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Over 187 logged MLB games, Jung Hoo Lee has gone over 0.5 hits 123 times (66%), and over their last 10 they have done it 6 times (60%). They average 1.1 hits across those 187 games. Their last 5 average 0.8, 24% below their 1.1 across the full log. Against the Los Angeles Dodgers in this log they have 16 games, averaging 0.8. These are measured box-score results from San Francisco Giants games, not a projection, and on their own they say nothing about whether tonight’s price is worth taking.
| Market | Logged games | Average | Most balanced line | Hit rate there |
|---|---|---|---|---|
| Home Runs | 187 | 0.1 home runs | Over 0.5 | 13 of 187 (7%) |
| Hits | 187 | 1.1 hits | Over 0.5 | 123 of 187 (66%) |
| RBIs | 187 | 0.4 RBIs | Over 0.5 | 51 of 187 (27%) |
Every market Jung Hoo Lee is currently priced in, on the same row as the game it came from. A dash means the box score carried no value in that market for that game, which is not the same as a zero.
| Date | Opponent | Venue | Home Runs | Hits | RBIs |
|---|---|---|---|---|---|
| 2026-09-20 | Los Angeles Dodgers | Away | 0 | 0 | 0 |
| 2026-09-19 | Los Angeles Dodgers | Away | 0 | 2 | 1 |
| 2026-09-18 | Los Angeles Dodgers | Away | 1 | 1 | 1 |
| 2026-09-16 | St. Louis Cardinals | Away | 0 | 0 | 0 |
| 2026-09-15 | St. Louis Cardinals | Away | 0 | 1 | 0 |
| 2026-09-14 | St. Louis Cardinals | Away | 0 | 1 | 0 |
| 2026-09-13 | San Diego Padres | Home | 0 | 0 | 0 |
| 2026-09-12 | San Diego Padres | Home | 0 | 1 | 0 |
Jung Hoo Lee has gone over 0.5 home runs in 13 of 187 logged games (7%).
At home they average 0.1 over 88 games; away, 0.1 over 99.
Jung Hoo Lee home runs: full game log, trend and hit rate by line
Jung Hoo Lee has gone over 0.5 hits in 123 of 187 logged games (66%).
At home they average 1.0 over 88 games; away, 1.1 over 99.
Jung Hoo Lee hits: full game log, trend and hit rate by line
Jung Hoo Lee has gone over 0.5 RBIs in 51 of 187 logged games (27%).
At home they average 0.4 over 88 games; away, 0.4 over 99.
Jung Hoo Lee RBIs: full game log, trend and hit rate by line
Prop research for Jung Hoo Lee of the San Francisco Giants. The books are currently pricing Home Runs, Hits and RBIs lines for Jung Hoo Lee, and each one is scored the same way every prop on this site is: their own game log measured against the exact line on offer, shrunk toward a league prior so a hot fortnight cannot pass for an edge, then compared with the price. The game log and the splits below are measured history and are rebuilt daily; the lines and prices load live, because a MLB price printed into a page is wrong within the hour. None of it is a forecast of the next game.
Calculated by the ParlayBuilder Prop Engine.
Every figure on this page is counted from official MLB box scores, one row per game actually played — no projections, and a game the player missed is absent rather than scored as a zero. Hit rates against the live board are shrunk toward a league prior in proportion to how thin the sample is, so three-for-three does not read here as a certainty.
Past performance does not predict future results, and Parlay Builder does not accept wagers, hold funds or settle bets. No locks and no guaranteed wins — this is measured history and a price, and what you do with them is your decision.
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Whatever the books have priced — currently Home Runs, Hits and RBIs. The board on this page loads live rather than from a saved snapshot, so it reflects what is actually on offer now, with the best posted price across the major US sportsbooks against each line.
It depends on the line, which is why this page shows a rate per prop rather than one number. Each is the share of logged games finishing above the exact line on offer, over the deepest window available, shrunk toward a league prior so a short sample cannot masquerade as a trend. The number of games behind every rate is printed beside it.
The home and away splits on this page are measured from the same game log, so you can see the gap rather than assume one. Read them with the sample sizes next to them: a split measured over a handful of games each way is a difference you cannot distinguish from noise, and this page prints the denominator so you can tell.
No one knows, and any MLB tool that says otherwise is selling you something. Every figure here is measured history against a current price, and history is not a forecast. Across roughly 96,000 graded props the model tracked the de-vigged consensus across five books to within the margin those books charge: historical testing showed calibration alone is not enough to overcome sportsbook pricing. What this page does is show you the sample behind every number in seconds.
How MLB prop markets behave, measured across the league
Odds and lines come from licensed data feeds and refresh on a schedule; hit rates, edges and grades are Parlay Builder’s own calculations.