independent statistics service and is not affiliated with, endorsed by, or connected to The Hong Kong Jockey Club.

GREEN ENERGY

Developing · Ran 2574d ago

Form 2862947121 finishing position trend

GREEN ENERGY is a Bay gelding, sired by Rip Van Winkle out of Medrano. In 16 career starts in Hong Kong, he has won 3 times and placed in the first three 7 times. He most recently ran on 2019-07-01 at Sha Tin, finishing 1st.

Career Record

Record

16-3-7

Runs-Wins-Places

Current Rating

with season change

Win rate

18.8%

Place 43.8%

Season prize (HK$)

Total 3,914,525

Age

NZ · PP

Profile & pedigree

Sire

Rip Van Winkle

Dam

Medrano

Colour / Sex

Bay / Gelding

Owner

Chadwick Mok Cham Hung, Wong Wing Hong & Wilson Lam Jing Shing

Race History

18 runs
Date Race Pos Odds
2019-07-01 Sha Tin · 1200m · Class 2 H T Mo · N 1 42.0
2018-11-04 Sha Tin · 1400m · Class 2 H T Mo · N 2 8.1
2018-10-13 Sha Tin · 1600m · Class 2 H T Mo
2018-10-01 Sha Tin · 1400m · Class 3 H T Mo · 1/2 1 4.9
2018-07-15 Sha Tin · 1600m · Class 3 A Sanna · 7 7 7.5
2018-05-20 Sha Tin · 1400m · Class 3 A Sanna · 1 4 7.2
2018-04-08 Sha Tin · 1800m · Class 3 N Rawiller · 4-1/4 9 11.0
2018-03-25 Sha Tin · 1600m · Class 3 N Rawiller · 1-3/4 2 10.0
2018-03-07 Happy Valley · 1650m · Class 3 N Rawiller · 3-1/2 6 8.0
2018-01-28 Sha Tin · 1600m · Class 3 K C Leung · 5 8 17.0
Full history (8 more runs)
2017-12-17 Sha Tin · 1600m · Class 3 K C Leung · 1 2 21.0
2017-10-22 Sha Tin · 1600m · Class 3 Z Purton · 6-3/4 12 5.1
2017-09-27 Happy Valley · 1650m · Class 3 Z Purton · 3-1/4 7 8.0
2017-07-16 Sha Tin · 1600m · Class 3 Z Purton · 1/2 1 7.2
2017-06-11 Sha Tin · 1400m · Class 3 N Callan
2017-05-13 Sha Tin · 1400m · Class 3 C Schofield · 2-1/2 5 7.2
2017-04-30 Sha Tin · 1400m · Class 3 C Schofield · 2-3/4 3 12.0
2017-02-08 Happy Valley · 1200m · Class 3 K C Leung · 3-1/2 5 14.0

We rate every runner, every meeting

A nightly model scores each field — the Model column above shows its pre-race rank for this horse's past runs.

How the model works →