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Over 91 logged MLB games, Jacob Gonzalez has gone over 0.5 hits 38 times (42%), and over their last 10 they have done it 4 times (40%). They average 0.5 hits across those 91 games. Their last 5 average 0.2, 63% below their 0.5 across the full log. Against the St. Louis Cardinals in this log they have 2 games, averaging 0.5. These are measured box-score results from Pittsburgh Pirates 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 | 91 | 0.1 home runs | Over 0.5 | 6 of 91 (7%) |
| RBIs | 91 | 0.4 RBIs | Over 0.5 | 19 of 91 (21%) |
| Hits | 91 | 0.5 hits | Over 0.5 | 38 of 91 (42%) |
Every market Jacob Gonzalez 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 | RBIs | Hits |
|---|---|---|---|---|---|
| 2026-09-16 | Milwaukee Brewers | Home | 0 | 0 | 0 |
| 2026-09-13 | Chicago Cubs | Away | 0 | 0 | 0 |
| 2026-09-12 | Chicago Cubs | Away | 0 | 0 | 1 |
| 2026-09-11 | Chicago Cubs | Away | 0 | 0 | 0 |
| 2026-09-10 | Chicago White Sox | Away | 0 | 0 | 0 |
| 2026-09-09 | Chicago White Sox | Away | 0 | 0 | 1 |
| 2026-09-08 | Chicago White Sox | Away | 0 | 0 | 1 |
| 2026-09-06 | Los Angeles Angels | Home | 0 | 0 | 0 |
| 2026-09-04 | Los Angeles Angels | Home | 0 | 0 | 1 |
| 2026-09-03 | San Francisco Giants | Home | 0 | 0 | 0 |
| 2026-09-02 | San Francisco Giants | Home | 0 | 0 | 1 |
| 2026-09-01 | San Francisco Giants | Home | 0 | 1 | 2 |
| 2026-08-29 | St. Louis Cardinals | Away | 0 | 1 | 1 |
| 2026-08-28 | St. Louis Cardinals | Away | 0 | 0 | 0 |
| 2026-08-26 | San Diego Padres | Away | 0 | 0 | 0 |
| 2026-08-25 | San Diego Padres | Away | 0 | 0 | 0 |
Counted from the same 91 logged games as the tables above. Measured history, not a projection and not a read on tonight's price.
| Percentile | Hits |
|---|---|
| Lowest logged game | 0 |
| 25th percentile | 0 |
| Median | 0 |
| 75th percentile | 1 |
| Highest logged game | 3 |
82 of 91 games (90%) landed between 0 and 1; 91 (100%) finished at or above the 0 median, and the spread from 0 to 3 is the whole range of the log. Nearest-rank, so every figure is a score Jacob Gonzalez actually recorded.
| Month | Logged games | Average |
|---|---|---|
| September 2026 | 12 | 0.6 |
| August 2026 | 23 | 0.4 |
| July 2026 | 19 | 0.5 |
| June 2026 | 23 | 0.8 |
| March 2026 | 8 | 0.4 |
| February 2026 | 5 | 0.2 |
| Gap | Logged games | Average |
|---|---|---|
| 1 day | 52 | 0.5 |
| 2 days | 27 | 0.5 |
| 3 to 4 days | 6 | 0.3 |
| 5 or more days | 3 | 1.3 |
The gap is the distance to the previous game in this log, not a rest figure — a box score does not record a game a player sat out inside it.
| Opponent | Logged games | Average | Best |
|---|---|---|---|
| Cleveland Guardians | 8 | 0.9 | 2 |
| Chicago Cubs | 7 | 0.3 | 1 |
| Milwaukee Brewers | 7 | 0.1 | 1 |
| Detroit Tigers | 6 | 0.3 | 1 |
| New York Yankees | 6 | 0.3 | 1 |
| Los Angeles Dodgers | 6 | 0 | 0 |
Most-faced in this log is Cleveland Guardians, 8 games at 0.9, best of 2. Counts sit beside every average because two meetings is a low bar; opponents faced once are left out.
Jacob Gonzalez has gone over 0.5 home runs in 6 of 91 logged games (7%).
At home they average 0.0 over 41 games; away, 0.1 over 50.
Jacob Gonzalez home runs: full game log, trend and hit rate by line
Jacob Gonzalez has gone over 0.5 RBIs in 19 of 91 logged games (21%).
At home they average 0.3 over 41 games; away, 0.4 over 50.
Jacob Gonzalez RBIs: full game log, trend and hit rate by line
Jacob Gonzalez has gone over 0.5 hits in 38 of 91 logged games (42%).
At home they average 0.5 over 41 games; away, 0.5 over 50.
Jacob Gonzalez hits: full game log, trend and hit rate by line
Prop research for Jacob Gonzalez of the Pittsburgh Pirates. The books are currently pricing Home Runs, RBIs and Hits lines for Jacob Gonzalez, 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, RBIs and Hits. 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.